A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2017-02-01

To) 15 July 2010 – 2 Nov.2016 4 . TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP...resistance in vitro, and to investigate the mechanism for this effect. The major goal for Aim 4 was to determine the reproducibility of the BRCAness...we used the epithelial ovarian cancer (EOC) dataset from The Cancer Genome Atlas (TCGA) ( 4 ). The TCGA dataset is a unique tool for these studies as

Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.

PubMed

Grimes, Tyler; Walker, Alejandro R; Datta, Susmita; Datta, Somnath

2018-05-30

Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles. The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets. Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients. This article was reviewed by Subharup Guha and Isabel Nepomuceno.

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

PubMed Central

Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David

2001-01-01

Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681

Lung tumor diagnosis and subtype discovery by gene expression profiling.

PubMed

Wang, Lu-yong; Tu, Zhuowen

2006-01-01

The optimal treatment of patients with complex diseases, such as cancers, depends on the accurate diagnosis by using a combination of clinical and histopathological data. In many scenarios, it becomes tremendously difficult because of the limitations in clinical presentation and histopathology. To accurate diagnose complex diseases, the molecular classification based on gene or protein expression profiles are indispensable for modern medicine. Moreover, many heterogeneous diseases consist of various potential subtypes in molecular basis and differ remarkably in their response to therapies. It is critical to accurate predict subgroup on disease gene expression profiles. More fundamental knowledge of the molecular basis and classification of disease could aid in the prediction of patient outcome, the informed selection of therapies, and identification of novel molecular targets for therapy. In this paper, we propose a new disease diagnostic method, probabilistic boosting tree (PB tree) method, on gene expression profiles of lung tumors. It enables accurate disease classification and subtype discovery in disease. It automatically constructs a tree in which each node combines a number of weak classifiers into a strong classifier. Also, subtype discovery is naturally embedded in the learning process. Our algorithm achieves excellent diagnostic performance, and meanwhile it is capable of detecting the disease subtype based on gene expression profile.

A long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection.

PubMed

Lv, Yufeng; Wei, Wenhao; Huang, Zhong; Chen, Zhichao; Fang, Yuan; Pan, Lili; Han, Xueqiong; Xu, Zihai

2018-06-20

The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection. Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) group and non-early recurrence (non-ER) group of HCC. Least absolute shrinkage and selection operator (LASSO) for logistic regression models were used to develop a lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validated the predictive value of this classifier. Futhermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were performed. We identified 10 differentially expressed lncRNAs, including 3 that were upregulated and 7 that were downregulated in ER group. The lncRNA-based classifier was constructed based on 7 lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861 and LINC02084), and its accuracy was 0.83 in training set, 0.87 in test set and 0.84 in total set. And ROC curve analysis showed the AUROC was 0.741 in training set, 0.824 in the test set and 0.765 in total set. A functional enrichment analysis suggested that the genes of which is highly related to 4 lncRNAs were involved in immune system. This 7-lncRNA expression profile can effectively predict the early recurrence after surgical resection for HCC. This article is protected by copyright. All rights reserved.

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

PubMed

Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

Genome-wide analyses of long noncoding RNA expression profiles correlated with radioresistance in nasopharyngeal carcinoma via next-generation deep sequencing.

PubMed

Li, Guo; Liu, Yong; Liu, Chao; Su, Zhongwu; Ren, Shuling; Wang, Yunyun; Deng, Tengbo; Huang, Donghai; Tian, Yongquan; Qiu, Yuanzheng

2016-09-06

Radioresistance is one of the major factors limiting the therapeutic efficacy and prognosis of patients with nasopharyngeal carcinoma (NPC). Accumulating evidence has suggested that aberrant expression of long noncoding RNAs (lncRNAs) contributes to cancer progression. Therefore, here we identified lncRNAs associated with radioresistance in NPC. The differential expression profiles of lncRNAs associated with NPC radioresistance were constructed by next-generation deep sequencing by comparing radioresistant NPC cells with their parental cells. LncRNA-related mRNAs were predicted and analyzed using bioinformatics algorithms compared with the mRNA profiles related to radioresistance obtained in our previous study. Several lncRNAs and associated mRNAs were validated in established NPC radioresistant cell models and NPC tissues. By comparison between radioresistant CNE-2-Rs and parental CNE-2 cells by next-generation deep sequencing, a total of 781 known lncRNAs and 2054 novel lncRNAs were annotated. The top five upregulated and downregulated known/novel lncRNAs were detected using quantitative real-time reverse transcription-polymerase chain reaction, and 7/10 known lncRNAs and 3/10 novel lncRNAs were demonstrated to have significant differential expression trends that were the same as those predicted by deep sequencing. From the prediction process, 13 pairs of lncRNAs and their associated genes were acquired, and the prediction trends of three pairs were validated in both radioresistant CNE-2-Rs and 6-10B-Rs cell lines, including lncRNA n373932 and SLITRK5, n409627 and PRSS12, and n386034 and RIMKLB. LncRNA n373932 and its related SLITRK5 showed dramatic expression changes in post-irradiation radioresistant cells and a negative expression correlation in NPC tissues (R = -0.595, p < 0.05). Our study provides an overview of the expression profiles of radioresistant lncRNAs and potentially related mRNAs, which will facilitate future investigations into the function of lncRNAs in NPC radioresistance.

Identification and substrate prediction of new Fragaria x ananassa aquaporins and expression in different tissues and during strawberry fruit development.

PubMed

Merlaen, Britt; De Keyser, Ellen; Van Labeke, Marie-Christine

2018-01-01

The newly identified aquaporin coding sequences presented here pave the way for further insights into the plant-water relations in the commercial strawberry ( Fragaria x ananassa ). Aquaporins are water channel proteins that allow water to cross (intra)cellular membranes. In Fragaria x ananassa , few of them have been identified hitherto, hampering the exploration of the water transport regulation at cellular level. Here, we present new aquaporin coding sequences belonging to different subclasses: plasma membrane intrinsic proteins subtype 1 and subtype 2 (PIP1 and PIP2) and tonoplast intrinsic proteins (TIP). The classification is based on phylogenetic analysis and is confirmed by the presence of conserved residues. Substrate-specific signature sequences (SSSSs) and specificity-determining positions (SDPs) predict the substrate specificity of each new aquaporin. Expression profiling in leaves, petioles and developing fruits reveals distinct patterns, even within the same (sub)class. Expression profiles range from leaf-specific expression over constitutive expression to fruit-specific expression. Both upregulation and downregulation during fruit ripening occur. Substrate specificity and expression profiles suggest that functional specialization exists among aquaporins belonging to a different but also to the same (sub)class.

GENE EXPRESSION PROFILING OF MOUSE SKIN AND PAPILLOMAS FOLLOWING CHRONIC EXPOSURE TO MONOMETHYLARSONOUS ACID IN K6/ODC TRANSGENIC MICE

EPA Science Inventory

Methylarsonous acid [MMA(III)], a common metabolite of inorganic arsenic metabolism, increases tumor frequency in the skin of K6/ODC transgenic mice following a chronic exposure. To characterize gene expression profiles predictive of MMA(III) exposure and mode of action of carcin...

Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

EPA Science Inventory

Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

iPcc: a novel feature extraction method for accurate disease class discovery and prediction

PubMed Central

Ren, Xianwen; Wang, Yong; Zhang, Xiang-Sun; Jin, Qi

2013-01-01

Gene expression profiling has gradually become a routine procedure for disease diagnosis and classification. In the past decade, many computational methods have been proposed, resulting in great improvements on various levels, including feature selection and algorithms for classification and clustering. In this study, we present iPcc, a novel method from the feature extraction perspective to further propel gene expression profiling technologies from bench to bedside. We define ‘correlation feature space’ for samples based on the gene expression profiles by iterative employment of Pearson’s correlation coefficient. Numerical experiments on both simulated and real gene expression data sets demonstrate that iPcc can greatly highlight the latent patterns underlying noisy gene expression data and thus greatly improve the robustness and accuracy of the algorithms currently available for disease diagnosis and classification based on gene expression profiles. PMID:23761440

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

PubMed Central

Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

2007-01-01

Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (<4 kgs weight loss). We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box) approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%±8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier) improved prediction accuracy to 80.9%±2.2%. Conclusion Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

Extended Lindhard-Scharf-Schiott Theory for Ion Implantation Profiles Expressed with Pearson Function

NASA Astrophysics Data System (ADS)

Suzuki, Kunihiro

2009-04-01

Ion implantation profiles are expressed by the Pearson function with first, second, third, and fourth moment parameters of Rp, ΔRp, γ, and β. We derived an analytical model for these profile moments by solving a Lindhard-Scharf-Schiott (LSS) integration equation using perturbation approximation. This analytical model reproduces Monte Carlo data that were well calibrated to reproduce a vast experimental database. The extended LSS theory is vital for instantaneously predicting ion implantation profiles with any combination of incident ions and substrate atoms including their energy dependence.

Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

PubMed

Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

2014-10-15

To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

Analysis of baseline gene expression levels from toxicogenomics study control animals to identify sources of variation and predict responses to chemicals

EPA Science Inventory

The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control ...

Molecular classification and molecular forecasting of breast cancer: ready for clinical application?

PubMed

Brenton, James D; Carey, Lisa A; Ahmed, Ahmed Ashour; Caldas, Carlos

2005-10-10

Profiling breast cancer with expression arrays has become common, and it has been suggested that the results from early studies will lead to understanding of the molecular differences between clinical cases and allow individualization of care. We critically review two main applications of expression profiling; studies unraveling novel breast cancer classifications and those that aim to identify novel markers for prediction of clinical outcome. Breast cancer may now be subclassified into luminal, basal, and HER2 subtypes with distinct differences in prognosis and response to therapy. However, profiling studies to identify predictive markers have suffered from methodologic problems that prevent general application of their results. Future work will need to reanalyze existing microarray data sets to identify more representative sets of candidate genes for use as prognostic signatures and will need to take into account the new knowledge of molecular subtypes of breast cancer when assessing predictive effects.

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling.

PubMed

Ando, Tatsuya; Suguro, Miyuki; Kobayashi, Takeshi; Seto, Masao; Honda, Hiroyuki

2003-10-01

A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937-47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases.

Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets.

PubMed

Kim, Tae-Hwan; Choi, Sung Jae; Lee, Young Ho; Song, Gwan Gyu; Ji, Jong Dae

2014-07-01

Anti-tumor necrosis factor (TNF) therapy is the treatment of choice for rheumatoid arthritis (RA) patients in whom standard disease-modifying anti-rheumatic drugs are ineffective. However, a substantial proportion of RA patients treated with anti-TNF agents do not show a significant clinical response. Therefore, biomarkers predicting response to anti-TNF agents are needed. Recently, gene expression profiling has been applied in research for developing such biomarkers. We compared gene expression profiles reported by previous studies dealing with the responsiveness of anti-TNF therapy in RA patients and attempted to identify differentially expressed genes (DEGs) that discriminated between responders and non-responders to anti-TNF therapy. We used microarray datasets available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). This analysis included 6 studies and 5 sets of microarray data that used peripheral blood samples for identification of DEGs predicting response to anti-TNF therapy. We found little overlap in the DEGs that were highly ranked in each study. Three DEGs including IL2RB, SH2D2A and G0S2 appeared in more than 1 study. In addition, a meta-analysis designed to increase statistical power found one DEG, G0S2 by the Fisher's method. Our finding suggests the possibility that G0S2 plays as a biomarker to predict response to anti-TNF therapy in patients with rheumatoid arthritis. Further investigations based on larger studies are therefore needed to confirm the significance of G0S2 in predicting response to anti-TNF therapy. Copyright © 2014 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

The Application of Gene Expression Profiling in Predictions of Occult Lymph Node Metastasis in Colorectal Cancer Patients

PubMed Central

Peyravian, Noshad; Larki, Pegah; Gharib, Ehsan; Nazemalhosseini-Mojarad, Ehsan; Anaraki, Fakhrosadate; Young, Chris; McClellan, James; Ashrafian Bonab, Maziar; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

2018-01-01

A key factor in determining the likely outcome for a patient with colorectal cancer is whether or not the tumour has metastasised to the lymph nodes—information which is also important in assessing any possibilities of lymph node resection so as to improve survival. In this review we perform a wide-range assessment of literature relating to recent developments in gene expression profiling (GEP) of the primary tumour, to determine their utility in assessing node status. A set of characteristic genes seems to be involved in the prediction of lymph node metastasis (LNM) in colorectal patients. Hence, GEP is applicable in personalised/individualised/tailored therapies and provides insights into developing novel therapeutic targets. Not only is GEP useful in prediction of LNM, but it also allows classification based on differences such as sample size, target gene expression, and examination method. PMID:29498671

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Small RNA-based prediction of hybrid performance in maize.

PubMed

Seifert, Felix; Thiemann, Alexander; Schrag, Tobias A; Rybka, Dominika; Melchinger, Albrecht E; Frisch, Matthias; Scholten, Stefan

2018-05-21

Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program. Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics. Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

On Predicting Sociodemographic Traits and Emotions from Communications in Social Networks and Their Implications to Online Self-Disclosure.

PubMed

Volkova, Svitlana; Bachrach, Yoram

2015-12-01

Social media services such as Twitter and Facebook are virtual environments where people express their thoughts, emotions, and opinions and where they reveal themselves to their peers. We analyze a sample of 123,000 Twitter users and 25 million of their tweets to investigate the relation between the opinions and emotions that users express and their predicted psychodemographic traits. We show that the emotions that we express on online social networks reveal deep insights about ourselves. Our methodology is based on building machine learning models for inferring coarse-grained emotions and psychodemographic profiles from user-generated content. We examine several user attributes, including gender, income, political views, age, education, optimism, and life satisfaction. We correlate these predicted demographics with the emotional profiles emanating from user tweets, as captured by Ekman's emotion classification. We find that some users tend to express significantly more joy and significantly less sadness in their tweets, such as those predicted to be in a relationship, with children, or with a higher than average annual income or educational level. Users predicted to be women tend to be more opinionated, whereas those predicted to be men tend to be more neutral. Finally, users predicted to be younger and liberal tend to project more negative opinions and emotions. We discuss the implications of our findings to online privacy concerns and self-disclosure behavior.

Characterization and Prediction of Early Reading Abilities in Children on the Autism Spectrum

PubMed Central

Davidson, Meghan M.; Weismer, Susan Ellis

2013-01-01

Many children with autism spectrum disorder (ASD) have reading profiles characterized by higher decoding skills and lower reading comprehension. This study assessed whether this profile was apparent in young children with ASD and examined concurrent and longitudinal predictors of early reading. A discrepant profile of reading (higher alphabet and lower meaning) was found in 62% of this sample. Concurrent analyses revealed that reading proficiency was associated with higher nonverbal cognition and expressive language, and that social ability was negatively related to alphabet knowledge. Nonverbal cognition and expressive language at mean age 2½ years predicted later reading performance at mean age 5½ years. These results support the importance of early language skills as a foundation for reading in children with ASD. PMID:24022730

A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2013-08-01

like ( NBL ) corresponding to tumors predicted to have a BRCAness phenotype (BL tumors) or not ( NBL tumors). In the previous years we performed a...TCGA EOC project that have been characterized as BL or NBL by our profile to identify 3 candidate miRNAs (let-7f-2*, miR-744*, miR-342-5p) that may be

RNA Expression Profiles from Blood for the Diagnosis of Stroke and its Causes

PubMed Central

Sharp, Frank R; Jickling, Glen C; Stamova, Boryana; Tian, Yingfang; Zhan, Xinhua; Ander, Bradley P; Cox, Christopher; Kuczynski, Beth; Liu, DaZhi

2013-01-01

A blood test to detect stroke and its causes would be particularly useful in babies, young children, and patients in intensive care units, and for emergencies when imaging is difficult to obtain or unavailable. Using whole genome microarrays, we first showed specific gene expression profiles in rats 24 hours after ischemic and hemorrhagic stroke, hypoxia, and hypoglycemia. These proof-of-principle studies revealed that groups of genes (called gene profiles) can distinguish ischemic stroke patients from controls 3 hours to 24 hours after the strokes. In addition, gene expression profiles have been developed that distinguish stroke due to large-vessel atherosclerosis from cardioembolic stroke. These profiles will be useful for predicting the causes of cryptogenic stroke. Our results in adults suggest similar diagnostic tools could be developed for children. PMID:21636778

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemia.

PubMed

Cario, Gunnar; Stanulla, Martin; Fine, Bernard M; Teuffel, Oliver; Neuhoff, Nils V; Schrauder, André; Flohr, Thomas; Schäfer, Beat W; Bartram, Claus R; Welte, Karl; Schlegelberger, Brigitte; Schrappe, Martin

2005-01-15

Treatment resistance, as indicated by the presence of high levels of minimal residual disease (MRD) after induction therapy and induction consolidation, is associated with a poor prognosis in childhood acute lymphoblastic leukemia (ALL). We hypothesized that treatment resistance is an intrinsic feature of ALL cells reflected in the gene expression pattern and that resistance to chemotherapy can be predicted before treatment. To test these hypotheses, gene expression signatures of ALL samples with high MRD load were compared with those of samples without measurable MRD during treatment. We identified 54 genes that clearly distinguished resistant from sensitive ALL samples. Genes with low expression in resistant samples were predominantly associated with cell-cycle progression and apoptosis, suggesting that impaired cell proliferation and apoptosis are involved in treatment resistance. Prediction analysis using randomly selected samples as a training set and the remaining samples as a test set revealed an accuracy of 84%. We conclude that resistance to chemotherapy seems at least in part to be an intrinsic feature of ALL cells. Because treatment response could be predicted with high accuracy, gene expression profiling could become a clinically relevant tool for treatment stratification in the early course of childhood ALL.

Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

PubMed

Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

Ovary Transcriptome Profiling via Artificial Intelligence Reveals a Transcriptomic Fingerprint Predicting Egg Quality in Striped Bass, Morone saxatilis

PubMed Central

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness. PMID:24820964

Gene expression profile associated with superimposed non-alcoholic fatty liver disease and hepatic fibrosis in patients with chronic hepatitis C.

PubMed

Younossi, Zobair M; Afendy, Arian; Stepanova, Maria; Hossain, Noreen; Younossi, Issah; Ankrah, Kathy; Gramlich, Terry; Baranova, Ancha

2009-10-01

Hepatic steatosis occurs in 40-70% of patients chronically infected with hepatitis C virus [chronic hepatitis C (CH-C)]. Hepatic steatosis in CH-C is associated with progressive liver disease and a low response rate to antiviral therapy. Gene expression profiles were examined in CH-C patients with and without hepatic steatosis, non-alcoholic steatohepatitis (NASH) and fibrosis. This study included 65 CH-C patients who were not receiving antiviral treatment. Total RNA was extracted from peripheral blood mononuclear cells, quantified and used for one-step reverse transcriptase-polymerase chain reaction to profile 153 mRNAs that were normalized with six 'housekeeping' genes and a reference RNA. Multiple regression and stepwise selection assessed differences in gene expression and the models' performances were evaluated. Models predicting the grade of hepatic steatosis in patients with CH-C genotype 3 involved two genes: SOCS1 and IFITM1, which progressively changed their expression level with the increasing grade of steatosis. On the other hand, models predicting hepatic steatosis in non-genotype 3 patients highlighted MIP-1 cytokine encoding genes: CCL3 and CCL4 as well as IFNAR and PRKRIR. Expression levels of PRKRIR and SMAD3 differentiated patients with and without superimposed NASH only in the non-genotype 3 cohort (area under the receiver operating characteristic curve=0.822, P-value 0.006]. Gene expression signatures related to hepatic fibrosis were not genotype specific. Gene expression might predict moderate to severe hepatic steatosis, NASH and fibrosis in patients with CH-C, providing potential insights into the pathogenesis of hepatic steatosis and fibrosis in these patients.

Identification and profiling of Cyprinus carpio microRNAs during ovary differentiation by deep sequencing.

PubMed

Wang, Fang; Jia, Yongfang; Wang, Po; Yang, Qianwen; Du, QiYan; Chang, ZhongJie

2017-04-28

MicroRNAs (miRNAs) are endogenous small non-coding RNAs that regulate gene expression by targeting specific mRNAs. However, the possible role of miRNAs in the ovary differentiation and development of fish is not well understood. In this study, we examined the expression profiles and differential expression of miRNAs during three key stages of ovarian development and different developmental stages in common carp Cyprinus carpio. A total of 8765 miRNAs were identified, including 2155 conserved miRNAs highly conserved among various species, 145 miRNAs registered in miRBase for common carp, and 6505 novel miRNAs identified in common carp for the first time. Comparison of miRNA expression profiles among the five libraries identified 714 co-expressed and 2382 specific expressed miRNAs. Overall, 150, 628, and 431 specifically expressed miRNAs were identified in primordial gonad, juvenile ovary, and adult ovary, respectively. MiR-6758-3p, miR-3050-5p, and miR-2985-3p were highly expressed in primordial gonad, miR-3544-5p, miR-6877-3p, and miR-9086-5p were highly expressed in juvenile ovary, and miR-154-3p, miR-5307-5p, and miR-3958-3p were highly expressed in adult ovary. Predicted target genes of specific miRNAs in primordial gonad were involved in many reproductive biology signaling pathways, including transforming growth factor-β, Wnt, oocyte meiosis, mitogen-activated protein kinase, Notch, p53, and gonadotropin-releasing hormone pathways. Target-gene prediction revealed upward trends in miRNAs targeting male-bias genes, including dmrt1, atm, gsdf, and sox9, and downward trends in miRNAs targeting female-bias genes including foxl2, smad3, and smad4. Other sex-related genes such as sf1 were also predicted to be miRNA target genes. This comprehensive miRNA transcriptome analysis demonstrated differential expression profiles of miRNAs during ovary development in common carp. These results could facilitate future exploitation of the sex-regulatory roles and mechanisms of miRNAs, especially in primordial gonads, while the specifically expressed miRNAs represent candidates for studying the mechanisms of ovary determination in Yellow River carp.

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

PubMed

Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

2014-07-01

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Macromolecular Expression and Function: A New Paradigm for NASA Risk Assessment

NASA Technical Reports Server (NTRS)

Richmond, Robert

2003-01-01

Predicting risks in humans of either acute effects such as bone loss or muscle wasting, or late effects such as cancer, is challenging. To an approximation, this is because uncertainties of exposure to stress factors or toxic agents and the uniformity of processing subsequent damage at the cellular level within a complex set of biological variables degrade the confidence of predicting pathologic outcome. A cellular biodosimeter that simultaneously reports 1) the type of damage due to that exposure, 2) the quantity of damage incurred by that exposure, and 3) the dataset used to assess risk of developing pathologic outcome caused by that exposure would therefore be useful for predicting ultimate risks faced by an individual, such as an astronaut. It is suggested that such a biodosimeter can be based upon analyses of gene-expression and protein expression whereby large datasets of cellular response to damage are obtained and analyzed for expression-profiles correlated with established end points and molecular markers predictive for risks being assessed. The usefulness of multiparametric cellular biodosimeters could be realized by quantitatively profiling these datasets using techniques of bioinformatics. Such an approach contributes to the foundation of molecular epidemiology as a new scientific discipline, and represents a new paradigm of risk assessment.

Suppressed anger, evaluative threat, and cardiovascular reactivity: a tripartite profile approach.

PubMed

Jorgensen, Randall S; Kolodziej, Monika E

2007-11-01

Despite decades of theory and research implicating suppressed anger in the development of cardiovascular disorders involving cardiovascular reactivity (CVR), to date the theoretical components of low anger expression, guilt feelings over agonistic reactions, and defensive strivings to avoid social disapproval have not been used conjointly to profile suppressed anger for the prediction of CVR. The purpose of this study, then, was to cluster analyze measures of anger expression, hostility guilt, and social defensiveness to create a suppressed anger profile (low anger expression, high hostility guilt, high social defensiveness) and a non-suppressed profile from a sample of college males. Social evaluative threat may be a potent stressor for people who defensively suppress anger expression. Thus, to examine the combined effects of suppressed anger and social evaluative threat, participants, prior to telling a story to a Thematic Apperception Card (TAT), were randomly assigned to either a high-threat (story will be compared to stories created by the mentally ill) or a low-threat condition (story used to study effects of talking on cardiovascular responses). Blood pressure (BP) and heart rate (HR) were monitored during a rest period and the subsequent TAT card period. As predicted, suppressed anger males in the high-threat condition showed the highest levels of diastolic BP and HR change from the rest period. The suppressed anger group's systolic BP reactivity was independent of threat manipulation. Research implications are discussed.

Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

PubMed

Noh, Haneul; Park, Charny; Park, Soojun; Lee, Young Seek; Cho, Soo Young; Seo, Hyemyung

2014-08-03

Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells. Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

PubMed

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Calculation of skin-friction coefficients for low Reynolds number turbulent boundary layer flows. M.S. Thesis - California Univ. at Davis

NASA Technical Reports Server (NTRS)

Barr, P. K.

1980-01-01

An analysis is presented of the reliability of various generally accepted empirical expressions for the prediction of the skin-friction coefficient C/sub f/ of turbulent boundary layers at low Reynolds numbers in zero-pressure-gradient flows on a smooth flat plate. The skin-friction coefficients predicted from these expressions were compared to the skin-friction coefficients of experimental profiles that were determined from a graphical method formulated from the law of the wall. These expressions are found to predict values that are consistently different than those obtained from the graphical method over the range 600 Re/sub theta 2000. A curve-fitted empirical relationship was developed from the present data and yields a better estimated value of C/sub f/ in this range. The data, covering the range 200 Re/sub theta 7000, provide insight into the nature of transitional flows. They show that fully developed turbulent boundary layers occur at Reynolds numbers Re/sub theta/ down to 425. Below this level there appears to be a well-ordered evolutionary process from the laminar to the turbulent profiles. These profiles clearly display the development of the turbulent core region and the shrinking of the laminar sublayer with increasing values of Re/sub theta/.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

PubMed Central

Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

Combination of MUC1 and MUC4 expression predicts clinical outcome in patients with oral squamous cell carcinoma.

PubMed

Kamikawa, Yoshiaki; Kanmura, Yuji; Hamada, Tomofumi; Yamada, Norishige; Macha, Muzafar A; Batra, Surinder K; Higashi, Michiyo; Yonezawa, Suguru; Sugihara, Kazumasa

2015-04-01

Both MUC1 and MUC4 are high molecular weight glycoproteins and are independent indicators of worse prognosis in many human epithelial cancers including oral squamous cell carcinoma (OSCC). However, there has been no investigation of the clinical importance of the co-expression of MUC1 and MUC4 in OSCC. The aim of this study was to evaluate the co-expression profile of MUC1/MUC4 and analyze the prognostic significance in OSCC. We examined the expression profile of MUC1 and MUC4 in OSCC tissues from 206 patients using immunohistochemistry. The co-expression profile of MUC1/MUC4 and its prognostic significance in OSCC was statistically analyzed. MUC1 and MUC4 overexpression were strongly correlated with each other (p < 0.0001) and a combination of both MUC1 and MUC4 expression was a powerful indicator for tumor aggressiveness such as tumor size (p = 0.014), lymph node metastasis (0.0001), tumor stage (p = 0.006), diffuse invasion (p = 0.028), and vascular invasion (p = 0.014). The MUC1/MUC4 double-positive patients showed the poorest overall and disease-free survival. Multivariate analysis revealed that MUC1/MUC4 double-positivity was the strong independent prognostic factor for overall and disease-free survival (p = 0.007 and (p = 0.0019), in addition to regional recurrence (p = 0.0025). Taken together, these observations indicate that the use of a combination of MUC1/MUC4 can predict outcomes for patients with OSCC. This combination is also a useful marker for predicting regional recurrence. MUC1 and MUC4 may be attractive targets for the selection of treatment methods in OSCC.

Artificial neural network classifier predicts neuroblastoma patients' outcome.

PubMed

Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

2016-11-08

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

Early gene expression profiles of patients with chronic hepatitis C treated with pegylated interferon-alfa and ribavirin.

PubMed

Younossi, Zobair M; Baranova, Ancha; Afendy, Arian; Collantes, Rochelle; Stepanova, Maria; Manyam, Ganiraju; Bakshi, Anita; Sigua, Christopher L; Chan, Joanne P; Iverson, Ayuko A; Santini, Christopher D; Chang, Sheng-Yung P

2009-03-01

Responsiveness to hepatitis C virus (HCV) therapy depends on viral and host factors. Our aim was to assess sustained virologic response (SVR)-associated early gene expression in patients with HCV receiving pegylated interferon-alpha2a (PEG-IFN-alpha2a) or PEG-IFN-alpha2b and ribavirin with the duration based on genotypes. Blood samples were collected into PAXgene tubes prior to treatment as well as 1, 7, 28, and 56 days after treatment. From the peripheral blood cells, total RNA was extracted, quantified, and used for one-step reverse transcription polymerase chain reaction to profile 154 messenger RNAs. Expression levels of messenger RNAs were normalized with six "housekeeping" genes and a reference RNA. Multiple regression and stepwise selection were performed to assess differences in gene expression at different time points, and predictive performance was evaluated for each model. A total of 68 patients were enrolled in the study and treated with combination therapy. The results of gene expression showed that SVR could be predicted by the gene expression of signal transducer and activator of transcription-6 (STAT-6) and suppressor of cytokine signaling-1 in the pretreatment samples. After 24 hours, SVR was predicted by the expression of interferon-dependent genes, and this dependence continued to be prominent throughout the treatment. Early gene expression during anti-HCV therapy may elucidate important molecular pathways that may be influencing the probability of achieving virologic response.

Profile of microRNA in Giant Panda Blood: A Resource for Immune-Related and Novel microRNAs

PubMed Central

Yang, Mingyu; Du, Lianming; Li, Wujiao; Shen, Fujun; Fan, Zhenxin; Jian, Zuoyi; Hou, Rong; Shen, Yongmei; Yue, Bisong; Zhang, Xiuyue

2015-01-01

The giant panda (Ailuropoda melanoleuca) is one of the world’s most beloved endangered mammals. Although the draft genome of this species had been assembled, little was known about the composition of its microRNAs (miRNAs) or their functional profiles. Recent studies demonstrated that changes in the expression of miRNAs are associated with immunity. In this study, miRNAs were extracted from the blood of four healthy giant pandas and sequenced by Illumina next generation sequencing technology. As determined by miRNA screening, a total of 276 conserved miRNAs and 51 novel putative miRNAs candidates were detected. After differential expression analysis, we noticed that the expressions of 7 miRNAs were significantly up-regulated in young giant pandas compared with that of adults. Moreover, 2 miRNAs were up-regulated in female giant pandas and 1 in the male individuals. Target gene prediction suggested that the miRNAs of giant panda might be relevant to the expressions of 4,602 downstream genes. Subseuqently, the predicted target genes were conducted to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and we found that these genes were mainly involved in host immunity, including the Ras signaling pathway, the PI3K-Akt signaling pathway, and the MAPK signaling pathway. In conclusion, our results provide the first miRNA profiles of giant panda blood, and the predicted functional analyses may open an avenue for further study of giant panda immunity. PMID:26599861

Profile of microRNA in Giant Panda Blood: A Resource for Immune-Related and Novel microRNAs.

PubMed

Yang, Mingyu; Du, Lianming; Li, Wujiao; Shen, Fujun; Fan, Zhenxin; Jian, Zuoyi; Hou, Rong; Shen, Yongmei; Yue, Bisong; Zhang, Xiuyue

2015-01-01

The giant panda (Ailuropoda melanoleuca) is one of the world's most beloved endangered mammals. Although the draft genome of this species had been assembled, little was known about the composition of its microRNAs (miRNAs) or their functional profiles. Recent studies demonstrated that changes in the expression of miRNAs are associated with immunity. In this study, miRNAs were extracted from the blood of four healthy giant pandas and sequenced by Illumina next generation sequencing technology. As determined by miRNA screening, a total of 276 conserved miRNAs and 51 novel putative miRNAs candidates were detected. After differential expression analysis, we noticed that the expressions of 7 miRNAs were significantly up-regulated in young giant pandas compared with that of adults. Moreover, 2 miRNAs were up-regulated in female giant pandas and 1 in the male individuals. Target gene prediction suggested that the miRNAs of giant panda might be relevant to the expressions of 4,602 downstream genes. Subseuqently, the predicted target genes were conducted to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and we found that these genes were mainly involved in host immunity, including the Ras signaling pathway, the PI3K-Akt signaling pathway, and the MAPK signaling pathway. In conclusion, our results provide the first miRNA profiles of giant panda blood, and the predicted functional analyses may open an avenue for further study of giant panda immunity.

Genome-wide DNA methylation profiling integrated with gene expression profiling identifies PAX9 as a novel prognostic marker in chronic lymphocytic leukemia.

PubMed

Rani, Lata; Mathur, Nitin; Gupta, Ritu; Gogia, Ajay; Kaur, Gurvinder; Dhanjal, Jaspreet Kaur; Sundar, Durai; Kumar, Lalit; Sharma, Atul

2017-01-01

In chronic lymphocytic leukemia (CLL), epigenomic and genomic studies have expanded the existing knowledge about the disease biology and led to the identification of potential biomarkers relevant for implementation of personalized medicine. In this study, an attempt has been made to examine and integrate the global DNA methylation changes with gene expression profile and their impact on clinical outcome in early stage CLL patients. The integration of DNA methylation profile ( n  = 14) with the gene expression profile ( n  = 21) revealed 142 genes as hypermethylated-downregulated and; 62 genes as hypomethylated-upregulated in early stage CLL patients compared to CD19+ B-cells from healthy individuals. The mRNA expression levels of 17 genes identified to be differentially methylated and/or differentially expressed was further examined in early stage CLL patients ( n  = 93) by quantitative real time PCR (RQ-PCR). Significant differences were observed in the mRNA expression of MEIS1 , PMEPA1 , SOX7 , SPRY1 , CDK6 , TBX2 , and SPRY2 genes in CLL cells as compared to B-cells from healthy individuals. The analysis in the IGHV mutation based categories (Unmutated = 39, Mutated = 54) revealed significantly higher mRNA expression of CRY1 and PAX9 genes in the IGHV unmutated subgroup ( p  < 0.001). The relative risk of treatment initiation was significantly higher among patients with high expression of CRY1 (RR = 1.91, p  = 0.005) or PAX9 (RR = 1.87, p  = 0.001). High expression of CRY1 (HR: 3.53, p  < 0.001) or PAX9 (HR: 3.14, p  < 0.001) gene was significantly associated with shorter time to first treatment. The high expression of PAX9 gene (HR: 3.29, 95% CI 1.172-9.272, p  = 0.016) was also predictive of shorter overall survival in CLL. The DNA methylation changes associated with mRNA expression of CRY1 and PAX9 genes allow risk stratification of early stage CLL patients. This comprehensive analysis supports the concept that the epigenetic changes along with the altered expression of genes have the potential to predict clinical outcome in early stage CLL patients.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles.

PubMed

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection.

Biological mechanism analysis of acute renal allograft rejection: integrated of mRNA and microRNA expression profiles

PubMed Central

Huang, Shi-Ming; Zhao, Xia; Zhao, Xue-Mei; Wang, Xiao-Ying; Li, Shan-Shan; Zhu, Yu-Hui

2014-01-01

Objectives: Renal transplantation is the preferred method for most patients with end-stage renal disease, however, acute renal allograft rejection is still a major risk factor for recipients leading to renal injury. To improve the early diagnosis and treatment of acute rejection, study on the molecular mechanism of it is urgent. Methods: MicroRNA (miRNA) expression profile and mRNA expression profile of acute renal allograft rejection and well-functioning allograft downloaded from ArrayExpress database were applied to identify differentially expressed (DE) miRNAs and DE mRNAs. DE miRNAs targets were predicted by combining five algorithm. By overlapping the DE mRNAs and DE miRNAs targets, common genes were obtained. Differentially co-expressed genes (DCGs) were identified by differential co-expression profile (DCp) and differential co-expression enrichment (DCe) methods in Differentially Co-expressed Genes and Links (DCGL) package. Then, co-expression network of DCGs and the cluster analysis were performed. Functional enrichment analysis for DCGs was undergone. Results: A total of 1270 miRNA targets were predicted and 698 DE mRNAs were obtained. While overlapping miRNA targets and DE mRNAs, 59 common genes were gained. We obtained 103 DCGs and 5 transcription factors (TFs) based on regulatory impact factors (RIF), then built the regulation network of miRNA targets and DE mRNAs. By clustering the co-expression network, 5 modules were obtained. Thereinto, module 1 had the highest degree and module 2 showed the most number of DCGs and common genes. TF CEBPB and several common genes, such as RXRA, BASP1 and AKAP10, were mapped on the co-expression network. C1R showed the highest degree in the network. These genes might be associated with human acute renal allograft rejection. Conclusions: We conducted biological analysis on integration of DE mRNA and DE miRNA in acute renal allograft rejection, displayed gene expression patterns and screened out genes and TFs that may be related to acute renal allograft rejection. PMID:25664019

MicroRNA Expression Profiles as Biomarkers of Minor Salivary Gland Inflammation and Dysfunction in Sjögren's Syndrome

PubMed Central

Alevizos, Ilias; Alexander, Stefanie; Turner, R. James; Illei, Gabor G.

2013-01-01

Objective MicroRNA reflect physiologic and pathologic processes and may be used as biomarkers of concurrent pathophysiologic events in complex settings such as autoimmune diseases. We generated microRNA microarray profiles from the minor salivary glands of control subjects without Sjögren's syndrome (SS) and patients with SS who had low-grade or high-grade inflammation and impaired or normal saliva production, to identify microRNA patterns specific to salivary gland inflammation or dysfunction. Methods MicroRNA expression profiles were generated by Agilent microRNA arrays. We developed a novel method for data normalization by identifying housekeeping microRNA. MicroRNA profiles were compared by unsupervised mathematical methods to test how well they distinguish between control subjects and various subsets of patients with SS. Several bioinformatics methods were used to predict the messenger RNA targets of the differentially expressed microRNA. Results MicroRNA expression patterns accurately distinguished salivary glands from control subjects and patients with SS who had low-degree or high-degree inflammation. Using real-time quantitative polymerase chain reaction, we validated 2 microRNA as markers of inflammation in an independent cohort. Comparing microRNA from patients with preserved or low salivary flow identified a set of differentially expressed microRNA, most of which were up-regulated in the group with decreased salivary gland function, suggesting that the targets of microRNA may have a protective effect on epithelial cells. The predicted biologic targets of microRNA associated with inflammation or salivary gland dysfunction identified both overlapping and distinct biologic pathways and processes. Conclusion Distinct microRNA expression patterns are associated with salivary gland inflammation and dysfunction in patients with SS, and microRNA represent a novel group of potential biomarkers. PMID:21280008

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PubMed Central

Kutchukian, Peter S.; Li, Jing; Tudor, Matthew

2017-01-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

Meta-analysis of Gene Expression in the Mouse Liver Reveals Biomarkers Associated with Inflammation Increased Early During Aging

EPA Science Inventory

Aging is associated with a predictable loss of cellular homeostasis, a decline in physiological function and an increase in various diseases. We hypothesized that similar age-related gene expression profiles would be observed in mice across independent studies. Employing a metaan...

Molecular Classifiers for Acute Kidney Transplant Rejection in Peripheral Blood by Whole Genome Gene Expression Profiling

PubMed Central

Kurian, S. M.; Williams, A. N.; Gelbart, T.; Campbell, D.; Mondala, T. S.; Head, S. R.; Horvath, S.; Gaber, L.; Thompson, R.; Whisenant, T.; Lin, W.; Langfelder, P.; Robison, E. H.; Schaffer, R. L.; Fisher, J. S.; Friedewald, J.; Flechner, S. M.; Chan, L. K.; Wiseman, A. C.; Shidban, H.; Mendez, R.; Heilman, R.; Abecassis, M. M.; Marsh, C. L.; Salomon, D. R.

2015-01-01

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction. PMID:24725967

Transcript profiling reveals expression differences in wild-type and glabrous soybean lines

PubMed Central

2011-01-01

Background Trichome hairs affect diverse agronomic characters such as seed weight and yield, prevent insect damage and reduce loss of water but their molecular control has not been extensively studied in soybean. Several detailed models for trichome development have been proposed for Arabidopsis thaliana, but their applicability to important crops such as cotton and soybean is not fully known. Results Two high throughput transcript sequencing methods, Digital Gene Expression (DGE) Tag Profiling and RNA-Seq, were used to compare the transcriptional profiles in wild-type (cv. Clark standard, CS) and a mutant (cv. Clark glabrous, i.e., trichomeless or hairless, CG) soybean isoline that carries the dominant P1 allele. DGE data and RNA-Seq data were mapped to the cDNAs (Glyma models) predicted from the reference soybean genome, Williams 82. Extending the model length by 250 bp at both ends resulted in significantly more matches of authentic DGE tags indicating that many of the predicted gene models are prematurely truncated at the 5' and 3' UTRs. The genome-wide comparative study of the transcript profiles of the wild-type versus mutant line revealed a number of differentially expressed genes. One highly-expressed gene, Glyma04g35130, in wild-type soybean was of interest as it has high homology to the cotton gene GhRDL1 gene that has been identified as being involved in cotton fiber initiation and is a member of the BURP protein family. Sequence comparison of Glyma04g35130 among Williams 82 with our sequences derived from CS and CG isolines revealed various SNPs and indels including addition of one nucleotide C in the CG and insertion of ~60 bp in the third exon of CS that causes a frameshift mutation and premature truncation of peptides in both lines as compared to Williams 82. Conclusion Although not a candidate for the P1 locus, a BURP family member (Glyma04g35130) from soybean has been shown to be abundantly expressed in the CS line and very weakly expressed in the glabrous CG line. RNA-Seq and DGE data are compared and provide experimental data on the expression of predicted soybean gene models as well as an overview of the genes expressed in young shoot tips of two closely related isolines. PMID:22029708

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.

Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.

PubMed

Xu, Joshua; Gong, Binsheng; Wu, Leihong; Thakkar, Shraddha; Hong, Huixiao; Tong, Weida

2016-03-15

Studies on gene expression in response to therapy have led to the discovery of pharmacogenomics biomarkers and advances in precision medicine. Whole transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene expression and has received wide adoption in the biomedical research community. However, its value in regulatory decision making requires rigorous assessment and consensus between various stakeholders, including the research community, regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC) consortium has made considerable progress in this direction, and is the subject of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites to assess cross-site and cross-platform reproducibility. The results demonstrated that relative gene expression measurements were consistently comparable across labs and platforms, but not so for the measurement of absolute expression levels. As part of the quality evaluation several studies were included to evaluate the utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma study profiled tumor samples from 498 pediatric neuroblastoma patients by both microarray and RNA-seq. RNA-seq offers more utilities than microarray in determining the transcriptomic characteristics of cancer. However, RNA-seq and microarray-based models were comparable in clinical endpoint prediction, even when including additional features unique to RNA-seq beyond gene expression. The toxicogenomics study compared microarray and RNA-seq profiles of the liver samples from rats exposed to 27 different chemicals representing multiple toxicity modes of action. Cross-platform concordance was dependent on chemical treatment and transcript abundance. Though both RNA-seq and microarray are suitable for developing gene expression based predictive models with comparable prediction performance, RNA-seq offers advantages over microarray in profiling genes with low expression. The rat BodyMap study provided a comprehensive rat transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the transferability study demonstrated that signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development using a comprehensive approach with two large clinical data sets. This result suggests continued usefulness of legacy microarray data in the coming RNA-seq era. In conclusion, the SEQC project enhances our understanding of RNA-seq and provides valuable guidelines for RNA-seq based clinical application and safety evaluation to advance precision medicine.

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

Global miRNA expression profile reveals novel molecular players in aneurysmal subarachnoid haemorrhage.

PubMed

Lopes, Katia de Paiva; Vinasco-Sandoval, Tatiana; Vialle, Ricardo Assunção; Paschoal, Fernando Mendes; Bastos, Vanessa Albuquerque P Aviz; Bor-Seng-Shu, Edson; Teixeira, Manoel Jacobsen; Yamada, Elizabeth Sumi; Pinto, Pablo; Vidal, Amanda Ferreira; Ribeiro-Dos-Santos, Arthur; Moreira, Fabiano; Santos, Sidney; Paschoal, Eric Homero Albuquerque; Ribeiro-Dos-Santos, Ândrea

2018-06-08

The molecular mechanisms behind aneurysmal subarachnoid haemorrhage (aSAH) are still poorly understood. Expression patterns of miRNAs may help elucidate the post-transcriptional gene expression in aSAH. Here, we evaluate the global miRNAs expression profile (miRnome) of patients with aSAH to identify potential biomarkers. We collected 33 peripheral blood samples (27 patients with cerebral aneurysm, collected 7 to 10 days after the haemorrhage, when usually is the cerebral vasospasm risk peak, and six controls). Then, were performed small RNA sequencing using an Illumina Next Generation Sequencing (NGS) platform. Differential expression analysis identified eight differentially expressed miRNAs. Among them, three were identified being up-regulated, and five down-regulated. miR-486-5p was the most abundant expressed and is associated with poor neurological admission status. In silico miRNA gene target prediction showed 148 genes associated with at least two differentially expressed miRNAs. Among these, THBS1 and VEGFA, known to be related to thrombospondin and vascular endothelial growth factor. Moreover, MYC gene was found to be regulated by four miRNAs, suggesting an important role in aneurysmal subarachnoid haemorrhage. Additionally, 15 novel miRNAs were predicted being expressed only in aSAH, suggesting possible involvement in aneurysm pathogenesis. These findings may help the identification of novel biomarkers of clinical interest.

Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer

PubMed Central

Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M.; Shapiro, Charles L.; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways. Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis. PMID:23405235

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

PubMed

Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2014-08-01

allylamino-17-demethoxygeldanamycin) downregulated HR, ATM and Fanconi Anemia pathways. In HR- proficient EOC cells, 17-AAG suppressed HR as assessed...downregulated HR (pɘ.005), ATM (p=0.015) and Fanconi Anemia (pɘ.005) pathways, and downregulated the expression levels of several genes of these

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689

A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2011-08-01

tumors as BRCA-like (BL) or non-BRCA-like ( NBL ) corresponding to tumors predicted to have a BRCAness phenotype (BL tumors) or not ( NBL tumors). In...of six specimens with ATM knock down had the BL signature and six of six control specimens had the NBL signature (Fisher’s exact two sided p=0.002...control specimens had the NBL signature (Fisher’s exact two sided p=0.067). Figure 2. BRCAness profile distinguishes between BRCA1 knock down

Gene Expression Profiling of Peripheral Blood From Kidney Transplant Recipients for the Early Detection of Digestive System Cancer.

PubMed

Kusaka, M; Okamoto, M; Takenaka, M; Sasaki, H; Fukami, N; Kataoka, K; Ito, T; Kenmochi, T; Hoshinaga, K; Shiroki, R

2017-06-01

Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract). Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm. The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period. The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system. Copyright © 2017 Elsevier Inc. All rights reserved.

Cancer survival classification using integrated data sets and intermediate information.

PubMed

Kim, Shinuk; Park, Taesung; Kon, Mark

2014-09-01

Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS was 75.51% (RF), 87.76% (SVM) 85.71% (FSCOX_median), 85.71% (FSCOX_SVM). These results are higher than the results of using miRNA expression and mRNA expression alone. In addition we predict 16 hsa-miR-23b and hsa-miR-27b target genes in ovarian cancer data sets, obtained by SVM-based feature selection through integration of sequence information and gene expression profiles. Among the approaches used, the integrated miRNA and mRNA data set yielded better results than the individual data sets. The best performance was achieved using the FSCOX_SVM method with independent feature selection, which uses intermediate survival information between short-term and long-term survival time and the combination of the 2 different data sets. The results obtained using the combined data set suggest that there are some strong interactions between miRNA and mRNA features that are not detectable in the individual analyses. Copyright © 2014 Elsevier B.V. All rights reserved.

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

PubMed

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

The role of childhood maltreatment in the altered trait and global expression of personality in cocaine addiction

PubMed Central

Brents, Lisa K; Tripathi, Shanti Prakash; Young, Jonathan; James, G Andrew; Kilts, Clinton D

2015-01-01

Background and aims Drug addictions are debilitating disorders that are highly associated with personality abnormalities. Early life stress (ELS) is a common risk factor for addiction and personality disturbances, but the relationships between ELS, addiction, and personality are poorly understood. Methods Ninety-five research participants were assessed for and grouped by ELS history and cocaine dependence. NEO-FFI personality measures were compared between the groups to define ELS− and addiction-related differences in personality traits. ELS and cocaine dependence were then examined as predictors of personality trait scores. Finally, k-means clustering was used to uncover clusters of personality trait configurations within the sample. Odds of cluster membership across subject groups was then determined. Results Trait expression differed significantly across subject groups. Cocaine-dependent subjects with a history of ELS (cocaine+/ELS+) displayed the greatest deviations in normative personality. Cocaine dependence significantly predicted four traits, while ELS predicted neuroticism and agreeableness; there was no interaction effect between ELS and cocaine dependence. The cluster analysis identified four distinct personality profiles: Open, Gregarious, Dysphoric, and Closed. Distribution of these profiles across subject groups differed significantly. Inclusion in cocaine+/ELS+, cocaine−/ELS+, and cocaine−/ELS− groups significantly increased the odds of expressing the Dysphoric, Open and Gregarious profiles, respectively. Conclusions Cocaine dependence and early life stress were significantly and differentially associated with altered expression of individual personality traits and their aggregation as personality profiles, suggesting that individuals who are at-risk for developing addictions due to ELS exposure may benefit from personality centered approaches as an early intervention and prevention. PMID:25805246

A stochastic model for optimizing composite predictors based on gene expression profiles.

PubMed

Ramanathan, Murali

2003-07-01

This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.

PubMed

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.

Gene Expression Differences in Peripheral Blood of Parkinson’s Disease Patients with Distinct Progression Profiles

PubMed Central

Soreq, Lilach; Lobo, Patrícia P.; Mestre, Tiago; Coelho, Miguel; Rosa, Mário M.; Gonçalves, Nilza; Wales, Pauline; Mendes, Tiago; Gerhardt, Ellen; Fahlbusch, Christiane; Bonifati, Vincenzo; Bonin, Michael; Miltenberger-Miltényi, Gabriel; Borovecki, Fran; Soreq, Hermona; Ferreira, Joaquim J.; F. Outeiro, Tiago

2016-01-01

The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson’s disease (PD) progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression analysis in aiding patient stratification and therapeutic intervention. PMID:27322389

Cross-Platform Toxicogenomics for the Prediction of Non-Genotoxic Hepatocarcinogenesis in Rat

PubMed Central

Metzger, Ute; Templin, Markus F.; Plummer, Simon; Ellinger-Ziegelbauer, Heidrun; Zell, Andreas

2014-01-01

In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens. PMID:24830643

Protein profiles associated with survival in lung adenocarcinoma

PubMed Central

Chen, Guoan; Gharib, Tarek G; Wang, Hong; Huang, Chiang-Ching; Kuick, Rork; Thomas, Dafydd G.; Shedden, Kerby A.; Misek, David E.; Taylor, Jeremy M. G.; Giordano, Thomas J.; Kardia, Sharon L. R.; Iannettoni, Mark D.; Yee, John; Hogg, Philip J.; Orringer, Mark B.; Hanash, Samir M.; Beer, David G.

2003-01-01

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer. PMID:14573703

Blood gene expression profiling of an early acetaminophen response.

PubMed

Bushel, P R; Fannin, R D; Gerrish, K; Watkins, P B; Paules, R S

2017-06-01

Acetaminophen can adversely affect the liver especially when overdosed. We used whole blood as a surrogate to identify genes as potential early indicators of an acetaminophen-induced response. In a clinical study, healthy human subjects were dosed daily with 4 g of either acetaminophen or placebo pills for 7 days and evaluated over the course of 14 days. Alanine aminotransferase (ALT) levels for responders to acetaminophen increased between days 4 and 9 after dosing, and 12 genes were detected with expression profiles significantly altered within 24 h. The early responsive genes separated the subjects by class and dose period. In addition, the genes clustered patients who overdosed on acetaminophen apart from controls and also predicted the exposure classifications with 100% accuracy. The responsive genes serve as early indicators of an acetaminophen exposure, and their gene expression profiles can potentially be evaluated as molecular indicators for further consideration.

Blood Gene Expression Profiling of an Early Acetaminophen Response

PubMed Central

Bushel, Pierre R.; Fannin, Rick D.; Gerrish, Kevin; Watkins, Paul B.; Paules, Richard S.

2018-01-01

Acetaminophen can adversely affect the liver especially when overdosed. We used whole blood as a surrogate to identify genes as potential early indicators of an acetaminophen-induced response. In a clinical study, healthy human subjects were dosed daily with 4g of either acetaminophen or placebo pills for 7 days and evaluated over the course of 14 days. Alanine aminotransferase (ALT) levels for responders to acetaminophen increased between days 4 and 9 after dosing and 12 genes were detected with expression profiles significantly altered within 24 hrs. The early responsive genes separated the subjects by class and dose period. In addition, the genes clustered patients who overdosed on acetaminophen apart from controls and also predicted the exposure classifications with 100% accuracy. The responsive genes serve as early indicators of an acetaminophen exposure and their gene expression profiles can potentially be evaluated as molecular indicators for further consideration. PMID:26927286

Genome-wide analysis and expression profiling of the Solanum tuberosum aquaporins.

PubMed

Venkatesh, Jelli; Yu, Jae-Woong; Park, Se Won

2013-12-01

Aquaporins belongs to the major intrinsic proteins involved in the transcellular membrane transport of water and other small solutes. A comprehensive genome-wide search for the homologues of Solanum tuberosum major intrinsic protein (MIP) revealed 41 full-length potato aquaporin genes. All potato aquaporins are grouped into five subfamilies; plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), NOD26-like intrinsic proteins (NIPs), small basic intrinsic proteins (SIPs) and x-intrinsic proteins (XIPs). Functional predictions based on the aromatic/arginine (ar/R) selectivity filters and Froger's positions showed a remarkable difference in substrate transport specificity among subfamilies. The expression pattern of potato aquaporins, examined by qPCR analysis, showed distinct expression profiles in various organs and tuber developmental stages. Furthermore, qPCR analysis of potato plantlets, subjected to various abiotic stresses revealed the marked effect of stresses on expression levels of aquaporins. Taken together, the expression profiles of aquaporins imply that aquaporins play important roles in plant growth and development, in addition to maintaining water homeostasis in response to environmental stresses. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism.

PubMed

Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E

2007-12-01

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Genes associated with metabolic syndrome predict disease-free survival in stage II colorectal cancer patients. A novel link between metabolic dysregulation and colorectal cancer.

PubMed

Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Ramos, Ricardo; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B; Reglero, Guillermo; Feliu, Jaime; Ramírez de Molina, Ana

2014-12-01

Studies have recently suggested that metabolic syndrome and its components increase the risk of colorectal cancer. Both diseases are increasing in most countries, and the genetic association between them has not been fully elucidated. The objective of this study was to assess the association between genetic risk factors of metabolic syndrome or related conditions (obesity, hyperlipidaemia, diabetes mellitus type 2) and clinical outcome in stage II colorectal cancer patients. Expression levels of several genes related to metabolic syndrome and associated alterations were analysed by real-time qPCR in two equivalent but independent sets of stage II colorectal cancer patients. Using logistic regression models and cross-validation analysis with all tumour samples, we developed a metabolic syndrome-related gene expression profile to predict clinical outcome in stage II colorectal cancer patients. The results showed that a gene expression profile constituted by genes previously related to metabolic syndrome was significantly associated with clinical outcome of stage II colorectal cancer patients. This metabolic profile was able to identify patients with a low risk and high risk of relapse. Its predictive value was validated using an independent set of stage II colorectal cancer patients. The identification of a set of genes related to metabolic syndrome that predict survival in intermediate-stage colorectal cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy and avoid the toxic and unnecessary chemotherapy in patients classified as low risk. Our results also confirm the linkage between metabolic disorder and colorectal cancer and suggest the potential for cancer prevention and/or treatment by targeting these genes. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Estimating replicate time shifts using Gaussian process regression

PubMed Central

Liu, Qiang; Andersen, Bogi; Smyth, Padhraic; Ihler, Alexander

2010-01-01

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual replicate. Our approach is based on Gaussian process regression (GPR) combined with a probabilistic model that accounts for uncertainty about the biological development time of each replicate. Results: We apply GPR with uncertain measurement times to a microarray dataset of mRNA expression for the hair-growth cycle in mouse back skin, predicting both profile shapes and biological times for each replicate. The predicted time shifts show high consistency with independently obtained morphological estimates of relative development. We also show that the method systematically reduces prediction error on out-of-sample data, significantly reducing the mean squared error in a cross-validation study. Availability: Matlab code for GPR with uncertain time shifts is available at http://sli.ics.uci.edu/Code/GPRTimeshift/ Contact: ihler@ics.uci.edu PMID:20147305

Prediction of the acoustic pressure above periodically uneven facings in industrial workplaces

NASA Astrophysics Data System (ADS)

Ducourneau, J.; Bos, L.; Planeau, V.; Faiz, Adil; Skali Lami, Salah; Nejade, A.

2010-05-01

The aim of this work is to predict sound pressure in front of wall facings based on periodic sound scattering surface profiles. The method involves investigating plane wave reflections randomly incident upon an uneven surface. The waveguide approach is well suited to the geometries usually encountered in industrial workplaces. This method simplifies the profile geometry by using elementary rectangular volumes. The acoustic field in the profile interstices can then be expressed as the superposition of waveguide modes. In past work, walls considered are of infinite dimensions and are subjected to a periodic surface profile in only one direction. We therefore generalise this approach by extending its applicability to "double-periodic" wall facings. Free-field measurements have been taken and the observed agreement between numerical and experimental results supports the validity of the waveguide method.

A community effort to assess and improve drug sensitivity prediction algorithms

PubMed Central

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2015-01-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods. PMID:24880487

A community effort to assess and improve drug sensitivity prediction algorithms.

PubMed

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2014-12-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.

Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

PubMed

Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

PubMed Central

Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

Temperature-Dependent Kinetic Prediction for Reactions Described by Isothermal Mathematics

DOE PAGES

Dinh, L. N.; Sun, T. C.; McLean, W.

2016-09-12

Most kinetic models are expressed in isothermal mathematics. In addition, this may lead unaware scientists either to the misconception that classical isothermal kinetic models cannot be used for any chemical process in an environment with a time-dependent temperature profile or, even worse, to a misuse of them. In reality, classical isothermal models can be employed to make kinetic predictions for reactions in environments with time-dependent temperature profiles, provided that there is a continuity/conservation in the reaction extent at every temperature–time step. In this article, fundamental analyses, illustrations, guiding tables, and examples are given to help the interested readers using eithermore » conventional isothermal reacted fraction curves or rate equations to make proper kinetic predictions for chemical reactions in environments with temperature profiles that vary, even arbitrarily, with time simply by the requirement of continuity/conservation of reaction extent whenever there is an external temperature change.« less

Transcriptional network inference from functional similarity and expression data: a global supervised approach.

PubMed

Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc

2012-01-06

An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.

A deep auto-encoder model for gene expression prediction.

PubMed

Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

2017-11-17

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

Sialotranscriptomics of Rhipicephalus zambeziensis reveals intricate expression profiles of secretory proteins and suggests tight temporal transcriptional regulation during blood-feeding.

PubMed

de Castro, Minique Hilda; de Klerk, Daniel; Pienaar, Ronel; Rees, D Jasper G; Mans, Ben J

2017-08-10

Ticks secrete a diverse mixture of secretory proteins into the host to evade its immune response and facilitate blood-feeding, making secretory proteins attractive targets for the production of recombinant anti-tick vaccines. The largely neglected tick species, Rhipicephalus zambeziensis, is an efficient vector of Theileria parva in southern Africa but its available sequence information is limited. Next generation sequencing has advanced sequence availability for ticks in recent years and has assisted the characterisation of secretory proteins. This study focused on the de novo assembly and annotation of the salivary gland transcriptome of R. zambeziensis and the temporal expression of secretory protein transcripts in female and male ticks, before the onset of feeding and during early and late feeding. The sialotranscriptome of R. zambeziensis yielded 23,631 transcripts from which 13,584 non-redundant proteins were predicted. Eighty-six percent of these contained a predicted start and stop codon and were estimated to be putatively full-length proteins. A fifth (2569) of the predicted proteins were annotated as putative secretory proteins and explained 52% of the expression in the transcriptome. Expression analyses revealed that 2832 transcripts were differentially expressed among feeding time points and 1209 between the tick sexes. The expression analyses further indicated that 57% of the annotated secretory protein transcripts were differentially expressed. Dynamic expression profiles of secretory protein transcripts were observed during feeding of female ticks. Whereby a number of transcripts were upregulated during early feeding, presumably for feeding site establishment and then during late feeding, 52% of these were downregulated, indicating that transcripts were required at specific feeding stages. This suggested that secretory proteins are under stringent transcriptional regulation that fine-tunes their expression in salivary glands during feeding. No open reading frames were predicted for 7947 transcripts. This class represented 17% of the differentially expressed transcripts, suggesting a potential transcriptional regulatory function of long non-coding RNA in tick blood-feeding. The assembled sialotranscriptome greatly expands the sequence availability of R. zambeziensis, assists in our understanding of the transcription of secretory proteins during blood-feeding and will be a valuable resource for future vaccine candidate selection.

MicroRNA signature of the human developing pancreas.

PubMed

Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L

2010-09-22

MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas.

MicroRNA signature of the human developing pancreas

PubMed Central

2010-01-01

Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas. PMID:20860821

MicroRNA Profile Predicts Recurrence after Resection in Patients with Hepatocellular Carcinoma within the Milan Criteria

PubMed Central

Sato, Fumiaki; Hatano, Etsuro; Kitamura, Koji; Myomoto, Akira; Fujiwara, Takeshi; Takizawa, Satoko; Tsuchiya, Soken; Tsujimoto, Gozoh; Uemoto, Shinji; Shimizu, Kazuharu

2011-01-01

Objective Hepatocellular carcinoma (HCC) is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection. Methods We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out cross-validation method, and the time-averaged area under the ROC curve (ta-AUROC). Results The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs) than in the tumor-derived microRNAs (T-miRs, P<0.0001). The best ta-AUROC using the whole dataset, T-miRs, N-miRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P = 0.00029). The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P<0.0001). This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the ‘field effect’. Conclusion microRNA profiling can predict HCC recurrence in Milan criteria cases. PMID:21298008

Unravelling site-specific breast cancer metastasis: a microRNA expression profiling study

PubMed Central

Schrijver, Willemijne A.M.E.; van Diest, Paul J.; Moelans, Cathy B

2017-01-01

Distant metastasis is still the main cause of death from breast cancer. MicroRNAs (miRs) are important regulators of many physiological and pathological processes, including metastasis. Molecular breast cancer subtypes are known to show a site-specific pattern of metastases formation. In this study, we set out to determine the underlying molecular mechanisms of site-specific breast cancer metastasis by microRNA expression profiling. To identify a miR signature for metastatic breast carcinoma that could predict metastatic localization, we compared global miR expression in 23 primary breast cancer specimens with their corresponding multiple distant metastases to ovary (n=9), skin (n=12), lung (n=10), brain (n=4) and gastrointestinal tract (n=10) by miRCURY microRNA expression arrays. For validation, we performed quantitative real-time (qRT) PCR on the discovery cohort and on an independent validation cohort of 29 primary breast cancer specimens and their matched metastases. miR expression was highly patient specific and miR signatures in the primary tumor were largely retained in the metastases, with the exception of several differentially expressed, location specific miRs. Validation with qPCR demonstrated that hsa-miR-106b-5p was predictive for the development of lung metastases. In time, the second metastasis often showed a miR upregulation compared to the first metastasis. This study discovered a metastatic site-specific miR and found miR expression to be highly patient specific. This may lead to novel biomarkers predicting site of distant metastases, and to adjuvant, personalized targeted therapy strategies that could prevent such metastases from becoming clinically manifest. PMID:27902972

Unravelling site-specific breast cancer metastasis: a microRNA expression profiling study.

PubMed

Schrijver, Willemijne A M E; van Diest, Paul J; Moelans, Cathy B

2017-01-10

Distant metastasis is still the main cause of death from breast cancer. MicroRNAs (miRs) are important regulators of many physiological and pathological processes, including metastasis. Molecular breast cancer subtypes are known to show a site-specific pattern of metastases formation. In this study, we set out to determine the underlying molecular mechanisms of site-specific breast cancer metastasis by microRNA expression profiling.To identify a miR signature for metastatic breast carcinoma that could predict metastatic localization, we compared global miR expression in 23 primary breast cancer specimens with their corresponding multiple distant metastases to ovary (n=9), skin (n=12), lung (n=10), brain (n=4) and gastrointestinal tract (n=10) by miRCURY microRNA expression arrays. For validation, we performed quantitative real-time (qRT) PCR on the discovery cohort and on an independent validation cohort of 29 primary breast cancer specimens and their matched metastases.miR expression was highly patient specific and miR signatures in the primary tumor were largely retained in the metastases, with the exception of several differentially expressed, location specific miRs. Validation with qPCR demonstrated that hsa-miR-106b-5p was predictive for the development of lung metastases. In time, the second metastasis often showed a miR upregulation compared to the first metastasis.This study discovered a metastatic site-specific miR and found miR expression to be highly patient specific. This may lead to novel biomarkers predicting site of distant metastases, and to adjuvant, personalized targeted therapy strategies that could prevent such metastases from becoming clinically manifest.

Bone Metastasis in Advanced Breast Cancer: Analysis of Gene Expression Microarray.

PubMed

Cosphiadi, Irawan; Atmakusumah, Tubagus D; Siregar, Nurjati C; Muthalib, Abdul; Harahap, Alida; Mansyur, Muchtarruddin

2018-03-08

Approximately 30% to 40% of breast cancer recurrences involve bone metastasis (BM). Certain genes have been linked to BM; however, none have been able to predict bone involvement. In this study, we analyzed gene expression profiles in advanced breast cancer patients to elucidate genes that can be used to predict BM. A total of 92 advanced breast cancer patients, including 46 patients with BM and 46 patients without BM, were identified for this study. Immunohistochemistry and gene expression analysis was performed on 81 formalin-fixed paraffin-embedded samples. Data were collected through medical records, and gene expression of 200 selected genes compiled from 6 previous studies was performed using NanoString nCounter. Genetic expression profiles showed that 22 genes were significantly differentially expressed between breast cancer patients with metastasis in bone and other organs (BM+) and non-BM, whereas subjects with only BM showed 17 significantly differentially expressed genes. The following genes were associated with an increasing incidence of BM in the BM+ group: estrogen receptor 1 (ESR1), GATA binding protein 3 (GATA3), and melanophilin with an area under the curve (AUC) of 0.804. In the BM group, the following genes were associated with an increasing incidence of BM: ESR1, progesterone receptor, B-cell lymphoma 2, Rab escort protein, N-acetyltransferase 1, GATA3, annexin A9, and chromosome 9 open reading frame 116. ESR1 and GATA3 showed an increased strength of association with an AUC of 0.928. A combination of the identified 3 genes in BM+ and 8 genes in BM showed better prediction than did each individual gene, and this combination can be used as a training set. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Immunohistochemical expression profiles of mucin antigens in salivary gland mucoepidermoid carcinoma: MUC4- and MUC6-negative expression predicts a shortened survival in the early postoperative phase.

PubMed

Honjo, Kie; Hiraki, Tsubasa; Higashi, Michiyo; Noguchi, Hirotsugu; Nomoto, Mitsuharu; Yoshimura, Takuya; Batra, Surinder K; Yonezawa, Suguru; Semba, Ichiro; Nakamura, Norifumi; Tanimoto, Akihide; Yamada, Sohsuke

2018-02-01

In mucoepidermoid carcinoma (MEC), the most common salivary gland carcinoma, there is a lack of novel prognostic markers, but post-operative early recurrence strongly affects the clinical course and a poor outcome. It is critical to predict which MEC patients are prone to develop recurrence/metastases. Mucins play pivotal roles in influencing cancer biology, thus affecting cell differentiation, adhesion, carcinoma invasion, aggressiveness and/or metastatic potential. Our aim is to elucidate the significance of expression profiles for mucins, particularly MUC4 and MUC6, and their correlations with various clinicopathological features and recurrence in salivary gland MECs. We performed immunohistochemical analyses on patients with surgically resected primary MEC using antibodies against mucin core proteins MUC4/8G7 and MUC6/CLH5 in 73 paraffin-embedded samples. Recurrence was noted in 15 of 73 (20.5%) patients. MUC4 or MUC6 expression was considered to be negative when <30% or 0% of the MEC cells showed positive staining, respectively. MUC4- and/or MUC6-negative expression respectively and variably showed a significant relationship to pathological tumor high-grade, the presence of lymphovascular invasion, lymph node metastasis and/or tumor-related death. In addition, MUC4 showed significantly negative co-expression with MUC6. Kaplan-Meier analyses revealed that not only single MUC4/6-negative expression but also the combination of both predicted significantly shorter disease-free and disease-specific survivals in MECs, especially within the first two years postoperatively. Therefore, each mucin plays a pivotal role in the pathogenesis of MEC progression. The detection of MUC4 and/or MUC6 might be a powerful parameter in the clinical management of MECs in the early postsurgical phase.

Extension of the Helmholtz-Smoluchowski velocity to the hydrophobic microchannels with velocity slip.

PubMed

Park, H M; Kim, T W

2009-01-21

Electrokinetic flows through hydrophobic microchannels experience velocity slip at the microchannel wall, which affects volumetric flow rate and solute retention time. The usual method of predicting the volumetric flow rate and velocity profile for hydrophobic microchannels is to solve the Navier-Stokes equation and the Poisson-Boltzmann equation for the electric potential with the boundary condition of velocity slip expressed by the Navier slip coefficient, which is computationally demanding and defies analytic solutions. In the present investigation, we have devised a simple method of predicting the velocity profiles and volumetric flow rates of electrokinetic flows by extending the concept of the Helmholtz-Smoluchowski velocity to microchannels with Navier slip. The extended Helmholtz-Smoluchowski velocity is simple to use and yields accurate results as compared to the exact solutions. Employing the extended Helmholtz-Smoluchowski velocity, the analytical expressions for volumetric flow rate and velocity profile for electrokinetic flows through rectangular microchannels with Navier slip have been obtained at high values of zeta potential. The range of validity of the extended Helmholtz-Smoluchowski velocity is also investigated.

A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons

PubMed Central

Tian, Tian; Salis, Howard M.

2015-01-01

Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. PMID:26117546

A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger

PubMed Central

Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; van den Hondel, Cees A.; Ram, Arthur F.; Meyer, Vera

2016-01-01

Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes. PMID:27835655

A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger.

PubMed

Paege, Norman; Jung, Sascha; Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; Nitsche, Benjamin M; van den Hondel, Cees A; Ram, Arthur F; Meyer, Vera

2016-01-01

Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes.

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Integrative functional transcriptomic analyses implicate specific molecular pathways in pulmonary toxicity from exposure to aluminum oxide nanoparticles.

PubMed

Li, Xiaobo; Zhang, Chengcheng; Bian, Qian; Gao, Na; Zhang, Xin; Meng, Qingtao; Wu, Shenshen; Wang, Shizhi; Xia, Yankai; Chen, Rui

2016-09-01

Gene expression profiling has developed rapidly in recent years and it can predict and define mechanisms underlying chemical toxicity. Here, RNA microarray and computational technology were used to show that aluminum oxide nanoparticles (Al2O3 NPs) were capable of triggering up-regulation of genes related to the cell cycle and cell death in a human A549 lung adenocarcinoma cell line. Gene expression levels were validated in Al2O3 NPs exposed A549 cells and mice lung tissues, most of which showed consistent trends in regulation. Gene-transcription factor network analysis coupled with cell- and animal-based assays demonstrated that the genes encoding PTPN6, RTN4, BAX and IER play a role in the biological responses induced by the nanoparticle exposure, which caused cell death and cell cycle arrest in the G2/S phase. Further, down-regulated PTPN6 expression demonstrated a core role in the network, thus expression level of PTPN6 was rescued by plasmid transfection, which showed ameliorative effects of A549 cells against cell death and cell cycle arrest. These results demonstrate the feasibility of using gene expression profiling to predict cellular responses induced by nanomaterials, which could be used to develop a comprehensive knowledge of nanotoxicity.

microRNA expression profiling in fetal single ventricle malformation identified by deep sequencing.

PubMed

Yu, Zhang-Bin; Han, Shu-Ping; Bai, Yun-Fei; Zhu, Chun; Pan, Ya; Guo, Xi-Rong

2012-01-01

microRNAs (miRNAs) have emerged as key regulators in many biological processes, particularly cardiac growth and development, although the specific miRNA expression profile associated with this process remains to be elucidated. This study aimed to characterize the cellular microRNA profile involved in the development of congenital heart malformation, through the investigation of single ventricle (SV) defects. Comprehensive miRNA profiling in human fetal SV cardiac tissue was performed by deep sequencing. Differential expression of 48 miRNAs was revealed by sequencing by oligonucleotide ligation and detection (SOLiD) analysis. Of these, 38 were down-regulated and 10 were up-regulated in differentiated SV cardiac tissue, compared to control cardiac tissue. This was confirmed by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. Predicted target genes of the 48 differentially expressed miRNAs were analyzed by gene ontology and categorized according to cellular process, regulation of biological process and metabolic process. Pathway-Express analysis identified the WNT and mTOR signaling pathways as the most significant processes putatively affected by the differential expression of these miRNAs. The candidate genes involved in cardiac development were identified as potential targets for these differentially expressed microRNAs and the collaborative network of microRNAs and cardiac development related-mRNAs was constructed. These data provide the basis for future investigation of the mechanism of the occurrence and development of fetal SV malformations.

Prediction of epigenetically regulated genes in breast cancer cell lines.

PubMed

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

2010-06-04

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

MicroRNA expression profiling in alveolar macrophages of indigenous Chinese Tongcheng pigs infected with PRRSV in vivo.

PubMed

Zhou, Xiang; Michal, Jennifer J; Jiang, Zhihua; Liu, Bang

2017-11-01

Porcine respiratory and reproductive syndrome (PRRS), caused by PRRS virus (PRRSV), is one of the most serious infectious diseases in the swine industry worldwide. Indigenous Chinese Tongcheng (TC) pigs reportedly show strong resistance to PRRSV infection. The miRNA expression profiles of porcine alveolar macrophages (PAMs) of control TC pigs and those infected with PRRSV in vivo were analyzed by high-throughput sequencing to explore changes induced by infection. A total of 182 known miRNAs including 101 miRNA-5p and 81 miRNA-3p were identified with 23 up-regulated differentially expressed miRNAs (DEmiRNAs) and 25 down-regulated DEmiRNAs. Gene Ontology analysis showed that predicted target genes for the DEmiRNAs were enriched in immune response, transcription regulation, and cell death. The integrative analysis of mRNA and miRNA expression revealed that down-regulated methylation-related genes (DNMT1 and DNMT3b) were targeted by five up-regulated DEmiRNAs. Furthermore, 35 pairs of miRNAs (70 miRNAs) were co-expressed after PRRSV infection and six pairs were co-expressed differently. Our results describe miRNA expression profiles of TC pigs in response to PRRSV infection and lay a strong foundation for developing novel therapies to control PRRS in pigs.

A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy.

PubMed

Gillet, Jean-Pierre; Andersen, Jesper B; Madigan, James P; Varma, Sudhir; Bagni, Rachel K; Powell, Katie; Burgan, William E; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V; Thorgeirsson, Snorri S; Gottesman, Michael M

2016-02-01

Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. U.S. Government work not protected by U.S. copyright.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

Arsenic responsive microRNAs in vivo and their potential involvement in arsenic-induced oxidative stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Xuefeng, E-mail: xuefengr@buffalo.edu; Department of Pharmacology and Toxicology, School of Biomedical Sciences, The State University of New York, Buffalo, NY 14214; Gaile, Daniel P.

Arsenic exposure is postulated to modify microRNA (miRNA) expression, leading to changes of gene expression and toxicities, but studies relating the responses of miRNAs to arsenic exposure are lacking, especially with respect to in vivo studies. We utilized high-throughput sequencing technology and generated miRNA expression profiles of liver tissues from Sprague Dawley (SD) rats exposed to various concentrations of sodium arsenite (0, 0.1, 1, 10 and 100 mg/L) for 60 days. Unsupervised hierarchical clustering analysis of the miRNA expression profiles clustered the SD rats into different groups based on the arsenic exposure status, indicating a highly significant association between arsenicmore » exposure and cluster membership (p-value of 0.0012). Multiple miRNA expressions were altered by arsenic in an exposure concentration-dependent manner. Among the identified arsenic-responsive miRNAs, several are predicted to target Nfe2l2-regulated antioxidant genes, including glutamate–cysteine ligase (GCL) catalytic subunit (GCLC) and modifier subunit (GCLM) which are involved in glutathione (GSH) synthesis. Exposure to low concentrations of arsenic increased mRNA expression for Gclc and Gclm, while high concentrations significantly reduced their expression, which were correlated to changes in hepatic GCL activity and GSH level. Moreover, our data suggested that other mechanisms, e.g., miRNAs, rather than Nfe2l2-signaling pathway, could be involved in the regulation of mRNA expression of Gclc and Gclm post-arsenic exposure in vivo. Together, our findings show that arsenic exposure disrupts the genome-wide expression of miRNAs in vivo, which could lead to the biological consequence, such as an altered balance of antioxidant defense and oxidative stress. - Highlights: • Chronic arsenic exposure induces changes of hepatic miRNA expression profiles. • Hepatic GCL activity and GSH level in rats are altered following arsenic exposure. • Arsenic induced GCL expression change is independent to Nfe2l2-signaling pathway. • Expression of several miRNAs predicted to target GCL changed after arsenic exposure.« less

Predicting Gene Expression Level from Relative Codon Usage Bias: An Application to Escherichia coli Genome

PubMed Central

Roymondal, Uttam; Das, Shibsankar; Sahoo, Satyabrata

2009-01-01

We present an expression measure of a gene, devised to predict the level of gene expression from relative codon bias (RCB). There are a number of measures currently in use that quantify codon usage in genes. Based on the hypothesis that gene expressivity and codon composition is strongly correlated, RCB has been defined to provide an intuitively meaningful measure of an extent of the codon preference in a gene. We outline a simple approach to assess the strength of RCB (RCBS) in genes as a guide to their likely expression levels and illustrate this with an analysis of Escherichia coli (E. coli) genome. Our efforts to quantitatively predict gene expression levels in E. coli met with a high level of success. Surprisingly, we observe a strong correlation between RCBS and protein length indicating natural selection in favour of the shorter genes to be expressed at higher level. The agreement of our result with high protein abundances, microarray data and radioactive data demonstrates that the genomic expression profile available in our method can be applied in a meaningful way to the study of cell physiology and also for more detailed studies of particular genes of interest. PMID:19131380

Profiling microRNA expression during multi-staged date palm (Phoenix dactylifera L.) fruit development.

PubMed

Xin, Chengqi; Liu, Wanfei; Lin, Qiang; Zhang, Xiaowei; Cui, Peng; Li, Fusen; Zhang, Guangyu; Pan, Linlin; Al-Amer, Ali; Mei, Hailiang; Al-Mssallem, Ibrahim S; Hu, Songnian; Al-Johi, Hasan Awad; Yu, Jun

2015-04-01

MicroRNAs (miRNAs) play crucial roles in multiple stages of plant development and regulate gene expression at posttranscriptional and translational levels. In this study, we first identified 238 conserved miRNAs in date palm (Phoenix dactylifera) based on a high-quality genome assembly and defined 78 fruit-development-associated (FDA) miRNAs, whose expression profiles are variable at different fruit development stages. Using experimental data, we subsequently detected 276 novel P. dactylifera-specific FDA miRNAs and predicted their targets. We also revealed that FDA miRNAs function mainly in regulating genes involved in starch/sucrose metabolisms and other carbon metabolic pathways; among them, 221 FDA miRNAs exhibit negative correlation with their corresponding targets, which suggests their direct regulatory roles on mRNA targets. Our data define a comprehensive set of conserved and novel FDA miRNAs along with their expression profiles, which provide a basis for further experimentation in assigning discrete functions of these miRNAs in P. dactylifera fruit development. Copyright © 2015. Published by Elsevier Inc.

TP53, STK11 and EGFR Mutations Predict Tumor Immune Profile and the Response to anti-PD-1 in Lung Adenocarcinoma.

PubMed

Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane

2018-05-15

By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.

Spermatozoa from patients with seminal alterations exhibit a differential micro-ribonucleic acid profile.

PubMed

Salas-Huetos, Albert; Blanco, Joan; Vidal, Francesca; Godo, Anna; Grossmann, Mark; Pons, Maria Carme; F-Fernández, Silvia; Garrido, Nicolás; Anton, Ester

2015-09-01

To compare the microRNA (miRNA) expression profile in spermatozoa from three infertile populations vs. a group of fertile men. Evaluation of the expression level of 736 miRNAs in human spermatozoa using TaqMan quantitative reverse transcription-polymerase chain reaction. University research facility. Semen samples with a single seminal alteration were collected from infertile individuals: asthenozoospermic (n = 10), teratozoospermic (n = 10), and oligozoospermic (n = 10). None. Correlation of the expression level of each miRNA with seminal parameters, age, and chromosome instability; clustering of the individuals according to their miRNA expression profiles and influence of the seminogram, age, chromosome instability, and assisted reproductive technology outcome in the clustering; analysis of the differentially expressed miRNAs (DE-miRNAs) in each infertile population; genome annotation of these DE-miRNAs; and ontological analysis of their predicted targets. The hsa-miR-34b-3p correlated with age, the hsa-miR-629-3p with sperm motility, and the hsa-miR-335-5p, hsa-miR-885-5p, and hsa-miR-152-3p with sperm concentration. The individuals clustered into two groups, and only the seminogram was differentially distributed. We identified 32 DE-miRNAs in the asthenozoospermic group, 19 in the teratozoospermic group, and 18 in the oligozoospermic group. The up-regulated miRNAs presented an enriched localization in introns, affecting relevant genes for spermatogenesis. The predicted targets of the DE-miRNAs contained critical genes associated to infertility, and their ontological analysis revealed significantly associated functions related to the seminal alterations of each group. Spermatozoa from patients with seminal alterations exhibit a differential miRNA profile. This provides new evidence that miRNAs have an essential role in spermatogenesis, contributing to the mechanisms involved in human fertility. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

The role of microRNAs in myopia.

PubMed

Jiang, Bo; Huo, Yanan; Gu, Yangshun; Wang, Jianyong

2017-01-01

In recent years, research on microRNAs (miRNAs) has become popular because of the critical role these macromolecules play in post-transcriptional gene regulation. Recent efforts have been made to identify miRNAs and their possible roles in myopia. The aim of this review was to summarize the expression and function of miRNAs during the development of myopia. In this article, we reviewed the current research on the mechanisms that regulate miRNA expression, the potential for miRNAs as a diagnostic biomarker for myopia, and the mechanisms by which miRNAs promote the development of myopia. We also discussed the miRNA expression profiles in human fetal sclera. We summarized the miRNA expression profiles in myopia, including miR-328, miR-184, miR-29a, and miR-let-7i, and also the miRNA expression profiles in fetal sclera, including miR-214, miR-let-7, miR-103, miR-107, miR-29b, miR-328, and miR-98. Such knowledge could lead to more precise diagnosis, prognosis, and response predictions for future treatments for myopia, and the pace of discovery is expected to accelerate dramatically in the near future.

Predictive biomarkers of sensitivity to the phosphatidylinositol 3' kinase inhibitor GDC-0941 in breast cancer preclinical models.

PubMed

O'Brien, Carol; Wallin, Jeffrey J; Sampath, Deepak; GuhaThakurta, Debraj; Savage, Heidi; Punnoose, Elizabeth A; Guan, Jane; Berry, Leanne; Prior, Wei Wei; Amler, Lukas C; Belvin, Marcia; Friedman, Lori S; Lackner, Mark R

2010-07-15

The class I phosphatidylinositol 3' kinase (PI3K) plays a major role in proliferation and survival in a wide variety of human cancers. A key factor in successful development of drugs targeting this pathway is likely to be the identification of responsive patient populations with predictive diagnostic biomarkers. This study sought to identify candidate biomarkers of response to the selective PI3K inhibitor GDC-0941. We used a large panel of breast cancer cell lines and in vivo xenograft models to identify candidate predictive biomarkers for a selective inhibitor of class I PI3K that is currently in clinical development. The approach involved pharmacogenomic profiling as well as analysis of gene expression data sets from cells profiled at baseline or after GDC-0941 treatment. We found that models harboring mutations in PIK3CA, amplification of human epidermal growth factor receptor 2, or dual alterations in two pathway components were exquisitely sensitive to the antitumor effects of GDC-0941. We found that several models that do not harbor these alterations also showed sensitivity, suggesting a need for additional diagnostic markers. Gene expression studies identified a collection of genes whose expression was associated with in vitro sensitivity to GDC-0941, and expression of a subset of these genes was found to be intimately linked to signaling through the pathway. Pathway focused biomarkers and the gene expression signature described in this study may have utility in the identification of patients likely to benefit from therapy with a selective PI3K inhibitor. Copyright 2010 AACR.

Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

Cancer.gov

The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

TANDEM: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types.

PubMed

Aben, Nanne; Vis, Daniel J; Michaut, Magali; Wessels, Lodewyk F A

2016-09-01

Clinical response to anti-cancer drugs varies between patients. A large portion of this variation can be explained by differences in molecular features, such as mutation status, copy number alterations, methylation and gene expression profiles. We show that the classic approach for combining these molecular features (Elastic Net regression on all molecular features simultaneously) results in models that are almost exclusively based on gene expression. The gene expression features selected by the classic approach are difficult to interpret as they often represent poorly studied combinations of genes, activated by aberrations in upstream signaling pathways. To utilize all data types in a more balanced way, we developed TANDEM, a two-stage approach in which the first stage explains response using upstream features (mutations, copy number, methylation and cancer type) and the second stage explains the remainder using downstream features (gene expression). Applying TANDEM to 934 cell lines profiled across 265 drugs (GDSC1000), we show that the resulting models are more interpretable, while retaining the same predictive performance as the classic approach. Using the more balanced contributions per data type as determined with TANDEM, we find that response to MAPK pathway inhibitors is largely predicted by mutation data, while predicting response to DNA damaging agents requires gene expression data, in particular SLFN11 expression. TANDEM is available as an R package on CRAN (for more information, see http://ccb.nki.nl/software/tandem). m.michaut@nki.nl or l.wessels@nki.nl Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Studying the MicroRNA role as a survival predictor and revealing its part in malignancy level determination in patients with supratentorial gliomas of brain

NASA Astrophysics Data System (ADS)

Stupak, E. V.; Veryaskina, Yu. A.; Titov, S. E.; Achmerova, L. G.; Stupak, V. V.; Dolzhenko, D. A.; Rabinovich, S. S.; Narodov, A. A.; Ivanov, M. K.; Zhimulev, I. F.; Kolesnikov, N. N.

2017-09-01

The numerous data show, that microRNA (miRNA) are direct participants of carcinogenesis. Also miRNA plays the role of a diagnostic and prognostic marker for different types of cancer, including gliomas. The aim of this research is to make the comparative analysis of 10 micro RNA (miR-124, -125b, -16, -181b, -191, -21, -221, -223, -31 and -451) expression profiles. The analysis was made for gliomas with different malignancy degree, then compared with the samples of the adjacent not changed tissues (n = 90). During the study the specific profiles of miRNA expression for various histotypes of tumors were revealed. It was determined, that miRNA acts as a predictor of patient survival in the cases with malignant supratentorial brain tumors. The diagnostic approaches based on miRNA expression profile were designed. It will help to determine the malignancy level and to predict the course of the disease.

Circular RNAs play an important role in late-stage gastric cancer: Circular RNA expression profiles and bioinformatics analyses.

PubMed

Fang, Yantian; Ma, Minzhe; Wang, Jiangli; Liu, Xiaowen; Wang, Yanong

2017-06-01

Gastric cancer is one of the most common tumors of the digestive system. Here, analysis of the expression profiles of circular RNAs in advanced gastric adenocarcinoma and adjacent normal mucosa tissues revealed differential expression of 306 circular RNAs, among which 273 were predicted to exert regulatory effects on target microRNAs. The downstream pathway networks of circular RNA-microRNA were mapped and the node genes were identified. In particular, we found that the expression of hsa_circ_0058246 was elevated in tumor specimens of patients with poor clinical outcomes. Our collective findings indicate that circular RNAs play a critical role in gastric cancer tumorigenesis. Data from this study provide a new perspective on the molecular pathways underlying metastasis and recurrence of gastric cancer and highlight potential therapeutic targets that may contribute to more effective diagnosis and treatment of the disease.

High-throughput deep screening and identification of four peripheral leucocyte microRNAs as novel potential combination biomarkers for preeclampsia

PubMed Central

Wang, Yonghong; Yang, Xukui; Yang, Yuanyuan; Wang, Wenjun; Zhao, Meiling; Liu, Huiqiang; Li, Dongyan; Hao, Min

2016-01-01

Objective: To identify the specific microRNA (miRNA) biomarkers of preeclampsia (PE), the miRNA profiles analysis were performed. Study Design: The blood samples were obtained from five PE patients and five normal healthy pregnant women. The small RNA profiles were analyzed to identify miRNA expression levels and find out miRNAs that may associate with PE. The quantitative reverse transcriptase–PCR (qRT-PCR) assay was used to validate differentially expressed peripheral leucocyte miRNAs in a new cohort. Result: The data analysis showed that 10 peripheral leucocyte miRNAs were significantly differently expressed in severe PE patients. Four differently expressed miRNAs were successfully validated using qRT-PCR method. Conclusion: We successfully constructed a model with high accuracy to predict PE. A combination of four peripheral leucocyte miRNAs has great potential to serve as diagnostic biomarkers of PE. PMID:26675000

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

PubMed Central

Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

2011-01-01

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

ESTIMATION OF FREE HYDROCARBON VOLUME FROM FLUID LEVELS IN MONITORING WELLS

EPA Science Inventory

Under the assumption of local vertical equilibrium, fluid pressure distributions specified from well fluid levels in monitoring wells may be used to predict water and hydrocarbon saturation profiles given expressions for air-water-hydrocarbon saturation-pressure relations. Verti...

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However,more » the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.« less

Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

PubMed

Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

2016-11-01

Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Cigarette Smoking Decreases Global MicroRNA Expression in Human Alveolar Macrophages

PubMed Central

Graff, Joel W.; Powers, Linda S.; Dickson, Anne M.; Kim, Jongkwang; Reisetter, Anna C.; Hassan, Ihab H.; Kremens, Karol; Gross, Thomas J.

2012-01-01

Human alveolar macrophages are critical components of the innate immune system. Cigarette smoking-induced changes in alveolar macrophage gene expression are linked to reduced resistance to pulmonary infections and to the development of emphysema/COPD. We hypothesized that microRNAs (miRNAs) could control, in part, the unique messenger RNA (mRNA) expression profiles found in alveolar macrophages of cigarette smokers. Activation of macrophages with different stimuli in vitro leads to a diverse range of M1 (inflammatory) and M2 (anti-inflammatory) polarized phenotypes that are thought to mimic activated macrophages in distinct tissue environments. Microarray mRNA data indicated that smoking promoted an “inverse” M1 mRNA expression program, defined by decreased expression of M1-induced transcripts and increased expression of M1-repressed transcripts with few changes in M2-regulated transcripts. RT-PCR arrays identified altered expression of many miRNAs in alveolar macrophages of smokers and a decrease in global miRNA abundance. Stratification of human subjects suggested that the magnitude of the global decrease in miRNA abundance was associated with smoking history. We found that many of the miRNAs with reduced expression in alveolar macrophages of smokers were predicted to target mRNAs upregulated in alveolar macrophages of smokers. For example, miR-452 is predicted to target the transcript encoding MMP12, an important effector of smoking-related diseases. Experimental antagonism of miR-452 in differentiated monocytic cells resulted in increased expression of MMP12. The comprehensive mRNA and miRNA expression profiles described here provide insight into gene expression regulation that may underlie the adverse effects cigarette smoking has on alveolar macrophages. PMID:22952876

Sexual selection and population divergence I: The influence of socially flexible cuticular hydrocarbon expression in male field crickets (Teleogryllus oceanicus).

PubMed

Pascoal, Sonia; Mendrok, Magdalena; Mitchell, Christopher; Wilson, Alastair J; Hunt, John; Bailey, Nathan W

2016-01-01

Debates about how coevolution of sexual traits and preferences might promote evolutionary diversification have permeated speciation research for over a century. Recent work demonstrates that the expression of such traits can be sensitive to variation in the social environment. Here, we examined social flexibility in a sexually selected male trait-cuticular hydrocarbon (CHC) profiles-in the field cricket Teleogryllus oceanicus and tested whether population genetic divergence predicts the extent or direction of social flexibility in allopatric populations. We manipulated male crickets' social environments during rearing and then characterized CHC profiles. CHC signatures varied considerably across populations and also in response to the social environment, but our prediction that increased social flexibility would be selected in more recently founded populations exposed to fluctuating demographic environments was unsupported. Furthermore, models examining the influence of drift and selection failed to support a role of sexual selection in driving population divergence in CHC profiles. Variation in social environments might alter the dynamics of sexual selection, but our results align with theoretical predictions that the role social flexibility plays in modulating evolutionary divergence depends critically on whether responses to variation in the social environment are homogeneous across populations, or whether gene by social environment interactions occur. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Temporal analysis of reciprocal miRNA-mRNA expression patterns predicts regulatory networks during differentiation in human skeletal muscle cells

PubMed Central

Sjögren, Rasmus J. O.; Egan, Brendan; Katayama, Mutsumi; Zierath, Juleen R.

2014-01-01

microRNAs (miRNAs) are short noncoding RNAs that regulate gene expression through posttranscriptional repression of target genes. miRNAs exert a fundamental level of control over many developmental processes, but their role in the differentiation and development of skeletal muscle from myogenic progenitor cells in humans remains incompletely understood. Using primary cultures established from human skeletal muscle satellite cells, we performed microarray profiling of miRNA expression during differentiation of myoblasts (day 0) into myotubes at 48 h intervals (day 2, 4, 6, 8, and 10). Based on a time-course analysis, we identified 44 miRNAs with altered expression [false discovery rate (FDR) < 5%, fold change > ±1.2] during differentiation, including the marked upregulation of the canonical myogenic miRNAs miR-1, miR-133a, miR-133b, and miR-206. Microarray profiling of mRNA expression at day 0, 4, and 10 identified 842 and 949 genes differentially expressed (FDR < 10%) at day 4 and 10, respectively. At day 10, 42% of altered transcripts demonstrated reciprocal expression patterns in relation to the directional change of their in silico predicted regulatory miRNAs based on analysis using Ingenuity Pathway Analysis microRNA Target Filter. Bioinformatic analysis predicted networks of regulation during differentiation including myomiRs miR-1/206 and miR-133a/b, miRNAs previously established in differentiation including miR-26 and miR-30, and novel miRNAs regulated during differentiation of human skeletal muscle cells such as miR-138-5p and miR-20a. These reciprocal expression patterns may represent new regulatory nodes in human skeletal muscle cell differentiation. This analysis serves as a reference point for future studies of human skeletal muscle differentiation and development in healthy and disease states. PMID:25547110

Circular RNA expression profile of articular chondrocytes in an IL-1β-induced mouse model of osteoarthritis.

PubMed

Zhou, Zhibin; Du, Di; Chen, Aimin; Zhu, Lei

2018-02-20

Osteoarthritis (OA) is a widely prevalent degenerative joint disease characterized by articular cartilage degradation and joint inflammation. The pathogenesis of OA remains unclear, leading to a lack of effective treatment. Previous studies have reported that circular RNAs (circRNAs) are involved in the development of various diseases. However, the function of circRNAs and their roles in OA is largely unknown. Therefore, we aimed to investigate changes in circRNA expression and predict their functions in OA by using bioinformatics analysis. An OA model was established in mouse articular chondrocytes (MACs) treated by interleukin-1β (IL-1β), and then the circRNA profile was screened by Next Generation Sequencing. By comparing circRNA expression in IL-1β- treated MACs and normal controls, differentially expressed circRNAs were identified during OA pathogenesis, and differential expression levels of selected circRNAs were validated by qRT-PCR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to predict the functions of these circRNAs. Because circRNAs can act as "miRNA sponges", we also constructed a circRNA-miRNA network to predict their functions. A total of 255 circRNAs were found to be differentially expressed in IL-1β-treated MACs (p≤0.05; fold-change≥2) from the expression of the normal controls. Among them, 119 circRNAs were significantly up-regulated, and the other 136 were down-regulated. Seven circRNAs were randomly selected to verify the reliability of these profiles by quantitative qRT-PCR. After obtaining the parental genes of differentially expressed circRNA, the top 30 enrichment GO entries and KEGG pathways were annotated. Then, two significantly differentially expressed circRNAs (mmu-circRNA-30365 and mmu-circRNA-36866) were identified and selected for further analysis, meanwhile a circRNA-miRNA regulation network was created and the top five most likely functional-related target miRNAs of the circRNAs were collected. Although the exact mechanisms and biological functions of these circRNAs in the development of OA need further exploration, our findings do suggest that the differentially expressed circRNAs were involved in the pathogenesis of OA. Thus, our study brings us closer to understanding the pathogenic mechanisms and finding new molecular targets for the clinical treatment of osteoarthritis. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of gene expression profiling associated with erlotinib-related skin toxicity in pancreatic adenocarcinoma patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caba, Octavio, E-mail: ocaba@ujaen.es

Erlotinib is an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that showed activity against pancreatic ductal adenocarcinoma (PDAC). The drug's most frequently reported side effect as a result of EGFR inhibition is skin rash (SR), a symptom which has been associated with a better therapeutic response to the drug. Gene expression profiling can be used as a tool to predict which patients will develop this important cutaneous manifestation. The aim of the present study was to identify which genes may influence the appearance of SR in PDAC patients. The study included 34 PDAC patients treated with erlotinib: 21 patientsmore » developed any grade of SR, while 13 patients did not (controls). Before administering any chemotherapy regimen and the development of SR, we collected RNA from peripheral blood samples of all patients and studied the differential gene expression pattern using the Illumina microarray platform HumanHT-12 v4 Expression BeadChip. Seven genes (FAM46C, IFITM3, GMPR, DENND6B, SELENBP1, NOL10, and SIAH2), involved in different pathways including regulatory, migratory, and signalling processes, were downregulated in PDAC patients with SR. Our results suggest the existence of a gene expression profiling significantly correlated with erlotinib-induced SR in PDAC that could be used as prognostic indicator in this patients. - Highlights: • Skin rash (SR) is the most characteristic side effect of erlotinib in PDAC patients. • Erlotinib-induced SR has been associated with a better clinical outcome. • Gene expression profiling was used to determine who will develop this manifestation. • 7 genes involved in different pathways were downregulated in PDAC patients with SR. • Our profile correlated with erlotinib-induced SR in PDAC could be used for prognosis.« less

Genome-wide expression profiling of in vivo-derived bloodstream parasite stages and dynamic analysis of mRNA alterations during synchronous differentiation in Trypanosoma brucei

PubMed Central

Kabani, Sarah; Fenn, Katelyn; Ross, Alan; Ivens, Al; Smith, Terry K; Ghazal, Peter; Matthews, Keith

2009-01-01

Background Trypanosomes undergo extensive developmental changes during their complex life cycle. Crucial among these is the transition between slender and stumpy bloodstream forms and, thereafter, the differentiation from stumpy to tsetse-midgut procyclic forms. These developmental events are highly regulated, temporally reproducible and accompanied by expression changes mediated almost exclusively at the post-transcriptional level. Results In this study we have examined, by whole-genome microarray analysis, the mRNA abundance of genes in slender and stumpy forms of T.brucei AnTat1.1 cells, and also during their synchronous differentiation to procyclic forms. In total, five biological replicates representing the differentiation of matched parasite populations derived from five individual mouse infections were assayed, with RNAs being derived at key biological time points during the time course of their synchronous differentiation to procyclic forms. Importantly, the biological context of these mRNA profiles was established by assaying the coincident cellular events in each population (surface antigen exchange, morphological restructuring, cell cycle re-entry), thereby linking the observed gene expression changes to the well-established framework of trypanosome differentiation. Conclusion Using stringent statistical analysis and validation of the derived profiles against experimentally-predicted gene expression and phenotypic changes, we have established the profile of regulated gene expression during these important life-cycle transitions. The highly synchronous nature of differentiation between stumpy and procyclic forms also means that these studies of mRNA profiles are directly relevant to the changes in mRNA abundance within individual cells during this well-characterised developmental transition. PMID:19747379

Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

PubMed

Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

2017-10-01

Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531

PubMed Central

Voigt, Andrew P.; Brodersen, Lisa Eidenschink; Alonzo, Todd A.; Gerbing, Robert B.; Menssen, Andrew J.; Wilson, Elisabeth R.; Kahwash, Samir; Raimondi, Susana C.; Hirsch, Betsy A.; Gamis, Alan S.; Meshinchi, Soheil; Wells, Denise A.; Loken, Michael R.

2017-01-01

Diagnostic biomarkers can be used to determine relapse risk in acute myeloid leukemia, and certain genetic aberrancies have prognostic relevance. A diagnostic immunophenotypic expression profile, which quantifies the amounts of distinct gene products, not just their presence or absence, was established in order to improve outcome prediction for patients with acute myeloid leukemia. The immunophenotypic expression profile, which defines each patient’s leukemia as a location in 15-dimensional space, was generated for 769 patients enrolled in the Children’s Oncology Group AAML0531 protocol. Unsupervised hierarchical clustering grouped patients with similar immunophenotypic expression profiles into eleven patient cohorts, demonstrating high associations among phenotype, genotype, morphology, and outcome. Of 95 patients with inv(16), 79% segregated in Cluster A. Of 109 patients with t(8;21), 92% segregated in Clusters A and B. Of 152 patients with 11q23 alterations, 78% segregated in Clusters D, E, F, G, or H. For both inv(16) and 11q23 abnormalities, differential phenotypic expression identified patient groups with different survival characteristics (P<0.05). Clinical outcome analysis revealed that Cluster B (predominantly t(8;21)) was associated with favorable outcome (P<0.001) and Clusters E, G, H, and K were associated with adverse outcomes (P<0.05). Multivariable regression analysis revealed that Clusters E, G, H, and K were independently associated with worse survival (P range <0.001 to 0.008). The Children’s Oncology Group AAML0531 trial: clinicaltrials.gov Identifier: 00372593. PMID:28883080

cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila

PubMed Central

2014-01-01

Background Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. Description It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. Conclusions cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms of metazoan gene regulation. We believe that the information deposited in cisMEP will greatly facilitate the comparative usage of different CRM prediction tools and will help biologists to study the modular regulatory mechanisms between different TFs and their target genes. PMID:25521507

Expression profiling in canine osteosarcoma: identification of biomarkers and pathways associated with outcome

PubMed Central

2010-01-01

Background Osteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities. Methods We analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform. Results Potential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion. Conclusions This profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention. PMID:20860831

[Development of the devices for synthetic biology of triterpene saponins at an early stage: cloning and expression profiling of squalene epoxidase genes in panax notoginseng].

PubMed

Niu, Yun-Yun; Zhu, Xiao-Xuan; Luo, Hong-Mei; Sun, Chao; Huang, Lin-Fang; Chen, Shi-Lin

2013-02-01

Synthetic biology of traditional Chinese medicine (TCM) is a new and developing subject based on the research of secondary metabolite biosynthesis for nature products. The early development of synthetic biology focused on the screening and modification of parts or devices, and establishment of standardized device libraries. Panax notoginseng (Burk.) F.H.Chen is one of the most famous medicinal plants in Panax species. Triterpene saponins have important pharmacological activities in P. notoginseng. Squalene epoxidase (SE) has been considered as a key rate-limiting enzyme in biosynthetic pathways of triterpene saponins and phytosterols. SE acts as one of necessary devices for biosynthesis of triterpene saponins and phytosterols in vitro via synthetic biology approach. Here we cloned two genes encoding squalene epoxidase (PnSE1 and PnSE2) and analyzed the predict amino acid sequences by bioinformatic analysis. Further, we detected the gene expression profiling in different organs and the expression level of SEs in leaves elicited by methyl jasmonate (MeJA) treatment in 4-year-old P notoginseng using real-time quantitative PCR (real-time PCR). The study will provide a foundation for discovery and modification of devices in previous research by TCM synthetic biology. PnSE1 and PnSE2 encoded predicted proteins of 537 and 545 amino acids, respectively. Two amino acid sequences predicted from PnSEs shared strong similarity (79%), but were highly divergent in N-terminal regions (the first 70 amino acids). The genes expression profiling detected by real-time PCR, PnSE1 mRNA abundantly accumulated in all organs, especially in flower. PnSE2 was only weakly expressed and preferentially in flower. MeJA treatment enhanced the accumulation of PnSEI mRNA expression level in leaves, while there is no obvious enhancement of PnSE2 in same condition. Results indicated that the gene expressions of PnSE1 and PnSE2 were differently transcribed in four organs, and two PnSEs differently responded to MeJA stimuli. It was strongly suggested that PnSEs play different roles in secondary metabolite biosynthesis in P. notoginseng. PnSE1 might be involved in triterpenoid biosynthesis and PnSE2 might be involved in phytosterol biosynthesis.

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Genome-wide Expression Profiling, In Vivo DNA Binding Analysis, and Probabilistic Motif Prediction Reveal Novel Abf1 Target Genes during Fermentation, Respiration, and Sporulation in Yeast

PubMed Central

Schlecht, Ulrich; Erb, Ionas; Demougin, Philippe; Robine, Nicolas; Borde, Valérie; van Nimwegen, Erik; Nicolas, Alain

2008-01-01

The autonomously replicating sequence binding factor 1 (Abf1) was initially identified as an essential DNA replication factor and later shown to be a component of the regulatory network controlling mitotic and meiotic cell cycle progression in budding yeast. The protein is thought to exert its functions via specific interaction with its target site as part of distinct protein complexes, but its roles during mitotic growth and meiotic development are only partially understood. Here, we report a comprehensive approach aiming at the identification of direct Abf1-target genes expressed during fermentation, respiration, and sporulation. Computational prediction of the protein's target sites was integrated with a genome-wide DNA binding assay in growing and sporulating cells. The resulting data were combined with the output of expression profiling studies using wild-type versus temperature-sensitive alleles. This work identified 434 protein-coding loci as being transcriptionally dependent on Abf1. More than 60% of their putative promoter regions contained a computationally predicted Abf1 binding site and/or were bound by Abf1 in vivo, identifying them as direct targets. The present study revealed numerous loci previously unknown to be under Abf1 control, and it yielded evidence for the protein's variable DNA binding pattern during mitotic growth and meiotic development. PMID:18305101

Under the influence of the active deodorant ingredient 4-hydroxy-3-methoxybenzyl alcohol, the skin bacterium Corynebacterium jeikeium moderately responds with differential gene expression.

PubMed

Brune, Iris; Becker, Anke; Paarmann, Daniel; Albersmeier, Andreas; Kalinowski, Jörn; Pühler, Alfred; Tauch, Andreas

2006-12-15

A 70mer oligonucleotide microarray was constructed to analyze genome-wide expression profiles of Corynebacterium jeikeium, a skin bacterium that is predominantly present in the human axilla and involved in axillary odor formation. Oligonucleotides representing 100% of the predicted coding regions of the C. jeikeium K411 genome were designed and spotted in quadruplicate onto epoxy-coated glass slides. The quality of the printed microarray was demonstrated by co-hybridization with fluorescently labeled cDNA probes obtained from exponentially growing C. jeikeium cultures. Accordingly, genes detected with different intensities resulting in log(2) transformed ratios greater than 0.8 or smaller than -0.8 can be regarded as differentially expressed with a confidence level greater than 99%. In an application example, we measured global changes of gene expression during growth of C. jeikeium in the presence of different concentrations of the deodorant component 4-hydroxy-3-methoxybenzyl alcohol that is active in preventing body odor formation. Global expression profiling revealed that low concentrations of 4-hydroxy-3-methoxybenzyl alcohol (0.5 and 2.5mg/ml) had almost no detectable effect on the transcriptome of C. jeikeium. A slightly higher concentration of 4-hydroxy-3-methoxybenzyl alcohol (5mg/ml) resulted in differential expression of 95 genes, 86 of which showed an enhanced expression when compared to a control culture. Besides many genes encoding proteins that apparently participate in transcription and translation, the drug resistance determinant cmx and the predicted virulence factors sapA and sapD showed significantly enhanced expression levels. Differential expression of relevant genes was validated by real-time reverse transcription PCR assays.

Genome-wide profiles of CtBP link metabolism with genome stability and epithelial reprogramming in breast cancer.

PubMed

Di, Li-Jun; Byun, Jung S; Wong, Madeline M; Wakano, Clay; Taylor, Tara; Bilke, Sven; Baek, Songjoon; Hunter, Kent; Yang, Howard; Lee, Maxwell; Zvosec, Cecilia; Khramtsova, Galina; Cheng, Fan; Perou, Charles M; Miller, C Ryan; Raab, Rachel; Olopade, Olufunmilayo I; Gardner, Kevin

2013-01-01

The C-terminal binding protein (CtBP) is a NADH-dependent transcriptional repressor that links carbohydrate metabolism to epigenetic regulation by recruiting diverse histone-modifying complexes to chromatin. Here global profiling of CtBP in breast cancer cells reveals that it drives epithelial-to-mesenchymal transition, stem cell pathways and genome instability. CtBP expression induces mesenchymal and stem cell-like features, whereas CtBP depletion or caloric restriction reverses gene repression and increases DNA repair. Multiple members of the CtBP-targeted gene network are selectively downregulated in aggressive breast cancer subtypes. Differential expression of CtBP-targeted genes predicts poor clinical outcome in breast cancer patients, and elevated levels of CtBP in patient tumours predict shorter median survival. Finally, both CtBP promoter targeting and gene repression can be reversed by small molecule inhibition. These findings define broad roles for CtBP in breast cancer biology and suggest novel chromatin-based strategies for pharmacologic and metabolic intervention in cancer.

Mode-independent attenuation in evanescent-field sensors

NASA Astrophysics Data System (ADS)

Gnewuch, Harald; Renner, Hagen

1995-03-01

Generally, the total power attenuation in multimode evanescent-field sensor waveguides is nonproportional to the bulk absorbance because the modal attenuation constants differ. Hence a direct measurement is difficult and is additionally aggravated because the waveguide absorbance is highly sensitive to the specific launching conditions at the waveguide input. A general asymptotic formula for the modal power attenuation in strongly asymmetric inhomogeneous planar waveguides with arbitrarily distributed weak absorption in the low-index superstrate is derived. Explicit expressions for typical refractive-index profiles are given. Except when very close to the cutoff, the predicted asymptotic attenuation behavior agrees well with exact calculations. The ratio of TM versus TE absorption has been derived to be (2 - n0 2/nf2 ) for arbitrary profiles. Waveguides with a linear refractive-index profile show mode-independent attenuation coefficients within each polarization. Further, the asymptotic sensitivity is independent of the wavelength, so that it should be possible to directly measure the spectral variation of the bulk absorption. The mode independence of the attenuation has been verified experimentally for a second-order polynomial profile, which is close to a linear refractive-index distribution. In contrast, the attenuation in the step-profile waveguide has been found to depend strongly on the mode number, as predicted by theory. A strong spread of the modal attenuation coefficients is also predicted for the parabolic-profile waveguide sensor.

Expression of miR-15a, miR-145, and miR-182 in granulosa-lutein cells, follicular fluid, and serum of women with polycystic ovary syndrome (PCOS).

PubMed

Naji, Mohammad; Nekoonam, Saeid; Aleyasin, Ashraf; Arefian, Ehsan; Mahdian, Reza; Azizi, Elham; Shabani Nashtaei, Maryam; Amidi, Fardin

2018-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies that affects women in reproductive age. MicroRNAs (miRNAs) play crucial roles in normal function of female reproductive system and folliculogenesis. Deregulated expression of miRNAs in PCOS condition may be significantly implicated in the pathogenesis of PCOS. We determined relative expression of miR-15a, miR-145, and miR-182 in granulosa-lutein cells (GLCs), follicular fluid (FF), and serum of PCOS patients. Human subjects were divided into PCOS (n = 20) and control (n = 21) groups. GLCs, FF, and serum were isolated and stored. RNA isolation was performed and cDNA was reversely transcribed using specific stem-loop RT primers. Relative expression of miRNAs was calculated after normalization against U6 expression. Correlation of miRNAs' expression level with basic clinical features and predictive value of miRNAs in FF and serum were appraised. Relative expression of miR-145 and miR-182 in GLCs was significantly decreased in PCOS, but miR-182 in FF of PCOS patients revealed up-regulated levels. Significant correlations between level of miRNAs in FF and serum and hormonal profile of subjects were observed. MiR-182 in FF showed a significant predictive value with AUC of 0.73, 76.4% sensitivity, and 70.5% specificity which was improved after combination of miR-182 and miR-145. A significant dysregulation of miR-145 and miR-182 in GLCs of PCOS may indicate their involvement in pathogenesis of PCOS. Differential up-regulation of miR-182 in FF of PCOS patients with its promising predictive values for discrimination of PCOS reinforced the importance of studying miRNAs' profile in FF.

Characterization of circulating microRNA expression in patients with a ventricular septal defect.

PubMed

Li, Dong; Ji, Long; Liu, Lianbo; Liu, Yizhi; Hou, Haifeng; Yu, Kunkun; Sun, Qiang; Zhao, Zhongtang

2014-01-01

Ventricular septal defect (VSD), one of the most common types of congenital heart disease (CHD), results from a combination of environmental and genetic factors. Recent studies demonstrated that microRNAs (miRNAs) are involved in development of CHD. This study was to characterize the expression of miRNAs that might be involved in the development or reflect the consequences of VSD. MiRNA microarray analysis and reverse transcription-polymerase chain reaction (RT-PCR) were employed to determine the miRNA expression profile from 3 patients with VSD and 3 VSD-free controls. 3 target gene databases were employed to predict the target genes of differentially expressed miRNAs. miRNAs that were generally consensus across the three databases were selected and then independently validated using real time PCR in plasma samples from 20 VSD patients and 15 VSD-free controls. Target genes of validated 8 miRNAs were predicted using bioinformatic methods. 36 differentially expressed miRNAs were found in the patients with VSD and the VSD-free controls. Compared with VSD-free controls, expression of 15 miRNAs were up-regulated and 21 miRNAs were downregulated in the VSD group. 15 miRNAs were selected based on database analysis results and expression levels of 8 miRNAs were validated. The results of the real time PCR were consistent with those of the microarray analysis. Gene ontology analysis indicated that the top target genes were mainly related to cardiac right ventricle morphogenesis. NOTCH1, HAND1, ZFPM2, and GATA3 were predicted as targets of hsa-let-7e-5p, hsa-miR-222-3p and hsa-miR-433. We report for the first time the circulating miRNA profile for patients with VSD and showed that 7 miRNAs were downregulated and 1 upregulated when matched to VSD-free controls. Analysis revealed target genes involved in cardiac development were probably regulated by these miRNAs.

Expression profiles of miRNAs from bovine mammary glands in response to Streptococcus agalactiae-induced mastitis.

PubMed

Pu, Junhua; Li, Rui; Zhang, Chenglong; Chen, Dan; Liao, Xiangxiang; Zhu, Yihui; Geng, Xiaohan; Ji, Dejun; Mao, Yongjiang; Gong, Yunchen; Yang, Zhangping

2017-08-01

This study aimed to describe the expression profiles of microRNAs (miRNAs) from mammary gland tissues collected from dairy cows with Streptococcus agalactiae-induced mastitis and to identify differentially expressed miRNAs related to mastitis. The mammary glands of Chinese Holstein cows were challenged with Streptococcus agalactiae to induce mastitis. Small RNAs were isolated from the mammary tissues of the test and control groups and then sequenced using the Solexa sequencing technology to construct two small RNA libraries. Potential target genes of these differentially expressed miRNAs were predicted using the RNAhybrid software, and KEGG pathways associated with these genes were analysed. A total of 18 555 913 and 20 847 000 effective reads were obtained from the test and control groups, respectively. In total, 373 known and 399 novel miRNAs were detected in the test group, and 358 known and 232 novel miRNAs were uncovered in the control group. A total of 35 differentially expressed miRNAs were identified in the test group compared to the control group, including 10 up-regulated miRNAs and 25 down-regulated miRNAs. Of these miRNAs, miR-223 exhibited the highest degree of up-regulation with an approximately 3-fold increase in expression, whereas miR-26a exhibited the most decreased expression level (more than 2-fold). The RNAhybrid software predicted 18 801 genes as potential targets of these 35 miRNAs. Furthermore, several immune response and signal transduction pathways, including the RIG-I-like receptor signalling pathway, cytosolic DNA sensing pathway and Notch signal pathway, were enriched in these predicted targets. In summary, this study provided experimental evidence for the mechanism underlying the regulation of bovine mastitis by miRNAs and showed that miRNAs might be involved in signal pathways during S. agalactiae-induced mastitis.

Thyroid paraganglioma. Report of 3 cases and description of an immunohistochemical profile useful in the differential diagnosis with medullary thyroid carcinoma, based on complementary DNA array results.

PubMed

Castelblanco, Esmeralda; Gallel, Pilar; Ros, Susana; Gatius, Sonia; Valls, Joan; De-Cubas, Aguirre A; Maliszewska, Agnieszka; Yebra-Pimentel, M Teresa; Menarguez, Javier; Gamallo, Carlos; Opocher, Giuseppe; Robledo, Mercedes; Matias-Guiu, Xavier

2012-07-01

Thyroid paraganglioma is a rare disorder that sometimes poses problems in differential diagnosis with medullary thyroid carcinoma. So far, differential diagnosis is solved with the help of some markers that are frequently expressed in medullary thyroid carcinoma (thyroid transcription factor 1, calcitonin, and carcinoembryonic antigen). However, some of these markers are not absolutely specific of medullary thyroid carcinoma and may be expressed in other tumors. Here we report 3 new cases of thyroid paraganglioma and describe our strategy to design a diagnostic immunohistochemical battery. First, we performed a comparative analysis of the expression profile of head and neck paragangliomas and medullary thyroid carcinoma, obtained after complementary DNA array analysis of 2 series of fresh-frozen samples of paragangliomas and medullary thyroid carcinoma, respectively. Seven biomarkers showing differential expression were selected (nicotinamide adenine dinucleotide dehydrogenase 1 alpha subcomplex, 4-like 2, NDUFA4L2; cytochrome c oxidase subunit IV isoform 2; vesicular monoamine transporter 2; calcitonin gene-related protein/calcitonin; carcinoembryonic antigen; and thyroid transcription factor 1) for immunohistochemical analysis. Two tissue microarrays were constructed from 2 different series of paraffin-embedded samples of paragangliomas and medullary thyroid carcinoma. We provide a classifying rule for differential diagnosis that combines negativity or low staining for calcitonin gene-related protein (histologic score, <10) or calcitonin (histologic score, <50) together with positivity of any of NADH dehydrogenase 1 alpha subcomplex, 4-like 2; cytochrome c oxidase subunit IV isoform 2; or vesicular monoamine transporter 2 to predict paragangliomas, showing a prediction error of 0%. Finally, the immunohistochemical battery was checked in paraffin-embedded blocks from 4 examples of thyroid paraganglioma (1 previously reported case and 3 new cases), showing also a prediction error of 0%. Our results suggest that the comparative expression profile, obtained by complementary DNA arrays, seems to be a good tool to design immunohistochemical batteries used in differential diagnosis. Copyright © 2012 Elsevier Inc. All rights reserved.

Defining the limits of physiological plasticity: how gene expression can assess and predict the consequences of ocean change

PubMed Central

Evans, Tyler G.; Hofmann, Gretchen E.

2012-01-01

Anthropogenic stressors, such as climate change, are driving fundamental shifts in the abiotic characteristics of marine ecosystems. As the environmental aspects of our world's oceans deviate from evolved norms, of major concern is whether extant marine species possess the capacity to cope with such rapid change. In what many scientists consider the post-genomic era, tools that exploit the availability of DNA sequence information are being increasingly recognized as relevant to questions surrounding ocean change and marine conservation. In this review, we highlight the application of high-throughput gene-expression profiling, primarily transcriptomics, to the field of marine conservation physiology. Through the use of case studies, we illustrate how gene expression can be used to standardize metrics of sub-lethal stress, track organism condition in natural environments and bypass phylogenetic barriers that hinder the application of other physiological techniques to conservation. When coupled with fine-scale monitoring of environmental variables, gene-expression profiling provides a powerful approach to conservation capable of informing diverse issues related to ocean change, from coral bleaching to the spread of invasive species. Integrating novel approaches capable of improving existing conservation strategies, including gene-expression profiling, will be critical to ensuring the ecological and economic health of the global ocean. PMID:22566679

Comparative peptidomic profile between human hypertrophic scar tissue and matched normal skin for identification of endogenous peptides involved in scar pathology.

PubMed

Li, Jingyun; Chen, Ling; Li, Qian; Cao, Jing; Gao, Yanli; Li, Jun

2018-08-01

Endogenous peptides recently attract increasing attention for their participation in various biological processes. Their roles in the pathogenesis of human hypertrophic scar remains poorly understood. In this study, we used liquid chromatography-tandem mass spectrometry to construct a comparative peptidomic profiling between human hypertrophic scar tissue and matched normal skin. A total of 179 peptides were significantly differentially expressed in human hypertrophic scar tissue, with 95 upregulated and 84 downregulated peptides between hypertrophic scar tissue and matched normal skin. Further bioinformatics analysis (Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis) indicated that precursor proteins of these differentially expressed peptides correlate with cellular process, biological regulation, cell part, binding and structural molecule activity ribosome, and PPAR signaling pathway occurring during pathological changes of hypertrophic scar. Based on prediction database, we found that 78 differentially expressed peptides shared homology with antimicrobial peptides and five matched known immunomodulatory peptides. In conclusion, our results show significantly altered expression profiles of peptides in human hypertrophic scar tissue. These peptides may participate in the etiology of hypertrophic scar and provide beneficial scheme for scar evaluation and treatments. © 2017 Wiley Periodicals, Inc.

Progression Rate Associated Peripheral Blood Biomarkers of Parkinson's Disease.

PubMed

Fan, Yanxia; Xiao, Shuping

2018-06-23

Parkinson disease (PD) is one of the most frequent neurodegenerative disorders. The aim of this study was to identify blood biomarkers capable to discriminate PD patients with different progression rates. Differentially expressed genes (DEGs) were acquired by comparing the expression profiles of PD patients with rapid and slow progression rates, using an expression dataset from Gene Expression Omnibus (GEO) under accession code of GSE80599. Altered biological processes and pathways were revealed by functional annotation. Potential biomarkers of PD were identified by protein-protein interaction (PPI) network analysis. Critical transcription factors (TFs) and miRNAs regulating DEGs were predicted by TF analysis and miRNA analysis. A total of 225 DEGs were identified between PD patients with rapid and slow progression profiles. These genes were significantly enriched in biological processes and pathways related to fatty acid metabolism. Among these DEGs, ZFAND4, SRMS, UBL4B, PVALB, DIRAS1, PDP2, LRCH1, and MYL4 were potential progression rate associated biomarkers of PD. Additionally, these DEGs may be regulated by miRNAs of the miR-30 family and TFs STAT1 and GRHL3. Our results may contribute to our understanding of the molecular mechanisms underlying different PD progression profiles.

ARMOUR - A Rice miRNA: mRNA Interaction Resource.

PubMed

Sanan-Mishra, Neeti; Tripathi, Anita; Goswami, Kavita; Shukla, Rohit N; Vasudevan, Madavan; Goswami, Hitesh

2018-01-01

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Integrative Analysis of miRNA and mRNA Profiles in Response to Ethylene in Rose Petals during Flower Opening

PubMed Central

Pei, Haixia; Ma, Nan; Chen, Jiwei; Zheng, Yi; Tian, Ji; Li, Jing; Zhang, Shuai; Fei, Zhangjun; Gao, Junping

2013-01-01

MicroRNAs play an important role in plant development and plant responses to various biotic and abiotic stimuli. As one of the most important ornamental crops, rose (Rosa hybrida) possesses several specific morphological and physiological features, including recurrent flowering, highly divergent flower shapes, colors and volatiles. Ethylene plays an important role in regulating petal cell expansion during rose flower opening. Here, we report the population and expression profiles of miRNAs in rose petals during flower opening and in response to ethylene based on high throughput sequencing. We identified a total of 33 conserved miRNAs, as well as 47 putative novel miRNAs were identified from rose petals. The conserved and novel targets to those miRNAs were predicted using the rose floral transcriptome database. Expression profiling revealed that expression of 28 known (84.8% of known miRNAs) and 39 novel (83.0% of novel miRNAs) miRNAs was substantially changed in rose petals during the earlier opening period. We also found that 28 known and 22 novel miRNAs showed expression changes in response to ethylene treatment. Furthermore, we performed integrative analysis of expression profiles of miRNAs and their targets. We found that ethylene-caused expression changes of five miRNAs (miR156, miR164, miR166, miR5139 and rhy-miRC1) were inversely correlated to those of their seven target genes. These results indicate that these miRNA/target modules might be regulated by ethylene and were involved in ethylene-regulated petal growth. PMID:23696879

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes.

PubMed

Mehdi, Ahmed M; Hamilton-Williams, Emma E; Cristino, Alexandre; Ziegler, Anette; Bonifacio, Ezio; Le Cao, Kim-Anh; Harris, Mark; Thomas, Ranjeny

2018-03-08

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell-, DC-, and B cell-related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression.

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes

PubMed Central

Mehdi, Ahmed M.; Hamilton-Williams, Emma E.; Cristino, Alexandre; Ziegler, Anette; Harris, Mark

2018-01-01

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell–, DC-, and B cell–related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression. PMID:29515040

Divergent evolution of arrested development in the dauer stage of Caenorhabditis elegans and the infective stage of Heterodera glycines

PubMed Central

Elling, Axel A; Mitreva, Makedonka; Recknor, Justin; Gai, Xiaowu; Martin, John; Maier, Thomas R; McDermott, Jeffrey P; Hewezi, Tarek; McK Bird, David; Davis, Eric L; Hussey, Richard S; Nettleton, Dan; McCarter, James P; Baum, Thomas J

2007-01-01

Background The soybean cyst nematode Heterodera glycines is the most important parasite in soybean production worldwide. A comprehensive analysis of large-scale gene expression changes throughout the development of plant-parasitic nematodes has been lacking to date. Results We report an extensive genomic analysis of H. glycines, beginning with the generation of 20,100 expressed sequence tags (ESTs). In-depth analysis of these ESTs plus approximately 1,900 previously published sequences predicted 6,860 unique H. glycines genes and allowed a classification by function using InterProScan. Expression profiling of all 6,860 genes throughout the H. glycines life cycle was undertaken using the Affymetrix Soybean Genome Array GeneChip. Our data sets and results represent a comprehensive resource for molecular studies of H. glycines. Demonstrating the power of this resource, we were able to address whether arrested development in the Caenorhabditis elegans dauer larva and the H. glycines infective second-stage juvenile (J2) exhibits shared gene expression profiles. We determined that the gene expression profiles associated with the C. elegans dauer pathway are not uniformly conserved in H. glycines and that the expression profiles of genes for metabolic enzymes of C. elegans dauer larvae and H. glycines infective J2 are dissimilar. Conclusion Our results indicate that hallmark gene expression patterns and metabolism features are not shared in the developmentally arrested life stages of C. elegans and H. glycines, suggesting that developmental arrest in these two nematode species has undergone more divergent evolution than previously thought and pointing to the need for detailed genomic analyses of individual parasite species. PMID:17919324

Investigation of Gene Expression Correlating With Centrosome Amplification in Development and Progression of Breast Cancer

DTIC Science & Technology

2004-09-01

M. A., Broerse, J. J., deVries, J. B., vandenBerg, K. K., Knaan, 33. Papa, D., Li, S. A. & Li, J. J. (2003) Mol. Carcinog. 38, 97-105. S. & van der ...Veer LI, Dai H, van de Vijver MJ, et al. Gene (n = 84). These data are similar to those of van de expression profiling predicts clinical outcome of...breast Vijver et al,"O who demonstrated a significant cancer. Nature 2002;415:530-536. correlation between outcome and expression of 70 10 van de Vijver

Prognostic stratification improvement by integrating ID1/ID3/IGJ gene expression signature and immunophenotypic profile in adult patients with B-ALL.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Raney, Lauren F; Pinzon, Paula L; Lozano, Olga C; Campos, Alba M; Peñaloza, Niyireth; Solano, Julio; Herrera, Maria V; Zabaleta, Jovanny; Quijano, Sandra

2017-02-28

Survival of adults with B-Acute Lymphoblastic Leukemia requires accurate risk stratification of patients in order to provide the appropriate therapy. Contemporary techniques, using clinical and cytogenetic variables are incomplete for prognosis prediction. To improve the classification of adult patients diagnosed with B-ALL into prognosis groups, two strategies were examined and combined: the expression of the ID1/ID3/IGJ gene signature by RT-PCR and the immunophenotypic profile of 19 markers proposed in the EuroFlow protocol by Flow Cytometry in bone marrow samples. Both techniques were correlated to stratify patients into prognostic groups. An inverse relationship between survival and expression of the three-genes signature was observed and an immunophenotypic profile associated with clinical outcome was identified. Markers CD10 and CD20 were correlated with simultaneous overexpression of ID1, ID3 and IGJ. Patients with simultaneous expression of the poor prognosis gene signature and overexpression of CD10 or CD20, had worse Event Free Survival and Overall Survival than patients who had either the poor prognosis gene expression signature or only CD20 or CD10 overexpressed. By utilizing the combined evaluation of these two immunophenotypic markers along with the poor prognosis gene expression signature, the risk stratification can be significantly strengthened. Further studies including a large number of patients are needed to confirm these findings.

G-cimp status prediction of glioblastoma samples using mRNA expression data.

PubMed

Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K; Stevenson, Holly; Meltzer, Paul; Fine, Howard A

2012-01-01

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

G-Cimp Status Prediction Of Glioblastoma Samples Using mRNA Expression Data

PubMed Central

Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C.; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K.; Stevenson, Holly; Meltzer, Paul; Fine, Howard A.

2012-01-01

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data. PMID:23139755

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-06-14

Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Joule-Thomson effect and internal convection heat transfer in turbulent He II flow

NASA Technical Reports Server (NTRS)

Walstrom, P. L.

1988-01-01

The temperature rise in highly turbulent He II flowing in tubing was measured in the temperature range 1.6-2.1 K. The effect of internal convection heat transport on the predicted temperature profiles is calculated from the two-fluid model with mutual friction. The model predictions are in good agreement with the measurements, provided that the pressure gradient term is retained in the expression for internal convection heat flow.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Ma, Zihao; Carr, Steven A.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC).more » Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. Molecular & Cellular Proteomics 16: 10.1074/mcp.M116.060301, 121–134, 2017.« less

Effects of seawater acidification on gene expression: resolving broader-scale trends in sea urchins.

PubMed

Evans, Tyler G; Watson-Wynn, Priscilla

2014-06-01

Sea urchins are ecologically and economically important calcifying organisms threatened by acidification of the global ocean caused by anthropogenic CO2 emissions. Propelled by the sequencing of the purple sea urchin (Strongylocentrotus purpuratus) genome, profiling changes in gene expression during exposure to high pCO2 seawater has emerged as a powerful and increasingly common method to infer the response of urchins to ocean change. However, analyses of gene expression are sensitive to experimental methodology, and comparisons between studies of genes regulated by ocean acidification are most often made in the context of major caveats. Here we perform meta-analyses as a means of minimizing experimental discrepancies and resolving broader-scale trends regarding the effects of ocean acidification on gene expression in urchins. Analyses across eight studies and four urchin species largely support prevailing hypotheses about the impact of ocean acidification on marine calcifiers. The predominant expression pattern involved the down-regulation of genes within energy-producing pathways, a clear indication of metabolic depression. Genes with functions in ion transport were significantly over-represented and are most plausibly contributing to intracellular pH regulation. Expression profiles provided extensive evidence for an impact on biomineralization, epitomized by the down-regulation of seven spicule matrix proteins. In contrast, expression profiles provided limited evidence for CO2-mediated developmental delay or induction of a cellular stress response. Congruence between studies of gene expression and the ocean acidification literature in general validates the accuracy of gene expression in predicting the consequences of ocean change and justifies its continued use in future studies. © 2014 Marine Biological Laboratory.

FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

PubMed

El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

2016-01-01

A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein-DNA interfaces.

Identification of several circulating microRNAs from a genome-wide circulating microRNA expression profile as potential biomarkers for impaired glucose metabolism in polycystic ovarian syndrome.

PubMed

Jiang, Linlin; Huang, Jia; Chen, Yaxiao; Yang, Yabo; Li, Ruiqi; Li, Yu; Chen, Xiaoli; Yang, Dongzi

2016-07-01

This study aimed to detect serum microRNAs (miRNAs) differentially expressed between polycystic ovary syndrome (PCOS) patients with impaired glucose metabolism (IGM), PCOS patients with normal glucose tolerance (NGT), and healthy controls. A TaqMan miRNA array explored serum miRNA profiles as a pilot study, then selected miRNAs were analyzed in a validation cohort consisting of 65 PCOS women with IGM, 65 PCOS women with NGT, and 45 healthy women The relative expression of miR-122, miR-193b, and miR-194 was up-regulated in PCOS patients compared with controls, whereas that of miR-199b-5p was down-regulated. Furthermore, miR-122, miR-193b, and miR-194 were increased in the PCOS-IGM group compared with the PCOS-NGT group. Multiple linear regression analyses revealed that miR-193b and body mass index contributed independently to explain 43.7 % (P < 0.0001) of homeostasis model assessment-insulin resistance after adjustment for age. Investigation of diagnostic values confirmed the optimal combination of BMI and miR-193b to explore the possibility of IGM in PCOS women with area under the curve of 0.752 (95 % CI 0.667-0.837, P < 0.001). Bioinformatics analysis indicated that the predicted target functions of these miRNAs mainly involved glycometabolism and ovarian follicle development pathways, including the insulin signaling pathway, the neurotrophin signaling pathway, the PI3K-AKT signaling pathway, and regulation of actin cytoskeleton. This study expands our knowledge of the serum miRNA expression profiles of PCOS patients with IGM and the predicted target signal pathways involved in disease pathophysiology.

The HIV Nef protein modulates cellular and exosomal miRNA profiles in human monocytic cells.

PubMed

Aqil, Madeeha; Naqvi, Afsar Raza; Mallik, Saurav; Bandyopadhyay, Sanghamitra; Maulik, Ujjwal; Jameel, Shahid

2014-01-01

The HIV Nef protein is a multifunctional virulence factor that perturbs intracellular membranes and signalling and is secreted into exosomes. While Nef-containing exosomes have a distinct proteomic profile, no comprehensive analysis of their miRNA cargo has been carried out. Since Nef functions as a viral suppressor of RNA interference and disturbs the distribution of RNA-induced silencing complex proteins between cells and exosomes, we hypothesized that it might also affect the export of miRNAs into exosomes. Exosomes were purified from human monocytic U937 cells that stably expressed HIV-1 Nef. The RNA from cells and exosomes was profiled for 667 miRNAs using a Taqman Low Density Array. Selected miRNAs and their mRNA targets were validated by quantitative RT-PCR. Bioinformatics analyses were used to identify targets and predict pathways. Nef expression affected a significant fraction of miRNAs in U937 cells. Our analysis showed 47 miRNAs to be selectively secreted into Nef exosomes and 2 miRNAs to be selectively retained in Nef-expressing cells. The exosomal miRNAs were predicted to target several cellular genes in inflammatory cytokine and other pathways important for HIV pathogenesis, and an overwhelming majority had targets within the HIV genome. This is the first study to report miRnome analysis of HIV Nef expressing monocytes and exosomes. Our results demonstrate that Nef causes large-scale dysregulation of cellular miRNAs, including their secretion through exosomes. We suggest this to be a novel viral strategy to affect pathogenesis and to limit the effects of RNA interference on viral replication and persistence.

Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes.

PubMed

Daskalakis, Nikolaos P; Cohen, Hagit; Cai, Guiqing; Buxbaum, Joseph D; Yehuda, Rachel

2014-09-16

Delineating the molecular basis of individual differences in the stress response is critical to understanding the pathophysiology and treatment of posttraumatic stress disorder (PTSD). In this study, 7 d after predator-scent-stress (PSS) exposure, male and female rats were classified into vulnerable (i.e., "PTSD-like") and resilient (i.e., minimally affected) phenotypes on the basis of their performance on a variety of behavioral measures. Genome-wide expression profiling in blood and two limbic brain regions (amygdala and hippocampus), followed by quantitative PCR validation, was performed in these two groups of animals, as well as in an unexposed control group. Differentially expressed genes were identified in blood and brain associated with PSS-exposure and with distinct behavioral profiles postexposure. There was a small but significant between-tissue overlap (4-21%) for the genes associated with exposure-related individual differences, indicating convergent gene expression in both sexes. To uncover convergent signaling pathways across tissue and sex, upstream activated/deactivated transcription factors were first predicted for each tissue and then the respective pathways were identified. Glucocorticoid receptor (GR) signaling was the only convergent pathway associated with individual differences when using the most stringent statistical threshold. Corticosterone treatment 1 h after PSS-exposure prevented anxiety and hyperarousal 7 d later in both sexes, confirming the GR involvement in the PSS behavioral response. In conclusion, genes and pathways associated with extreme differences in the traumatic stress behavioral response can be distinguished from those associated with trauma exposure. Blood-based biomarkers can predict aspects of brain signaling. GR signaling is a convergent signaling pathway, associated with trauma-related individual differences in both sexes.

KRAS Genomic Status Predicts the Sensitivity of Ovarian Cancer Cells to Decitabine | Office of Cancer Genomics

Cancer.gov

Decitabine, a cancer therapeutic that inhibits DNA methylation, produces variable antitumor response rates in patients with solid tumors that might be leveraged clinically with identification of a predictive biomarker. In this study, we profiled the response of human ovarian, melanoma, and breast cancer cells treated with decitabine, finding that RAS/MEK/ERK pathway activation and DNMT1 expression correlated with cytotoxic activity. Further, we showed that KRAS genomic status predicted decitabine sensitivity in low-grade and high-grade serous ovarian cancer cells.

Profiles of neurological outcome prediction among intensivists.

PubMed

Racine, Eric; Dion, Marie-Josée; Wijman, Christine A C; Illes, Judy; Lansberg, Maarten G

2009-12-01

Advances in intensive care medicine have increased survival rates of patients with critical neurological conditions. The focus of prognostication for such patients is therefore shifting from predicting chances of survival to meaningful neurological recovery. This study assessed the variability in long-term outcome predictions among physicians and aimed to identify factors that may account for this variability. Based on a clinical vignette describing a comatose patient suffering from post-anoxic brain injury intensivists were asked in a semi-structured interview about the patient's specific neurological prognosis and about prognostication in general. Qualitative research methods were used to identify areas of variability in prognostication and to classify physicians according to specific prognostication profiles. Quantitative statistics were used to assess for associations between prognostication profiles and physicians' demographic and practice characteristics. Eighteen intensivists participated. Functional outcome predictions varied along an evaluative dimension (fair/good-poor) and a confidence dimension (certain-uncertain). More experienced physicians tended to be more pessimistic about the patient's functional outcome and more certain of their prognosis. Attitudes toward quality of life varied along an evaluative dimension (good-poor) and a "style" dimension (objective-subjective). Older and more experienced physicians were more likely to express objective judgments of quality of life and to predict a worse quality of life for the patient than their younger and less experienced counterparts. Various prognostication profiles exist among intensivists. These may be dictated by factors such as physicians' age and clinical experience. Awareness of these associations may be a first step to more uniform prognostication.

MicroRNA-106b~25 cluster is upregulated in relapsed MLL-rearranged pediatric acute myeloid leukemia

PubMed Central

Verboon, Lonneke J.; Obulkasim, Askar; de Rooij, Jasmijn D.E.; Katsman, Jenny E.; Sonneveld, Edwin; Baruchel, André; Trka, Jan; Reinhardt, Dirk; Pieters, Rob; Cloos, Jacqueline; Kaspers, Gertjan J.L.; Klusmann, Jan-Henning; Zwaan, Christian Michel; Fornerod, Maarten; van den Heuvel-Eibrink, Marry M.

2016-01-01

The most important reason for therapy failure in pediatric acute myeloid leukemia (AML) is relapse. In order to identify miRNAs that contribute to the clonal evolution towards relapse in pediatric AML, miRNA expression profiling of 127 de novo pediatric AML cases were used. In the diagnostic phase, no miRNA signatures could be identified that were predictive for relapse occurrence, in a large pediatric cohort, nor in a nested mixed lineage leukemia (MLL)-rearranged pediatric cohort. AML with MLL- rearrangements are found in 15-20% of all pediatric AML samples, and reveal a relapse rate up to 50% for certain translocation partner subgroups. Therefore, microRNA expression profiling of six paired initial diagnosis-relapse MLL-rearranged pediatric AML samples (test cohort) and additional eight paired initial diagnosis-relapse samples with MLL-rearrangements (validation cohort) was performed. A list of 53 differentially expressed miRNAs was identified of which the miR-106b~25 cluster, located in intron 13 of MCM7, was the most prominent. These differentially expressed miRNAs however could not predict a relapse in de novo AML samples with MLL-rearrangements at diagnosis. Furthermore, higher mRNA expression of both MCM7 and its upstream regulator E2F1 was found in relapse samples with MLL-rearrangements. In conclusion, we identified the miR-106b~25 cluster to be upregulated in relapse pediatric AML with MLL-rearrangements. PMID:27351222

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

PubMed Central

Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.

2014-01-01

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557

Individual differences in airline captains' personalities, communication strategies, and crew performance

NASA Technical Reports Server (NTRS)

Orasanu, Judith

1991-01-01

Aircrew effectiveness in coping with emergencies has been linked to captain's personality profile. The present study analyzed cockpit communication during simulated flight to examine the relation between captains' discourse strategies, personality profiles, and crew performance. Positive Instrumental/Expressive captains and Instrumental-Negative captains used very similar communication strategies and their crews made few errors. Their talk was distinguished by high levels of planning and strategizing, gathering information, predicting/alerting, and explaining, especially during the emergency flight phase. Negative-Expressive captains talked less overall, and engaged in little problem solving talk, even during emergencies. Their crews made many errors. Findings support the theory that high crew performance results when captains use language to build shared mental models for problem situations.

Differential Expression of MicroRNA and Predicted Targets in Pulmonary Sarcoidosis

PubMed Central

Crouser, Elliott D.; Julian, Mark W.; Crawford, Melissa; Shao, Guohong; Yu, Lianbo; Planck, Stephen R.; Rosenbaum, James T.; Nana-Sinkam, S. Patrick

2014-01-01

Background Recent studies show that various inflammatory diseases are regulated at the level of RNA translation by small non-coding RNAs, termed microRNAs (miRNAs). We sought to determine whether sarcoidosis tissues harbor a distinct pattern of miRNA expression and then considered their potential molecular targets. Methods and Results Genome-wide microarray analysis of miRNA expression in lung tissue and peripheral blood mononuclear cells (PBMCs) was performed and differentially expressed (DE)-miRNAs were then validated by real-time PCR. A distinct pattern of DE-miRNA expression was identified in both lung tissue and PBMCs of sarcoidosis patients. A subgroup of DE-miRNAs common to lung and lymph node tissues were predicted to target transforming growth factor (TGFβ)-regulated pathways. Likewise, the DE-miRNAs identified in PBMCs of sarcoidosis patients were predicted to target the TGFβ-regulated “wingless and integrase-1” (WNT) pathway. Conclusions This study is the first to profile miRNAs in sarcoidosis tissues and to consider their possible roles in disease pathogenesis. Our results suggest that miRNA regulate TGFβ and related WNT pathways in sarcoidosis tissues, pathways previously incriminated in the pathogenesis of sarcoidosis. PMID:22209793

Breast cancer: integrating the patient with her genome.

PubMed

Angrist, Misha

2005-01-01

Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.

Molecular profiling of single circulating tumor cells from lung cancer patients.

PubMed

Park, Seung-Min; Wong, Dawson J; Ooi, Chin Chun; Kurtz, David M; Vermesh, Ophir; Aalipour, Amin; Suh, Susie; Pian, Kelsey L; Chabon, Jacob J; Lee, Sang Hun; Jamali, Mehran; Say, Carmen; Carter, Justin N; Lee, Luke P; Kuschner, Ware G; Schwartz, Erich J; Shrager, Joseph B; Neal, Joel W; Wakelee, Heather A; Diehn, Maximilian; Nair, Viswam S; Wang, Shan X; Gambhir, Sanjiv S

2016-12-27

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

microRNA analysis of Taenia crassiceps cysticerci under praziquantel treatment and genome-wide identification of Taenia solium miRNAs.

PubMed

Pérez, Matías Gastón; Macchiaroli, Natalia; Lichtenstein, Gabriel; Conti, Gabriela; Asurmendi, Sebastián; Milone, Diego Humberto; Stegmayer, Georgina; Kamenetzky, Laura; Cucher, Marcela; Rosenzvit, Mara Cecilia

2017-09-01

MicroRNAs (miRNAs) are small non-coding RNAs that have emerged as important regulators of gene expression and perform critical functions in development and disease. In spite of the increased interest in miRNAs from helminth parasites, no information is available on miRNAs from Taenia solium, the causative agent of cysticercosis, a neglected disease affecting millions of people worldwide. Here we performed a comprehensive analysis of miRNAs from Taenia crassiceps, a laboratory model for T. solium studies, and identified miRNAs in the T. solium genome. Moreover, we analysed the effect of praziquantel, one of the two main drugs used for cysticercosis treatment, on the miRNA expression profile of T. crassiceps cysticerci. Using small RNA-seq and two independent algorithms for miRNA prediction, as well as northern blot validation, we found transcriptional evidence of 39 miRNA loci in T. crassiceps. Since miRNAs were mapped to the T. solium genome, these miRNAs are considered common to both parasites. The miRNA expression profile of T. crassiceps was biased to the same set of highly expressed miRNAs reported in other cestodes. We found a significant altered expression of miR-7b under praziquantel treatment. In addition, we searched for miRNAs predicted to target genes related to drug response. We performed a detailed target prediction for miR-7b and found genes related to drug action. We report an initial approach to study the effect of sub-lethal drug treatment on miRNA expression in a cestode parasite, which provides a platform for further studies of miRNA involvement in drug effects. The results of our work could be applied to drug development and provide basic knowledge of cysticercosis and other neglected helminth infections. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Expression of the filaggrin gene in umbilical cord blood predicts eczema risk in infancy: A birth cohort study.

PubMed

Ziyab, A H; Ewart, S; Lockett, G A; Zhang, H; Arshad, H; Holloway, J W; Karmaus, W

2017-09-01

Filaggrin gene (FLG) expression, particularly in the skin, has been linked to the development of the skin barrier and is associated with eczema risk. However, knowledge as to whether FLG expression in umbilical cord blood (UCB) is associated with eczema development and prediction is lacking. This study sought to assess whether FLG expression in UCB associates with and predicts the development of eczema in infancy. Infants enrolled in a birth cohort study (n=94) were assessed for eczema at ages 3, 6, and 12 months. Five probes measuring FLG transcripts expression in UCB were available from genomewide gene expression profiling. FLG genetic variants R501X, 2282del4, and S3247X were genotyped. Associations were assessed using Poisson regression with robust variance estimation. Area under the curve (AUC), describing the discriminatory/predictive performance of fitted models, was estimated from logistic regression. Increased level of FLG expression measured by probe A_24_P51322 was associated with reduced risk of eczema during the first year of life (RR=0.60, 95% CI: 0.38-0.95). In contrast, increased level of FLG antisense transcripts measured by probe A_21_P0014075 was associated with increased risk of eczema (RR=2.02, 95% CI: 1.10-3.72). In prediction models including FLG expression, FLG genetic variants, and sex, discrimination between children who will and will not develop eczema at 3 months of age was high (AUC: 0.91, 95% CI: 0.84-0.98). This study demonstrated, for the first time, that FLG expression in UCB is associated with eczema development in infancy. Moreover, our analysis provided prediction models that were capable of discriminating, to a great extent, between those who will and will not develop eczema in infancy. Therefore, early identification of infants at increased risk of developing eczema is possible and such high-risk newborns may benefit from early stratification and intervention. © 2017 John Wiley & Sons Ltd.

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Murine Hyperglycemic Vasculopathy and Cardiomyopathy: Whole-Genome Gene Expression Analysis Predicts Cellular Targets and Regulatory Networks Influenced by Mannose Binding Lectin

PubMed Central

Zou, Chenhui; La Bonte, Laura R.; Pavlov, Vasile I.; Stahl, Gregory L.

2012-01-01

Hyperglycemia, in the absence of type 1 or 2 diabetes, is an independent risk factor for cardiovascular disease. We have previously demonstrated a central role for mannose binding lectin (MBL)-mediated cardiac dysfunction in acute hyperglycemic mice. In this study, we applied whole-genome microarray data analysis to investigate MBL’s role in systematic gene expression changes. The data predict possible intracellular events taking place in multiple cellular compartments such as enhanced insulin signaling pathway sensitivity, promoted mitochondrial respiratory function, improved cellular energy expenditure and protein quality control, improved cytoskeleton structure, and facilitated intracellular trafficking, all of which may contribute to the organismal health of MBL null mice against acute hyperglycemia. Our data show a tight association between gene expression profile and tissue function which might be a very useful tool in predicting cellular targets and regulatory networks connected with in vivo observations, providing clues for further mechanistic studies. PMID:22375142

Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

PubMed

Uhl, Elizabeth W; Warner, Natalie J

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

RUNX1 and RUNX3 protect against YAP-mediated EMT, stem-ness and shorter survival outcomes in breast cancer

PubMed Central

Kulkarni, Madhura; Tan, Tuan Zea; Syed Sulaiman, Nurfarhanah Bte; Lamar, John M.; Bansal, Prashali; Cui, Jianzhou; Qiao, Yiting; Ito, Yoshiaki

2018-01-01

Hippo pathway target, YAP has emerged as an important player in solid tumor progression. Here, we identify RUNX1 and RUNX3 as novel negative regulators of oncogenic function of YAP in the context of breast cancer. RUNX proteins are one of the first transcription factors identified to interact with YAP. RUNX1 or RUNX3 expression abrogates YAP-mediated pro-tumorigenic properties of mammary epithelial cell lines in an interaction dependent manner. RUNX1 and RUNX3 inhibit YAP-mediated migration and stem-ness properties of mammary epithelial cell lines by co-regulating YAP-mediated gene expression. Analysis of whole genome expression profiles of breast cancer samples revealed significant co-relation between YAP–RUNX1/RUNX3 expression levels and survival outcomes of breast cancer patients. High RUNX1/RUNX3 expression proved protective towards YAP-dependent patient survival outcomes. High YAP in breast cancer patients’ expression profiles co-related with EMT and stem-ness gene signature enrichment. High RUNX1/RUNX3 expression along with high YAP reflected lower enrichment of EMT and stem-ness signatures. This antagonistic activity of RUNX1 and RUNX3 towards oncogenic function of YAP identified in mammary epithelial cells as well as in breast cancer expression profiles gives a novel mechanistic insight into oncogene–tumor suppressor interplay in the context of breast cancer progression. The novel interplay between YAP, RUNX1 and RUNX3 and its significance in breast cancer progression can serve as a prognostic tool to predict cancer recurrence. PMID:29581836

Identification of genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig.

PubMed

Komatsu, Yuuta; Sukegawa, Shin; Yamashita, Mai; Katsuda, Naoki; Tong, Bin; Ohta, Takeshi; Kose, Hiroyuki; Yamada, Takahisa

2016-06-01

Suppression subtractive hybridization was used to identify genes showing differential expression profile associated with growth rate in skeletal muscle tissue of Landrace weanling pig. Two subtracted cDNA populations were generated from musculus longissimus muscle tissues of selected pigs with extreme expected breeding values at the age of 100 kg. Three upregulated genes (EEF1A2, TSG101 and TTN) and six downregulated genes (ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7) in pig with genetic propensity for higher growth rate were identified by sequence analysis of 12 differentially expressed clones selected by differential screening following the generation of the subtracted cDNA population. Real-time PCR analysis confirmed difference in expression profiles of the identified genes in musculus longissimus muscle tissues between the two Landrace weanling pig groups with divergent genetic propensity for growth rate. Further, differential expression of the identified genes except for the TTN was validated by Western blot analysis. Additionally, the eight genes other than the ATP5C1 colocalized with the same chromosomal positions as QTLs that have been previously identified for growth rate traits. Finally, the changes of expression predicted from gene function suggested association of upregulation of expression of the EEF1A2, TSG101 and TTN genes and downregulation of the ATP5B, ATP5C1, COQ3, HADHA, MYH1 and MYH7 gene expression with increased growth rate. The identified genes will provide an important insight in understanding the molecular mechanism underlying growth rate in Landrace pig breed.

Multiscale mechanisms of cell migration during development: theory and experiment.

PubMed

McLennan, Rebecca; Dyson, Louise; Prather, Katherine W; Morrison, Jason A; Baker, Ruth E; Maini, Philip K; Kulesa, Paul M

2012-08-01

Long-distance cell migration is an important feature of embryonic development, adult morphogenesis and cancer, yet the mechanisms that drive subpopulations of cells to distinct targets are poorly understood. Here, we use the embryonic neural crest (NC) in tandem with theoretical studies to evaluate model mechanisms of long-distance cell migration. We find that a simple chemotaxis model is insufficient to explain our experimental data. Instead, model simulations predict that NC cell migration requires leading cells to respond to long-range guidance signals and trailing cells to short-range cues in order to maintain a directed, multicellular stream. Experiments confirm differences in leading versus trailing NC cell subpopulations, manifested in unique cell orientation and gene expression patterns that respond to non-linear tissue growth of the migratory domain. Ablation experiments that delete the trailing NC cell subpopulation reveal that leading NC cells distribute all along the migratory pathway and develop a leading/trailing cellular orientation and gene expression profile that is predicted by model simulations. Transplantation experiments and model predictions that move trailing NC cells to the migratory front, or vice versa, reveal that cells adopt a gene expression profile and cell behaviors corresponding to the new position within the migratory stream. These results offer a mechanistic model in which leading cells create and respond to a cell-induced chemotactic gradient and transmit guidance information to trailing cells that use short-range signals to move in a directional manner.

Mean of the typical decoding rates: a new translation efficiency index based on the analysis of ribosome profiling data.

PubMed

Dana, Alexandra; Tuller, Tamir

2014-12-01

Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism's ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs.tau.ac.il/~tamirtul/MTDR/MTDR_Install.html. Copyright © 2015 Dana and Tuller.

CrossLink: a novel method for cross-condition classification of cancer subtypes.

PubMed

Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

2016-08-22

We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

Gene expression patterns in formalin-fixed, paraffin-embedded core biopsies predict docetaxel chemosensitivity in breast cancer patients.

PubMed

Chang, Jenny C; Makris, Andreas; Gutierrez, M Carolina; Hilsenbeck, Susan G; Hackett, James R; Jeong, Jennie; Liu, Mei-Lan; Baker, Joffre; Clark-Langone, Kim; Baehner, Frederick L; Sexton, Krsytal; Mohsin, Syed; Gray, Tara; Alvarez, Laura; Chamness, Gary C; Osborne, C Kent; Shak, Steven

2008-03-01

Previously, we had identified gene expression patterns that predicted response to neoadjuvant docetaxel. Other studies have validated that a high Recurrence Score (RS) by the 21-gene RT-PCR assay is predictive of worse prognosis but better response to chemotherapy. We investigated whether tumor expression of these 21 genes and other candidate genes can predict response to docetaxel. Core biopsies from 97 patients were obtained before treatment with neoadjuvant docetaxel (4 cycles, 100 mg/m2 q3 weeks). Three 10-microm FFPE sections were submitted for quantitative RT-PCR assays of 192 genes that were selected from our previous work and the literature. Of the 97 patients, 81 (84%) had sufficient invasive cancer, 80 (82%) had sufficient RNA for QRTPCR assay, and 72 (74%) had clinical response data. Mean age was 48.5 years, and the median tumor size was 6 cm. Clinical complete responses (CR) were observed in 12 (17%), partial responses in 41 (57%), stable disease in 17 (24%), and progressive disease in 2 patients (3%). A significant relationship (P<0.05) between gene expression and CR was observed for 14 genes, including CYBA. CR was associated with lower expression of the ER gene group and higher expression of the proliferation gene group from the 21 gene assay. Of note, CR was more likely with a high RS (P=0.008). We have established molecular profiles of sensitivity to docetaxel. RT-PCR technology provides a potential platform for a predictive test of docetaxel chemosensitivity using small amounts of routinely processed material.

Comparative analysis of gene expression profiles of OPN signaling pathway in four kinds of liver diseases.

PubMed

Wang, Gaiping; Chen, Shasha; Zhao, Congcong; Li, Xiaofang; Zhao, Weiming; Yang, Jing; Chang, Cuifang; Xu, Cunshuan

2016-09-01

To explore the relevance of OPN signalling pathway to the occurrence and development of nonalcoholic fatty liver disease (NAFLD), liver cirrhosis (LC), hepatic cancer (HC) and acute hepatic failure (AHF) at transcriptional level, Rat Genome 230 2.0 Array was used to detect expression profiles of OPN signalling pathway-related genes in four kinds of liver diseases. The results showed that 23, 33, 59 and 74 genes were significantly changed in the above four kinds of liver diseases, respectively. H-clustering analysis showed that the expression profiles of OPN signalling-related genes were notably different in four kinds of liver diseases. Subsequently, a total of above-mentioned 147 genes were categorized into four clusters by k-means according to the similarity of gene expression, and expression analysis systematic explorer (EASE) functional enrichment analysis revealed that OPN signalling pathway-related genes were involved in cell adhesion and migration, cell proliferation, apoptosis, stress and inflammatory reaction, etc. Finally, ingenuity pathway analysis (IPA) software was used to predict the functions of OPN signalling-related genes, and the results indicated that the activities of ROS production, cell adhesion and migration, cell proliferation were remarkably increased, while that of apoptosis, stress and inflammatory reaction were reduced in four kinds of liver diseases. In summary, the above physiological activities changed more obviously in LC, HC and AHF than in NAFLD.

A biomarker-based screen of a gene expression compendium ...

EPA Pesticide Factsheets

Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse liver. A gene expression biomarker of 48 genes which accurately predicted Nrf2 activation was used to identify factors which resulted in a gene expression profile with significant correlation to the biomarker. A number of novel insights were made. Chemicals that activated the xenosensor constitutive activated receptor (CAR) consistently activated Nrf2 across hundreds of profiles, possibly downstream of Cyp-induced increases in oxidative stress. Nrf2 activation was also found to be negatively regulated by the growth hormone (GH)- and androgen-regulated transcription factor STAT5b, a transcription factor suppressed by CAR. Nrf2 was activated when STAT5b was suppressed in female mice vs. male mice, after exposure to estrogens, or in genetic mutants in which GH signaling was disrupted. A subset of the mutants that show STAT5b suppression and Nrf2 activation result in increased resistance to environmental stressors and increased longevity. This study describes a novel approach for understanding the network of factors that regulate the Nrf2 pathway and highlights novel interactions between Nrf2, CAR and STAT5b transcription factors. (This abstract does not represent EPA policy.) Computational appr

Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.

PubMed

Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L

2016-10-10

Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.

Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

PubMed Central

Wang, Liming; Zhu, L.; Luan, R.; Wang, L.; Fu, J.; Wang, X.; Sui, L.

2016-01-01

Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM. PMID:27737314

Emergent literacy profiles of preschool-age children with specific language impairment.

PubMed

Cabell, Sonia Q; Lomax, Richard G; Justice, Laura M; Breit-Smith, Allison; Skibbe, Lori E; McGinty, Anita S

2010-12-01

The primary aim of the present study was to explore the heterogeneity of emergent literacy skills among preschool-age children with specific language impairment (SLI) through examination of profiles of performance. Fifty-nine children with SLI were assessed on a battery of emergent literacy skills (i.e., alphabet knowledge, print concepts, emergent writing, rhyme awareness) and oral language skills (i.e., receptive/expressive vocabulary and grammar). Cluster analysis techniques identified three emergent literacy profiles: (1) Highest Emergent Literacy, Strength in Alphabet Knowledge; (2) Average Emergent Literacy, Strength in Print Concepts; and (3) Lowest Emergent Literacy across Skills. After taking into account the contribution of child age, receptive and expressive language skills made a small contribution to the prediction of profile membership. The present findings, which may be characterized as exploratory given the relatively modest sample size, suggest that preschool-age children with SLI display substantial individual differences with regard to their emergent literacy skills and that these differences cannot be fully determined by children's age or oral language performance. Replication of the present findings with a larger sample of children is needed.

Systems analysis of apoptosis protein expression allows the case-specific prediction of cell death responsiveness of melanoma cells

PubMed Central

Passante, E; Würstle, M L; Hellwig, C T; Leverkus, M; Rehm, M

2013-01-01

Many cancer entities and their associated cell line models are highly heterogeneous in their responsiveness to apoptosis inducers and, despite a detailed understanding of the underlying signaling networks, cell death susceptibility currently cannot be predicted reliably from protein expression profiles. Here, we demonstrate that an integration of quantitative apoptosis protein expression data with pathway knowledge can predict the cell death responsiveness of melanoma cell lines. By a total of 612 measurements, we determined the absolute expression (nM) of 17 core apoptosis regulators in a panel of 11 melanoma cell lines, and enriched these data with systems-level information on apoptosis pathway topology. By applying multivariate statistical analysis and multi-dimensional pattern recognition algorithms, the responsiveness of individual cell lines to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or dacarbazine (DTIC) could be predicted with very high accuracy (91 and 82% correct predictions), and the most effective treatment option for individual cell lines could be pre-determined in silico. In contrast, cell death responsiveness was poorly predicted when not taking knowledge on protein–protein interactions into account (55 and 36% correct predictions). We also generated mathematical predictions on whether anti-apoptotic Bcl-2 family members or x-linked inhibitor of apoptosis protein (XIAP) can be targeted to enhance TRAIL responsiveness in individual cell lines. Subsequent experiments, making use of pharmacological Bcl-2/Bcl-xL inhibition or siRNA-based XIAP depletion, confirmed the accuracy of these predictions. We therefore demonstrate that cell death responsiveness to TRAIL or DTIC can be predicted reliably in a large number of melanoma cell lines when investigating expression patterns of apoptosis regulators in the context of their network-level interplay. The capacity to predict responsiveness at the cellular level may contribute to personalizing anti-cancer treatments in the future. PMID:23933815

MicroRNA profiling reveals new aspects of HIV neurodegeneration: caspase-6 regulates astrocyte survival.

PubMed

Noorbakhsh, Farshid; Ramachandran, Rithwik; Barsby, Nicola; Ellestad, Kristofor K; LeBlanc, Andrea; Dickie, Peter; Baker, Glen; Hollenberg, Morley D; Cohen, Eric A; Power, Christopher

2010-06-01

MicroRNAs (miRNAs) are small noncoding RNA molecules, which are known to regulate gene expression in physiological and pathological conditions. miRNA profiling was performed using brain tissue from patients with HIV encephalitis (HIVE), a neuroinflammatory/degenerative disorder caused by HIV infection of the brain. Microarray analysis showed differential expression of multiple miRNAs in HIVE compared to control brains. Target prediction and gene ontology enrichment analysis disclosed targeting of several gene families/biological processes by differentially expressed miRNAs (DEMs), with cell death-related genes, including caspase-6, showing a bias toward down-regulated DEMs. Consistent with the miRNA data, HIVE brains exhibited higher levels of caspase-6 transcripts compared with control patients. Immunohistochemical analysis showed localization of the cleaved form of caspase-6 in astrocytes in HIVE brain sections. Exposure of cultured human primary astrocytes to HIV viral protein R (Vpr) induced p53 up-regulation, loss of mitochondrial membrane potential, and caspase-6 activation followed by cell injury. Transgenic mice, expressing Vpr in microglial cells, demonstrated astrocyte apoptosis in brain, which was associated with caspase-6 activation and neurobehavioral abnormalities. Overall, these data point to previously unrecognized alterations in miRNA profile in the brain during HIV infection, which contribute to cell death through dysregulation of cell death machinery.

Recombinant Human Lysyl Oxidase-like 2 Secreted from Human Embryonic Kidney Cells Displays Complex and Acidic Glycans at All Three N-Linked Glycosylation Sites.

PubMed

Go, Eden P; Moon, Hee-Jung; Mure, Minae; Desaire, Heather

2018-05-04

Human lysyl oxidase-like 2 (hLOXL2), a glycoprotein implicated in tumor progression and organ fibrosis, is a molecular target for anticancer and antifibrosis treatment. This glycoprotein contains three predicted N-linked glycosylation sites; one is near the protein's active site, and at least one more is known to facilitate the protein's secretion. Because the glycosylation impacts the protein's biology, we sought to characterize the native, mammalian glycosylation profile and to determine how closely this profile is recapitulated when the protein is expressed in insect cells. All three glycosylation sites on the protein, expressed in human embryonic kidney (HEK) cells, were characterized individually using a mass spectrometry-based glycopeptide analysis workflow. These data were compared to the glycosylation profile of the same protein expressed in insect cells. We found that the producer cell type imparts a substantial influence on the glycosylation of this important protein. The more-relevant version, expressed in HEK cells, contains large, acidic glycoforms; these glycans are not generated in insect cells. The glycosylation differences likely have structural and functional consequences, and these data should be considered when generating protein for functional studies or for high-throughput screening campaigns.

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ion channel gene expression predicts survival in glioma patients

PubMed Central

Wang, Rong; Gurguis, Christopher I.; Gu, Wanjun; Ko, Eun A; Lim, Inja; Bang, Hyoweon; Zhou, Tong; Ko, Jae-Hong

2015-01-01

Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients. PMID:26235283

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

PubMed

Jung, Ki-Hong; Dardick, Christopher; Bartley, Laura E; Cao, Peijian; Phetsom, Jirapa; Canlas, Patrick; Seo, Young-Su; Shultz, Michael; Ouyang, Shu; Yuan, Qiaoping; Frank, Bryan C; Ly, Eugene; Zheng, Li; Jia, Yi; Hsia, An-Ping; An, Kyungsook; Chou, Hui-Hsien; Rocke, David; Lee, Geun Cheol; Schnable, Patrick S; An, Gynheung; Buell, C Robin; Ronald, Pamela C

2008-10-06

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

Identification and Expression Analysis of microRNAs at the Grain Filling Stage in Rice(Oryza sativa L.)via Deep Sequencing

PubMed Central

Yi, Rong; Zhu, Zhixuan; Hu, Jihong; Qian, Qian; Dai, Jincheng; Ding, Yi

2013-01-01

MicroRNAs (miRNAs) have been shown to play crucial roles in the regulation of plant development. In this study, high-throughput RNA-sequencing technology was used to identify novel miRNAs, and to reveal miRNAs expression patterns at different developmental stages during rice (Oryza sativa L.) grain filling. A total of 434 known miRNAs (380, 402, 390 and 392 at 5, 7, 12 and 17 days after fertilization, respectively.) were obtained from rice grain. The expression profiles of these identified miRNAs were analyzed and the results showed that 161 known miRNAs were differentially expressed during grain development, a high proportion of which were up-regulated from 5 to 7 days after fertilization. In addition, sixty novel miRNAs were identified, and five of these were further validated experimentally. Additional analysis showed that the predicted targets of the differentially expressed miRNAs may participate in signal transduction, carbohydrate and nitrogen metabolism, the response to stimuli and epigenetic regulation. In this study, differences were revealed in the composition and expression profiles of miRNAs among individual developmental stages during the rice grain filling process, and miRNA editing events were also observed, analyzed and validated during this process. The results provide novel insight into the dynamic profiles of miRNAs in developing rice grain and contribute to the understanding of the regulatory roles of miRNAs in grain filling. PMID:23469249

Differential Responses to Wnt and PCP Disruption Predict Expression and Developmental Function of Conserved and Novel Genes in a Cnidarian

PubMed Central

Lapébie, Pascal; Ruggiero, Antonella; Barreau, Carine; Chevalier, Sandra; Chang, Patrick; Dru, Philippe; Houliston, Evelyn; Momose, Tsuyoshi

2014-01-01

We have used Digital Gene Expression analysis to identify, without bilaterian bias, regulators of cnidarian embryonic patterning. Transcriptome comparison between un-manipulated Clytia early gastrula embryos and ones in which the key polarity regulator Wnt3 was inhibited using morpholino antisense oligonucleotides (Wnt3-MO) identified a set of significantly over and under-expressed transcripts. These code for candidate Wnt signaling modulators, orthologs of other transcription factors, secreted and transmembrane proteins known as developmental regulators in bilaterian models or previously uncharacterized, and also many cnidarian-restricted proteins. Comparisons between embryos injected with morpholinos targeting Wnt3 and its receptor Fz1 defined four transcript classes showing remarkable correlation with spatiotemporal expression profiles. Class 1 and 3 transcripts tended to show sustained expression at “oral” and “aboral” poles respectively of the developing planula larva, class 2 transcripts in cells ingressing into the endodermal region during gastrulation, while class 4 gene expression was repressed at the early gastrula stage. The preferential effect of Fz1-MO on expression of class 2 and 4 transcripts can be attributed to Planar Cell Polarity (PCP) disruption, since it was closely matched by morpholino knockdown of the specific PCP protein Strabismus. We conclude that endoderm and post gastrula-specific gene expression is particularly sensitive to PCP disruption while Wnt-/β-catenin signaling dominates gene regulation along the oral-aboral axis. Phenotype analysis using morpholinos targeting a subset of transcripts indicated developmental roles consistent with expression profiles for both conserved and cnidarian-restricted genes. Overall our unbiased screen allowed systematic identification of regionally expressed genes and provided functional support for a shared eumetazoan developmental regulatory gene set with both predicted and previously unexplored members, but also demonstrated that fundamental developmental processes including axial patterning and endoderm formation in cnidarians can involve newly evolved (or highly diverged) genes. PMID:25233086

Differential responses to Wnt and PCP disruption predict expression and developmental function of conserved and novel genes in a cnidarian.

PubMed

Lapébie, Pascal; Ruggiero, Antonella; Barreau, Carine; Chevalier, Sandra; Chang, Patrick; Dru, Philippe; Houliston, Evelyn; Momose, Tsuyoshi

2014-09-01

We have used Digital Gene Expression analysis to identify, without bilaterian bias, regulators of cnidarian embryonic patterning. Transcriptome comparison between un-manipulated Clytia early gastrula embryos and ones in which the key polarity regulator Wnt3 was inhibited using morpholino antisense oligonucleotides (Wnt3-MO) identified a set of significantly over and under-expressed transcripts. These code for candidate Wnt signaling modulators, orthologs of other transcription factors, secreted and transmembrane proteins known as developmental regulators in bilaterian models or previously uncharacterized, and also many cnidarian-restricted proteins. Comparisons between embryos injected with morpholinos targeting Wnt3 and its receptor Fz1 defined four transcript classes showing remarkable correlation with spatiotemporal expression profiles. Class 1 and 3 transcripts tended to show sustained expression at "oral" and "aboral" poles respectively of the developing planula larva, class 2 transcripts in cells ingressing into the endodermal region during gastrulation, while class 4 gene expression was repressed at the early gastrula stage. The preferential effect of Fz1-MO on expression of class 2 and 4 transcripts can be attributed to Planar Cell Polarity (PCP) disruption, since it was closely matched by morpholino knockdown of the specific PCP protein Strabismus. We conclude that endoderm and post gastrula-specific gene expression is particularly sensitive to PCP disruption while Wnt-/β-catenin signaling dominates gene regulation along the oral-aboral axis. Phenotype analysis using morpholinos targeting a subset of transcripts indicated developmental roles consistent with expression profiles for both conserved and cnidarian-restricted genes. Overall our unbiased screen allowed systematic identification of regionally expressed genes and provided functional support for a shared eumetazoan developmental regulatory gene set with both predicted and previously unexplored members, but also demonstrated that fundamental developmental processes including axial patterning and endoderm formation in cnidarians can involve newly evolved (or highly diverged) genes.

Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles

PubMed Central

Thaden, Joshua T; Mogno, Ilaria; Wierzbowski, Jamey; Cottarel, Guillaume; Kasif, Simon; Collins, James J; Gardner, Timothy S

2007-01-01

Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data. PMID:17214507

Cell Fate Decision as High-Dimensional Critical State Transition

PubMed Central

Zhou, Joseph; Castaño, Ivan G.; Leong-Quong, Rebecca Y. Y.; Chang, Hannah; Trachana, Kalliopi; Giuliani, Alessandro; Huang, Sui

2016-01-01

Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of “rebellious cells” that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease. PMID:28027308

A novel FY*A allele with the 265T and 298A SNPs formerly associated exclusively with the FY*B allele and weak Fy(b) antigen expression: implication for genotyping interpretative algorithms.

PubMed

Lopez, G H; Condon, J A; Wilson, B; Martin, J R; Liew, Y-W; Flower, R L; Hyland, C A

2015-01-01

An Australian Caucasian blood donor consistently presented a serology profile for the Duffy blood group as Fy(a+b+) with Fy(a) antigen expression weaker than other examples of Fy(a+b+) red cells. Molecular typing studies were performed to investigate the reason for the observed serology profile. Blood group genotyping was performed using a commercial SNP microarray platform. Sanger sequencing was performed using primer sets to amplify across exons 1 and 2 of the FY gene and using allele-specific primers. The propositus was genotyped as FY*A/B, FY*X heterozygote that predicted the Fy(a+b+(w) ) phenotype. Sequencing identified the 265T and 298A variants on the FY*A allele. This link between FY*A allele and 265T was confirmed by allele-specific PCR. The reduced Fy(a) antigen reactivity is attributed to a FY*A allele-carrying 265T and 298A variants previously defined in combination only with the FY*B allele and associated with weak Fy(b) antigen expression. This novel allele should be considered in genotyping interpretative algorithms for generating a predicted phenotype. © 2014 International Society of Blood Transfusion.

Prediction of Metabolic Flux Distribution from Gene Expression Data Based on the Flux Minimization Principle

DTIC Science & Technology

2014-11-14

problem. Modification of the PLOS ONE | www.plosone.org 1 November 2014 | Volume 9 | Issue 11 | e112524 Report Documentation Page Form ApprovedOMB No. 0704... Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 FBA algorithm to incorporate additional biological information from gene expression profiles is...We set the maximization of biomass production as the objective of FBA and implemented it in two different forms : without flux minimization (or

A gene expression biomarker accurately predicts estrogen ...

EPA Pesticide Factsheets

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

Characterizing crown fuel distribution for conifers in the interior western United States

Treesearch

Seth Ex; Frederick W. Smith; Tara Keyser

2015-01-01

Canopy fire hazard evaluation is essential for prioritizing fuel treatments and for assessing potential risk to firefighters during suppression activities. Fire hazard is usually expressed as predicted potential fire behavior, which is sensitive to the methodology used to quantitatively describe fuel profiles: methodologies that assume that fuel is distributed...

A Dynamic Bronchial Airway Gene Expression Signature of Chronic Obstructive Pulmonary Disease and Lung Function Impairment

PubMed Central

Steiling, Katrina; van den Berge, Maarten; Hijazi, Kahkeshan; Florido, Roberta; Campbell, Joshua; Liu, Gang; Xiao, Ji; Zhang, Xiaohui; Duclos, Grant; Drizik, Eduard; Si, Huiqing; Perdomo, Catalina; Dumont, Charles; Coxson, Harvey O.; Alekseyev, Yuriy O.; Sin, Don; Pare, Peter; Hogg, James C.; McWilliams, Annette; Hiemstra, Pieter S.; Sterk, Peter J.; Timens, Wim; Chang, Jeffrey T.; Sebastiani, Paola; O’Connor, George T.; Bild, Andrea H.; Postma, Dirkje S.; Lam, Stephen

2013-01-01

Rationale: Molecular phenotyping of chronic obstructive pulmonary disease (COPD) has been impeded in part by the difficulty in obtaining lung tissue samples from individuals with impaired lung function. Objectives: We sought to determine whether COPD-associated processes are reflected in gene expression profiles of bronchial airway epithelial cells obtained by bronchoscopy. Methods: Gene expression profiling of bronchial brushings obtained from 238 current and former smokers with and without COPD was performed using Affymetrix Human Gene 1.0 ST Arrays. Measurements and Main Results: We identified 98 genes whose expression levels were associated with COPD status, FEV1% predicted, and FEV1/FVC. In silico analysis identified activating transcription factor 4 (ATF4) as a potential transcriptional regulator of genes with COPD-associated airway expression, and ATF4 overexpression in airway epithelial cells in vitro recapitulates COPD-associated gene expression changes. Genes with COPD-associated expression in the bronchial airway epithelium had similarly altered expression profiles in prior studies performed on small-airway epithelium and lung parenchyma, suggesting that transcriptomic alterations in the bronchial airway epithelium reflect molecular events found at more distal sites of disease activity. Many of the airway COPD-associated gene expression changes revert toward baseline after therapy with the inhaled corticosteroid fluticasone in independent cohorts. Conclusions: Our findings demonstrate a molecular field of injury throughout the bronchial airway of active and former smokers with COPD that may be driven in part by ATF4 and is modifiable with therapy. Bronchial airway epithelium may ultimately serve as a relatively accessible tissue in which to measure biomarkers of disease activity for guiding clinical management of COPD. PMID:23471465

High interleukin-15 expression characterizes childhood acute lymphoblastic leukemia with involvement of the CNS.

PubMed

Cario, Gunnar; Izraeli, Shai; Teichert, Anja; Rhein, Peter; Skokowa, Julia; Möricke, Anja; Zimmermann, Martin; Schrauder, Andre; Karawajew, Leonid; Ludwig, Wolf-Dieter; Welte, Karl; Schünemann, Holger J; Schlegelberger, Brigitte; Schrappe, Martin; Stanulla, Martin

2007-10-20

Applying current diagnostic methods, overt CNS involvement is a rare event in childhood acute lymphoblastic leukemia (ALL). In contrast, CNS-directed therapy is essential for all patients with ALL because without it, the majority of patients eventually will experience relapse. To approach this discrepancy and to explore potential distinct biologic properties of leukemic cells that migrate into the CNS, we compared gene expression profiles of childhood ALL patients with initial CNS involvement with the profiles of CNS-negative patients. We evaluated leukemic gene expression profiles from the bone marrow of 17 CNS-positive patients and 26 CNS-negative patients who were frequency matched for risk factors associated with CNS involvement. Results were confirmed by real-time quantitative polymerase chain reaction analysis and validated using independent patient samples. Interleukin-15 (IL-15) expression was consistently upregulated in leukemic cells of CNS-positive patients compared with CNS-negative patients. In multivariate analysis, IL-15 expression levels greater than the median were associated with CNS involvement compared with expression equal to or less than the median (odds ratio [OR] = 10.70; 95% CI, 2.95 to 38.81). Diagnostic likelihood ratios for CNS positivity were 0.09 (95% CI, 0.01 to 0.65) for the first and 6.93 (95% CI, 2.55 to 18.83) for the fourth IL-15 expression quartiles. In patients who were CNS negative at diagnosis, IL-15 levels greater than the median were associated with subsequent CNS relapse compared with expression equal to or less than the median (OR = 13.80; 95% CI, 3.38 to 56.31). Quantification of leukemic IL-15 expression at diagnosis predicts CNS status and could be a new tool to further tailor CNS-directed therapy in childhood ALL.

CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia.

PubMed

Jiang, Min; Lash, Gendie E; Zhao, Xueqing; Long, Yan; Guo, Caijiao; Yang, Hongling

2018-05-07

Circular RNAs (circRNAs) are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE), are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A) expression as a potential biomarker for PE before 20 weeks of pregnancy. A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis) at Guangzhou Women and Children's Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls). Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2). In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in which 884 circRNAs were downregulated and 1294 circRNAs were upregulated in the PE group compared with the control group. In the validation phase, two circRNAs, hsa_circ_0004904 and hsa_circ_0001855, were significantly upregulated in PE patients compared with healthy pregnant women (P < 0.05). PAPP-A expression levels, related to the two circRNAs based on bioinformatics prediction, were increased in the PE group compared with the control group. The area under the curve of the combined model was 0.94 in the predicted PE subjects. This is the first study to report circRNA profiling in patients with PE prior to the onset of symptoms. Our data suggested that hsa_circ_0004904 and hsa_circ_0001855 combined with PAPP-A might be promising biomarkers for the detection of PE. Moreover, circRNAs may provide new insights into the potential mechanisms underlying the pathophysiology of PE. © 2018 The Author(s). Published by S. Karger AG, Basel.

Evaluation of a 30-gene paclitaxel, fluorouracil, doxorubicin and cyclophosphamide chemotherapy response predictor in a multicenter randomized trial in breast cancer

PubMed Central

Tabchy, Adel; Valero, Vicente; Vidaurre, Tatiana; Lluch, Ana; Gomez, Henry; Martin, Miguel; Qi, Yuan; Barajas-Figueroa, Luis Javier; Souchon, Eduardo; Coutant, Charles; Doimi, Franco D; Ibrahim, Nuhad K; Gong, Yun; Hortobagyi, Gabriel N; Hess, Kenneth R; Symmans, W Fraser; Pusztai, Lajos

2010-01-01

Purpose We examined in a prospective, randomized, international clinical trial the performance of a previously defined 30-gene predictor (DLDA-30) of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil, doxorubicin, cyclophosphamide (T/FAC) chemotherapy, and assessed if DLDA-30 also predicts increased sensitivity to FAC-only chemotherapy. We compared the pCR rates after T/FAC versus FAC×6 preoperative chemotherapy. We also performed an exploratory analysis to identify novel candidate genes that differentially predict response in the two treatment arms. Experimental Design 273 patients were randomly assigned to receive either weekly paclitaxel × 12 followed by FAC × 4 (T/FAC, n=138), or FAC × 6 (n=135) neoadjuvant chemotherapy. All patients underwent a pretreatment FNA biopsy of the tumor for gene expression profiling and treatment response prediction. Results The pCR rates were 19% and 9% in the T/FAC and FAC arms, respectively (p<0.05). In the T/FAC arm, the positive predictive value (PPV) of the genomic predictor was 38% (95%CI:21–56%), the negative predictive value (NPV) 88% (CI:77–95%) and the AUC 0.711. In the FAC arm, the PPV was 9% (CI:1–29%) and the AUC 0.584. This suggests that the genomic predictor may have regimen-specificity. Its performance was similar to a clinical variable-based predictor nomogram. Conclusions Gene expression profiling for prospective response prediction was feasible in this international trial. The 30-gene predictor can identify patients with greater than average sensitivity to T/FAC chemotherapy. However, it captured molecular equivalents of clinical phenotype. Next generation predictive markers will need to be developed separately for different molecular subsets of breast cancers. PMID:20829329

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

PubMed

Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi

2017-09-01

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.

[Detection and analysis of the characteristic expression of microRNAs of anal fistula patients].

PubMed

Qiu, Jianming; Yu, Jiping; Yang, Guangen; Xu, Kan; Tao, Yong; Lin, Ali; Wang, Dong

2016-07-01

To detect and analyze the characteristic miRNAs profile of anal fistula and explore their possible target genes and potential clinical significance. The anal mucosa close to the hemorrhoids were collected from three patients undergoing fistulectomy and hemorrhoidectomy (fistula group) as well as three patients receiving only hemorroidectomy(hemorrhoids group), matching with fistula group in age, gender and body weight. miRNA microarray was used to compare the expression of 1 285 human miRNAs of the anal mucosa between two groups. Cluster analysis was adopted to analyze the accumulation of the differentially expressed miRNAs(P<0.05, fold≥2.0 or ≤0.5) and their target genes were predicted with 10 softwares such as DIANAmT, miRanda, miRDB, miRWalk etc. Comprehensive scoring was performed to identify genes with highest predictive score. Gene ontology (GO) concentration technique was used to analyze the target gene-associated biological process. Immunohistochemistry was used to examine protein expression of genes with the highest score. Among 1285 miRNAs in fistula group, 13 miRNAs were differentially expressed with those in hemorrhoid group, including 2 of up-regulation and 11 of down-regulation. Paired t test showed that in fistula group, miRNA-3609 up-regulation was 5.98 folds(P=0.0231) and miR-181a-2-3p down-regulation was 0.13 folds(P=0.0067) compared to those in hemorrhoid group, which had the greatest differential expression. Cluster analysis suggested that up-regulated miR-3609 and miR-6086 had similar change trend in both groups. Among 11 down-regulated miRNAs, miR-125bp-1-3p and miR-548q had similar expression and other 9 miRNAs had similar expression as well, including miR-1185-1-3p, miR-532-3p, miR-1233-5p, miR-769-5p, miR-149-5p, miR-99b-3p, miR-141-3p, miR-138-5p, and miR-181a-2-3p. Target gene prediction analysis of above 13 genes showed that 7 miRNAs(53.8%) were eligible to predict their potential target genes, yielding totally 104 possible target genes. The rest of 6 miRNAs(46.2%) failed to predict any target gene. The highest score in prediction of target gene was chitinase 1(ChIT1) and its corresponding differential miRNA was miR-769-5p(r=-0.94286, P=0.0167). Gene ontology analysis showed that the most associated biological process related with these 104 target genes was keratinization, immune response and signal transduction. Immunohistochemistry revealed ChiT1 expression of anal mucosa in fistula group was significantly higher compared to hemorrhoid group(P<0.01). There is a characteristic miRNAs profile in anal fistula patients, which may play a role in the occurrence and development of anal fistula.

Predictable enriched environment prevents development of hyper-emotionality in the VPA rat model of autism.

PubMed

Favre, Mônica R; La Mendola, Deborah; Meystre, Julie; Christodoulou, Dimitri; Cochrane, Melissa J; Markram, Henry; Markram, Kamila

2015-01-01

Understanding the effects of environmental stimulation in autism can improve therapeutic interventions against debilitating sensory overload, social withdrawal, fear and anxiety. Here, we evaluate the role of environmental predictability on behavior and protein expression, and inter-individual differences, in the valproic acid (VPA) model of autism. Male rats embryonically exposed (E11.5) either to VPA, a known autism risk factor in humans, or to saline, were housed from weaning into adulthood in a standard laboratory environment, an unpredictably enriched environment, or a predictably enriched environment. Animals were tested for sociability, nociception, stereotypy, fear conditioning and anxiety, and for tissue content of glutamate signaling proteins in the primary somatosensory cortex, hippocampus and amygdala, and of corticosterone in plasma, amygdala and hippocampus. Standard group analyses on separate measures were complemented with a composite emotionality score, using Cronbach's Alpha analysis, and with multivariate profiling of individual animals, using Hierarchical Cluster Analysis. We found that predictable environmental enrichment prevented the development of hyper-emotionality in the VPA-exposed group, while unpredictable enrichment did not. Individual variation in the severity of the autistic-like symptoms (fear, anxiety, social withdrawal and sensory abnormalities) correlated with neurochemical profiles, and predicted their responsiveness to predictability in the environment. In controls, the association between socio-affective behaviors, neurochemical profiles and environmental predictability was negligible. This study suggests that rearing in a predictable environment prevents the development of hyper-emotional features in animals exposed to an autism risk factor, and demonstrates that unpredictable environments can lead to negative outcomes, even in the presence of environmental enrichment.

Predictable enriched environment prevents development of hyper-emotionality in the VPA rat model of autism

PubMed Central

Favre, Mônica R.; La Mendola, Deborah; Meystre, Julie; Christodoulou, Dimitri; Cochrane, Melissa J.; Markram, Henry; Markram, Kamila

2015-01-01

Understanding the effects of environmental stimulation in autism can improve therapeutic interventions against debilitating sensory overload, social withdrawal, fear and anxiety. Here, we evaluate the role of environmental predictability on behavior and protein expression, and inter-individual differences, in the valproic acid (VPA) model of autism. Male rats embryonically exposed (E11.5) either to VPA, a known autism risk factor in humans, or to saline, were housed from weaning into adulthood in a standard laboratory environment, an unpredictably enriched environment, or a predictably enriched environment. Animals were tested for sociability, nociception, stereotypy, fear conditioning and anxiety, and for tissue content of glutamate signaling proteins in the primary somatosensory cortex, hippocampus and amygdala, and of corticosterone in plasma, amygdala and hippocampus. Standard group analyses on separate measures were complemented with a composite emotionality score, using Cronbach's Alpha analysis, and with multivariate profiling of individual animals, using Hierarchical Cluster Analysis. We found that predictable environmental enrichment prevented the development of hyper-emotionality in the VPA-exposed group, while unpredictable enrichment did not. Individual variation in the severity of the autistic-like symptoms (fear, anxiety, social withdrawal and sensory abnormalities) correlated with neurochemical profiles, and predicted their responsiveness to predictability in the environment. In controls, the association between socio-affective behaviors, neurochemical profiles and environmental predictability was negligible. This study suggests that rearing in a predictable environment prevents the development of hyper-emotional features in animals exposed to an autism risk factor, and demonstrates that unpredictable environments can lead to negative outcomes, even in the presence of environmental enrichment. PMID:26089770

Discovering functions of unannotated genes from a transcriptome survey of wild fungal isolates.

PubMed

Ellison, Christopher E; Kowbel, David; Glass, N Louise; Taylor, John W; Brem, Rachel B

2014-04-01

Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems. IMPORTANCE Some fungal species cause deadly infections in humans or crop plants, and other fungi are workhorses of industrial chemistry, including the production of biofuels. Advances in medical and industrial mycology require an understanding of the genes that control fungal traits. We developed a method to infer functions of uncharacterized genes by observing correlated expression of their mRNAs with those of known genes across wild fungal isolates. We applied this strategy to a filamentous fungus and predicted functions for thousands of unknown genes. In four cases, we experimentally validated the predictions from our method, discovering novel genes involved in the metabolism of nutrient sources relevant for biofuel production, as well as colony morphology and starvation resistance. Our strategy is straightforward, inexpensive, and applicable for predicting gene function in many fungal species.

Identification and characterization of microRNAs in white and brown alpaca skin

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are small, non-coding 21–25 nt RNA molecules that play an important role in regulating gene expression. Little is known about the expression profiles and functions of miRNAs in skin and their role in pigmentation. Alpacas have more than 22 natural coat colors, more than any other fiber producing species. To better understand the role of miRNAs in control of coat color we performed a comprehensive analysis of miRNA expression profiles in skin of white versus brown alpacas. Results Two small RNA libraries from white alpaca (WA) and brown alpaca (BA) skin were sequenced with the aid of Illumina sequencing technology. 272 and 267 conserved miRNAs were obtained from the WA and BA skin libraries, respectively. Of these conserved miRNAs, 35 and 13 were more abundant in WA and BA skin, respectively. The targets of these miRNAs were predicted and grouped based on Gene Ontology and KEGG pathway analysis. Many predicted target genes for these miRNAs are involved in the melanogenesis pathway controlling pigmentation. In addition to the conserved miRNAs, we also obtained 22 potentially novel miRNAs from the WA and BA skin libraries. Conclusion This study represents the first comprehensive survey of miRNAs expressed in skin of animals of different coat colors by deep sequencing analysis. We discovered a collection of miRNAs that are differentially expressed in WA and BA skin. The results suggest important potential functions of miRNAs in coat color regulation. PMID:23067000

MDM2 phenotypic and genotypic profiling, respective to TP53 genetic status, in diffuse large B-cell lymphoma patients treated with rituximab-CHOP immunochemotherapy: a report from the International DLBCL Rituximab-CHOP Consortium Program

PubMed Central

Xu-Monette, Zijun Y.; Møller, Michael B.; Tzankov, Alexander; Montes-Moreno, Santiago; Hu, Wenwei; Manyam, Ganiraju C.; Kristensen, Louise; Fan, Lei; Visco, Carlo; Dybkær, Karen; Chiu, April; Tam, Wayne; Zu, Youli; Bhagat, Govind; Richards, Kristy L.; Hsi, Eric D.; Choi, William W. L.; van Krieken, J. Han; Huang, Qin; Huh, Jooryung; Ai, Weiyun; Ponzoni, Maurilio; Ferreri, Andrés J. M.; Wu, Lin; Zhao, Xiaoying; Bueso-Ramos, Carlos E.; Wang, Sa A.; Go, Ronald S.; Li, Yong; Winter, Jane N.; Medeiros, L. Jeffrey

2013-01-01

MDM2 is a key negative regulator of the tumor suppressor p53, however, the prognostic significance of MDM2 overexpression in diffuse large B-cell lymphoma (DLBCL) has not been defined convincingly. In a p53 genetically–defined large cohort of de novo DLBCL patients treated with rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine, and prednisone (R-CHOP) chemotherapy, we assessed MDM2 and p53 expression by immunohistochemistry (n = 478), MDM2 gene amplification by fluorescence in situ hybridization (n = 364), and a single nucleotide polymorphism in the MDM2 promoter, SNP309, by SNP genotyping assay (n = 108). Our results show that MDM2 overexpression, unlike p53 overexpression, is not a significant prognostic factor in overall DLBCL. Both MDM2 and p53 overexpression do not predict for an adverse clinical outcome in patients with wild-type p53 but predicts for significantly poorer survival in patients with mutated p53. Variable p53 activities may ultimately determine the survival differences, as suggested by the gene expression profiling analysis. MDM2 amplification was observed in 3 of 364 (0.8%) patients with high MDM2 expression. The presence of SNP309 did not correlate with MDM2 expression and survival. This study indicates that evaluation of MDM2 and p53 expression correlating with TP53 genetic status is essential to assess their prognostic significance and is important for designing therapeutic strategies that target the MDM2-p53 interaction. PMID:23982177

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*

PubMed Central

Xiao, Yongsheng; Guo, Lei; Wang, Yinsheng

2014-01-01

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy. PMID:24520089

MicroRNA-142-5p contributes to Hashimoto's thyroiditis by targeting CLDN1.

PubMed

Zhu, Jin; Zhang, Yuehua; Zhang, Weichen; Zhang, Wei; Fan, Linni; Wang, Lu; Liu, Yixiong; Liu, Shasha; Guo, Ying; Wang, Yingmei; Yi, Jun; Yan, Qingguo; Wang, Zhe; Huang, Gaosheng

2016-06-08

MicroRNAs have the potential as diagnostic biomarkers and therapeutic targets in autoimmune diseases. However, very limited studies have evaluated the expression of microRNA profile in thyroid gland related to Hashimoto's thyroiditis (HT). MicroRNA microarray expression profiling was performed and validated by quantitative RT-PCR. The expression pattern of miR-142-5p was detected using locked nucleic acid-in situ hybridization. The target gene was predicted and validated using miRNA targets prediction database, gene expression analysis, quantitative RT-PCR, western blot, and luciferase assay. The potential mechanisms of miR-142-5p were studied using immunohistochemistry, immunofluorescence, and quantitative assay of thyrocyte permeability. Thirty-nine microRNAs were differentially expressed in HT (Fold change ≥2, P < 0.05) and miR-142-5p, miR-142-3p, and miR-146a were only high expression in HT thyroid gland (P < 0.001). miR-142-5p, which was expressed at high levels in injured follicular epithelial cells, was also detected in HT patient serum and positively correlated with thyroglobulin antibody (r ≥ 0.6, P < 0.05). Furthermore, luciferase assay demonstrated CLDN1 was the direct target gene of miR-142-5p (P < 0.05), and Immunohistochemical staining showed a reverse expression patterns with miR-142-5p and CLDN1. Overexpression of miR-142-5p in thyrocytes resulted in reducing of the expression of claudin-1 both in mRNA and protein level (P = 0.032 and P = 0.009 respectively) and increasing the permeability of thyrocytes monolayer (P < 0.01). Our findings indicate a previously unrecognized mechanism that miR-142-5p, targeting CLDN1, plays an important role in HT pathogenesis.

Profile analysis and prediction of tissue-specific CpG island methylation classes

PubMed Central

2009-01-01

Background The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern. Results We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation. Conclusion Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods. PMID:19383127

Presymptomatic Diagnosis of Celiac Disease in Predisposed Children: The Role of Gene Expression Profile.

PubMed

Galatola, Martina; Cielo, Donatella; Panico, Camilla; Stellato, Pio; Malamisura, Basilio; Carbone, Lorenzo; Gianfrani, Carmen; Troncone, Riccardo; Greco, Luigi; Auricchio, Renata

2017-09-01

The prevalence of celiac disease (CD) has increased significantly in recent years, and risk prediction and early diagnosis have become imperative especially in at-risk families. In a previous study, we identified individuals with CD based on the expression profile of a set of candidate genes in peripheral blood monocytes. Here we evaluated the expression of a panel of CD candidate genes in peripheral blood mononuclear cells from at-risk infants long time before any symptom or production of antibodies. We analyzed the gene expression of a set of 9 candidate genes, associated with CD, in 22 human leukocyte antigen predisposed children from at-risk families for CD, studied from birth to 6 years of age. Nine of them developed CD (patients) and 13 did not (controls). We analyzed gene expression at 3 different time points (age matched in the 2 groups): 4-19 months before diagnosis, at the time of CD diagnosis, and after at least 1 year of a gluten-free diet. At similar age points, controls were also evaluated. Three genes (KIAA, TAGAP [T-cell Activation GTPase Activating Protein], and SH2B3 [SH2B Adaptor Protein 3]) were overexpressed in patients, compared with controls, at least 9 months before CD diagnosis. At a stepwise discriminant analysis, 4 genes (RGS1 [Regulator of G-protein signaling 1], TAGAP, TNFSF14 [Tumor Necrosis Factor (Ligand) Superfamily member 14], and SH2B3) differentiate patients from controls before serum antibodies production and clinical symptoms. Multivariate equation correctly classified CD from non-CD children in 95.5% of patients. The expression of a small set of candidate genes in peripheral blood mononuclear cells can predict CD at least 9 months before the appearance of any clinical and serological signs of the disease.

The transcriptional landscape of age in human peripheral blood

PubMed Central

Peters, Marjolein J.; Joehanes, Roby; Pilling, Luke C.; Schurmann, Claudia; Conneely, Karen N.; Powell, Joseph; Reinmaa, Eva; Sutphin, George L.; Zhernakova, Alexandra; Schramm, Katharina; Wilson, Yana A.; Kobes, Sayuko; Tukiainen, Taru; Nalls, Michael A.; Hernandez, Dena G.; Cookson, Mark R.; Gibbs, Raphael J.; Hardy, John; Ramasamy, Adaikalavan; Zonderman, Alan B.; Dillman, Allissa; Traynor, Bryan; Smith, Colin; Longo, Dan L.; Trabzuni, Daniah; Troncoso, Juan; van der Brug, Marcel; Weale, Michael E.; O'Brien, Richard; Johnson, Robert; Walker, Robert; Zielke, Ronald H.; Arepalli, Sampath; Ryten, Mina; Singleton, Andrew B.; Ramos, Yolande F.; Göring, Harald H. H.; Fornage, Myriam; Liu, Yongmei; Gharib, Sina A.; Stranger, Barbara E.; De Jager, Philip L.; Aviv, Abraham; Levy, Daniel; Murabito, Joanne M.; Munson, Peter J.; Huan, Tianxiao; Hofman, Albert; Uitterlinden, André G.; Rivadeneira, Fernando; van Rooij, Jeroen; Stolk, Lisette; Broer, Linda; Verbiest, Michael M. P. J.; Jhamai, Mila; Arp, Pascal; Metspalu, Andres; Tserel, Liina; Milani, Lili; Samani, Nilesh J.; Peterson, Pärt; Kasela, Silva; Codd, Veryan; Peters, Annette; Ward-Caviness, Cavin K.; Herder, Christian; Waldenberger, Melanie; Roden, Michael; Singmann, Paula; Zeilinger, Sonja; Illig, Thomas; Homuth, Georg; Grabe, Hans-Jörgen; Völzke, Henry; Steil, Leif; Kocher, Thomas; Murray, Anna; Melzer, David; Yaghootkar, Hanieh; Bandinelli, Stefania; Moses, Eric K.; Kent, Jack W.; Curran, Joanne E.; Johnson, Matthew P.; Williams-Blangero, Sarah; Westra, Harm-Jan; McRae, Allan F.; Smith, Jennifer A.; Kardia, Sharon L. R.; Hovatta, Iiris; Perola, Markus; Ripatti, Samuli; Salomaa, Veikko; Henders, Anjali K.; Martin, Nicholas G.; Smith, Alicia K.; Mehta, Divya; Binder, Elisabeth B.; Nylocks, K Maria; Kennedy, Elizabeth M.; Klengel, Torsten; Ding, Jingzhong; Suchy-Dicey, Astrid M.; Enquobahrie, Daniel A.; Brody, Jennifer; Rotter, Jerome I.; Chen, Yii-Der I.; Houwing-Duistermaat, Jeanine; Kloppenburg, Margreet; Slagboom, P. Eline; Helmer, Quinta; den Hollander, Wouter; Bean, Shannon; Raj, Towfique; Bakhshi, Noman; Wang, Qiao Ping; Oyston, Lisa J.; Psaty, Bruce M.; Tracy, Russell P.; Montgomery, Grant W.; Turner, Stephen T.; Blangero, John; Meulenbelt, Ingrid; Ressler, Kerry J.; Yang, Jian; Franke, Lude; Kettunen, Johannes; Visscher, Peter M.; Neely, G. Gregory; Korstanje, Ron; Hanson, Robert L.; Prokisch, Holger; Ferrucci, Luigi; Esko, Tonu; Teumer, Alexander; van Meurs, Joyce B. J.; Johnson, Andrew D.

2015-01-01

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts. PMID:26490707

The first detection of the 3A g- state in carotenoids using resonance-Raman excitation profiles

NASA Astrophysics Data System (ADS)

Furuichi, Kentaro; Sashima, Tokutake; Koyama, Yasushi

2002-04-01

The singlet 3Ag- state that had been theoretically predicted in shorter polyenes [P. Tavan and K. Schulten J. Chem. Phys. 85 (1986) 6602; Phys. Rev. B 36 (1987) 4337] was first identified in bacterial carotenoids by measurements of resonance-Raman excitation profiles. It is almost overlapped with the 1Bu+ state in spheroidene (the number of conjugated double bonds, n=10), and located in-between the 1Bu+ and 1Bu- states in lycopene, anhydrorhodovibrin and spirilloxanthin (n=11-13). The slopes when the 2Ag--, 1Bu-- and 3Ag--state energies were expressed as linear functions of 1/(2n+1) exhibited the ratio of 2:3.1:3.8 in excellent agreement with that theoretically predicted, 2:3.1:3.7.

Genes involved in host-parasite interactions can be revealed by their correlated expression.

PubMed

Reid, Adam James; Berriman, Matthew

2013-02-01

Molecular interactions between a parasite and its host are key to the ability of the parasite to enter the host and persist. Our understanding of the genes and proteins involved in these interactions is limited. To better understand these processes it would be advantageous to have a range of methods to predict pairs of genes involved in such interactions. Correlated gene expression profiles can be used to identify molecular interactions within a species. Here we have extended the concept to different species, showing that genes with correlated expression are more likely to encode proteins, which directly or indirectly participate in host-parasite interaction. We go on to examine our predictions of molecular interactions between the malaria parasite and both its mammalian host and insect vector. Our approach could be applied to study any interaction between species, for example, between a host and its parasites or pathogens, but also symbiotic and commensal pairings.

The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity

PubMed Central

Barretina, Jordi; Caponigro, Giordano; Stransky, Nicolas; Venkatesan, Kavitha; Margolin, Adam A.; Kim, Sungjoon; Wilson, Christopher J.; Lehár, Joseph; Kryukov, Gregory V.; Sonkin, Dmitriy; Reddy, Anupama; Liu, Manway; Murray, Lauren; Berger, Michael F.; Monahan, John E.; Morais, Paula; Meltzer, Jodi; Korejwa, Adam; Jané-Valbuena, Judit; Mapa, Felipa A.; Thibault, Joseph; Bric-Furlong, Eva; Raman, Pichai; Shipway, Aaron; Engels, Ingo H.; Cheng, Jill; Yu, Guoying K.; Yu, Jianjun; Aspesi, Peter; de Silva, Melanie; Jagtap, Kalpana; Jones, Michael D.; Wang, Li; Hatton, Charles; Palescandolo, Emanuele; Gupta, Supriya; Mahan, Scott; Sougnez, Carrie; Onofrio, Robert C.; Liefeld, Ted; MacConaill, Laura; Winckler, Wendy; Reich, Michael; Li, Nanxin; Mesirov, Jill P.; Gabriel, Stacey B.; Getz, Gad; Ardlie, Kristin; Chan, Vivien; Myer, Vic E.; Weber, Barbara L.; Porter, Jeff; Warmuth, Markus; Finan, Peter; Harris, Jennifer L.; Meyerson, Matthew; Golub, Todd R.; Morrissey, Michael P.; Sellers, William R.; Schlegel, Robert; Garraway, Levi A.

2012-01-01

The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic avenues remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacologic annotation is available1. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacologic profiles for 24 anticancer drugs across 479 of the lines, this collection allowed identification of genetic, lineage, and gene expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Altogether, our results suggest that large, annotated cell line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of “personalized” therapeutic regimens2. PMID:22460905

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

PubMed

Barretina, Jordi; Caponigro, Giordano; Stransky, Nicolas; Venkatesan, Kavitha; Margolin, Adam A; Kim, Sungjoon; Wilson, Christopher J; Lehár, Joseph; Kryukov, Gregory V; Sonkin, Dmitriy; Reddy, Anupama; Liu, Manway; Murray, Lauren; Berger, Michael F; Monahan, John E; Morais, Paula; Meltzer, Jodi; Korejwa, Adam; Jané-Valbuena, Judit; Mapa, Felipa A; Thibault, Joseph; Bric-Furlong, Eva; Raman, Pichai; Shipway, Aaron; Engels, Ingo H; Cheng, Jill; Yu, Guoying K; Yu, Jianjun; Aspesi, Peter; de Silva, Melanie; Jagtap, Kalpana; Jones, Michael D; Wang, Li; Hatton, Charles; Palescandolo, Emanuele; Gupta, Supriya; Mahan, Scott; Sougnez, Carrie; Onofrio, Robert C; Liefeld, Ted; MacConaill, Laura; Winckler, Wendy; Reich, Michael; Li, Nanxin; Mesirov, Jill P; Gabriel, Stacey B; Getz, Gad; Ardlie, Kristin; Chan, Vivien; Myer, Vic E; Weber, Barbara L; Porter, Jeff; Warmuth, Markus; Finan, Peter; Harris, Jennifer L; Meyerson, Matthew; Golub, Todd R; Morrissey, Michael P; Sellers, William R; Schlegel, Robert; Garraway, Levi A

2012-03-28

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

High expression of ID family and IGJ genes signature as predictor of low induction treatment response and worst survival in adult Hispanic patients with B-acute lymphoblastic leukemia.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Quijano, Sandra M; Pinzon, Paula L; Lozano, Olga C; Castillo, Juan S; Li, Li; Bareño, Jose; Cardozo, Claudia; Solano, Julio; Herrera, Maria V; Cudris, Jennifer; Zabaleta, Jovanny

2016-04-05

B-Acute lymphoblastic leukemia (B-ALL) represents a hematologic malignancy with poor clinical outcome and low survival rates in adult patients. Remission rates in Hispanic population are almost 30% lower and Overall Survival (OS) nearly two years inferior than those reported in other ethnic groups. Only 61% of Colombian adult patients with ALL achieve complete remission (CR), median overall survival is 11.3 months and event-free survival (EFS) is 7.34 months. Identification of prognostic factors is crucial for the application of proper treatment strategies and subsequently for successful outcome. Our goal was to identify a gene expression signature that might correlate with response to therapy and evaluate the utility of these as prognostic tool in hispanic patients. We included 43 adult patients newly diagnosed with B-ALL. We used microarray analysis in order to identify genes that distinguish poor from good response to treatment using differential gene expression analysis. The expression profile was validated by real-time PCR (RT-PCT). We identified 442 differentially expressed genes between responders and non-responders to induction treatment. Hierarchical analysis according to the expression of a 7-gene signature revealed 2 subsets of patients that differed in their clinical characteristics and outcome. Our study suggests that response to induction treatment and clinical outcome of Hispanic patients can be predicted from the onset of the disease and that gene expression profiles can be used to stratify patient risk adequately and accurately. The present study represents the first that shows the gene expression profiling of B-ALL Colombian adults and its relevance for stratification in the early course of disease.

DiRE: identifying distant regulatory elements of co-expressed genes

PubMed Central

Gotea, Valer; Ovcharenko, Ivan

2008-01-01

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org. PMID:18487623

Quality Evaluation of Human Bone Marrow Mesenchymal Stem Cells for Cartilage Repair

PubMed Central

Shiraishi, Katsunori; Takeuchi, Shunsuke; Yanada, Shinobu; Mera, Hisashi; Wakitani, Shigeyuki; Adachi, Nobuo

2017-01-01

Quality evaluation of mesenchymal stem cells (MSCs) based on efficacy would be helpful for their clinical application. In this study, we aimed to find the factors of human bone marrow MSCs relating to cartilage repair. The expression profiles of humoral factors, messenger RNAs (mRNAs), and microRNAs (miRNAs) were analyzed in human bone marrow MSCs from five different donors. We investigated the correlations of these expression profiles with the capacity of the MSCs for proliferation, chondrogenic differentiation, and cartilage repair in vivo. The mRNA expression of MYBL1 was positively correlated with proliferation and cartilage differentiation. By contrast, the mRNA expression of RCAN2 and the protein expression of TIMP-1 and VEGF were negatively correlated with proliferation and cartilage differentiation. However, MSCs from all five donors had the capacity to promote cartilage repair in vivo regardless of their capacity for proliferation and cartilage differentiation. The mRNA expression of HLA-DRB1 was positively correlated with cartilage repair in vivo. Meanwhile, the mRNA expression of TMEM155 and expression of miR-486-3p, miR-148b, miR-93, and miR-320B were negatively correlated with cartilage repair. The expression analysis of these factors might help to predict the ability of bone marrow MSCs to promote cartilage repair. PMID:28835756

Genome-Wide Identification and Expression Profiling Analysis of the Xyloglucan Endotransglucosylase/Hydrolase Gene Family in Tobacco (Nicotiana tabacum L.).

PubMed

Wang, Meng; Xu, Zongchang; Ding, Anming; Kong, Yingzhen

2018-05-24

Xyloglucan endotransglucosylase/hydrolase genes ( XTHs ) encode enzymes required for the reconstruction and modification of xyloglucan backbones, which will result in changes of cell wall extensibility during growth. A total of 56 NtXTH genes were identified from common tobacco, and 50 cDNA fragments were verified by PCR amplification. The 56 NtXTH genes could be classified into two subfamilies: Group I/II and Group III according to their phylogenetic relationships. The gene structure, chromosomal localization, conserved protein domains prediction, sub-cellular localization of NtXTH proteins and evolutionary relationships among Nicotiana tabacum , Nicotiana sylvestrisis , Nicotiana tomentosiformis , Arabidopsis , and rice were also analyzed. The NtXTHs expression profiles analyzed by the TobEA database and qRT-PCR revealed that NtXTHs display different expression patterns in different tissues. Notably, the expression patterns of 12 NtXTHs responding to environment stresses, including salinity, alkali, heat, chilling, and plant hormones, including IAA and brassinolide, were characterized. All the results would be useful for the function study of NtXTHs during different growth cycles and stresses.

Transcriptome Profiling of Shewanella oneidensis Gene Expression following Exposure to Acidic and Alkaline pH†

PubMed Central

Leaphart, Adam B.; Thompson, Dorothea K.; Huang, Katherine; Alm, Eric; Wan, Xiu-Feng; Arkin, Adam; Brown, Steven D.; Wu, Liyou; Yan, Tingfen; Liu, Xueduan; Wickham, Gene S.; Zhou, Jizhong

2006-01-01

The molecular response of Shewanella oneidensis MR-1 to variations in extracellular pH was investigated based on genomewide gene expression profiling. Microarray analysis revealed that cells elicited both general and specific transcriptome responses when challenged with environmental acid (pH 4) or base (pH 10) conditions over a 60-min period. Global responses included the differential expression of genes functionally linked to amino acid metabolism, transcriptional regulation and signal transduction, transport, cell membrane structure, and oxidative stress protection. Response to acid stress included the elevated expression of genes encoding glycogen biosynthetic enzymes, phosphate transporters, and the RNA polymerase sigma-38 factor (rpoS), whereas the molecular response to alkaline pH was characterized by upregulation of nhaA and nhaR, which are predicted to encode an Na+/H+ antiporter and transcriptional activator, respectively, as well as sulfate transport and sulfur metabolism genes. Collectively, these results suggest that S. oneidensis modulates multiple transporters, cell envelope components, and pathways of amino acid consumption and central intermediary metabolism as part of its transcriptome response to changing external pH conditions. PMID:16452448

Structural features based genome-wide characterization and prediction of nucleosome organization

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization. The implementation of our DLaNe method based on structural features is available online. PMID:22449207

Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions.

PubMed

Zhou, Weichen; Ma, Yanyun; Zhang, Jun; Hu, Jingyi; Zhang, Menghan; Wang, Yi; Li, Yi; Wu, Lijun; Pan, Yida; Zhang, Yitong; Zhang, Xiaonan; Zhang, Xinxin; Zhang, Zhanqing; Zhang, Jiming; Li, Hai; Lu, Lungen; Jin, Li; Wang, Jiucun; Yuan, Zhenghong; Liu, Jie

2017-11-01

Liver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus-infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)-infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV-DNA) in large-scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions. We analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine-learning methods including Random Forest, K-nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model. Significant genes related to clinical parameters were found enriching in the immune system, interferon-stimulated, regulation of cytokine production, anti-apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77-0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65-0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible. This is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Safety assessment of genetically modified rice expressing human serum albumin from urine metabonomics and fecal bacterial profile.

PubMed

Qi, Xiaozhe; Chen, Siyuan; Sheng, Yao; Guo, Mingzhang; Liu, Yifei; He, Xiaoyun; Huang, Kunlun; Xu, Wentao

2015-02-01

The genetically modified (GM) rice expressing human serum albumin (HSA) is used for non-food purposes; however, its food safety assessment should be conducted due to the probability of accidental mixture with conventional food. In this research, Sprague Dawley rats were fed diets containing 50% (wt/wt) GM rice expressing HSA or non-GM rice for 90 days. Urine metabolites were detected by (1)H NMR to examine the changes of the metabolites in the dynamic process of metabolism. Fecal bacterial profiles were detected by denaturing gradient gel electrophoresis to reflect intestinal health. Additionally, short chain fatty acids and fecal enzymes were investigated. The results showed that compared with rats fed the non-GM rice, some significant differences were observed in rats fed with the GM rice; however, these changes were not significantly different from the control diet group. Additionally, the gut microbiota was associated with blood indexes and urine metabolites. In conclusion, the GM rice diet is as safe as the traditional daily diet. Furthermore, urine metabonomics and fecal bacterial profiles provide a non-invasive food safety assessment rat model for genetically modified crops that are used for non-food/feed purposes. Fecal bacterial profiles have the potential for predicting the change of blood indexes in future. Copyright © 2014 Elsevier Ltd. All rights reserved.

Liposomal curcumin alters chemosensitivity of breast cancer cells to Adriamycin via regulating microRNA expression.

PubMed

Zhou, Siying; Li, Jian; Xu, Hanzi; Zhang, Sijie; Chen, Xiu; Chen, Wei; Yang, Sujin; Zhong, Shanliang; Zhao, Jianhua; Tang, Jinhai

2017-07-30

Emerging evidence suggests that curcumin can overcome drug resistance to classical chemotherapies, but poor bioavailability and low absorption have limited its clinical use and the mechanisms remain unclear. Also, Adriamycin (Adr) is one of the most active cytotoxic agents in breast cancer; however, the high resistant rate of Adr leads to a poor prognosis. We utilized encapsulation in liposomes as a strategy to improve the bioavailability of curcumin and demonstrated that liposomal curcumin altered chemosensitivity of Adr-resistant MCF-7 human breast cancer (MCF-7/Adr) by MTT assay. The miRNA and mRNA expression profiles of MCF-7/S, MCF-7/Adr and curcumin-treated MCF-7/Adr cells were analyzed by microarray and further confirmed by real-time PCR. We focused on differentially expressed miR-29b-1-5p to explore the involvement of miR-29b-1-5p in the resistance of Adr. Candidate genes of dysregulated miRNAs were identified by prediction algorithms based on gene expression profiles. Networks of KEGG pathways were organized by the selected dysregulated miRNAs. Moreover, protein-protein interaction (PPI) was utilized to map protein interaction networks of curcumin regulated proteins. We first demonstrated liposomal curcumin could rescue part of Adriamycin resistance in breast cancer and further identified 67 differentially expressed microRNAs among MCF-7/S, MCF-7/Adr and curcumin-treated MCF-7/Adr. The results showed that lower expressed miR-29b-1-5p decreased the IC50 of MCF-7/Adr cells and higher expressed miR-29b-1-5p, weaken the effects of liposomal curcumin to Adr-resistance. Besides, we found that 20 target genes (mRNAs) of each dysregulated miRNA were not only predicted by prediction algorithms, but also differentially expressed in the microarray. The results showed that MAPK, mTOR, PI3K-Akt, AMPK, TNF, Ras signaling pathways and several target genes such as PPARG, RRM2, SRSF1and EPAS1, may associate with drug resistance of breast cancer cells to Adr. We determined that an altered miRNA expression pattern is involved in acquiring resistance to Adr, and that liposomal curcumin could change the resistance to Adr through miRNA signaling pathways in breast cancer MCF-7 cells. Copyright © 2017 Elsevier B.V. All rights reserved.

GLUT1 expression in pediatric adrenocortical tumors: a promising candidate to predict clinical behavior.

PubMed

Pinheiro, Céline; Granja, Sara; Longatto-Filho, Adhemar; Faria, André M; Fragoso, Maria C B V; Lovisolo, Silvana M; Bonatelli, Murilo; Costa, Ricardo F A; Lerário, Antonio M; Almeida, Madson Q; Baltazar, Fátima; Zerbini, Maria C N

2017-09-08

Discrimination between benign and malignant tumors is a challenging process in pediatric adrenocortical tumors. New insights in the metabolic profile of pediatric adrenocortical tumors may contribute to this distinction, predict prognosis, as well as identify new molecular targets for therapy. The aim of this work is to characterize the expression of the metabolism-related proteins MCT1, MCT2, MCT4, CD147, CD44, GLUT1 and CAIX in a series of pediatric adrenocortical tumors. A total of 50 pediatric patients presenting adrenocortical tumors, including 41 clinically benign and 9 clinically malignant tumors, were included. Protein expression was evaluated using immunohistochemistry in samples arranged in tissue microarrays. The immunohistochemical analysis showed a significant increase in plasma membrane expression of GLUT1 in malignant lesions, when compared to benign lesions ( p =0.004), being the expression of this protein associated with shorter overall and disease-free survival ( p =0.004 and p =0.001, respectively). Although significant differences were not observed for proteins other than GLUT1, MCT1, MCT4 and CD147 were highly expressed in pediatric adrenocortical neoplasias (around 90%). GLUT1 expression was differentially expressed in pediatric adrenocortical tumors, with higher expression in clinically malignant tumors, and associated with shorter survival, suggesting a metabolic remodeling towards a hyperglycolytic phenotype in this malignancy.

DeSigN: connecting gene expression with therapeutics for drug repurposing and development.

PubMed

Lee, Bernard Kok Bang; Tiong, Kai Hung; Chang, Jit Kang; Liew, Chee Sun; Abdul Rahman, Zainal Ariff; Tan, Aik Choon; Khang, Tsung Fei; Cheong, Sok Ching

2017-01-25

The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously. We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC 50 ) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC 50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control. DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

Genomics and expression profiles of the Hedgehog and Notch signaling pathways in sea urchin development.

PubMed

Walton, Katherine D; Croce, Jenifer C; Glenn, Thomas D; Wu, Shu-Yu; McClay, David R

2006-12-01

The Hedgehog (Hh) and Notch signal transduction pathways control a variety of developmental processes including cell fate choice, differentiation, proliferation, patterning and boundary formation. Because many components of these pathways are conserved, it was predicted and confirmed that pathway components are largely intact in the sea urchin genome. Spatial and temporal location of these pathways in the embryo, and their function in development offer added insight into their mechanistic contributions. Accordingly, all major components of both pathways were identified and annotated in the sea urchin Strongylocentrotus purpuratus genome and the embryonic expression of key components was explored. Relationships of the pathway components, and modifiers predicted from the annotation of S. purpuratus, were compared against cnidarians, arthropods, urochordates, and vertebrates. These analyses support the prediction that the pathways are highly conserved through metazoan evolution. Further, the location of these two pathways appears to be conserved among deuterostomes, and in the case of Notch at least, display similar capacities in endomesoderm gene regulatory networks. RNA expression profiles by quantitative PCR and RNA in situ hybridization reveal that Hedgehog is produced by the endoderm beginning just prior to invagination, and signals to the secondary mesenchyme-derived tissues at least until the pluteus larva stage. RNA in situ hybridization of Notch pathway members confirms that Notch functions sequentially in the vegetal-most secondary mesenchyme cells and later in the endoderm. Functional analyses in future studies will embed these pathways into the growing knowledge of gene regulatory networks that govern early specification and morphogenesis.

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.

PubMed

Devonshire, Alison S; Elaswarapu, Ramnath; Foy, Carole A

2010-11-24

Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting. Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms. ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.

Hepatic transcriptome profiles differ among maturing beef heifers supplemented with inorganic, organic, or mixed (50% inorganic:50% organic) forms of dietary selenium.

PubMed

Matthews, James C; Zhang, Zhi; Patterson, Jennifer D; Bridges, Phillip J; Stromberg, Arnold J; Boling, J A

2014-09-01

Selenium (Se) is an important trace mineral that, due to deficiencies in the soil in many parts of the USA, must be supplemented directly to the diet of foraging cattle. Both organic and inorganic forms of dietary Se supplements are available and commonly used, and it is known that Se form affects tissue assimilation, bioavailability, and physiological responses. However, little is known about the effects of form of dietary Se supplements on gene expression profiles, which ostensibly account for Se form-dependent physiological processes. To determine if hepatic transcriptomes of growing beef (Angus-cross) heifers (0.5 kg gain/day) was altered by form of dietary supplemental Se, none (Control), or 3 mg Se/day as inorganic Se (ISe, sodium selenite), organic (OSe, Sel-Plex®), or a blend of ISe and OSe (1.5 mg:1.5 mg, Mix) Se was fed for 168 days, and the RNA expression profiles from biopsied liver tissues was compared by microarray analysis. The relative abundance of 139 RNA transcripts was affected by Se treatment, with 86 of these with complete gene annotations. Statistical and bioinformatic analysis of the annotated RNA transcripts revealed clear differences among the four Se treatment groups in their hepatic expression profiles, including (1) solely and commonly affected transcripts; (2) Control and OSe profiles being more similar than Mix and ISe treatments; (3) distinct OSe-, Mix-, and ISe-Se treatment-induced "phenotypes" that possessed both common and unique predicted physiological capacities; and (4) expression of three microRNAs were uniquely sensitive to OSe, ISe, or Mix treatments, including increased capacity for redox potential induced by OSe and Mix Se treatments resulting from decreased expression of MiR2300b messenger RNA. These findings indicate that the form of supplemental dietary Se consumed by cattle will affect the composition of liver transcriptomes resulting, presumably, in different physiological capacities.

An ensemble predictive modeling framework for breast cancer classification.

PubMed

Nagarajan, Radhakrishnan; Upreti, Meenakshi

2017-12-01

Molecular changes often precede clinical presentation of diseases and can be useful surrogates with potential to assist in informed clinical decision making. Recent studies have demonstrated the usefulness of modeling approaches such as classification that can predict the clinical outcomes from molecular expression profiles. While useful, a majority of these approaches implicitly use all molecular markers as features in the classification process often resulting in sparse high-dimensional projection of the samples often comparable to that of the sample size. In this study, a variant of the recently proposed ensemble classification approach is used for predicting good and poor-prognosis breast cancer samples from their molecular expression profiles. In contrast to traditional single and ensemble classifiers, the proposed approach uses multiple base classifiers with varying feature sets obtained from two-dimensional projection of the samples in conjunction with a majority voting strategy for predicting the class labels. In contrast to our earlier implementation, base classifiers in the ensembles are chosen based on maximal sensitivity and minimal redundancy by choosing only those with low average cosine distance. The resulting ensemble sets are subsequently modeled as undirected graphs. Performance of four different classification algorithms is shown to be better within the proposed ensemble framework in contrast to using them as traditional single classifier systems. Significance of a subset of genes with high-degree centrality in the network abstractions across the poor-prognosis samples is also discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Using patient-derived xenograft models of colorectal liver metastases to predict chemosensitivity.

PubMed

Brown, Kai M; Xue, Aiqun; Julovi, Sohel M; Gill, Anthony J; Pavlakis, Nick; Samra, Jaswinder S; Smith, Ross C; Hugh, Thomas J

2018-07-01

Few in vivo models for colorectal cancer have been demonstrated to show external validity by accurately predicting clinical patient outcomes. Patient-derived xenograft (PDX) models of cancer have characteristics that might provide a form of translational research leading to personalized cancer care. The aim of this pilot study was to assess the feasibility of using PDXs as a platform for predicting patient colorectal liver metastases responses, in this case by correlating PDX and patient tumor responses to either folinic acid, fluorouracil plus oxaliplatin or folinic acid, fluorouracil plus irinotecan-based regimens. Sixteen patients underwent potentially curative resection of colorectal liver metastases, and tumors were grafted into NOD.CB17-Prkdc scid /Arc mice. Mice were divided into groups to determine relative tumor growth in response to treatment. Tumors were analyzed by immunohistochemistry for Ki67 and Excision repair cross-complementation group 1. An engraftment rate of 81% was achieved. Overall, there was a 67% positive match rate between eligible patient and PDX chemosensitivity profiles. There was a significant difference in relative decrease in Ki67 expression between sensitive/stable versus resistant PDXs for both treatment regimens. There was no statistically significant correlation between baseline ERCC1 expression and response to Oxaliplatin + 5-Fluorouracil in the PDXs. This pilot study supports the feasibility of using PDX models of advanced colorectal cancer in larger studies to potentially predict patient chemosensitivity profiles. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessing mechanisms of toxicant response in the amphipod Melita plumulosa through transcriptomic profiling.

PubMed

Hook, Sharon E; Osborn, Hannah L; Spadaro, David A; Simpson, Stuart L

2014-01-01

This study describes the function of transcripts with altered abundance in the epibenthic amphipod, Melita plumulosa, following whole-sediment exposure to a series of common environmental contaminants. M. plumulosa were exposed for 48 h to sediments spiked and equilibrated with the following contaminants at concentrations predicted to cause sublethal effects to reproduction: porewater ammonia 30 mg L(-1); bifenthrin at 100 μg kg(-1); fipronil at 50 μg kg(-1); 0.6% diesel; 0.3% crude oil; 250 mg Cu kg(-1); 400 mg Ni kg(-1); and 400 mg Zn kg(-1). RNA was extracted and hybridized against a custom Agilent microarray developed for this species. Although the microarray represented a partial transcriptome and not all features on the array could be annotated, unique transcriptomic profiles were generated for each of the contaminant exposures. Hierarchical clustering grouped the expression profiles together by contaminant class, with copper and zinc, the petroleum products and nickel, and the pesticides each forming a distinct cluster. Many of the transcriptional changes observed were consistent with patterns previously described in other crustaceans. The changes in the transcriptome demonstrated that contaminant exposure caused changes in digestive function, growth and moulting, and the cytoskeleton following metal exposure, whereas exposure to petroleum products caused changes in carbohydrate metabolism, xenobiotic metabolism and hormone cycling. Functional analysis of these gene expression profiles can provide a better understanding of modes of toxic action and permits the prediction of mixture effects within contaminated ecosystems. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Flow over Canopies with Complex Morphologies

NASA Astrophysics Data System (ADS)

Rubol, S.; Ling, B.; Battiato, I.

2017-12-01

Quantifying and predicting how submerged vegetation affects the velocity profile of riverine systems is crucial in ecohydraulics to properly assess the water quality and ecological functions or rivers. The state of the art includes a plethora of models to study the flow and transport over submerged canopies. However, most of them are validated against data collected in flume experiments with rigid cylinders. With the objective of investigating the capability of a simple analytical solution for vegetated flow to reproduce and predict the velocity profile of complex shaped flexible canopies, we use the flow model proposed by Battiato and Rubol [WRR 2013] as the analytical approximation of the mean velocity profile above and within the canopy layer. This model has the advantages (i) to threat the canopy layer as a porous medium, whose geometrical properties are associated with macroscopic effective permeability and (ii) to use input parameters that can be estimated by remote sensing techniques, such us the heights of the water level and the canopy. The analytical expressions for the average velocity profile and the discharge are tested against data collected across a wide range of canopy morphologies commonly encountered in riverine systems, such as grasses, woody vegetation and bushes. Results indicate good agreement between the analytical expressions and the data for both simple and complex plant geometry shapes. The rescaled low submergence velocities in the canopy layer followed the same scaling found in arrays of rigid cylinders. In addition, for the dataset analyzed, the Darcy friction factor scaled with the inverse of the bulk Reynolds number multiplied by the ratio of the fluid to turbulent viscosity.

The triglyceride to high-density lipoprotein-cholesterol ratio in adolescence and subsequent weight gain predict nuclear magnetic resonance-measured lipoprotein subclasses in adulthood.

PubMed

Weiss, Ram; Otvos, James D; Sinnreich, Ronit; Miserez, Andre R; Kark, Jeremy D

2011-01-01

To assess whether the fasting triglyceride-to-high-density lipoprotein (HDL)-cholesterol (TG/HDL) ratio in adolescence is predictive of a proatherogenic lipid profile in adulthood. A longitudinal follow-up of 770 Israeli adolescents 16 to 17 years of age who participated in the Jerusalem Lipid Research Clinic study and were reevaluated 13 years later. Lipoprotein particle size was assessed at the follow-up with proton nuclear magnetic resonance. The TG/HDL ratio measured in adolescence was strongly associated with low-density lipoprotein, very low-density lipoprotein (VLDL), and HDL mean particle size in young adulthood in both sexes, even after adjustment for baseline body mass index and body mass index change. The TG/HDL ratio measured in adolescence and subsequent weight gain independently predicted atherogenic small low-density lipoprotein and large VLDL particle concentrations (P < .001 in both sexes). Baseline TG/HDL and weight gain interacted to increase large VLDL concentration in men (P < .001). Adolescents with an elevated TG/HDL ratio are prone to express a proatherogenic lipid profile in adulthood. This profile is additionally worsened by weight gain. Copyright © 2011 Mosby, Inc. All rights reserved.

Circular RNA hsa_circ_0003575 regulates oxLDL induced vascular endothelial cells proliferation and angiogenesis.

PubMed

Li, Chen-Ye; Ma, Lan; Yu, Bo

2017-11-01

Circular RNAs (circRNAs) are a novel class of RNAs generated from back-splicing and characterized by covalently closed continuous loops. Recently, circRNAs have recently shown large regulation on cardiovascular system, including atherosclerosis. The present study aims to investigate the circRNA expression profile and identify their roles on vascular endothelial cells induced by oxLDL. Human circRNA microarray analysis revealed that total 943 differently expressed circRNAs were screened with 2 fold change. Hsa_circ_0003575 was validated to be significantly up-regulated in oxLDL induced HUVECs. Loss-of-function experiments indicated that hsa_circ_0003575 silencing promoted the proliferation and angiogenesis ability of HUVECs. Bioinformatics online programs predicted the potential circRNA-miRNA-mRNA network for hsa_circ_0003575. In summary, circRNA microarray analysis reveals the expression profiles of HUVECs and verifies the role of hsa_circ_0003575 on HUVECs, providing a therapeutic strategy for vascular endothelial cell injury of atherosclerosis. Copyright © 2017. Published by Elsevier Masson SAS.

Current status of gene expression profiling in the diagnosis and management of acute leukaemia.

PubMed

Bacher, Ulrike; Kohlmann, Alexander; Haferlach, Torsten

2009-06-01

Gene expression profiling (GEP) enables the simultaneous investigation of the expression of tens of thousands of genes and was successfully introduced in leukaemia research a decade ago. Aiming to better understand the diversity of genetic aberrations in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), pioneer studies investigated and confirmed the predictability of many cytogenetic and molecular subclasses in AML and ALL. In addition, GEP can define new prognostic subclasses within distinct leukaemia subgroups, as illustrated in AML with normal karyotype. Another approach is the development of treatment-specific sensitivity assays, which might contribute to targeted therapy studies. Finally, GEP might enable the detection of new molecular targets for therapy in patients with acute leukaemia. Meanwhile, large multicentre studies, e.g. the Microarray Innovations in LEukaemia (MILE) study, prepare for a standardised introduction of GEP in leukaemia diagnostic algorithms, aiming to translate this novel methodology into clinical routine for the benefit of patients with the complex disorders of AML and ALL.

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?

PubMed

Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David

2014-04-01

Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.

Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools

PubMed Central

Sasaki, Eita; Momose, Haruka; Hiradate, Yuki; Furuhata, Keiko; Takai, Mamiko; Asanuma, Hideki; Ishii, Ken J.

2018-01-01

Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development. PMID:29408882

Drug transporter expression profiling in a three-dimensional kidney proximal tubule in vitro nephrotoxicity model.

PubMed

Diekjürgen, Dorina; Grainger, David W

2018-05-09

Given currently poor toxicity translational predictions for drug candidates, improved mechanistic understanding underlying nephrotoxicity and drug renal clearance is needed to improve drug development and safety screening. Therefore, better relevant and well-characterized in vitro screening models are required to reliably predict human nephrotoxicity. Because kidney proximal tubules are central to active drug uptake and secretion processes and therefore to nephrotoxicity, this study acquired regio-specific expression data from recently reported primary proximal tubule three-dimensional (3D) hyaluronic acid gel culture and non-gel embedded cultured murine proximal tubule suspensions used in nephrotoxicity assays. Quantitative assessment of the mRNA expression of 21 known kidney tubule markers and important proximal tubule transporters with known roles in drug transport was obtained. Asserting superior gene expression levels over current commonly used two-dimensional (2D) kidney cell culture lines was the study objective. Hence, we compare previously published gel-based 3D proximal tubule fragment culture and their non-gel suspensions for up to 1 week. We demonstrate that 3D tubule culture exhibits superior gene expression levels and profiles compared to published commonly used 2D kidney cell lines (Caki-1 and HK-2) in plastic plate monocultures. Additionally, nearly all tested genes retain mRNA expression after 7 days in both proximal tubule cultures, a limitation of 2D cell culture lines. Importantly, gel presence is shown not to interfere with the gene expression assay. Western blots confirm protein expression of OAT1 and 3 and OCT2. Functional transport assays confirm their respective transporter functions in vitro. Overall, results validate retention of essential toxicity-relevant transporters in this published 3D proximal tubule model over conventional 2D kidney cell cultures, producing opportunities for more reliable, sensitive, and comprehensive drug toxicity studies relevant to drug development and nephrotoxicity goals.

A Genomic Score Prognostic of Outcome in Trauma Patients

PubMed Central

Warren, H Shaw; Elson, Constance M; Hayden, Douglas L; Schoenfeld, David A; Cobb, J Perren; Maier, Ronald V; Moldawer, Lyle L; Moore, Ernest E; Harbrecht, Brian G; Pelak, Kimberly; Cuschieri, Joseph; Herndon, David N; Jeschke, Marc G; Finnerty, Celeste C; Brownstein, Bernard H; Hennessy, Laura; Mason, Philip H; Tompkins, Ronald G

2009-01-01

Traumatic injuries frequently lead to infection, organ failure, and death. Health care providers rely on several injury scoring systems to quantify the extent of injury and to help predict clinical outcome. Physiological, anatomical, and clinical laboratory analytic scoring systems (Acute Physiology and Chronic Health Evaluation [APACHE], Injury Severity Score [ISS]) are utilized, with limited success, to predict outcome following injury. The recent development of techniques for measuring the expression level of all of a person’s genes simultaneously may make it possible to develop an injury scoring system based on the degree of gene activation. We hypothesized that a peripheral blood leukocyte gene expression score could predict outcome, including multiple organ failure, following severe blunt trauma. To test such a scoring system, we measured gene expression of peripheral blood leukocytes from patients within 12 h of traumatic injury. cRNA derived from whole blood leukocytes obtained within 12 h of injury provided gene expression data for the entire genome that were used to create a composite gene expression score for each patient. Total blood leukocytes were chosen because they are active during inflammation, which is reflective of poor outcome. The gene expression score combines the activation levels of all the genes into a single number which compares the patient’s gene expression to the average gene expression in uninjured volunteers. Expression profiles from healthy volunteers were averaged to create a reference gene expression profile which was used to compute a difference from reference (DFR) score for each patient. This score described the overall genomic response of patients within the first 12 h following severe blunt trauma. Regression models were used to compare the association of the DFR, APACHE, and ISS scores with outcome. We hypothesized that patients with a total gene response more different from uninjured volunteers would tend to have poorer outcome than those more similar. Our data show that for measures of poor outcome, such as infections, organ failures, and length of hospital stay, this is correct. DFR scores were associated significantly with adverse outcome, including multiple organ failure, duration of ventilation, length of hospital stay, and infection rate. The association remained significant after adjustment for injury severity as measured by APACHE or ISS. A single score representing changes in gene expression in peripheral blood leukocytes within hours of severe blunt injury is associated with adverse clinical outcomes that develop later in the hospital course. Assessment of genome-wide gene expression provides useful clinical information that is different from that provided by currently utilized anatomic or physiologic scores. PMID:19593405

Genome-Wide Characterization of Major Intrinsic Proteins in Four Grass Plants and Their Non-Aqua Transport Selectivity Profiles with Comparative Perspective

PubMed Central

Azad, Abul Kalam; Ahmed, Jahed; Alum, Md. Asraful; Hasan, Md. Mahbub; Ishikawa, Takahiro; Sawa, Yoshihiro; Katsuhara, Maki

2016-01-01

Major intrinsic proteins (MIPs), commonly known as aquaporins, transport not only water in plants but also other substrates of physiological significance and heavy metals. In most of the higher plants, MIPs are divided into five subfamilies (PIPs, TIPs, NIPs, SIPs and XIPs). Herein, we identified 68, 42, 38 and 28 full-length MIPs, respectively in the genomes of four monocot grass plants, specifically Panicum virgatum, Setaria italica, Sorghum bicolor and Brachypodium distachyon. Phylogenetic analysis showed that the grass plants had only four MIP subfamilies including PIPs, TIPs, NIPs and SIPs without XIPs. Based on structural analysis of the homology models and comparing the primary selectivity-related motifs [two NPA regions, aromatic/arginine (ar/R) selectivity filter and Froger's positions (FPs)] of all plant MIPs that have been experimentally proven to transport non-aqua substrates, we predicted the transport profiles of all MIPs in the four grass plants and also in eight other plants. Groups of MIP subfamilies based on ar/R selectivity filter and FPs were linked to the non-aqua transport profiles. We further deciphered the substrate selectivity profiles of the MIPs in the four grass plants and compared them with their counterparts in rice, maize, soybean, poplar, cotton, Arabidopsis thaliana, Physcomitrella patens and Selaginella moellendorffii. In addition to two NPA regions, ar/R filter and FPs, certain residues, especially in loops B and C, contribute to the functional distinctiveness of MIP groups. Expression analysis of transcripts in different organs indicated that non-aqua transport was related to expression of MIPs since most of the unexpressed MIPs were not predicted to facilitate the transport of non-aqua molecules. Among all MIPs in every plant, TIP (BdTIP1;1, SiTIP1;2, SbTIP2;1 and PvTIP1;2) had the overall highest mean expression. Our study generates significant information for understanding the diversity, evolution, non-aqua transport profiles and insight into comparative transport selectivity of plant MIPs, and provides tools for the development of transgenic plants. PMID:27327960

Genome-Wide Characterization of Major Intrinsic Proteins in Four Grass Plants and Their Non-Aqua Transport Selectivity Profiles with Comparative Perspective.

PubMed

Azad, Abul Kalam; Ahmed, Jahed; Alum, Md Asraful; Hasan, Md Mahbub; Ishikawa, Takahiro; Sawa, Yoshihiro; Katsuhara, Maki

2016-01-01

Major intrinsic proteins (MIPs), commonly known as aquaporins, transport not only water in plants but also other substrates of physiological significance and heavy metals. In most of the higher plants, MIPs are divided into five subfamilies (PIPs, TIPs, NIPs, SIPs and XIPs). Herein, we identified 68, 42, 38 and 28 full-length MIPs, respectively in the genomes of four monocot grass plants, specifically Panicum virgatum, Setaria italica, Sorghum bicolor and Brachypodium distachyon. Phylogenetic analysis showed that the grass plants had only four MIP subfamilies including PIPs, TIPs, NIPs and SIPs without XIPs. Based on structural analysis of the homology models and comparing the primary selectivity-related motifs [two NPA regions, aromatic/arginine (ar/R) selectivity filter and Froger's positions (FPs)] of all plant MIPs that have been experimentally proven to transport non-aqua substrates, we predicted the transport profiles of all MIPs in the four grass plants and also in eight other plants. Groups of MIP subfamilies based on ar/R selectivity filter and FPs were linked to the non-aqua transport profiles. We further deciphered the substrate selectivity profiles of the MIPs in the four grass plants and compared them with their counterparts in rice, maize, soybean, poplar, cotton, Arabidopsis thaliana, Physcomitrella patens and Selaginella moellendorffii. In addition to two NPA regions, ar/R filter and FPs, certain residues, especially in loops B and C, contribute to the functional distinctiveness of MIP groups. Expression analysis of transcripts in different organs indicated that non-aqua transport was related to expression of MIPs since most of the unexpressed MIPs were not predicted to facilitate the transport of non-aqua molecules. Among all MIPs in every plant, TIP (BdTIP1;1, SiTIP1;2, SbTIP2;1 and PvTIP1;2) had the overall highest mean expression. Our study generates significant information for understanding the diversity, evolution, non-aqua transport profiles and insight into comparative transport selectivity of plant MIPs, and provides tools for the development of transgenic plants.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Gene expression profiling in whole blood of patients with coronary artery disease

PubMed Central

Taurino, Chiara; Miller, William H.; McBride, Martin W.; McClure, John D.; Khanin, Raya; Moreno, María U.; Dymott, Jane A.; Delles, Christian; Dominiczak, Anna F.

2010-01-01

Owing to the dynamic nature of the transcriptome, gene expression profiling is a promising tool for discovery of disease-related genes and biological pathways. In the present study, we examined gene expression in whole blood of 12 patients with CAD (coronary artery disease) and 12 healthy control subjects. Furthermore, ten patients with CAD underwent whole-blood gene expression analysis before and after the completion of a cardiac rehabilitation programme following surgical coronary revascularization. mRNA and miRNA (microRNA) were isolated for expression profiling. Gene expression analysis identified 365 differentially expressed genes in patients with CAD compared with healthy controls (175 up- and 190 down-regulated in CAD), and 645 in CAD rehabilitation patients (196 up- and 449 down-regulated post-rehabilitation). Biological pathway analysis identified a number of canonical pathways, including oxidative phosphorylation and mitochondrial function, as being significantly and consistently modulated across the groups. Analysis of miRNA expression revealed a number of differentially expressed miRNAs, including hsa-miR-140-3p (control compared with CAD, P=0.017), hsa-miR-182 (control compared with CAD, P=0.093), hsa-miR-92a and hsa-miR-92b (post- compared with pre-exercise, P<0.01). Global analysis of predicted miRNA targets found significantly reduced expression of genes with target regions compared with those without: hsa-miR-140-3p (P=0.002), hsa-miR-182 (P=0.001), hsa-miR-92a and hsa-miR-92b (P=2.2×10−16). In conclusion, using whole blood as a ‘surrogate tissue’ in patients with CAD, we have identified differentially expressed miRNAs, differentially regulated genes and modulated pathways which warrant further investigation in the setting of cardiovascular function. This approach may represent a novel non-invasive strategy to unravel potentially modifiable pathways and possible therapeutic targets in cardiovascular disease. PMID:20528768

Expressions of the fundamental equation of gradient elution and a numerical solution of these equations under any gradient profile.

PubMed

Nikitas, P; Pappa-Louisi, A

2005-09-01

The original work carried out by Freiling and Drake in gradient liquid chromatography is rewritten in the current language of reversed-phase liquid chromatography. This allows for the rigorous derivation of the fundamental equation for gradient elution and the development of two alternative expressions of this equation, one of which is free from the constraint that the holdup time must be constant. In addition, the above derivation results in a very simple numerical solution of the various equations of gradient elution under any gradient profile. The theory was tested using eight catechol-related solutes in mobile phases modified with methanol, acetonitrile, or 2-propanol. It was found to be a satisfactory prediction of solute gradient retention behavior even if we used a simple linear description for the isocratic elution of these solutes.

Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma.

PubMed

Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey

2018-04-01

Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.

Model-based redesign of global transcription regulation

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

2009-01-01

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257

Electric pulses used in electrochemotherapy and electrogene therapy do not significantly change the expression profile of genes involved in the development of cancer in malignant melanoma cells.

PubMed

Mlakar, Vid; Todorovic, Vesna; Cemazar, Maja; Glavac, Damjan; Sersa, Gregor

2009-08-26

Electroporation is a versatile method for in vitro or in vivo delivery of different molecules into cells. However, no study so far has analysed the effects of electric pulses used in electrochemotherapy (ECT pulses) or electric pulses used in electrogene therapy (EGT pulses) on malignant cells. We studied the effect of ECT and EGT pulses on human malignant melanoma cells in vitro in order to understand and predict the possible effect of electric pulses on gene expression and their possible effect on cell behaviour. We used microarrays with 2698 different oligonucleotides to obtain the expression profile of genes involved in apoptosis and cancer development in a malignant melanoma cell line (SK-MEL28) exposed to ECT pulses and EGT pulses. Cells exposed to ECT pulses showed a 68.8% average survival rate, while cells exposed to EGT pulses showed a 31.4% average survival rate. Only seven common genes were found differentially expressed in cells 16 h after exposure to ECT and EGT pulses. We found that ECT and EGT pulses induce an HSP70 stress response mechanism, repress histone protein H4, a major protein involved in chromatin assembly, and down-regulate components involved in protein synthesis. Our results show that electroporation does not significantly change the expression profile of major tumour suppressor genes or oncogenes of the cell cycle. Moreover, electroporation also does not changes the expression of genes involved in the stability of DNA, supporting current evidence that electroporation is a safe method that does not promote tumorigenesis. However, in spite of being considered an isothermal method, it does to some extent induce stress, which resulted in the expression of the environmental stress response mechanism, HSP70.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

PubMed

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

Integrating microRNA and mRNA expression profiles of acute promyelocytic leukemia cells to explore the occurrence mechanisms of differentiation syndrome

PubMed Central

Ge, Fei; Cao, Fenglin; Li, Haitao; Wang, Ping; Xu, Mengyuan; Song, Peng; Li, Xiaoxia; Wang, Shuye; Li, Jinmei; Han, Xueying; Zhao, Yanhong; Su, Yanhua; Li, Yinghua; Fan, Shengjin; Li, Limin; Zhou, Jin

2016-01-01

The pathogenesis of therapy-induced differentiation syndrome (DS) in patients with acute promyelocytic leukemia (APL) remains unclear. In this study, mRNA and microRNA (miRNA) expression profiling of peripheral blood APL cells from patients complicated with vs. without DS were integratively analyzed to explore the mechanisms underlying arsenic trioxide treatment-associated DS. By integrating the differentially expressed data with the data of differentially expressed microRNAs and their computationally predicted target genes, as well as the data of transcription factors and differentially expressed target microRNAs obtained from a literature search, a DS-related genetic regulatory network was constructed. Then using an EAGLE algorithm in clusterViz, the network was subdivided into 10 modules. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database the modules were annotated functionally, and three functionally active modules were recognized. The further in-depth analyses on the annotated functions of the three modules and the expression and roles of the related genes revealed that proliferation, differentiation, apoptosis and infiltration capability of APL cells might play important roles in the DS pathogenesis. The results could improve our understanding of DS pathogenesis from a more overall perspective, and could provide new clues for future research. PMID:27634874

Functional expression of dental plaque microbiota.

PubMed

Peterson, Scott N; Meissner, Tobias; Su, Andrew I; Snesrud, Erik; Ong, Ana C; Schork, Nicholas J; Bretz, Walter A

2014-01-01

Dental caries remains a significant public health problem and is considered pandemic worldwide. The prediction of dental caries based on profiling of microbial species involved in disease and equally important, the identification of species conferring dental health has proven more difficult than anticipated due to high interpersonal and geographical variability of dental plaque microbiota. We have used RNA-Seq to perform global gene expression analysis of dental plaque microbiota derived from 19 twin pairs that were either concordant (caries-active or caries-free) or discordant for dental caries. The transcription profiling allowed us to define a functional core microbiota consisting of nearly 60 species. Similarities in gene expression patterns allowed a preliminary assessment of the relative contribution of human genetics, environmental factors and caries phenotype on the microbiota's transcriptome. Correlation analysis of transcription allowed the identification of numerous functional networks, suggesting that inter-personal environmental variables may co-select for groups of genera and species. Analysis of functional role categories allowed the identification of dominant functions expressed by dental plaque biofilm communities, that highlight the biochemical priorities of dental plaque microbes to metabolize diverse sugars and cope with the acid and oxidative stress resulting from sugar fermentation. The wealth of data generated by deep sequencing of expressed transcripts enables a greatly expanded perspective concerning the functional expression of dental plaque microbiota.

Functional expression of dental plaque microbiota

PubMed Central

Peterson, Scott N.; Meissner, Tobias; Su, Andrew I.; Snesrud, Erik; Ong, Ana C.; Schork, Nicholas J.; Bretz, Walter A.

2014-01-01

Dental caries remains a significant public health problem and is considered pandemic worldwide. The prediction of dental caries based on profiling of microbial species involved in disease and equally important, the identification of species conferring dental health has proven more difficult than anticipated due to high interpersonal and geographical variability of dental plaque microbiota. We have used RNA-Seq to perform global gene expression analysis of dental plaque microbiota derived from 19 twin pairs that were either concordant (caries-active or caries-free) or discordant for dental caries. The transcription profiling allowed us to define a functional core microbiota consisting of nearly 60 species. Similarities in gene expression patterns allowed a preliminary assessment of the relative contribution of human genetics, environmental factors and caries phenotype on the microbiota's transcriptome. Correlation analysis of transcription allowed the identification of numerous functional networks, suggesting that inter-personal environmental variables may co-select for groups of genera and species. Analysis of functional role categories allowed the identification of dominant functions expressed by dental plaque biofilm communities, that highlight the biochemical priorities of dental plaque microbes to metabolize diverse sugars and cope with the acid and oxidative stress resulting from sugar fermentation. The wealth of data generated by deep sequencing of expressed transcripts enables a greatly expanded perspective concerning the functional expression of dental plaque microbiota. PMID:25177549

Profilings of MicroRNAs in the Liver of Common Carp (Cyprinus carpio) Infected with Flavobacterium columnare

PubMed Central

Zhao, Lijuan; Lu, Hong; Meng, Qinglei; Wang, Jinfu; Wang, Weimin; Yang, Ling; Lin, Li

2016-01-01

MicroRNAs (miRNAs) play important roles in regulation of many biological processes in eukaryotes, including pathogen infection and host interactions. Flavobacterium columnare (FC) infection can cause great economic loss of common carp (Cyprinus carpio) which is one of the most important cultured fish in the world. However, miRNAs in response to FC infection in common carp has not been characterized. To identify specific miRNAs involved in common carp infected with FC, we performed microRNA sequencing using livers of common carp infected with and without FC. A total of 698 miRNAs were identified, including 142 which were identified and deposited in the miRbase database (Available online: http://www.mirbase.org/) and 556 had only predicted miRNAs. Among the deposited miRNAs, eight miRNAs were first identified in common carp. Thirty of the 698 miRNAs were differentially expressed miRNAs (DIE-miRNAs) between the FC infected and control samples. From the DIE-miRNAs, seven were selected randomly and their expression profiles were confirmed to be consistent with the microRNA sequencing results using RT-PCR and qRT-PCR. In addition, a total of 27,363 target genes of the 30 DIE-miRNAs were predicted. The target genes were enriched in five Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including focal adhesion, extracellular matrix (ECM)-receptor interaction, erythroblastic leukemia viral oncogene homolog (ErbB) signaling pathway, regulation of actin cytoskeleton, and adherent junction. The miRNA expression profile of the liver of common carp infected with FC will pave the way for the development of effective strategies to fight against FC infection. PMID:27092486

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster

PubMed Central

Hoffman, Jessica M; Soltow, Quinlyn A; Li, Shuzhao; Sidik, Alfire; Jones, Dean P; Promislow, Daniel E L

2014-01-01

Researchers have used whole-genome sequencing and gene expression profiling to identify genes associated with age, in the hope of understanding the underlying mechanisms of senescence. But there is a substantial gap from variation in gene sequences and expression levels to variation in age or life expectancy. In an attempt to bridge this gap, here we describe the effects of age, sex, genotype, and their interactions on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Among the 6800 features analyzed, we found that over one-quarter of all metabolites were significantly associated with age, sex, genotype, or their interactions, and multivariate analysis shows that individual metabolomic profiles are highly predictive of these traits. Using a metabolomic equivalent of gene set enrichment analysis, we identified numerous metabolic pathways that were enriched among metabolites associated with age, sex, and genotype, including pathways involving sugar and glycerophospholipid metabolism, neurotransmitters, amino acids, and the carnitine shuttle. Our results suggest that high-sensitivity metabolomic studies have excellent potential not only to reveal mechanisms that lead to senescence, but also to help us understand differences in patterns of aging among genotypes and between males and females. PMID:24636523

Small RNAome profiling from human skeletal muscle: novel miRNAs and their targets associated with cancer cachexia.

PubMed

Narasimhan, Ashok; Ghosh, Sunita; Stretch, Cynthia; Greiner, Russell; Bathe, Oliver F; Baracos, Vickie; Damaraju, Sambasivarao

2017-06-01

MicroRNAs (miRs) are small non-coding RNAs that regulate gene (mRNA) expression. Although the pathological role of miRs have been studied in muscle wasting conditions such as myotonic and muscular dystrophy, their roles in cancer cachexia (CC) are still emerging. The objectives are (i) to profile human skeletal muscle expressed miRs; (ii) to identify differentially expressed (DE) miRs between cachectic and non-cachectic cancer patients; (iii) to identify mRNA targets for the DE miRs to gain mechanistic insights; and (iv) to investigate if miRs show potential prognostic and predictive value. Study subjects were classified based on the international consensus diagnostic criteria for CC. Forty-two cancer patients were included, of which 22 were cachectic cases and 20 were non-cachectic cancer controls. Total RNA isolated from muscle biopsies were subjected to next-generation sequencing. A total of 777 miRs were profiled, and 82 miRs with read counts of ≥5 in 80% of samples were retained for analysis. We identified eight DE miRs (up-regulated, fold change of ≥1.4 at P < 0.05). A total of 191 potential mRNA targets were identified for the DE miRs using previously described human skeletal muscle mRNA expression data (n = 90), and a majority of them were also confirmed in an independent mRNA transcriptome dataset. Ingenuity pathway analysis identified pathways related to myogenesis and inflammation. qRT-PCR analysis of representative miRs showed similar direction of effect (P < 0.05), as observed in next-generation sequencing. The identified miRs also showed prognostic and predictive value. In all, we identified eight novel miRs associated with CC. © 2017 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of the Society on Sarcopenia, Cachexia and Wasting Disorders.

Uncovering leaf rust responsive miRNAs in wheat (Triticum aestivum L.) using high-throughput sequencing and prediction of their targets through degradome analysis.

PubMed

Kumar, Dhananjay; Dutta, Summi; Singh, Dharmendra; Prabhu, Kumble Vinod; Kumar, Manish; Mukhopadhyay, Kunal

2017-01-01

Deep sequencing identified 497 conserved and 559 novel miRNAs in wheat, while degradome analysis revealed 701 targets genes. QRT-PCR demonstrated differential expression of miRNAs during stages of leaf rust progression. Bread wheat (Triticum aestivum L.) is an important cereal food crop feeding 30 % of the world population. Major threat to wheat production is the rust epidemics. This study was targeted towards identification and functional characterizations of micro(mi)RNAs and their target genes in wheat in response to leaf rust ingression. High-throughput sequencing was used for transcriptome-wide identification of miRNAs and their expression profiling in retort to leaf rust using mock and pathogen-inoculated resistant and susceptible near-isogenic wheat plants. A total of 1056 mature miRNAs were identified, of which 497 miRNAs were conserved and 559 miRNAs were novel. The pathogen-inoculated resistant plants manifested more miRNAs compared with the pathogen infected susceptible plants. The miRNA counts increased in susceptible isoline due to leaf rust, conversely, the counts decreased in the resistant isoline in response to pathogenesis illustrating precise spatial tuning of miRNAs during compatible and incompatible interaction. Stem-loop quantitative real-time PCR was used to profile 10 highly differentially expressed miRNAs obtained from high-throughput sequencing data. The spatio-temporal profiling validated the differential expression of miRNAs between the isolines as well as in retort to pathogen infection. Degradome analysis provided 701 predicted target genes associated with defense response, signal transduction, development, metabolism, and transcriptional regulation. The obtained results indicate that wheat isolines employ diverse arrays of miRNAs that modulate their target genes during compatible and incompatible interaction. Our findings contribute to increase knowledge on roles of microRNA in wheat-leaf rust interactions and could help in rust resistance breeding programs.

Evaluation of 5-fluorouracil metabolic enzymes as predictors of response to adjuvant chemotherapy outcomes in patients with stage II/III colorectal cancer: a decision-curve analysis.

PubMed

Shigeta, Kohei; Ishii, Yoshiyuki; Hasegawa, Hirotoshi; Okabayashi, Koji; Kitagawa, Yuko

2014-12-01

The effectiveness of 5-fluorouracil (5-FU)-based adjuvant chemotherapy is reported in patients with colorectal cancer (CRC), but the usefulness of 5-FU metabolic enzymes as predictive biomarkers of the efficacy of this chemotherapy remains unclear. This study aims to verify whether 5-FU metabolic enzymes are predictive biomarkers in the clinical setting of adjuvant chemotherapy for stage II/III CRC. In total, 179 patients with stage II/III CRC who were treated at our institute between 2000 and 2010 were enrolled. Messenger RNA (mRNA) expression of major 5-FU metabolic enzymes, namely thymidylate synthase, dihydropyrimidine dehydrogenase, thymidine phosphorylase (TP), orotate phosphoribosyl transferase, and β-actin (control) was evaluated using the Danenberg Tumor Profile method. mRNA expression and other clinicopathological data were investigated with regard to CRC relapse. A total of 78 patients underwent surgery alone, while 101 underwent adjuvant chemotherapy (5-FU plus leucovorin [LV] or tegafur plus uracil /LV) following surgery. Relapse-free survival was longer and risk of recurrence was lower in association with high TP mRNA expression than in association with low TP mRNA expression in the adjuvant chemotherapy group (hazard ratio 0.66; 95 % confidence interval 0.47-0.92; p = 0.016), but not in the surgery alone group. mRNA expression of no other enzymes was associated with relapse in both groups. In decision-curve analyses, the predictive efficiency of TP mRNA expression plus clinicopathological factors was slightly better than that of clinicopathological factors only. TP mRNA expression in tumors predicted the effects of adjuvant chemotherapy for stage II/III CRC, although the beneficial effects were marginal.

LncRNA Expression Profile of Human Thoracic Aortic Dissection by High-Throughput Sequencing.

PubMed

Sun, Jie; Chen, Guojun; Jing, Yuanwen; He, Xiang; Dong, Jianting; Zheng, Junmeng; Zou, Meisheng; Li, Hairui; Wang, Shifei; Sun, Yili; Liao, Wangjun; Liao, Yulin; Feng, Li; Bin, Jianping

2018-01-01

In this study, the long non-coding RNA (lncRNA) expression profile in human thoracic aortic dissection (TAD), a highly lethal cardiovascular disease, was investigated. Human TAD (n=3) and normal aortic tissues (NA) (n=3) were examined by high-throughput sequencing. Bioinformatics analyses were performed to predict the roles of aberrantly expressed lncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the results. A total of 269 lncRNAs (159 up-regulated and 110 down-regulated) and 2, 255 mRNAs (1 294 up-regulated and 961 down-regulated) were aberrantly expressed in human TAD (fold-change> 1.5, P< 0.05). QRT-PCR results of five dysregulated genes were consistent with HTS data. A lncRNA-mRNA coexpression analysis showed positive correlations between the up-regulated lncRNA (ENSG00000269936) and its adjacent up-regulated mRNA (MAP2K6, R=0.940, P< 0.01), and between the down-regulated lncRNA_1421 and its down-regulated mRNAs (FBLN5, R=0.950, P< 0.01; ACTA2, R=0.96, P< 0.01; TIMP3, R=0.96, P< 0.05). The lncRNA-miRNA-mRNA network indicated that the up-regulated lncRNA XIST and p21 had similar sequences targeted by has-miR-17-5p. The results of luciferase assay and fluorescence immuno-cytochemistry were consistent with that. And qRT-PCR results showed that lncRNA XIST and p21 were expressed at a higher level and has-miR-17-5p was expressed at a lower level in TAD than in NA. The predicted binding motifs of three up-regulated lncRNAs (ENSG00000248508, ENSG00000226530, and EG00000259719) were correlated with up-regulated RUNX1 (R=0.982, P< 0.001; R=0.967, P< 0.01; R=0.960, P< 0.01, respectively). Our study revealed a set of dysregulated lncRNAs and predicted their multiple potential functions in human TAD. These findings suggest that lncRNAs are novel potential therapeutic targets for human TAD. © 2018 The Author(s). Published by S. Karger AG, Basel.

RNA expression of genes involved in cytarabine metabolism and transport predicts cytarabine response in acute myeloid leukemia.

PubMed

Abraham, Ajay; Varatharajan, Savitha; Karathedath, Sreeja; Philip, Chepsy; Lakshmi, Kavitha M; Jayavelu, Ashok Kumar; Mohanan, Ezhilpavai; Janet, Nancy Beryl; Srivastava, Vivi M; Shaji, Ramachandran V; Zhang, Wei; Abraham, Aby; Viswabandya, Auro; George, Biju; Chandy, Mammen; Srivastava, Alok; Mathews, Vikram; Balasubramanian, Poonkuzhali

2015-07-01

Variation in terms of outcome and toxic side effects of treatment exists among acute myeloid leukemia (AML) patients on chemotherapy with cytarabine (Ara-C) and daunorubicin (Dnr). Candidate Ara-C metabolizing gene expression in primary AML cells is proposed to account for this variation. Ex vivo Ara-C sensitivity was determined in primary AML samples using MTT assay. mRNA expression of candidate Ara-C metabolizing genes were evaluated by RQPCR analysis. Global gene expression profiling was carried out for identifying differentially expressed genes between exvivo Ara-C sensitive and resistant samples. Wide interindividual variations in ex vivo Ara-C cytotoxicity were observed among samples from patients with AML and were stratified into sensitive, intermediately sensitive and resistant, based on IC50 values obtained by MTT assay. RNA expression of deoxycytidine kinase (DCK), human equilibrative nucleoside transporter-1 (ENT1) and ribonucleotide reductase M1 (RRM1) were significantly higher and cytidine deaminase (CDA) was significantly lower in ex vivo Ara-C sensitive samples. Higher DCK and RRM1 expression in AML patient's blast correlated with better DFS. Ara-C resistance index (RI), a mathematically derived quotient was proposed based on candidate gene expression pattern. Ara-C ex vivo sensitive samples were found to have significantly lower RI compared with resistant as well as samples from patients presenting with relapse. Patients with low RI supposedly highly sensitive to Ara-C were found to have higher incidence of induction death (p = 0.002; RR: 4.35 [95% CI: 1.69-11.22]). Global gene expression profiling undertaken to find out additional contributors of Ara-C resistance identified many apoptosis as well as metabolic pathway genes to be differentially expressed between Ara-C resistant and sensitive samples. This study highlights the importance of evaluating expression of candidate Ara-C metabolizing genes in predicting ex vivo drug response as well as treatment outcome. RI could be a predictor of ex vivo Ara-C response irrespective of cytogenetic and molecular risk groups and a potential biomarker for AML treatment outcome and toxicity. Original submitted 22 December 2014; Revision submitted 9 April 2015.

Functional genomic mRNA profiling of a large cancer data base demonstrates mesothelin overexpression in a broad range of tumor types.

PubMed

Lamberts, Laetitia E; de Groot, Derk Jan A; Bense, Rico D; de Vries, Elisabeth G E; Fehrmann, Rudolf S N

2015-09-29

The membrane bound glycoprotein mesothelin (MSLN) is a highly specific tumor marker, which is currently exploited as target for drugs. There are only limited data available on MSLN expression by human tumors. Therefore we determined overexpression of MSLN across different tumor types with Functional Genomic mRNA (FGM) profiling of a large cancer database. Results were compared with data in articles reporting immunohistochemical (IHC) MSLN tumor expression. FGM profiling is a technique that allows prediction of biologically relevant overexpression of proteins from a robust data set of mRNA microarrays. This technique was used in a database comprising 19,746 tumors to identify for 41 tumor types the percentage of samples with an overexpression of MSLN compared to a normal background. A literature search was performed to compare the FGM profiling data with studies reporting IHC MSLN tumor expression. FGM profiling showed MSLN overexpression in gastrointestinal (12-36%) and gynecological tumors (20-66%), non-small cell lung cancer (21%) and synovial sarcomas (30%). The overexpression found in thyroid cancers (5%) and renal cell cancers (10%) was not yet reported with IHC analyses. We observed that MSLN amplification rate within esophageal cancer depends on the histotype (31% for adenocarcinomas versus 3% for squamous-cell carcinomas). Subset analysis in breast cancer showed MSLN amplification rates of 28% in triple-negative breast cancer (TNBC) and 33% in basal-like breast cancer. Further subtype analysis of TNBCs showed the highest amplification rate (42%) in the basal-like 1 subtype and the lowest amplification rate (9%) in the luminal androgen receptor subtype.

A mathematical model for predicting cyclic voltammograms of electronically conductive polypyrrole

NASA Technical Reports Server (NTRS)

Yeu, Taewhan; Nguyen, Trung V.; White, Ralph E.

1988-01-01

Polypyrrole is an attractive polymer for use as a high-energy-density secondary battery because of its potential as an inexpensive, lightweight, and noncorrosive electrode material. A mathematical model to simulate cyclic voltammograms for polypyrrole is presented. The model is for a conductive porous electrode film on a rotating disk electrode (RDE) and is used to predict the spatial and time dependence of concentration, overpotential, and stored charge profiles within a polypyrrole film. The model includes both faradic and capacitance charge components in the total current density expression.

A mathematical model for predicting cyclic voltammograms of electronically conductive polypyrrole

NASA Technical Reports Server (NTRS)

Yeu, Taewhan; Nguyen, Trung V.; White, Ralph E.

1987-01-01

Polypyrrole is an attractive polymer for use as a high-energy-density secondary battery because of its potential as an inexpensive, lightweight, and noncorrosive electrode material. A mathematical model to simulate cyclic voltammograms for polypyrrole is presented. The model is for a conductive porous electrode film on a rotating disk electrode (RDE) and is used to predict the spatial and time dependence of concentration, overpotential, and stored charge profiles within a polypyrrole film. The model includes both faradic and capacitance charge components in the total current density expression.

Transcriptomics in cancer diagnostics: developments in technology, clinical research and commercialization.

PubMed

Sager, Monica; Yeat, Nai Chien; Pajaro-Van der Stadt, Stefan; Lin, Charlotte; Ren, Qiuyin; Lin, Jimmy

2015-01-01

Transcriptomic technologies are evolving to diagnose cancer earlier and more accurately to provide greater predictive and prognostic utility to oncologists and patients. Digital techniques such as RNA sequencing are replacing still-imaging techniques to provide more detailed analysis of the transcriptome and aberrant expression that causes oncogenesis, while companion diagnostics are developing to determine the likely effectiveness of targeted treatments. This article examines recent advancements in molecular profiling research and technology as applied to cancer diagnosis, clinical applications and predictions for the future of personalized medicine in oncology.

A new biologic prognostic model based on immunohistochemistry predicts survival in patients with diffuse large B-cell lymphoma.

PubMed

Perry, Anamarija M; Cardesa-Salzmann, Teresa M; Meyer, Paul N; Colomo, Luis; Smith, Lynette M; Fu, Kai; Greiner, Timothy C; Delabie, Jan; Gascoyne, Randy D; Rimsza, Lisa; Jaffe, Elaine S; Ott, German; Rosenwald, Andreas; Braziel, Rita M; Tubbs, Raymond; Cook, James R; Staudt, Louis M; Connors, Joseph M; Sehn, Laurie H; Vose, Julie M; López-Guillermo, Armando; Campo, Elias; Chan, Wing C; Weisenburger, Dennis D

2012-09-13

Biologic factors that predict the survival of patients with a diffuse large B-cell lymphoma, such as cell of origin and stromal signatures, have been discovered by gene expression profiling. We attempted to simulate these gene expression profiling findings and create a new biologic prognostic model based on immunohistochemistry. We studied 199 patients (125 in the training set, 74 in the validation set) with de novo diffuse large B-cell lymphoma treated with rituximab and CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) or CHOP-like therapies, and immunohistochemical stains were performed on paraffin-embedded tissue microarrays. In the model, 1 point was awarded for each adverse prognostic factor: nongerminal center B cell-like subtype, SPARC (secreted protein, acidic, and rich in cysteine) < 5%, and microvascular density quartile 4. The model using these 3 biologic markers was highly predictive of overall survival and event-free survival in multivariate analysis after adjusting for the International Prognostic Index in both the training and validation sets. This new model delineates 2 groups of patients, 1 with a low biologic score (0-1) and good survival and the other with a high score (2-3) and poor survival. This new biologic prognostic model could be used with the International Prognostic Index to stratify patients for novel or risk-adapted therapies.

miR-205 and miR-200c: Predictive Micro RNAs for Lymph Node Metastasis in Triple Negative Breast Cancer

PubMed Central

Yilmaz, Ismail; Narli, Gizem; Haholu, Aptullah; Kucukodaci, Zafer; Demirel, Dilaver

2014-01-01

Purpose We examined expression profiles of 16 micro RNAs (miRNAs) in triple negative breast cancers to identify their potential as biomarkers for lymph node metastasis. Methods The expression profiles of miR-9, miR-21, miR-30a, miR-30d, miR-31, miR-34a, miR-34c, miR-100, miR-122, miR-125b, miR-146a, miR-146b, miR-155, miR-181a, miR-200c, and miR-205 were examined by using real-time quantitative reverse transcription polymerase chain reaction in tumor samples and corresponding benign breast tissues. Their associations with histopathological features and prognostic parameters were assessed. Results When compared with the expression in benign breast tissues, seven of the miRNAs (miR-31, miR-205, miR-34a, miR-146a, miR-125b, miR-34c, and miR-181a) were downregulated more than 1.5-fold in tumor tissues, whereas, only miR-21 was found to be upregulated more than 1.5-fold in tumor tissues. Although miR-200c levels were decreased only 1.12-fold in tumor tissues, the reduced expressions of miR-200c and miR-205 were significantly associated with lymph node metastasis (p=0.021 and p=0.016, respectively). Conclusion Our results demonstrate that miR-205 and miR-200c expression levels may be useful in predicting lymph node metastasis in triple negative breast cancer patients. PMID:25013435

Exploring Regulatory Mechanisms of Atrial Myocyte Hypertrophy of Mitral Regurgitation through Gene Expression Profiling Analysis: Role of NFAT in Cardiac Hypertrophy

PubMed Central

Chang, Tzu-Hao; Chen, Mien-Cheng; Chang, Jen-Ping; Huang, Hsien-Da; Ho, Wan-Chun; Lin, Yu-Sheng; Pan, Kuo-Li; Huang, Yao-Kuang; Liu, Wen-Hao; Wu, Chia-Chen

2016-01-01

Background Left atrial enlargement in mitral regurgitation (MR) predicts a poor prognosis. The regulatory mechanisms of atrial myocyte hypertrophy of MR patients remain unknown. Methods and Results This study comprised 14 patients with MR, 7 patients with aortic valve disease (AVD), and 6 purchased samples from normal subjects (NC). We used microarrays, enrichment analysis and quantitative RT-PCR to study the gene expression profiles in the left atria. Microarray results showed that 112 genes were differentially up-regulated and 132 genes were differentially down-regulated in the left atria between MR patients and NC. Enrichment analysis of differentially expressed genes demonstrated that “NFAT in cardiac hypertrophy” pathway was not only one of the significant associated canonical pathways, but also the only one predicted with a non-zero score of 1.34 (i.e. activated) through Ingenuity Pathway Analysis molecule activity predictor. Ingenuity Pathway Analysis Global Molecular Network analysis exhibited that the highest score network also showed high association with cardiac related pathways and functions. Therefore, 5 NFAT associated genes (PPP3R1, PPP3CB, CAMK1, MEF2C, PLCE1) were studies for validation. The mRNA expressions of PPP3CB and MEF2C were significantly up-regulated, and CAMK1 and PPP3R1 were significantly down-regulated in MR patients compared to NC. Moreover, MR patients had significantly increased mRNA levels of PPP3CB, MEF2C and PLCE1 compared to AVD patients. The atrial myocyte size of MR patients significantly exceeded that of the AVD patients and NC. Conclusions Differentially expressed genes in the “NFAT in cardiac hypertrophy” pathway may play a critical role in the atrial myocyte hypertrophy of MR patients. PMID:27907007

Emotional labor actors: a latent profile analysis of emotional labor strategies.

PubMed

Gabriel, Allison S; Daniels, Michael A; Diefendorff, James M; Greguras, Gary J

2015-05-01

Research on emotional labor focuses on how employees utilize 2 main regulation strategies-surface acting (i.e., faking one's felt emotions) and deep acting (i.e., attempting to feel required emotions)-to adhere to emotional expectations of their jobs. To date, researchers largely have considered how each strategy functions to predict outcomes in isolation. However, this variable-centered perspective ignores the possibility that there are subpopulations of employees who may differ in their combined use of surface and deep acting. To address this issue, we conducted 2 studies that examined surface acting and deep acting from a person-centered perspective. Using latent profile analysis, we identified 5 emotional labor profiles-non-actors, low actors, surface actors, deep actors, and regulators-and found that these actor profiles were distinguished by several emotional labor antecedents (positive affectivity, negative affectivity, display rules, customer orientation, and emotion demands-abilities fit) and differentially predicted employee outcomes (emotional exhaustion, job satisfaction, and felt inauthenticity). Our results reveal new insights into the nature of emotion regulation in emotional labor contexts and how different employees may characteristically use distinct combinations of emotion regulation strategies to manage their emotional expressions at work. (c) 2015 APA, all rights reserved.

Computer program for calculation of real gas turbulent boundary layers with variable edge entropy

NASA Technical Reports Server (NTRS)

Boney, L. R.

1974-01-01

A user's manual for a computer program which calculates real gas turbulent boundary layers with variable edge entropy on a blunt cone or flat plate at zero angle of attack is presented. An integral method is used. The method includes the effect of real gas in thermodynamic equilibrium and variable edge entropy. A modified Crocco enthalpy velocity relationship is used for the enthalpy profiles and an empirical correlation of the N-power law profile is used for the velocity profile. The skin-friction-coefficient expressions of Spalding and Chi and Van Driest are used in the solution of the momentum equation and in the heat-transfer predictions that use several modified forms of Reynolds analogy.

Development and Validation of a Scale to Measure an Adaptive Culture Profile Using Student Affairs Divisions in Higher Education

ERIC Educational Resources Information Center

Fowler, Tammy Lynne

2013-01-01

The landscape of higher education in the United States shifts and moves in response to environmental challenges often hard to predict or measure. A joint taskforce of the American College Personnel Association and the National Association of Student Personnel Administrators taskforce expressed the concern that no other time in history has the…

Mars Ozone Absorption Line Shapes from Infrared Heterodyne Spectra Applied to GCM-Predicted Ozone Profiles and to MEX/SPICAM Column Retrievals

NASA Technical Reports Server (NTRS)

Fast, Kelly E.; Kostiuk, T.; Annen, J.; Hewagama, T.; Delgado, J.; Livengood, T. A.; Lefevre, F.

2008-01-01

We present the application of infrared heterodyne line shapes of ozone on Mars to those produced by radiative transfer modeling of ozone profiles predicted by general circulation models (GCM), and to contemporaneous column abundances measured by Mars Express SPICAM. Ozone is an important tracer of photochemistry Mars' atmosphere, serving as an observable with which to test predictions of photochemistry-coupled GCMs. Infrared heterodyne spectroscopy at 9.5 microns with spectral resolving power >1,000,000 is the only technique that can directly measure fully-resolved line shapes of Martian ozone features from the surface of the Earth. Measurements were made with Goddard Space Flight Center's Heterodyne instrument for Planetary Wind And Composition (HIPWAC) at the NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii on February 21-24 2008 UT at Ls=35deg on or near the MEX orbital path. The HIPWAC observations were used to test GCM predictions. For example, a GCM-generated ozone profile for 60degN 112degW was scaled so that a radiative transfer calculation of its absorption line shape matched an observed HIPWAC absorption feature at the same areographic position, local time, and season. The RMS deviation of the model from the data was slightly smaller for the GCM-generated profile than for a line shape produced by a constant-with-height profile, even though the total column abundances were the same, showing potential for testing and constraining GCM ozone-profiles. The resulting ozone column abundance from matching the model to the HIPWAC line shape was 60% higher than that observed by SPICAM at the same areographic position one day earlier and 2.5 hours earlier in local time. This could be due to day-to-day, diurnal, or north polar region variability, or to measurement sensitivity to the ozone column and its distribution, and these possibilities will be explored. This work was supported by NASA's Planetary Astronomy Program.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Comprehensive circular RNA profiling reveals that circular RNA100783 is involved in chronic CD28-associated CD8(+)T cell ageing.

PubMed

Wang, Yu-Hong; Yu, Xu-Hui; Luo, Shan-Shun; Han, Hui

2015-01-01

Ageing brings about the gradual deterioration of the immune system, also known as immunosenescence. The role of non-coding circular RNA in immunosenescence is under studied. Using circular RNA microarray data, we assembled Comparison groups (C1, C2, C3 and C4) that allowed us to compare the circular RNA expression profiles between CD28(+)CD8(+) T cells and CD28(-)CD8(+) T cells isolated from healthy elderly or adult control subjects. Using a step-wise biomathematical strategy, the differentially-expressed circRNAs were identified in C1 (CD28(+)CD8(+) vs CD28(-)CD8(+)T cells in the elderly) and C4 (CD28(-)CD8(+)T cells in the elderly vs in the adult), and the commonly-expressed circRNA species from these profiles were optimized as immunosenescence biomarkers. Four overlapping upregulated circular RNAs (100550, 100783, 101328 and 102592) expressed in cross-comparison between C1 and C4 were validated using quantitative polymerase chain reaction. Of these, only circular RNA100783 exhibited significant validation. None of the down-regulated circular RNAs were expressed in the C1 and the C4 cross-comparisons. Therefore, we further predicted circular RNA100783-targeted miRNA-gene interactions using online DAVID annotation. The analysis revealed that a circular RNA100783-targeted miRNA-mRNA network may be involved in alternative splicing, the production of splice variants, and in the regulation of phosphoprotein expression. Considering the hypothesis of splicing-related biogenesis of circRNAs, we propose that circular RNA100783 may play a role in phosphoprotein-associated functions duringCD28-related CD8(+) T cell ageing. This study is the first to employ circular RNA profiling to investigate circular RNA-micro RNA interactions in ageing human CD8(+)T cell populations and the accompanying loss of CD28 expression. The overlapping expression of circular RNA100783 may represent a novel biomarker for the longitudinal tracking ofCD28-related CD8(+) T cell ageing and global immunosenescence.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

Integrated genome-wide Alu methylation and transcriptome profiling analyses reveal novel epigenetic regulatory networks associated with autism spectrum disorder.

PubMed

Saeliw, Thanit; Tangsuwansri, Chayanin; Thongkorn, Surangrat; Chonchaiya, Weerasak; Suphapeetiporn, Kanya; Mutirangura, Apiwat; Tencomnao, Tewin; Hu, Valerie W; Sarachana, Tewarit

2018-01-01

Alu elements are a group of repetitive elements that can influence gene expression through CpG residues and transcription factor binding. Altered gene expression and methylation profiles have been reported in various tissues and cell lines from individuals with autism spectrum disorder (ASD). However, the role of Alu elements in ASD remains unclear. We thus investigated whether Alu elements are associated with altered gene expression profiles in ASD. We obtained five blood-based gene expression profiles from the Gene Expression Omnibus database and human Alu-inserted gene lists from the TranspoGene database. Differentially expressed genes (DEGs) in ASD were identified from each study and overlapped with the human Alu-inserted genes. The biological functions and networks of Alu-inserted DEGs were then predicted by Ingenuity Pathway Analysis (IPA). A combined bisulfite restriction analysis of lymphoblastoid cell lines (LCLs) derived from 36 ASD and 20 sex- and age-matched unaffected individuals was performed to assess the global DNA methylation levels within Alu elements, and the Alu expression levels were determined by quantitative RT-PCR. In ASD blood or blood-derived cells, 320 Alu-inserted genes were reproducibly differentially expressed. Biological function and pathway analysis showed that these genes were significantly associated with neurodevelopmental disorders and neurological functions involved in ASD etiology. Interestingly, estrogen receptor and androgen signaling pathways implicated in the sex bias of ASD, as well as IL-6 signaling and neuroinflammation signaling pathways, were also highlighted. Alu methylation was not significantly different between the ASD and sex- and age-matched control groups. However, significantly altered Alu methylation patterns were observed in ASD cases sub-grouped based on Autism Diagnostic Interview-Revised scores compared with matched controls. Quantitative RT-PCR analysis of Alu expression also showed significant differences between ASD subgroups. Interestingly, Alu expression was correlated with methylation status in one phenotypic ASD subgroup. Alu methylation and expression were altered in LCLs from ASD subgroups. Our findings highlight the association of Alu elements with gene dysregulation in ASD blood samples and warrant further investigation. Moreover, the classification of ASD individuals into subgroups based on phenotypes may be beneficial and could provide insights into the still unknown etiology and the underlying mechanisms of ASD.

Circular RNA profile in gliomas revealed by identification tool UROBORUS.

PubMed

Song, Xiaofeng; Zhang, Naibo; Han, Ping; Moon, Byoung-San; Lai, Rose K; Wang, Kai; Lu, Wange

2016-05-19

Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play roles in biological processes. However, the expression patterns and functions of circRNAs in human diseases are not well understood. Computationally identifying circRNAs from total RNA-seq data is a primary step in studying their expression pattern and biological roles. In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected thousands of circRNAs supported by at least two read counts, followed by successful experimental validation on 24 circRNAs from the randomly selected 27 circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low expression levels in total RNA-seq without RNase R treatment. The circRNAs expression profiling revealed more than 476 circular RNAs differentially expressed in control brain tissues and gliomas. Together with parental gene expression, we found that circRNA and its parental gene have diversified expression patterns in gliomas and control brain tissues. This study establishes an efficient and sensitive approach for predicting circRNAs using total RNA-seq data. The UROBORUS pipeline can be accessed freely for non-commercial purposes at http://uroborus.openbioinformatics.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transcript expression and genetic variability analysis of caspases in breast carcinomas suggests CASP9 as the most interesting target.

PubMed

Brynychova, Veronika; Hlavac, Viktor; Ehrlichova, Marie; Vaclavikova, Radka; Nemcova-Furstova, Vlasta; Pecha, Vaclav; Trnkova, Marketa; Mrhalova, Marcela; Kodet, Roman; Vrana, David; Gatek, Jiri; Bendova, Marie; Vernerova, Zdenka; Kovar, Jan; Soucek, Pavel

2017-01-01

Apoptosis plays a critical role in cancer cell survival and tumor development. We provide a hypothesis-generating screen for further research by exploring the expression profile and genetic variability of caspases (2, 3, 7, 8, 9, and 10) in breast carcinoma patients. This study addressed isoform-specific caspase transcript expression and genetic variability in regulatory sequences of caspases 2 and 9. Gene expression profiling was performed by quantitative real-time PCR in tumor and paired non-malignant tissues of two independent groups of patients. Genetic variability was determined by high resolution melting, allelic discrimination, and sequencing analysis in tumor and peripheral blood lymphocyte DNA of the patients. CASP3 A+B and S isoforms were over-expressed in tumors of both patient groups. The CASP9 transcript was down-regulated in tumors of both groups of patients and significantly associated with expression of hormonal receptors and with the presence of rs4645978-rs2020903-rs4646034 haplotype in the CASP9 gene. Patients with a low intratumoral CASP9A/B isoform expression ratio (predicted to shift equilibrium towards anti-apoptotic isoform) subsequently treated with adjuvant chemotherapy had a significantly shorter disease-free survival than those with the high ratio (p=0.04). Inheritance of CC genotype of rs2020903 in CASP9 was associated with progesterone receptor expression in tumors (p=0.003). Genetic variability in CASP9 and expression of its splicing variants present targets for further study.

Emotion appraisal dimensions inferred from vocal expressions are consistent across cultures: a comparison between Australia and India.

PubMed

Nordström, Henrik; Laukka, Petri; Thingujam, Nutankumar S; Schubert, Emery; Elfenbein, Hillary Anger

2017-11-01

This study explored the perception of emotion appraisal dimensions on the basis of speech prosody in a cross-cultural setting. Professional actors from Australia and India vocally portrayed different emotions (anger, fear, happiness, pride, relief, sadness, serenity and shame) by enacting emotion-eliciting situations. In a balanced design, participants from Australia and India then inferred aspects of the emotion-eliciting situation from the vocal expressions, described in terms of appraisal dimensions (novelty, intrinsic pleasantness, goal conduciveness, urgency, power and norm compatibility). Bayesian analyses showed that the perceived appraisal profiles for the vocally expressed emotions were generally consistent with predictions based on appraisal theories. Few group differences emerged, which suggests that the perceived appraisal profiles are largely universal. However, some differences between Australian and Indian participants were also evident, mainly for ratings of norm compatibility. The appraisal ratings were further correlated with a variety of acoustic measures in exploratory analyses, and inspection of the acoustic profiles suggested similarity across groups. In summary, results showed that listeners may infer several aspects of emotion-eliciting situations from the non-verbal aspects of a speaker's voice. These appraisal inferences also seem to be relatively independent of the cultural background of the listener and the speaker.

Emotion appraisal dimensions inferred from vocal expressions are consistent across cultures: a comparison between Australia and India

PubMed Central

Thingujam, Nutankumar S.; Schubert, Emery

2017-01-01

This study explored the perception of emotion appraisal dimensions on the basis of speech prosody in a cross-cultural setting. Professional actors from Australia and India vocally portrayed different emotions (anger, fear, happiness, pride, relief, sadness, serenity and shame) by enacting emotion-eliciting situations. In a balanced design, participants from Australia and India then inferred aspects of the emotion-eliciting situation from the vocal expressions, described in terms of appraisal dimensions (novelty, intrinsic pleasantness, goal conduciveness, urgency, power and norm compatibility). Bayesian analyses showed that the perceived appraisal profiles for the vocally expressed emotions were generally consistent with predictions based on appraisal theories. Few group differences emerged, which suggests that the perceived appraisal profiles are largely universal. However, some differences between Australian and Indian participants were also evident, mainly for ratings of norm compatibility. The appraisal ratings were further correlated with a variety of acoustic measures in exploratory analyses, and inspection of the acoustic profiles suggested similarity across groups. In summary, results showed that listeners may infer several aspects of emotion-eliciting situations from the non-verbal aspects of a speaker's voice. These appraisal inferences also seem to be relatively independent of the cultural background of the listener and the speaker. PMID:29291085

Multi-walled carbon nanotube-induced gene signatures in the mouse lung: potential predictive value for human lung cancer risk and prognosis

PubMed Central

Guo, Nancy L; Wan, Ying-Wooi; Denvir, James; Porter, Dale W; Pacurari, Maricica; Wolfarth, Michael G; Castranova, Vincent; Qian, Yong

2012-01-01

Concerns over the potential for multi-walled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n=160) exposed to 0, 10, 20, 40, or 80 µg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 days post-exposure. By using pairwise-Statistical Analysis of Microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5 fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at day 56 post-exposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at day 56 post-exposure to 10 µg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n=256) and test set (n=186). Furthermore, both gene signatures were associated with human lung cancer risk (n=164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace. PMID:22891886

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

PubMed Central

Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

2012-01-01

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

Digital gene expression analysis of the zebra finch genome

PubMed Central

2010-01-01

Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata) with special emphasis on the genes of the major histocompatibility complex (MHC). Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint) than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression patterns in other vertebrates. PMID:20359325

Epigenetic Alteration by DNA Methylation of ESR1, MYOD1 and hTERT Gene Promoters is Useful for Prediction of Response in Patients of Locally Advanced Invasive Cervical Carcinoma Treated by Chemoradiation.

PubMed

Sood, S; Patel, F D; Ghosh, S; Arora, A; Dhaliwal, L K; Srinivasan, R

2015-12-01

Locally advanced invasive cervical cancer [International Federation of Gynecology and Obstetrics (FIGO) IIB/III] is treated by chemoradiation. The response to treatment is variable within a given FIGO stage. Therefore, the aim of the present study was to evaluate the gene promoter methylation profile and corresponding transcript expression of a panel of six genes to identify genes which could predict the response of patients treated by chemoradiation. In total, 100 patients with invasive cervical cancer in FIGO stage IIB/III who underwent chemoradiation treatment were evaluated. Ten patients developed systemic metastases during therapy and were excluded. On the basis of patient follow-up, 69 patients were chemoradiation-sensitive, whereas 21 were chemoradiation-resistant. Gene promoter methylation and gene expression was determined by TaqMan assay and quantitative real-time PCR, respectively, in tissue samples. The methylation frequency of ESR1, BRCA1, RASSF1A, MLH1, MYOD1 and hTERT genes ranged from 40 to 70%. Univariate and hierarchical cluster analysis revealed that gene promoter methylation of MYOD1, ESR1 and hTERT could predict for chemoradiation response. A pattern of unmethylated MYOD1, unmethylated ESR1 and methylated hTERT promoter as well as lower ESR1 transcript levels predicted for chemoradiation resistance. Methylation profiling of a panel of three genes that includes MYOD1, ESR1 and hTERT may be useful to predict the response of invasive cervical carcinoma patients treated with standard chemoradiation therapy. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Genome-wide identification of translationally inhibited and degraded miR-155 targets using RNA-interacting protein-IP

PubMed Central

Meier, Jan; Hovestadt, Volker; Zapatka, Marc; Pscherer, Armin; Lichter, Peter; Seiffert, Martina

2013-01-01

MicroRNAs (miRNAs) are single-stranded, small, non-coding RNAs, which fine-tune protein expression by degrading and/or translationally inhibiting mRNAs. Manipulation of miRNA expression in animal models frequently results in severe phenotypes indicating their relevance in controlling cellular functions, most likely by interacting with multiple targets. To better understand the effect of miRNA activities, genome-wide analysis of their targets are required. MicroRNA profiling as well as transcriptome analysis upon enforced miRNA expression were frequently used to investigate their relevance. However, these approaches often fail to identify relevant miRNAs targets. Therefore, we tested the precision of RNA-interacting protein immunoprecipitation (RIP) using AGO2-specific antibodies, a core component of the “RNA-induced silencing complex” (RISC), followed by RNA sequencing (Seq) in a defined cellular system, the HEK293T cells with stable, ectopic expression of miR-155. Thereby, we identified 100 AGO2-associated mRNAs in miR-155-expressing cells, of which 67 were in silico predicted miR-155 target genes. An integrated analysis of the corresponding expression profiles indicated that these targets were either regulated by mRNA decay or by translational repression. Of the identified miR-155 targets, 17 were related to cell cycle control, suggesting their involvement in the observed increase in cell proliferation of HEK293T cells upon miR-155 expression. Additional, secondary changes within the gene expression profile were detected and might contribute to this phenotype as well. Interestingly, by analyzing RIP-Seq data of HEK-293T cells and two B-cell lines we identified a recurrent disproportional enrichment of several miRNAs, including miR-155 and miRNAs of the miR-17-92 cluster, in the AGO2-associated precipitates, suggesting discrepancies in miRNA expression and activity. PMID:23673373

Resolving Heart Regeneration by Replacement Histone Profiling.

PubMed

Goldman, Joseph Aaron; Kuzu, Guray; Lee, Nutishia; Karasik, Jaclyn; Gemberling, Matthew; Foglia, Matthew J; Karra, Ravi; Dickson, Amy L; Sun, Fei; Tolstorukov, Michael Y; Poss, Kenneth D

2017-02-27

Chromatin regulation is a principal mechanism governing animal development, yet it is unclear to what extent structural changes in chromatin underlie tissue regeneration. Non-mammalian vertebrates such as zebrafish activate cardiomyocyte (CM) division after tissue damage to regenerate lost heart muscle. Here, we generated transgenic zebrafish expressing a biotinylatable H3.3 histone variant in CMs and derived cell-type-specific profiles of histone replacement. We identified an emerging program of putative enhancers that revise H3.3 occupancy during regeneration, overlaid upon a genome-wide reduction of H3.3 from promoters. In transgenic reporter lines, H3.3-enriched elements directed gene expression in subpopulations of CMs. Other elements increased H3.3 enrichment and displayed enhancer activity in settings of injury- and/or Neuregulin1-elicited CM proliferation. Dozens of consensus sequence motifs containing predicted transcription factor binding sites were enriched in genomic regions with regeneration-responsive H3.3 occupancy. Thus, cell-type-specific regulatory programs of tissue regeneration can be revealed by genome-wide H3.3 profiling. Copyright © 2017 Elsevier Inc. All rights reserved.

Feasibility of implementing molecular-guided therapy for the treatment of patients with relapsed or refractory neuroblastoma

PubMed Central

Saulnier Sholler, Giselle L; Bond, Jeffrey P; Bergendahl, Genevieve; Dutta, Akshita; Dragon, Julie; Neville, Kathleen; Ferguson, William; Roberts, William; Eslin, Don; Kraveka, Jacqueline; Kaplan, Joel; Mitchell, Deanna; Parikh, Nehal; Merchant, Melinda; Ashikaga, Takamaru; Hanna, Gina; Lescault, Pamela Jean; Siniard, Ashley; Corneveaux, Jason; Huentelman, Matthew; Trent, Jeffrey

2015-01-01

The primary objective of the study was to evaluate the feasibility and safety of a process which would utilize genome-wide expression data from tumor biopsies to support individualized treatment decisions. Current treatment options for recurrent neuroblastoma are limited and ineffective, with a survival rate of <10%. Molecular profiling may provide data which will enable the practitioner to select the most appropriate therapeutic option for individual patients, thus improving outcomes. Sixteen patients with neuroblastoma were enrolled of which fourteen were eligible for this study. Feasibility was defined as completion of tumor biopsy, pathological evaluation, RNA quality control, gene expression profiling, bioinformatics analysis, generation of a drug prediction report, molecular tumor board yielding a treatment plan, independent medical monitor review, and treatment initiation within a 21 day period. All eligible biopsies passed histopathology and RNA quality control. Expression profiling by microarray and RNA sequencing were mutually validated. The average time from biopsy to report generation was 5.9 days and from biopsy to initiation of treatment was 12.4 days. No serious adverse events were observed and all adverse events were expected. Clinical benefit was seen in 64% of patients as stabilization of disease for at least one cycle of therapy or partial response. The overall response rate was 7% and the progression free survival was 59 days. This study demonstrates the feasibility and safety of performing real-time genomic profiling to guide treatment decision making for pediatric neuroblastoma patients. PMID:25720842

Data-Driven prioritisation of antibody-drug conjugate targets in head and neck squamous cell carcinoma.

PubMed

Hanemaaijer, Saskia H; van Gijn, Stephanie E; Oosting, Sjoukje F; Plaat, Boudewijn E C; Moek, Kirsten L; Schuuring, Ed M; van der Laan, Bernard F A M; Roodenburg, Jan L N; van Vugt, Marcel A T M; van der Vegt, Bert; Fehrmann, Rudolf S N

2018-05-01

For patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) palliative treatment options that improve overall survival are limited. The prognosis in this group remains poor and there is an unmet need for new therapeutic options. An emerging class of therapeutics, targeting tumor-specific antigens, are antibodies bound to a cytotoxic agent, known as antibody-drug conjugates (ADCs). The aim of this study was to prioritize ADC targets in HNSCC. With a systematic search, we identified 55 different ADC targets currently targeted by registered ADCs and ADCs under clinical evaluation. For these 55 ADC targets, protein overexpression was predicted in a dataset containing 344 HNSCC mRNA expression profiles by using a method called functional genomic mRNA profiling. The ADC target with the highest predicted overexpression was validated by performing immunohistochemistry (IHC) on an independent tissue microarray containing 414 HNSCC tumors. The predicted top 5 overexpressed ADC targets in HNSCC were: glycoprotein nmb (GPNMB), SLIT and NTRK-like family member 6, epidermal growth factor receptor, CD74 and CD44. IHC validation showed combined cytoplasmic and membranous GPNMB protein expression in 92.0% of the cases. Strong expression was seen in 65.9% of the cases. In addition, 86.5% and 67.7% of cases showed ≥5% and >25% GPNMB positive tumor cells, respectively. This study provides a data-driven prioritization of ADCs targets that will facilitate clinicians and drug developers in deciding which ADC should be taken for further clinical evaluation in HNSCC. This might help to improve disease outcome of HNSCC patients. Copyright © 2018 Elsevier Ltd. All rights reserved.

Molecular subtypes of osteosarcoma identified by reducing tumor heterogeneity through an interspecies comparative approach

PubMed Central

Scott, Milcah C.; Sarver, Aaron L.; Gavin, Katherine J.; Thayanithy, Venugopal; Getzy, David M.; Newman, Robert A.; Cutter, Gary R.; Lindblad-Toh, Kerstin; Kisseberth, William C.; Hunter, Lawrence E.; Subramanian, Subbaya; Breen, Matthew; Modiano, Jaime F.

2011-01-01

The heterogeneous and chaotic nature of osteosarcoma has confounded accurate molecular classification, prognosis, and prediction for this tumor. The occurrence of spontaneous osteosarcoma is largely confined to humans and dogs. While the clinical features are remarkably similar in both species, the organization of dogs into defined breeds provides a more homogeneous genetic background that may increase the likelihood to uncover molecular subtypes for this complex disease. We thus hypothesized that molecular profiles derived from canine osteosarcoma would aid in molecular subclassification of this disease when applied to humans. To test the hypothesis, we performed genome wide gene expression profiling in a cohort of dogs with osteosarcoma, primarily from high-risk breeds. To further reduce inter-sample heterogeneity, we assessed tumor-intrinsic properties through use of an extensive panel of osteosarcoma-derived cell lines. We observed strong differential gene expression that segregated samples into two groups with differential survival probabilities. Groupings were characterized by the inversely correlated expression of genes associated with G2/M transition and DNA damage checkpoint and microenvironment-interaction categories. This signature was preserved in data from whole tumor samples of three independent dog osteosarcoma cohorts, with stratification into the two expected groups. Significantly, this restricted signature partially overlapped a previously defined, predictive signature for soft tissue sarcomas, and it unmasked orthologous molecular subtypes and their corresponding natural histories in five independent data sets from human patients with osteosarcoma. Our results indicate that the narrower genetic diversity of dogs can be utilized to group complex human osteosarcoma into biologically and clinically relevant molecular subtypes. This in turn may enhance prognosis and prediction, and identify relevant therapeutic targets. PMID:21621658

A gene expression signature associated with survival in metastatic melanoma

PubMed Central

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

Indications for distinct pathogenic mechanisms of asbestos and silica through gene expression profiling of the response of lung epithelial cells

PubMed Central

Perkins, Timothy N.; Peeters, Paul M.; Shukla, Arti; Arijs, Ingrid; Dragon, Julie; Wouters, Emiel F.M.; Reynaert, Niki L.; Mossman, Brooke T.

2015-01-01

Occupational and environmental exposures to airborne asbestos and silica are associated with the development of lung fibrosis in the forms of asbestosis and silicosis, respectively. However, both diseases display distinct pathologic presentations, likely associated with differences in gene expression induced by different mineral structures, composition and bio-persistent properties. We hypothesized that effects of mineral exposure in the airway epithelium may dictate deviating molecular events that may explain the different pathologies of asbestosis versus silicosis. Using robust gene expression-profiling in conjunction with in-depth pathway analysis, we assessed early (24 h) alterations in gene expression associated with crocidolite asbestos or cristobalite silica exposures in primary human bronchial epithelial cells (NHBEs). Observations were confirmed in an immortalized line (BEAS-2B) by QRT-PCR and protein assays. Utilization of overall gene expression, unsupervised hierarchical cluster analysis and integrated pathway analysis revealed gene alterations that were common to both minerals or unique to either mineral. Our findings reveal that both minerals had potent effects on genes governing cell adhesion/migration, inflammation, and cellular stress, key features of fibrosis. Asbestos exposure was most specifically associated with aberrant cell proliferation and carcinogenesis, whereas silica exposure was highly associated with additional inflammatory responses, as well as pattern recognition, and fibrogenesis. These findings illustrate the use of gene-profiling as a means to determine early molecular events that may dictate pathological processes induced by exogenous cellular insults. In addition, it is a useful approach for predicting the pathogenicity of potentially harmful materials. PMID:25351596

Differential Expression of In Vivo and In Vitro Protein Profile of Outer Membrane of Acidovorax avenae Subsp. avenae

PubMed Central

Qiu, Hui; Li, Bin; Jabeen, Amara; Li, Liping; Liu, He; Kube, Michael; Xie, Guanlin; Wang, Yanli; Sun, Guochang

2012-01-01

Outer membrane (OM) proteins play a significant role in bacterial pathogenesis. In this work, we examined and compared the expression of the OM proteins of the rice pathogen Acidovorax avenae subsp. avenae strain RS-1, a Gram-negative bacterium, both in an in vitro culture medium and in vivo rice plants. Global proteomic profiling of A. avenae subsp. avenae strain RS-1 comparing in vivo and in vitro conditions revealed the differential expression of proteins affecting the survival and pathogenicity of the rice pathogen in host plants. The shotgun proteomics analysis of OM proteins resulted in the identification of 97 proteins in vitro and 62 proteins in vivo by mass spectrometry. Among these OM proteins, there is a high number of porins, TonB-dependent receptors, lipoproteins of the NodT family, ABC transporters, flagellins, and proteins of unknown function expressed under both conditions. However, the major proteins such as phospholipase and OmpA domain containing proteins were expressed in vitro, while the proteins such as the surface anchored protein F, ATP-dependent Clp protease, OmpA and MotB domain containing proteins were expressed in vivo. This may indicate that these in vivo OM proteins have roles in the pathogenicity of A. avenae subsp. avenae strain RS-1. In addition, the LC-MS/MS identification of OmpA and MotB validated the in silico prediction of the existance of Type VI secretion system core components. To the best of our knowledge, this is the first study to reveal the in vitro and in vivo protein profiles, in combination with LC-MS/MS mass spectra, in silico OM proteome and in silico genome wide analysis, of pathogenicity or plant host required proteins of a plant pathogenic bacterium. PMID:23166741

Transcriptomics analysis of lungs and peripheral blood of crystalline silica-exposed rats

PubMed Central

Sellamuthu, Rajendran; Umbright, Christina; Roberts, Jenny R.; Chapman, Rebecca; Young, Shih-Houng; Richardson, Diana; Cumpston, Jared; McKinney, Walter; Chen, Bean T.; Frazer, David; Li, Shengqiao; Kashon, Michael; Joseph, Pius

2015-01-01

Minimally invasive approaches to detect/predict target organ toxicity have significant practical applications in occupational toxicology. The potential application of peripheral blood transcriptomics as a practical approach to study the mechanisms of silica-induced pulmonary toxicity was investigated. Rats were exposed by inhalation to crystalline silica (15 mg/m3, 6 h/day, 5 days) and pulmonary toxicity and global gene expression profiles of lungs and peripheral blood were determined at 32 weeks following termination of exposure. A significant elevation in bronchoalveolar lavage fluid lactate dehydrogenase activity and moderate histological changes in the lungs, including type II pneumocyte hyperplasia and fibrosis, indicated pulmonary toxicity in the rats. Similarly, significant infiltration of neutrophils and elevated monocyte chemotactic protein-1 levels in the lungs showed pulmonary inflammation in the rats. Microarray analysis of global gene expression profiles identified significant differential expression [>1.5-fold change and false discovery rate (FDR) p < 0.01] of 520 and 537 genes, respectively, in the lungs and blood of the exposed rats. Bioinformatics analysis of the differentially expressed genes demonstrated significant similarity in the biological processes, molecular networks, and canonical pathways enriched by silica exposure in the lungs and blood of the rats. Several genes involved in functions relevant to silica-induced pulmonary toxicity such as inflammation, respiratory diseases, cancer, cellular movement, fibrosis, etc, were found significantly differentially expressed in the lungs and blood of the silica-exposed rats. The results of this study suggested the potential application of peripheral blood gene expression profiling as a toxicologically relevant and minimally invasive surrogate approach to study the mechanisms underlying silica-induced pulmonary toxicity. PMID:22861000

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

PubMed

Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

2018-04-01

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification.

PubMed

Ferris, Laura K; Farberg, Aaron S; Middlebrook, Brooke; Johnson, Clare E; Lassen, Natalie; Oelschlager, Kristen M; Maetzold, Derek J; Cook, Robert W; Rigel, Darrell S; Gerami, Pedram

2017-05-01

A significant proportion of patients with American Joint Committee on Cancer (AJCC)-defined early-stage cutaneous melanoma have disease recurrence and die. A 31-gene expression profile (GEP) that accurately assesses metastatic risk associated with primary cutaneous melanomas has been described. We sought to compare accuracy of the GEP in combination with risk determined using the web-based AJCC Individualized Melanoma Patient Outcome Prediction Tool. GEP results from 205 stage I/II cutaneous melanomas with sufficient clinical data for prognostication using the AJCC tool were classified as low (class 1) or high (class 2) risk. Two 5-year overall survival cutoffs (AJCC 79% and 68%), reflecting survival for patients with stage IIA or IIB disease, respectively, were assigned for binary AJCC risk. Cox univariate analysis revealed significant risk classification of distant metastasis-free and overall survival (hazard ratio range 3.2-9.4, P < .001) for both tools. In all, 43 (21%) cases had discordant GEP and AJCC classification (using 79% cutoff). Eleven of 13 (85%) deaths in that group were predicted as high risk by GEP but low risk by AJCC. Specimens reflect tertiary care center referrals; more effective therapies have been approved for clinical use after accrual. The GEP provides valuable prognostic information and improves identification of high-risk melanomas when used together with the AJCC online prediction tool. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

BICD1 expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas

PubMed Central

Huang, Shang-Pen; Chang, Yu-Chan; Low, Qie Hua; Wu, Alexander T.H.; Chen, Chi-Long; Lin, Yuan-Feng; Hsiao, Michael

2017-01-01

There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by in silico meta-analysis of the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Our results demonstrated that BICD1 expression could predict both prognosis and response to therapy in GBM patients. First, high BICD1 expression was correlated with poor prognosis in the TCGA GBM cohort (n=523) and in the CGGA glioma cohort (n=220). Second, high BICD1 expression predicted poor outcome in patients with TMZ treatment (n=301) and radiation therapy (n=405). Third, multivariable Cox regression analysis confirmed BICD1 expression as an independent factor affecting the prognosis and therapeutic response of TMZ and radiation in GBM patients. Additionally, age, MGMT and BICD1 expression were combinedly utilized to stratify GBM patients into more distinct risk groups, which may provide better outcome assessment. Finally, we observed a strong correlation between BICD1 expression and epithelial-mesenchymal transition (EMT) in GBMs, and proposed a possible mechanism of BICD1-associated survival or therapeutic resistance in GBMs accordingly. In conclusion, our study suggests that high BICD1 expression may result in worse prognosis and could be a predictor of poor response to TMZ and radiation therapies in GBM patients. PMID:29371945

Metabolic Disturbances in Adult-Onset Still's Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis.

PubMed

Chen, Der-Yuan; Chen, Yi-Ming; Chien, Han-Ju; Lin, Chi-Chen; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting; Lai, Chien-Chen

2016-01-01

Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still's disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis.

Exposure of Lactating Dairy Cows to Acute Pre-Ovulatory Heat Stress Affects Granulosa Cell-Specific Gene Expression Profiles in Dominant Follicles

PubMed Central

Vanselow, Jens; Vernunft, Andreas; Koczan, Dirk; Spitschak, Marion; Kuhla, Björn

2016-01-01

High environmental temperatures induce detrimental effects on various reproductive processes in cattle. According to the predicted global warming the number of days with unfavorable ambient temperatures will further increase. The objective of this study was to investigate effects of acute heat stress during the late pre-ovulatory phase on morphological, physiological and molecular parameters of dominant follicles in cycling cows during lactation. Eight German Holstein cows in established lactation were exposed to heat stress (28°C) or thermoneutral conditions (15°C) with pair-feeding for four days. After hormonal heat induction growth of the respective dominant follicles was monitored by ultrasonography for two days, then an ovulatory GnRH dose was given and follicular steroid hormones and granulosa cell-specific gene expression profiles were determined 23 hrs thereafter. The data showed that the pre-ovulatory growth of dominant follicles and the estradiol, but not the progesterone concentrations tended to be slightly affected. mRNA microarray and hierarchical cluster analysis revealed distinct expression profiles in granulosa cells derived from heat stressed compared to pair-fed animals. Among the 255 affected genes heatstress-, stress- or apoptosis associated genes were not present. But instead, we found up-regulation of genes essentially involved in G-protein coupled signaling pathways, extracellular matrix composition, and several members of the solute carrier family as well as up-regulation of FST encoding follistatin. In summary, the data of the present study show that acute pre-ovulatory heat stress can specifically alter gene expression profiles in granulosa cells, however without inducing stress related genes and pathways and suggestively can impair follicular growth due to affecting the activin-inhibin-follistatin system. PMID:27532452

Exposure of Lactating Dairy Cows to Acute Pre-Ovulatory Heat Stress Affects Granulosa Cell-Specific Gene Expression Profiles in Dominant Follicles.

PubMed

Vanselow, Jens; Vernunft, Andreas; Koczan, Dirk; Spitschak, Marion; Kuhla, Björn

2016-01-01

High environmental temperatures induce detrimental effects on various reproductive processes in cattle. According to the predicted global warming the number of days with unfavorable ambient temperatures will further increase. The objective of this study was to investigate effects of acute heat stress during the late pre-ovulatory phase on morphological, physiological and molecular parameters of dominant follicles in cycling cows during lactation. Eight German Holstein cows in established lactation were exposed to heat stress (28°C) or thermoneutral conditions (15°C) with pair-feeding for four days. After hormonal heat induction growth of the respective dominant follicles was monitored by ultrasonography for two days, then an ovulatory GnRH dose was given and follicular steroid hormones and granulosa cell-specific gene expression profiles were determined 23 hrs thereafter. The data showed that the pre-ovulatory growth of dominant follicles and the estradiol, but not the progesterone concentrations tended to be slightly affected. mRNA microarray and hierarchical cluster analysis revealed distinct expression profiles in granulosa cells derived from heat stressed compared to pair-fed animals. Among the 255 affected genes heatstress-, stress- or apoptosis associated genes were not present. But instead, we found up-regulation of genes essentially involved in G-protein coupled signaling pathways, extracellular matrix composition, and several members of the solute carrier family as well as up-regulation of FST encoding follistatin. In summary, the data of the present study show that acute pre-ovulatory heat stress can specifically alter gene expression profiles in granulosa cells, however without inducing stress related genes and pathways and suggestively can impair follicular growth due to affecting the activin-inhibin-follistatin system.

Altered expression of four miRNA (miR-1238-3p, miR-202-3p, miR-630 and miR-766-3p) and their potential targets in peripheral blood from vitiligo patients.

PubMed

Shang, Zhiwei; Li, Hongwen

2017-10-01

Vitiligo is an acquired skin disease with pigmentary disorder. Autoimmune destruction of melanocytes is thought to be major factor in the etiology of vitiligo. miRNA-based regulators of gene expression have been reported to play crucial roles in autoimmune disease. Therefore, we attempt to profile the miRNA expressions and predict their potential targets, assessing the biological functions of differentially expressed miRNA. Total RNA was extracted from peripheral blood of vitiligo (experimental group, n = 5) and non-vitiligo (control group, n = 5) age-matched patients. Samples were hybridized to a miRNA array. Box, scatter and principal component analysis plots were performed, followed by unsupervised hierarchical clustering analysis to classify the samples. Quantitative reverse transcription polymerase chain reaction (RT-PCR) was conducted for validation of microarray data. Three different databases, TargetScan, PITA and microRNA.org, were used to predict the potential target genes. Gene ontology (GO) annotation and pathway analysis were performed to assess the potential functions of predicted genes of identified miRNA. A total of 100 (29 upregulated and 71 downregulated) miRNA were filtered by volcano plot analysis. Four miRNA were validated by quantitative RT-PCR as significantly downregulated in the vitiligo group. The functions of predicted target genes associated with differentially expressed miRNA were assessed by GO analysis, showing that the GO term with most significantly enriched target genes was axon guidance, and that the axon guidance pathway was most significantly correlated with these miRNA. In conclusion, we identified four downregulated miRNA in vitiligo and assessed the potential functions of target genes related to these differentially expressed miRNA. © 2017 Japanese Dermatological Association.

Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model.

PubMed

Aryankalayil, Molykutty J; Chopra, Sunita; Makinde, Adeola; Eke, Iris; Levin, Joel; Shankavaram, Uma; MacMillan, Laurel; Vanpouille-Box, Claire; Demaria, Sandra; Coleman, C Norman

2018-06-19

Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. Mice were whole body irradiated with X-rays (2 Gy-15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Gene Expression Profile Analysis as a Prognostic Indicator of Normal Tissue Response to Simulated Space Radiations

NASA Technical Reports Server (NTRS)

Story, Michael; Stivers, David N.

2004-01-01

This project was funded as a pilot project to determine the feasibility of using gene expression profiles to characterize the response of human cells to exposure to particulate radiations such as those encountered in the spaceflight environment. We proposed to use microarray technology to examine the gene expression patterns of a bank of well-characterized human fibroblast cell cultures. These fibroblast cultures were derived from breast or head and neck cancer patients who exhibited normal, minimal, or severe normal tissue reactions following low LET radiation exposure via radiotherapy. Furthermore, determination of SF2 values from fibroblasts cultured from these individuals were predictive of risk for severe late reactions. We hypothesized that by determining the expression of thousands of genes we could identify gene expression patterns that reflect how normal tissues respond to high Z and energy (HZE) particles, that is, that there are molecular signatures for HZE exposures. We also hypothesized that individuals who are intrinsically radiosensitive may elicit a unique response. Because this was funded as a pilot project we focused our initial studies on logistics and appropriate experimental design, and then to test our hypothesis that there is a unique molecular response to specific particles, in this case C and Fe, for primary human skin fibroblasts.

Microarray Analysis of Differential Gene Expression Profile Between Human Fetal and Adult Heart.

PubMed

Geng, Zhimin; Wang, Jue; Pan, Lulu; Li, Ming; Zhang, Jitai; Cai, Xueli; Chu, Maoping

2017-04-01

Although many changes have been discovered during heart maturation, the genetic mechanisms involved in the changes between immature and mature myocardium have only been partially elucidated. Here, gene expression profile changed between the human fetal and adult heart was characterized. A human microarray was applied to define the gene expression signatures of the fetal (13-17 weeks of gestation, n = 4) and adult hearts (30-40 years old, n = 4). Gene ontology analyses, pathway analyses, gene set enrichment analyses, and signal transduction network were performed to predict the function of the differentially expressed genes. Ten mRNAs were confirmed by quantificational real-time polymerase chain reaction. 5547 mRNAs were found to be significantly differentially expressed. "Cell cycle" was the most enriched pathway in the down-regulated genes. EFGR, IGF1R, and ITGB1 play a central role in the regulation of heart development. EGFR, IGF1R, and FGFR2 were the core genes regulating cardiac cell proliferation. The quantificational real-time polymerase chain reaction results were concordant with the microarray data. Our data identified the transcriptional regulation of heart development in the second trimester and the potential regulators that play a prominent role in the regulation of heart development and cardiac cells proliferation.

Kidney Transplant Rejection and Tissue Injury by Gene Profiling of Biopsies and Peripheral Blood Lymphocytes

PubMed Central

Flechner, Stuart M.; Kurian, Sunil M.; Head, Steven R.; Sharp, Starlette M.; Whisenant, Thomas C.; Zhang, Jie; Chismar, Jeffrey D.; Horvath, Steve; Mondala, Tony; Gilmartin, Timothy; Cook, Daniel J.; Kay, Steven A.; Walker, John R.; Salomon, Daniel R.

2007-01-01

A major challenge for kidney transplantation is balancing the need for immunosuppression to prevent rejection, while minimizing drug-induced toxicities. We used DNA microarrays (HG-U95Av2 GeneChips, Affymetrix) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients including normal donor kidneys, well-functioning transplants without rejection, kidneys undergoing acute rejection, and transplants with renal dysfunction without rejection. We developed a data analysis schema based on expression signal determination, class comparison and prediction, hierarchical clustering, statistical power analysis and real-time quantitative PCR validation. We identified distinct gene expression signatures for both biopsies and PBLs that correlated significantly with each of the different classes of transplant patients. This is the most complete report to date using commercial arrays to identify unique expression signatures in transplant biopsies distinguishing acute rejection, acute dysfunction without rejection and well-functioning transplants with no rejection history. We demonstrate for the first time the successful application of high density DNA chip analysis of PBL as a diagnostic tool for transplantation. The significance of these results, if validated in a multicenter prospective trial, would be the establishment of a metric based on gene expression signatures for monitoring the immune status and immunosuppression of transplanted patients. PMID:15307835

Psychoacoustic cues to emotion in speech prosody and music.

PubMed

Coutinho, Eduardo; Dibben, Nicola

2013-01-01

There is strong evidence of shared acoustic profiles common to the expression of emotions in music and speech, yet relatively limited understanding of the specific psychoacoustic features involved. This study combined a controlled experiment and computational modelling to investigate the perceptual codes associated with the expression of emotion in the acoustic domain. The empirical stage of the study provided continuous human ratings of emotions perceived in excerpts of film music and natural speech samples. The computational stage created a computer model that retrieves the relevant information from the acoustic stimuli and makes predictions about the emotional expressiveness of speech and music close to the responses of human subjects. We show that a significant part of the listeners' second-by-second reported emotions to music and speech prosody can be predicted from a set of seven psychoacoustic features: loudness, tempo/speech rate, melody/prosody contour, spectral centroid, spectral flux, sharpness, and roughness. The implications of these results are discussed in the context of cross-modal similarities in the communication of emotion in the acoustic domain.

A detailed gene expression study of the Miscanthus genus reveals changes in the transcriptome associated with the rejuvenation of spring rhizomes.

PubMed

Barling, Adam; Swaminathan, Kankshita; Mitros, Therese; James, Brandon T; Morris, Juliette; Ngamboma, Ornella; Hall, Megan C; Kirkpatrick, Jessica; Alabady, Magdy; Spence, Ashley K; Hudson, Matthew E; Rokhsar, Daniel S; Moose, Stephen P

2013-12-09

The Miscanthus genus of perennial C4 grasses contains promising biofuel crops for temperate climates. However, few genomic resources exist for Miscanthus, which limits understanding of its interesting biology and future genetic improvement. A comprehensive catalog of expressed sequences were generated from a variety of Miscanthus species and tissue types, with an emphasis on characterizing gene expression changes in spring compared to fall rhizomes. Illumina short read sequencing technology was used to produce transcriptome sequences from different tissues and organs during distinct developmental stages for multiple Miscanthus species, including Miscanthus sinensis, Miscanthus sacchariflorus, and their interspecific hybrid Miscanthus × giganteus. More than fifty billion base-pairs of Miscanthus transcript sequence were produced. Overall, 26,230 Sorghum gene models (i.e., ~ 96% of predicted Sorghum genes) had at least five Miscanthus reads mapped to them, suggesting that a large portion of the Miscanthus transcriptome is represented in this dataset. The Miscanthus × giganteus data was used to identify genes preferentially expressed in a single tissue, such as the spring rhizome, using Sorghum bicolor as a reference. Quantitative real-time PCR was used to verify examples of preferential expression predicted via RNA-Seq. Contiguous consensus transcript sequences were assembled for each species and annotated using InterProScan. Sequences from the assembled transcriptome were used to amplify genomic segments from a doubled haploid Miscanthus sinensis and from Miscanthus × giganteus to further disentangle the allelic and paralogous variations in genes. This large expressed sequence tag collection creates a valuable resource for the study of Miscanthus biology by providing detailed gene sequence information and tissue preferred expression patterns. We have successfully generated a database of transcriptome assemblies and demonstrated its use in the study of genes of interest. Analysis of gene expression profiles revealed biological pathways that exhibit altered regulation in spring compared to fall rhizomes, which are consistent with their different physiological functions. The expression profiles of the subterranean rhizome provides a better understanding of the biological activities of the underground stem structures that are essentials for perenniality and the storage or remobilization of carbon and nutrient resources.

Antihistamines modulate the integrin signaling pathway in h9c2 rat cardiomyocytes: Possible association with cardiotoxicity.

PubMed

Yun, J S; Kim, S Y

2015-08-01

The identification of biomarkers for toxicity prediction is crucial for drug development and safety evaluation. The selective and specific biomarkers for antihistamines-induced cardiotoxicity is not well identified yet. In order to evaluate the mechanism of the life-threatening effects caused by antihistamines, we used DNA microarrays to analyze genomic profiles in H9C2 rat cardiomyocytes that were treated with antihistamines. The gene expression profiles from drug-treated cells revealed changes in the integrin signaling pathway, suggesting that cardiac arrhythmias induced by antihistamine treatment may be mediated by changes in integrin-mediated signaling. It has been reported that integrin plays a role in QT prolongation that may induce cardiac arrhythmia. These results indicate that the integrin-mediated signaling pathway induced by antihistamines is involved in various biological mechanisms that lead to cardiac QT prolongation. Therefore, we suggest that genomic profiling of antihistamine-treated cardiomyocytes has the potential to reveal the mechanism of adverse drug reactions, and this signal pathway is applicable to prediction of in vitro cardiotoxicity induced by antihistamines as a biomarker candidate. © The Author(s) 2014.

Expression profiles of urbilaterian genes uniquely shared between honey bee and vertebrates

PubMed Central

Matsui, Toshiaki; Yamamoto, Toshiyuki; Wyder, Stefan; Zdobnov, Evgeny M; Kadowaki, Tatsuhiko

2009-01-01

Background Large-scale comparison of metazoan genomes has revealed that a significant fraction of genes of the last common ancestor of Bilateria (Urbilateria) is lost in each animal lineage. This event could be one of the underlying mechanisms involved in generating metazoan diversity. However, the present functions of these ancient genes have not been addressed extensively. To understand the functions and evolutionary mechanisms of such ancient Urbilaterian genes, we carried out comprehensive expression profile analysis of genes shared between vertebrates and honey bees but not with the other sequenced ecdysozoan genomes (honey bee-vertebrate specific, HVS genes) as a model. Results We identified 30 honey bee and 55 mouse HVS genes. Many HVS genes exhibited tissue-selective expression patterns; intriguingly, the expression of 60% of honey bee HVS genes was found to be brain enriched, and 24% of mouse HVS genes were highly expressed in either or both the brain and testis. Moreover, a minimum of 38% of mouse HVS genes demonstrated neuron-enriched expression patterns, and 62% of them exhibited expression in selective brain areas, particularly the forebrain and cerebellum. Furthermore, gene ontology (GO) analysis of HVS genes predicted that 35% of genes are associated with DNA transcription and RNA processing. Conclusion These results suggest that HVS genes include genes that are biased towards expression in the brain and gonads. They also demonstrate that at least some of Urbilaterian genes retained in the specific animal lineage may be selectively maintained to support the species-specific phenotypes. PMID:19138430

Expression profiles of urbilaterian genes uniquely shared between honey bee and vertebrates.

PubMed

Matsui, Toshiaki; Yamamoto, Toshiyuki; Wyder, Stefan; Zdobnov, Evgeny M; Kadowaki, Tatsuhiko

2009-01-12

Large-scale comparison of metazoan genomes has revealed that a significant fraction of genes of the last common ancestor of Bilateria (Urbilateria) is lost in each animal lineage. This event could be one of the underlying mechanisms involved in generating metazoan diversity. However, the present functions of these ancient genes have not been addressed extensively. To understand the functions and evolutionary mechanisms of such ancient Urbilaterian genes, we carried out comprehensive expression profile analysis of genes shared between vertebrates and honey bees but not with the other sequenced ecdysozoan genomes (honey bee-vertebrate specific, HVS genes) as a model. We identified 30 honey bee and 55 mouse HVS genes. Many HVS genes exhibited tissue-selective expression patterns; intriguingly, the expression of 60% of honey bee HVS genes was found to be brain enriched, and 24% of mouse HVS genes were highly expressed in either or both the brain and testis. Moreover, a minimum of 38% of mouse HVS genes demonstrated neuron-enriched expression patterns, and 62% of them exhibited expression in selective brain areas, particularly the forebrain and cerebellum. Furthermore, gene ontology (GO) analysis of HVS genes predicted that 35% of genes are associated with DNA transcription and RNA processing. These results suggest that HVS genes include genes that are biased towards expression in the brain and gonads. They also demonstrate that at least some of Urbilaterian genes retained in the specific animal lineage may be selectively maintained to support the species-specific phenotypes.

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiac allograft gene expression profiling test... Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a) Identification. A cardiac allograft gene expression profiling test system is a device that measures the...

Modeling contemporary climate profiles of whitebark pine (Pinus albicaulis) and predicting responses to global warming

Treesearch

Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

2006-01-01

The Random Forests multiple regression tree was used to develop an empirically-based bioclimate model for the distribution of Pinus albicaulis (whitebark pine) in western North America, latitudes 31° to 51° N and longitudes 102° to 125° W. Independent variables included 35 simple expressions of temperature and precipitation and their interactions....

miR-34a screened by miRNA profiling negatively regulates Wnt/β-catenin signaling pathway in Aflatoxin B1 induced hepatotoxicity

PubMed Central

Zhu, Liye; Gao, Jing; Huang, Kunlun; Luo, Yunbo; Zhang, Boyang; Xu, Wentao

2015-01-01

Aflatoxin-B1 (AFB1), a hepatocarcinogenic mycotoxin, was demonstrated to induce the high rate of hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) participate in the regulation of several biological processes in HCC. However, the function of miRNAs in AFB1-induced HCC has received a little attention. Here, we applied Illumina deep sequencing technology for high-throughout profiling of microRNAs in HepG2 cells lines after treatment with AFB1. Analysis of the differential expression profile of miRNAs in two libraries, we identified 9 known miRNAs and 1 novel miRNA which exhibited abnormal expression. KEGG analysis indicated that predicted target genes of differentially expressed miRNAs are involved in cancer-related pathways. Down-regulated of Drosha, DGCR8 and Dicer 1 indicated an impairment of miRNA biogenesis in response to AFB1. miR-34a was up-regulated significantly, down-regulating the expression of Wnt/β-catenin signaling pathway by target gene β-catenin. Anti-miR-34a can significantly relieved the down-regulated β-catenin and its downstream genes, c-myc and Cyclin D1, and the S-phase arrest in cell cycle induced by AFB1 can also be relieved. These results suggested that AFB1 might down-regulate Wnt/β-catenin signaling pathway in HepG2 cells by up-regulating miR-34a, which may involve in the mechanism of liver tumorigenesis. PMID:26567713

The altered liver microRNA profile in hepatotoxicity induced by rhizome Dioscorea bulbifera in mice.

PubMed

Yang, Rui; Bai, Qingyun; Zhang, Jiaqi; Sheng, Yuchen; Ji, Lili

2017-08-01

MicroRNA (miRNA) has been reported to play important roles in regulating drug-induced liver injury. Ethyl acetate extract isolated from rhizoma Dioscoreae bulbifera (EF) has been reported to induce hepatotoxicity in our previous studies. This study aims to observe the altered liver miRNA profile and its related signalling pathway involved in EF-induced hepatotoxicity. Serum alanine/aspartate aminotransferase assay showed that EF (450 mg/kg)-induced hepatotoxicity in mice. Results of miRNA chip analysis showed that the expression of eight miRNAs was up-regulated and of other nine miRNAs was down-regulated in livers from EF-treated mice. Further, the altered expression of miR-200a-3p, miR-5132-5p and miR-5130 was validated using real-time polymerase chain reaction (PCR) assay. There were total seven predicted target genes of miR-200a-3p, miR-5132-5p and miR-5130. Only one kyoto encyclopedia genes and genomes pathway was annotated using those target genes, which is protein processing in endoplasmic reticulum (ER). Furthermore, liver expression of DnaJ subfamily A member 1, a key gene involved in protein processing in ER based on the altered miRNAs, was increased in EF-treated mice. In conclusion, the results demonstrated that EF altered the expression of liver miRNA profile and its related signalling pathway, which may be involved in EF-induced hepatotoxicity.

Viral Fitness Correlates with the Magnitude and Direction of the Perturbation Induced in the Host's Transcriptome: The Tobacco Etch Potyvirus-Tobacco Case Study.

PubMed

Cervera, Héctor; Ambrós, Silvia; Bernet, Guillermo P; Rodrigo, Guillermo; Elena, Santiago F

2018-07-01

Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a complex property that captures, in a single figure, differences in performance at every stage of viral infection. To what extent does viral fitness result from specific molecular interactions with host factors and regulatory networks during infection? Can we identify host genes in functional classes whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with the virus' fitness. Differentially expressed genes which were positively correlated with viral fitness activate hormone- and RNA silencing-mediated pathways of plant defense. In contrast, those that were negatively correlated with fitness affect metabolism, reducing growth, and development. Overall, these results reveal the high information content of viral fitness and suggest its potential use to predict differences in genomic profiles of infected hosts.

Viral Fitness Correlates with the Magnitude and Direction of the Perturbation Induced in the Host’s Transcriptome: The Tobacco Etch Potyvirus—Tobacco Case Study

PubMed Central

Cervera, Héctor; Ambrós, Silvia; Bernet, Guillermo P; Rodrigo, Guillermo; Elena, Santiago F

2018-01-01

Abstract Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a complex property that captures, in a single figure, differences in performance at every stage of viral infection. To what extent does viral fitness result from specific molecular interactions with host factors and regulatory networks during infection? Can we identify host genes in functional classes whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with the virus' fitness. Differentially expressed genes which were positively correlated with viral fitness activate hormone- and RNA silencing-mediated pathways of plant defense. In contrast, those that were negatively correlated with fitness affect metabolism, reducing growth, and development. Overall, these results reveal the high information content of viral fitness and suggest its potential use to predict differences in genomic profiles of infected hosts. PMID:29562354

Identification and characterization of miRNAs and targets in flax (Linum usitatissimum) under saline, alkaline, and saline-alkaline stresses.

PubMed

Yu, Ying; Wu, Guangwen; Yuan, Hongmei; Cheng, Lili; Zhao, Dongsheng; Huang, Wengong; Zhang, Shuquan; Zhang, Liguo; Chen, Hongyu; Zhang, Jian; Guan, Fengzhi

2016-05-27

MicroRNAs (miRNAs) play a critical role in responses to biotic and abiotic stress and have been characterized in a large number of plant species. Although flax (Linum usitatissimum L.) is one of the most important fiber and oil crops worldwide, no reports have been published describing flax miRNAs (Lus-miRNAs) induced in response to saline, alkaline, and saline-alkaline stresses. In this work, combined small RNA and degradome deep sequencing was used to analyze flax libraries constructed after alkaline-salt stress (AS2), neutral salt stress (NSS), alkaline stress (AS), and the non-stressed control (CK). From the CK, AS, AS2, and NSS libraries, a total of 118, 119, 122, and 120 known Lus-miRNAs and 233, 213, 211, and 212 novel Lus-miRNAs were isolated, respectively. After assessment of differential expression profiles, 17 known Lus-miRNAs and 36 novel Lus-miRNAs were selected and used to predict putative target genes. Gene ontology term enrichment analysis revealed target genes that were involved in responses to stimuli, including signaling and catalytic activity. Eight Lus-miRNAs were selected for analysis using qRT-PCR to confirm the accuracy and reliability of the miRNA-seq results. The qRT-PCR results showed that changes in stress-induced expression profiles of these miRNAs mirrored expression trends observed using miRNA-seq. Degradome sequencing and transcriptome profiling showed that expression of 29 miRNA-target pairs displayed inverse expression patterns under saline, alkaline, and saline-alkaline stresses. From the target prediction analysis, the miR398a-targeted gene codes for a copper/zinc superoxide dismutase, and the miR530 has been shown to explicitly target WRKY family transcription factors, which suggesting that these two micRNAs and their targets may significant involve in the saline, alkaline, and saline-alkaline stress response in flax. Identification and characterization of flax miRNAs, their target genes, functional annotations, and gene expression patterns are reported in this work. These findings will enhance our understanding of flax miRNA regulatory mechanisms under saline, alkaline, and saline-alkaline stresses and provide a foundation for future elucidation of the specific functions of these miRNAs.

Levels of cystathionine gamma lyase production by Geotrichum candidum in synthetic media and correlation with the presence of sulphur flavours in cheese.

PubMed

Gente, Stéphanie; La Carbona, Stéphanie; Guéguen, Micheline

2007-03-10

Geotrichum candidum is a cheese-ripening agent with the potential to produce sulphur flavour compounds in soft cheeses. We aimed to develop an alternative test for predicting the aromatic (sulphur flavours) potential of G. candidum strains in soft cheese. Twelve strains of G. candidum with different levels of demethiolase activity (determined by a chemical method) in YEL-met (yeast extract, lactate methionine) medium were studied. We investigated cgl (cystathionine gamma lyase) gene expression after culture in three media - YEL-met, casamino acid and curd media - and then carried out sensory analysis on a Camembert cheese matrix. We found no correlation between demethiolase activity in vitro and cgl gene expression. Sensory analysis (detection of sulphur flavours) identified different aromatic profiles linked to cgl expression, but not to demethiolase activity. The RT-PCR technique described here is potentially useful for predicting the tendency of a given strain of G. candidum to develop sulphur flavours in cheese matrix. This is the first demonstration that an in vitro molecular approach could be used as a predictive test for evaluating the potential of G. candidum strains to generate sulphur compounds in situ (Camembert cheese matrix).

Arabidopsis Defense against Botrytis cinerea: Chronology and Regulation Deciphered by High-Resolution Temporal Transcriptomic Analysis[C][W

PubMed Central

Windram, Oliver; Madhou, Priyadharshini; McHattie, Stuart; Hill, Claire; Hickman, Richard; Cooke, Emma; Jenkins, Dafyd J.; Penfold, Christopher A.; Baxter, Laura; Breeze, Emily; Kiddle, Steven J.; Rhodes, Johanna; Atwell, Susanna; Kliebenstein, Daniel J.; Kim, Youn-sung; Stegle, Oliver; Borgwardt, Karsten; Zhang, Cunjin; Tabrett, Alex; Legaie, Roxane; Moore, Jonathan; Finkenstadt, Bärbel; Wild, David L.; Mead, Andrew; Rand, David; Beynon, Jim; Ott, Sascha; Buchanan-Wollaston, Vicky; Denby, Katherine J.

2012-01-01

Transcriptional reprogramming forms a major part of a plant’s response to pathogen infection. Many individual components and pathways operating during plant defense have been identified, but our knowledge of how these different components interact is still rudimentary. We generated a high-resolution time series of gene expression profiles from a single Arabidopsis thaliana leaf during infection by the necrotrophic fungal pathogen Botrytis cinerea. Approximately one-third of the Arabidopsis genome is differentially expressed during the first 48 h after infection, with the majority of changes in gene expression occurring before significant lesion development. We used computational tools to obtain a detailed chronology of the defense response against B. cinerea, highlighting the times at which signaling and metabolic processes change, and identify transcription factor families operating at different times after infection. Motif enrichment and network inference predicted regulatory interactions, and testing of one such prediction identified a role for TGA3 in defense against necrotrophic pathogens. These data provide an unprecedented level of detail about transcriptional changes during a defense response and are suited to systems biology analyses to generate predictive models of the gene regulatory networks mediating the Arabidopsis response to B. cinerea. PMID:23023172

Target research on tumor biology characteristics of mir-155-5p regulation on gastric cancer cell.

PubMed

Feng, Jun-an

2016-03-01

After the mir-155-5p over expressed in gastric cancer cells, the expression profile chip was adopted to screen its target genes. Some of the intersection of target genes were selected based on the bioinformatics prediction, in order to study the mechanism of its function and role of research. Affymetrix eukaryotic gene expression spectrum was conducted to screen mir-155-5p regulated genetic experiment. Western blot technique was employed to detect and screen the protein expression of target genes. Mimics was transfected in BGC-823 of gastric cancer cells. Compared with mimics-nc group and mock group, the mRNA expression quantities of SMAD1, STAT1, CAB39, CXCR4 and CA9 were significantly lower. After the gastric cancer cells BGC-823 and MKN-45 had been transfected by mimics, compared with mimics-nc (MNC) group and mock (MOCK) group, it was decreased for the protein expression of SMAD1, STAT1 and CAB39 in mimics (MIMICS) group. The verification of qRT-PCR demonstrated that SMAD1, STAT1, CAB39, CXCR4 and CA9 were the predicted target genes and target proteins of mir-155-5p, the over expression of mir-155-5p could enable the decreasing of its expression level in gastric cancer cells MKN-45 and BGC-823.

Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature.

PubMed

Haberman, Yael; Tickle, Timothy L; Dexheimer, Phillip J; Kim, Mi-Ok; Tang, Dora; Karns, Rebekah; Baldassano, Robert N; Noe, Joshua D; Rosh, Joel; Markowitz, James; Heyman, Melvin B; Griffiths, Anne M; Crandall, Wallace V; Mack, David R; Baker, Susan S; Huttenhower, Curtis; Keljo, David J; Hyams, Jeffrey S; Kugathasan, Subra; Walters, Thomas D; Aronow, Bruce; Xavier, Ramnik J; Gevers, Dirk; Denson, Lee A

2014-08-01

Interactions between the host and gut microbial community likely contribute to Crohn disease (CD) pathogenesis; however, direct evidence for these interactions at the onset of disease is lacking. Here, we characterized the global pattern of ileal gene expression and the ileal microbial community in 359 treatment-naive pediatric patients with CD, patients with ulcerative colitis (UC), and control individuals. We identified core gene expression profiles and microbial communities in the affected CD ilea that are preserved in the unaffected ilea of patients with colon-only CD but not present in those with UC or control individuals; therefore, this signature is specific to CD and independent of clinical inflammation. An abnormal increase of antimicrobial dual oxidase (DUOX2) expression was detected in association with an expansion of Proteobacteria in both UC and CD, while expression of lipoprotein APOA1 gene was downregulated and associated with CD-specific alterations in Firmicutes. The increased DUOX2 and decreased APOA1 gene expression signature favored oxidative stress and Th1 polarization and was maximally altered in patients with more severe mucosal injury. A regression model that included APOA1 gene expression and microbial abundance more accurately predicted month 6 steroid-free remission than a model using clinical factors alone. These CD-specific host and microbe profiles identify the ileum as the primary inductive site for all forms of CD and may direct prognostic and therapeutic approaches.

Sex-specific patterns and deregulation of endocrine pathways in the gene expression profiles of Bangladeshi adults exposed to arsenic contaminated drinking water

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muñoz, Alexandra; Chervona, Yana; Hall, Megan

Arsenic contamination of drinking water occurs globally and is associated with numerous diseases including skin, lung and bladder cancers, and cardiovascular disease. Recent research indicates that arsenic may be an endocrine disruptor. This study was conducted to evaluate the nature of gene expression changes among males and females exposed to arsenic contaminated water in Bangladesh at high and low doses. Twenty-nine (55% male) Bangladeshi adults with water arsenic exposure ranging from 50 to 1000 μg/L were selected from the Folic Acid Creatinine Trial. RNA was extracted from peripheral blood mononuclear cells for gene expression profiling using Affymetrix 1.0 ST arrays.more » Differentially expressed genes were assessed between high and low exposure groups for males and females separately and findings were validated using quantitative real-time PCR. There were 534 and 645 differentially expressed genes (p < 0.05) in the peripheral blood mononuclear cells of males and females, respectively, when high and low water arsenic exposure groups were compared. Only 43 genes overlapped between the two sexes, with 29 changing in opposite directions. Despite the difference in gene sets both males and females exhibited common biological changes including deregulation of 17β-hydroxysteroid dehydrogenase enzymes, deregulation of genes downstream of Sp1 (specificity protein 1) transcription factor, and prediction of estrogen receptor alpha as a key hub in cardiovascular networks. Arsenic-exposed adults exhibit sex-specific gene expression profiles that implicate involvement of the endocrine system. Due to arsenic's possible role as an endocrine disruptor, exposure thresholds for arsenic may require different parameters for males and females. - Highlights: • Males and females exhibit unique gene expression changes in response to arsenic. • Only 23 genes are common among the differentially expressed genes for the sexes. • Male and female gene lists exhibit common biological implications. • Both sexes exhibit deregulation of cardiovascular and endocrine pathways.« less

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

Glycopeptide Susceptibility Profiles of Staphylococcus haemolyticus Bloodstream Isolates

PubMed Central

Biavasco, Francesca; Vignaroli, Carla; Lazzarini, Raffaella; Varaldo, Pietro E.

2000-01-01

Twelve clinical strains of Staphylococcus haemolyticus (eight methicillin resistant and three methicillin susceptible), isolated from blood cultures between 1982 and 1997, were investigated for teicoplanin and vancomycin susceptibility profiles. On the basis of conventional MIC tests and breakpoints, four isolates were susceptible (MICs, 1 to 8 μg/ml) and eight were resistant (MICs, 32 to 64 μg/ml) to teicoplanin while all were susceptible to vancomycin (MICs, 1 to 2 μg/ml). All four strains for which the conventional teicoplanin MICs were within the range of susceptibility expressed heterogeneous resistance to teicoplanin and homogeneous vancomycin susceptibility. Of the eight strains for which the conventional teicoplanin MICs were within the range of resistance, six expressed heterogeneous and two expressed homogeneous teicoplanin resistance while seven showed heterogeneous vancomycin resistance profiles (with subpopulations growing on 8 μg of the drug per ml at frequencies of ≥10−6 for six strains and 10−7 for one) and one demonstrated homogeneous vancomycin susceptibility. Of six bloodstream isolates of other staphylococcal species (S. aureus, S. epidermidis, and S. simulans), for all of which the conventional teicoplanin MICs were ≥4 μg/ml and the vancomycin MICs were ≤2 μg/ml, none exhibited heterogeneous susceptibility profiles for teicoplanin while three showed homogeneous and three showed heterogeneous susceptibility profiles for vancomycin (with subpopulations growing on 8 μg of the drug per ml found for only one strain). The results of this study indicate that a heterogeneous response to glycopeptides is a common feature of S. haemolyticus isolates and suggest that susceptibility to glycopeptides as determined by conventional MIC tests may not be predictive of the outcome of glycopeptide therapy. PMID:11036034

Conjugated bilirubin affects cytokine profiles in hepatitis A virus infection by modulating function of signal transducer and activator of transcription factors

PubMed Central

Castro-García, Flor P; Corral-Jara, Karla F; Escobedo-Melendez, Griselda; Sandoval-Hernandez, Monserrat A; Rosenstein, Yvonne; Roman, Sonia; Panduro, Arturo; Fierro, Nora A

2014-01-01

Hepatitis A virus (HAV) infection is the major cause of acute liver failure in paediatric patients. The clinical spectrum of infection is variable, and liver injury is determined by altered hepatic enzyme function and bilirubin concentration. We recently reported differences in cytokine profiles between distinct HAV-induced clinical courses, and bilirubin has been recognized as a potential immune-modulator. However, how bilirubin may affect cytokine profiles underlying the variability in the course of infection has not been determined. Herein, we used a transcription factor (TF) binding site identification approach to retrospectively analyse cytokine expression in HAV-infected children and to predict the entire set of TFs associated with the expression of specific cytokine profiles. The results suggested that modulation of the activity of signal transducers and activators of transcription proteins (STATs) may play a central role during HAV infection. This led us to compare the degree of STAT phosphorylation in peripheral blood lymphoid cells (PBLCs) from paediatric patients with distinct levels of conjugated bilirubin (CB). Low CB levels in sera were associated with increased STAT-1 and STAT-5 phosphorylation. A positive correlation was observed between the serum interleukin-6 (IL-6) content and CB values, whereas higher levels of CB correlated with reduced serum IL-8 values and with a reduction in the proportion of PBLCs positive for STAT-5 phosphorylation. When CB was used to stimulate patients’ PBLCs in vitro, the levels of IL-6 and tumour necrosis factor-α were increased. The data showed that bilirubin plays a role in STAT function and affects cytokine profile expression during HAV infection. PMID:24943111

SERUM THYROTROPIN CONCENTRATIONS ARE NOT PREDICTIVE OF AGGRESSIVE BREAST CANCER BIOLOGY IN EUTHYROID INDIVIDUALS

PubMed Central

Villa, Natalie M.; Li, Ning; Yeh, Michael W.; Hurvitz, Sara A.; Dawson, Nicole A.; Leung, Angela M.

2015-01-01

Objective The potential influence of hypothyroidism on breast cancer remains incompletely understood. The objective of this study was to investigate the relationship between serum thyrotropin [thyroid-stimulating hormone (TSH)] concentration and markers of aggressive breast cancer biology, as defined by receptor expression profile, tumor grade, and American Joint Committee on Cancer (AJCC) stage characteristics. Methods This was a retrospective cohort study of patients from 2002–2014. All breast cancer patients who had complete receptor (estrogen receptor, ER; progesterone receptor, PR; and Her2/neu) and pre-diagnosis serum TSH data (n=437) were included. All patients had one of six receptor profiles: ER+ PR+ Her2/neu −, ER+ PR− Her2/neu−, ER+ PR+ Her2/neu+, ER+ PRHer2/ neu+, ER− PR− Her2/neu+, ER− PR− Her2/neu−. Log-transformed serum TSH concentrations were analyzed using multinomial and logistic regressions for a potential relationship with markers of breast cancer aggressiveness. Results Increasing serum TSH concentration was associated with a lower probability of having the receptor expression profile ER+ PR+ Her2/neu+ compared to patients with the ER+ PR+ Her2/neu− profile (OR=0.52, p=0.0045). No significant associations between other receptor expression profiles and serum TSH concentration were found. All time-weighted and unweighted median serum TSH concentrations were within normal limits. No significant associations between serum TSH concentration and tumor grade, overall AJCC stage, or tumor size (T), lymph node positivity (N), or presence of metastasis (M) were observed. Conclusions Serum TSH was not associated with markers of breast cancer aggressiveness in our cohort. PMID:26121443

Conjugated bilirubin affects cytokine profiles in hepatitis A virus infection by modulating function of signal transducer and activator of transcription factors.

PubMed

Castro-García, Flor P; Corral-Jara, Karla F; Escobedo-Melendez, Griselda; Sandoval-Hernandez, Monserrat A; Rosenstein, Yvonne; Roman, Sonia; Panduro, Arturo; Fierro, Nora A

2014-12-01

Hepatitis A virus (HAV) infection is the major cause of acute liver failure in paediatric patients. The clinical spectrum of infection is variable, and liver injury is determined by altered hepatic enzyme function and bilirubin concentration. We recently reported differences in cytokine profiles between distinct HAV-induced clinical courses, and bilirubin has been recognized as a potential immune-modulator. However, how bilirubin may affect cytokine profiles underlying the variability in the course of infection has not been determined. Herein, we used a transcription factor (TF) binding site identification approach to retrospectively analyse cytokine expression in HAV-infected children and to predict the entire set of TFs associated with the expression of specific cytokine profiles. The results suggested that modulation of the activity of signal transducers and activators of transcription proteins (STATs) may play a central role during HAV infection. This led us to compare the degree of STAT phosphorylation in peripheral blood lymphoid cells (PBLCs) from paediatric patients with distinct levels of conjugated bilirubin (CB). Low CB levels in sera were associated with increased STAT-1 and STAT-5 phosphorylation. A positive correlation was observed between the serum interleukin-6 (IL-6) content and CB values, whereas higher levels of CB correlated with reduced serum IL-8 values and with a reduction in the proportion of PBLCs positive for STAT-5 phosphorylation. When CB was used to stimulate patients' PBLCs in vitro, the levels of IL-6 and tumour necrosis factor-α were increased. The data showed that bilirubin plays a role in STAT function and affects cytokine profile expression during HAV infection. © 2014 John Wiley & Sons Ltd.

Orientations for the successful categorization of facial expressions and their link with facial features.

PubMed

Duncan, Justin; Gosselin, Frédéric; Cobarro, Charlène; Dugas, Gabrielle; Blais, Caroline; Fiset, Daniel

2017-12-01

Horizontal information was recently suggested to be crucial for face identification. In the present paper, we expand on this finding and investigate the role of orientations for all the basic facial expressions and neutrality. To this end, we developed orientation bubbles to quantify utilization of the orientation spectrum by the visual system in a facial expression categorization task. We first validated the procedure in Experiment 1 with a simple plaid-detection task. In Experiment 2, we used orientation bubbles to reveal the diagnostic-i.e., task relevant-orientations for the basic facial expressions and neutrality. Overall, we found that horizontal information was highly diagnostic for expressions-surprise excepted. We also found that utilization of horizontal information strongly predicted performance level in this task. Despite the recent surge of research on horizontals, the link with local features remains unexplored. We were thus also interested in investigating this link. In Experiment 3, location bubbles were used to reveal the diagnostic features for the basic facial expressions. Crucially, Experiments 2 and 3 were run in parallel on the same participants, in an interleaved fashion. This way, we were able to correlate individual orientation and local diagnostic profiles. Our results indicate that individual differences in horizontal tuning are best predicted by utilization of the eyes.

Differential expression of folate receptor 1 in medulloblastoma and the correlation with clinicopathological characters and target therapeutic potential.

PubMed

Liu, Hailong; Sun, Qianwen; Zhang, Mingshan; Zhang, Zhihua; Fan, Xinyi; Yuan, Hongyu; Li, Cheng; Guo, Yuduo; Ning, Weihai; Sun, Youliang; Song, Yongmei; Yu, Chunjiang

2017-04-04

Medulloblastoma is the most common malignant brain tumor in children. Folate receptor 1 (Folr1) was abundantly expressed in some epithelial malignancies. However the expression profile and the role of clinicopathological significance and therapeutic target potential in medulloblastoma still remain elusive. Currently we detected the expression of Folr1 in medulloblastoma and identified the diagnostic application by evaluating the clinical, pathological and neuroimaging values. Then we developed a target therapeutic compound with Folr1, which exhibited promising efficiency in treatment of medulloblastoma. Folr1 expression was up-regulated in medulloblastoma and positively correlated with percentage of Ki-67 and MMP9 labeling, pathological subtypes, serum Folr1 levels and CSF spreading on MRI. The level of serum Folr1 showed rational sensitivity and specificity in predicting histological subgroups. Strong Folr1 expression was recommended as the independent value regarding the prognosis of patients with medulloblastoma. Folr1 targeted therapy attenuated the tumor growth and metastasis with down-regulation of MMPs proteins and activation of apoptosis. Immunostaining analysis in the xenograft samples showed the decreased Ki-67 and MMP9 index providing the strong evidences that Folr1 targeted application can suppress the proliferation and invasion. Our findings uncovered in Folr1 a predictive candidate and therapeutic target for medulloblastoma.

Highly buoyant bent-over plumes in a boundary layer

NASA Astrophysics Data System (ADS)

Tohidi, Ali; Kaye, Nigel B.

2016-04-01

Highly buoyant plumes, such as wildfire plumes, in low to moderate wind speeds have initial trajectories that are steeper than many industrial waste plumes. They will rise further into the atmosphere before bending significantly. In such cases the plume's trajectory will be influenced by the vertical variation in horizontal velocity of the atmospheric boundary layer. This paper examined the behavior of a plume in an unstratified environment with a power-law ambient velocity profile. Examination of previously published experimental measurements of plume trajectory show that inclusion of the boundary layer velocity profile in the plume model often provides better predictions of the plume trajectory compared to algebraic expressions developed for uniform flow plumes. However, there are many cases in which uniform velocity profile algebraic expressions are as good as boundary layer models. It is shown that it is only important to model the role of the atmospheric boundary layer velocity profile in cases where either the momentum length (square root of source momentum flux divided by the reference wind speed) or buoyancy length (buoyancy flux divided by the reference wind speed cubed) is significantly greater than the plume release height within the boundary layer. This criteria is rarely met with industrial waste plumes, but it is important in modeling wildfire plumes.

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

Bleomycin induces molecular changes directly relevant to idiopathic pulmonary fibrosis: a model for "active" disease.

PubMed

Peng, Ruoqi; Sridhar, Sriram; Tyagi, Gaurav; Phillips, Jonathan E; Garrido, Rosario; Harris, Paul; Burns, Lisa; Renteria, Lorena; Woods, John; Chen, Leena; Allard, John; Ravindran, Palanikumar; Bitter, Hans; Liang, Zhenmin; Hogaboam, Cory M; Kitson, Chris; Budd, David C; Fine, Jay S; Bauer, Carla M T; Stevenson, Christopher S

2013-01-01

The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF), has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease.

ALDH1 is an immunohistochemical diagnostic marker for solitary fibrous tumours and haemangiopericytomas of the meninges emerging from gene profiling study

PubMed Central

2013-01-01

Background Solitary Fibrous Tumours (SFT) and haemangiopericytomas (HPC) are rare meningeal tumours that have to be distinguished from meningiomas and more rarely from synovial sarcomas. We recently found that ALDH1A1 was overexpressed in SFT and HPC as compared to soft tissue sarcomas. Using whole-genome DNA microarrays, we defined the gene expression profiles of 16 SFT/HPC (9 HPC and 7 SFT). Expression profiles were compared to publicly available expression profiles of additional SFT or HPC, meningiomas and synovial sarcomas. We also performed an immunohistochemical (IHC) study with anti-ALDH1 and anti-CD34 antibodies on Tissue Micro-Arrays including 38 SFT (25 meningeal and 13 extrameningeal), 55 meningeal haemangiopericytomas (24 grade II, 31 grade III), 163 meningiomas (86 grade I, 62 grade II, 15 grade III) and 98 genetically confirmed synovial sarcomas. Results ALDH1A1 gene was overexpressed in SFT/HPC, as compared to meningiomas and synovial sarcomas. These findings were confirmed at the protein level. 84% of the SFT and 85.4% of the HPC were positive with anti-ALDH1 antibody, while only 7.1% of synovial sarcomas and 1.2% of meningiomas showed consistent expression. Positivity was usually more diffuse in SFT/HPC compared to other tumours with more than 50% of tumour cells immunostained in 32% of SFT and 50.8% of HPC. ALDH1 was a sensitive and specific marker for the diagnosis of SFT (SE = 84%, SP = 98.8%) and HPC (SE = 84.5%, SP = 98.7%) of the meninges. In association with CD34, ALDH1 expression had a specificity and positive predictive value of 100%. Conclusion We show that ALDH1, a stem cell marker, is an accurate diagnostic marker for SFT and HPC, which improves the diagnostic value of CD34. ALDH1 could also be a new therapeutic target for these tumours which are not sensitive to conventional chemotherapy. PMID:24252471

Significance of aquaporins’ expression in the prognosis of gastric cancer

PubMed Central

Thapa, Saroj; Chetry, Mandika; Huang, Kaiyu; Peng, Yangpei; Wang, Jinsheng; Wang, Jiaoni; Zhou, Yingying; Shen, Yigen; Xue, Yangjing; Ji, Kangting

2018-01-01

Gastric carcinoma is one of the most lethal malignancy at present with leading cause of cancer-related deaths worldwide. Aquaporins (AQPs) are a family of small, integral membrane proteins, which have been evidenced to play a crucial role in cell migration and proliferation of different cancer cells including gastric cancers. However, the aberrant expression of specific AQPs and its correlation to detect predictive and prognostic significance in gastric cancer remains elusive. In the present study, we comprehensively explored immunohistochemistry based map of protein expression profiles in normal tissues, cancer and cell lines from publicly available Human Protein Atlas (HPA) database. Moreover, to improve our understanding of general gastric biology and guide to find novel predictive prognostic gastric cancer biomarker, we also retrieved ‘The Kaplan–Meier plotter’ (KM plotter) online database with specific AQPs mRNA to overall survival (OS) in different clinicopathological features. We revealed that ubiquitous expression of AQPs protein can be effective tools to generate gastric cancer biomarker. Furthermore, high level AQP3, AQP9, and AQP11 mRNA expression were correlated with better OS in all gastric patients, whereas AQP0, AQP1, AQP4, AQP5, AQP6, AQP8, and AQP10 mRNA expression were associated with poor OS. With regard to the clinicopathological features including Laurens classification, clinical stage, human epidermal growth factor receptor 2 (HER2) status, and different treatment strategy, we could illustrate significant role of individual AQP mRNA expression in the prognosis of gastric cancer patients. Thus, our results indicated that AQP’s protein and mRNA expression in gastric cancer patients provide effective role to predict prognosis and act as an essential agent to therapeutic strategy. PMID:29678898

Model-based Analysis of HER Activation in Cells Co-Expressing EGFR, HER2 and HER3.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Zhang, Yi; Tan, Yunbing

2013-08-22

The HER/ErbB family of receptor tyrosine kinases drive critical responses in normal physiology and cancer, and the expression levels of the various HER receptors are critical determinants of clinical outcomes. HER activation is driven by the formation of various dimer complexes between members of this receptor family. The HER dimer types can have differential effects on downstream signaling and phenotypic outcomes. We constructed an integrated mathematical model of HER activation and trafficking to quantitatively link receptor expression levels to dimerization and activation. We parameterized the model with a comprehensive set of HER phosphorylation and abundance data collected in a panelmore » of human mammary epithelial cells expressing varying levels of EGFR, HER2 and HER3. Although parameter estimation yielded multiple solutions, predictions for dimer phosphorylation were in agreement with each other. We validated the model using experiments where pertuzumab was used to block HER2 dimerization. We used the model to predict HER dimerization and activation patterns in a panel of epithelial cells lines with known HER expression levels. Simulations over the range of expression levels seen in various cell lines indicate that: i) EGFR phosphorylation is driven by HER1/1 and HER1/2 dimers, and not HER1/3 dimers, ii) HER1/2 and HER2/3 dimers both contribute significantly to HER2 activation with the EGFR expression level determining the relative importance of these species, and iii) the HER2/3 dimer is largely responsible for HER3 activation. The model can be used to predict phosphorylated dimer levels for any given HER expression profile. This information in turn can be used to quantify the potencies of the various HER dimers, and can potentially inform personalized therapeutic approaches.« less

Platelets miRNA as a Prediction Marker of Thrombotic Episodes

PubMed Central

Dzieciol, Malgorzata

2016-01-01

The blood platelets are crucial for the coagulation physiology to maintain haemostatic balance and are involved in various pathologies such as atherosclerosis and thrombosis. The studies of recent years have shown that anucleated platelets are able to succeed protein synthesis. Additionally, mRNA translation in blood platelets is regulated by miRNA molecules. Recent works postulate the possibility of using miRNAs as biomarkers of atherosclerosis and ischemic episodes. This review article describes clinical studies that presented blood platelets miRNAs expression profile changes in different thrombotic states, which suggest use of these molecules as predictive biomarkers. PMID:28042196

Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites.

PubMed

Liu, Xuewu; Huang, Yuxiao; Liang, Jiao; Zhang, Shuai; Li, Yinghui; Wang, Jun; Shen, Yan; Xu, Zhikai; Zhao, Ya

2014-11-30

The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs. In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites. We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

PubMed

Coleman, Jonathan R I; Lester, Kathryn J; Roberts, Susanna; Keers, Robert; Lee, Sang Hyuck; De Jong, Simone; Gaspar, Héléna; Teismann, Tobias; Wannemüller, André; Schneider, Silvia; Jöhren, Peter; Margraf, Jürgen; Breen, Gerome; Eley, Thalia C

2017-04-01

Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

Serum protein profiling using an aptamer array predicts clinical outcomes of stage IIA colon cancer: A leave-one-out crossvalidation

PubMed Central

Huh, Jung Wook; Kim, Sung Chun; Sohn, Insuk; Jung, Sin-Ho; Kim, Hee Cheol

2016-01-01

Background In this study, we established and validated a model for predicting prognosis of stage IIA colon cancer patients based on expression profiles of aptamers in serum. Methods Bloods samples were collected from 227 consecutive patients with pathologic T3N0M0 (stage IIA) colon cancer. We incubated 1,149 serum molecule-binding aptamer pools of clinical significance with serum from patients to obtain aptamers bound to serum molecules, which were then amplified and marked. Oligonucleotide arrays were constructed with the base sequences of the 1,149 aptamers, and the marked products identified above were reacted with one another to produce profiles of the aptamers bound to serum molecules. These profiles were organized into low- and high-risk groups of colon cancer patients based on clinical information for the serum samples. Cox proportional hazards model and leave-one-out cross-validation (LOOCV) were used to evaluate predictive performance. Results During a median follow-up period of 5 years, 29 of the 227 patients (11.9%) experienced recurrence. There were 212 patients (93.4%) in the low-risk group and 15 patients (6.6%) in the high-risk group in our aptamer prognosis model. Postoperative recurrence significantly correlated with age and aptamer risk stratification (p = 0.046 and p = 0.001, respectively). In multivariate analysis, aptamer risk stratification (p < 0.001) was an independent predictor of recurrence. Disease-free survival curves calculated according to aptamer risk level predicted through a LOOCV procedure and age showed significant differences (p < 0.001 from permutations). Conclusion Aptamer risk stratification can be a valuable prognostic factor in stage II colon cancer patients. PMID:26908450

Evidence that specific executive functions predict symptom variance among schizophrenia patients with a predominantly negative symptom profile.

PubMed

Donohoe, Gary; Corvin, Aiden; Robertson, Ian H

2006-01-01

Although deficits in executive functioning in schizophrenia have been consistently reported, their precise relationship to symptomatology remains unclear. Recent approaches to executive functioning in nonschizophrenia studies have aimed to "fractionate" the individual cognitive processes involved. In this study, we hypothesised that if these processes are fractionable, then particular symptom syndromes may be selectively related to executive deficits. In particular, it was hoped that this approach could clarify whether negative and positive symptoms of schizophrenia are differentially related to particular aspects of executive/attentional functions. A total of 32 patients with schizophrenia and 16 matched controls were assessed on a series of tasks designed to tap the theoretically derived executive functions of Inhibition, Shifting set, Working memory, and Sustained attention. Negative symptoms were significantly predicted by performance on an "Inhibition" task (Stroop), and not by performance on any other task. Furthermore, for a subgroup of patients with predominantly negative symptoms variance in positive symptoms was only significantly predicted by performance on a set-shifting task (Visual Elevator), and not by performance on other tasks, including inhibition. Our results support the contention that negative symptoms can, at least partly, be conceived of as cognitive behaviours expressing specific executive deficits. Specifically, we discuss the possibility that negative symptoms may, in part, express a failure in response monitoring. We further suggest that the disordered metacognition resulting in positive symptoms may be mediated by cognitive flexibility in patients with a predominantly negative symptom profile.

Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states

PubMed Central

Chandrasekaran, Sriram; Ament, Seth A.; Eddy, James A.; Rodriguez-Zas, Sandra L.; Schatz, Bruce R.; Price, Nathan D.; Robinson, Gene E.

2011-01-01

Using brain transcriptomic profiles from 853 individual honey bees exhibiting 48 distinct behavioral phenotypes in naturalistic contexts, we report that behavior-specific neurogenomic states can be inferred from the coordinated action of transcription factors (TFs) and their predicted target genes. Unsupervised hierarchical clustering of these transcriptomic profiles showed three clusters that correspond to three ecologically important behavioral categories: aggression, maturation, and foraging. To explore the genetic influences potentially regulating these behavior-specific neurogenomic states, we reconstructed a brain transcriptional regulatory network (TRN) model. This brain TRN quantitatively predicts with high accuracy gene expression changes of more than 2,000 genes involved in behavior, even for behavioral phenotypes on which it was not trained, suggesting that there is a core set of TFs that regulates behavior-specific gene expression in the bee brain, and other TFs more specific to particular categories. TFs playing key roles in the TRN include well-known regulators of neural and behavioral plasticity, e.g., Creb, as well as TFs better known in other biological contexts, e.g., NF-κB (immunity). Our results reveal three insights concerning the relationship between genes and behavior. First, distinct behaviors are subserved by distinct neurogenomic states in the brain. Second, the neurogenomic states underlying different behaviors rely upon both shared and distinct transcriptional modules. Third, despite the complexity of the brain, simple linear relationships between TFs and their putative target genes are a surprisingly prominent feature of the networks underlying behavior. PMID:21960440

Gene expression profiles associated with anaemia and ITPA genotypes in patients with chronic hepatitis C (CH-C).

PubMed

Birerdinc, A; Estep, M; Afendy, A; Stepanova, M; Younossi, I; Baranova, A; Younossi, Z M

2012-06-01

Anaemia is a common side effect of ribavirin (RBV) which is used for the treatment of hepatitis C. Inosine triphosphatase gene polymorphism (C to A) protects against RBV-induced anaemia. The aim of our study was to genotype patients for inosine triphosphatase gene polymorphism rs1127354 SNP (CC or CA) and associate treatment-induced anaemia with gene expression profile and genotypes. We used 67 hepatitis C patients with available gene expression, clinical, laboratory data and whole-blood samples. Whole blood was used to determine inosine triphosphatase gene polymorphism rs1127354 genotypes (CC or CA). The cohort with inosine triphosphatase gene polymorphism CA genotype revealed a distinct pattern of protection against anaemia and a lower drop in haemoglobin. A variation in the propensity of CC carriers to develop anaemia prompted us to look for additional predictors of anaemia during pegylated interferon (PEG-IFN) and RBV. Pretreatment blood samples of patients receiving a full course of PEG-IFN and RBV were used to assess expression of 153 genes previously implicated in host response to viral infections. The gene expression data were analysed according to presence of anaemia and inosine triphosphatase gene polymorphism genotypes. Thirty-six genes were associated with treatment-related anaemia, six of which are involved in the response to hypoxia pathway (HIF1A, AIF1, RHOC, PTEN, LCK and PDGFB). There was a substantial overlap between sustained virological response (SVR)-predicting and anaemia-related genes; however, of the nine JAK-STAT pathway-related genes associated with SVR, none were implicated in anaemia. These observations exclude the direct involvement of antiviral response in the development of anaemia associated with PEG-IFN and RBV treatment, whereas another, distinct component within the SVR-associated gene expression response may predict anaemia. We have identified baseline gene expression signatures associated with RBV-induced anaemia and identified its functional pathways. In particular, we identified the hypoxia response pathway and the apoptosis/survival-related gene network, as differentially expressed in chronic hepatitis C patients with anaemia. © 2011 Blackwell Publishing Ltd.

Cell-Type–Specific Transcriptional Profiles of the Dimorphic Pathogen Penicillium marneffei Reflect Distinct Reproductive, Morphological, and Environmental Demands

PubMed Central

Pasricha, Shivani; Payne, Michael; Canovas, David; Pase, Luke; Ngaosuwankul, Nathamon; Beard, Sally; Oshlack, Alicia; Smyth, Gordon K.; Chaiyaroj, Sansanee C.; Boyce, Kylie J.; Andrianopoulos, Alex

2013-01-01

Penicillium marneffei is an opportunistic human pathogen endemic to Southeast Asia. At 25° P. marneffei grows in a filamentous hyphal form and can undergo asexual development (conidiation) to produce spores (conidia), the infectious agent. At 37° P. marneffei grows in the pathogenic yeast cell form that replicates by fission. Switching between these growth forms, known as dimorphic switching, is dependent on temperature. To understand the process of dimorphic switching and the physiological capacity of the different cell types, two microarray-based profiling experiments covering approximately 42% of the genome were performed. The first experiment compared cells from the hyphal, yeast, and conidiation phases to identify “phase or cell-state–specific” gene expression. The second experiment examined gene expression during the dimorphic switch from one morphological state to another. The data identified a variety of differentially expressed genes that have been organized into metabolic clusters based on predicted function and expression patterns. In particular, C-14 sterol reductase–encoding gene ergM of the ergosterol biosynthesis pathway showed high-level expression throughout yeast morphogenesis compared to hyphal. Deletion of ergM resulted in severe growth defects with increased sensitivity to azole-type antifungal agents but not amphotericin B. The data defined gene classes based on spatio-temporal expression such as those expressed early in the dimorphic switch but not in the terminal cell types and those expressed late. Such classifications have been helpful in linking a given gene of interest to its expression pattern throughout the P. marneffei dimorphic life cycle and its likely role in pathogenicity. PMID:24062530

Clinical Response to Vedolizumab in Ulcerative Colitis Patients Is Associated with Changes in Integrin Expression Profiles.

PubMed

Fuchs, Friederike; Schillinger, Daniela; Atreya, Raja; Hirschmann, Simon; Fischer, Sarah; Neufert, Clemens; Atreya, Imke; Neurath, Markus F; Zundler, Sebastian

2017-01-01

Despite large clinical success, deeper insights into the immunological effects of vedolizumab therapy for inflammatory bowel diseases are scarce. In particular, the reasons for differential clinical response in individual patients, the precise impact on the equilibrium of integrin-expressing T cell subsets, and possible associations between these issues are not clear. Blood samples from patients receiving clinical vedolizumab therapy were sequentially collected and analyzed for expression of integrins and chemokine receptors on T cells. Moreover, clinical and laboratory data from the patients were collected, and changes between homing marker expression and clinical parameters were analyzed for possible correlations. While no significant correlation of changes in integrin expression and changes in outcome parameters were identified in Crohn's disease (CD), increasing α4β7 levels in ulcerative colitis (UC) seemed to be associated with favorable clinical development, whereas increasing α4β1 and αEβ7 correlated with negative changes in outcome parameters. Changes in α4β1 integrin expression after 6 weeks were significantly different in responders and non-responders to vedolizumab therapy as assessed after 16 weeks with a cutoff of +4.2% yielding 100% sensitivity and 100% specificity in receiver-operator-characteristic analysis. Our data show that clinical response to vedolizumab therapy in UC but not in CD is associated with specific changes in integrin expression profiles opening novel avenues for mechanistic research and possibly prediction of response to therapy.

Octreotide and pasireotide (dis)similarly inhibit pituitary tumor cells in vitro.

PubMed

Ibáñez-Costa, Alejandro; Rivero-Cortés, Esther; Vázquez-Borrego, Mari C; Gahete, Manuel D; Jiménez-Reina, Luis; Venegas-Moreno, Eva; de la Riva, Andrés; Arráez, Miguel Ángel; González-Molero, Inmaculada; Schmid, Herbert A; Maraver-Selfa, Silvia; Gavilán-Villarejo, Inmaculada; García-Arnés, Juan Antonio; Japón, Miguel A; Soto-Moreno, Alfonso; Gálvez, María A; Luque, Raúl M; Castaño, Justo P

2016-11-01

Somatostatin analogs (SSA) are the mainstay of pharmacological treatment for pituitary adenomas. However, some patients escape from therapy with octreotide, a somatostatin receptor 2 (sst2)-preferring SSA, and pasireotide, a novel multi-sst-preferring SSA, may help to overcome this problem. It has been proposed that correspondence between sst1-sst5 expression pattern and SSA-binding profile could predict patient's response. To explore the cellular/molecular features associated with octreotide/pasireotide response, we performed a parallel comparison of their in vitro effects, evaluating sst1-sst5 expression, intracellular Ca 2+ signaling ([Ca 2+ ] i ), hormone secretion and cell viability, in a series of 85 pituitary samples. Somatotropinomas expressed sst5>sst2, yet octreotide reduced [Ca 2+ ] i more efficiently than pasireotide, while both SSA similarly decreased growth hormone release/expression and viability. Corticotropinomas predominantly expressed sst5, but displayed limited response to pasireotide, while octreotide reduced functional endpoints. Non-functioning adenomas preferentially expressed sst3 but, surprisingly, both SSA increased cell viability. Prolactinomas mainly expressed sst1 but were virtually unresponsive to SSA. Finally, both SSA decreased [Ca 2+ ] i in normal pituitaries. In conclusion, both SSA act in vitro on pituitary adenomas exerting both similar and distinct effects; however, no evident correspondence was found with the sst1-sst5 profile. Thus, it seems plausible that additional factors, besides the simple abundance of a given sst, critically influence the SSA response. © 2016 Society for Endocrinology.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

PubMed Central

Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

g:Profiler-a web server for functional interpretation of gene lists (2016 update).

PubMed

Reimand, Jüri; Arak, Tambet; Adler, Priit; Kolberg, Liis; Reisberg, Sulev; Peterson, Hedi; Vilo, Jaak

2016-07-08

Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene function related terms. Translation of hundreds of gene identifiers is another core feature of g:Profiler. Since its first publication in 2007, our web server has become a popular tool of choice among basic and translational researchers. Timeliness is a major advantage of g:Profiler as genome and pathway information is synchronized with the Ensembl database in quarterly updates. g:Profiler supports 213 species including mammals and other vertebrates, plants, insects and fungi. The 2016 update of g:Profiler introduces several novel features. We have added further functional datasets to interpret gene lists, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms. Besides the interactive web interface, g:Profiler can be accessed in computational pipelines using our R package, Python interface and BioJS component. g:Profiler is freely available at http://biit.cs.ut.ee/gprofiler/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

MicroRNAs as a potential prognostic factor in gastric cancer

PubMed Central

Brenner, Baruch; Hoshen, Moshe B; Purim, Ofer; David, Miriam Ben; Ashkenazi, Karin; Marshak, Gideon; Kundel, Yulia; Brenner, Ronen; Morgenstern, Sara; Halpern, Marisa; Rosenfeld, Nitzan; Chajut, Ayelet; Niv, Yaron; Kushnir, Michal

2011-01-01

AIM: To compare the microRNA (miR) profiles in the primary tumor of patients with recurrent and non-recurrent gastric cancer. METHODS: The study group included 45 patients who underwent curative gastrectomies from 1995 to 2005 without adjuvant or neoadjuvant therapy and for whom adequate tumor content was available. Total RNA was extracted from formalin-fixed paraffin-embedded tumor samples, preserving the small RNA fraction. Initial profiling using miR microarrays was performed to identify potential biomarkers of recurrence after resection. The expression of the differential miRs was later verified by quantitative real-time polymerase chain reaction (qRT-PCR). Findings were compared between patients who had a recurrence within 36 mo of surgery (bad-prognosis group, n = 14, 31%) and those who did not (good-prognosis group, n = 31, 69%). RESULTS: Three miRs, miR-451, miR-199a-3p and miR-195 were found to be differentially expressed in tumors from patients with good prognosis vs patients with bad prognosis (P < 0.0002, 0.0027 and 0.0046 respectively). High expression of each miR was associated with poorer prognosis for both recurrence and survival. Using miR-451, the positive predictive value for non-recurrence was 100% (13/13). The expression of the differential miRs was verified by qRT-PCR, showing high correlation to the microarray data and similar separation into prognosis groups. CONCLUSION: This study identified three miRs, miR-451, miR-199a-3p and miR-195 to be predictive of recurrence of gastric cancer. Of these, miR-451 had the strongest prognostic impact. PMID:22046085

Vascular biology: cellular and molecular profiling.

PubMed

Baird, Alison E; Wright, Violet L

2006-02-01

Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

MicroRNA Expression-Based Model Indicates Event-Free Survival in Pediatric Acute Myeloid Leukemia | Office of Cancer Genomics

Cancer.gov

Children with acute myeloid leukemia (AML) whose disease is refractory to standard induction chemotherapy therapy or who experience relapse after initial response have dismal outcomes. We sought to comprehensively profile pediatric AML microRNA (miRNA) samples to identify dysregulated genes and assess the utility of miRNAs for improved outcome prediction.

Mucin expression in pleomorphic adenoma of salivary gland: a potential role for MUC1 as a marker to predict recurrence.

PubMed

Hamada, T; Matsukita, S; Goto, M; Kitajima, S; Batra, S K; Irimura, T; Sueyoshi, K; Sugihara, K; Yonezawa, S

2004-08-01

Pleomorphic adenoma of the salivary gland (PA) is essentially a benign neoplasm. However, patients with recurrent PA are difficult to manage. There are rare reports on useful immunohistochemical markers to detect a high risk of recurrence when the primary lesions are resected. To find a new marker to predict the recurrence of PA. Primary lesions of PA were collected from nine patients showing subsequent recurrence and from 40 patients without recurrence during at least 10 years of follow up of the disease. Paraffin wax embedded tumour samples of the two groups were examined for the expression profiles of MUC1 (differentially glycosylated forms), MUC2, MUC4, MUC5AC, and MUC6 using immunohistochemistry. Several clinicopathological factors were also examined. In univariate analysis of the factors examined, MUC1/DF3 high expression (more than 30% of the neoplastic cells stained) in the primary lesions was seen more frequently in patients with recurrence (four of nine) than in those without recurrence (three of 40; p = 0.011). Larger tumour size (more than 3.0 cm) of the primary PA was also a significant (p = 0.035) risk factor for the recurrence of PA. In multivariate analysis, only high expression of MUC1/DF3 was found to be a significant independent risk factor for the recurrence of PA (p = 0.021). Expression of MUC1/DF3 in PA is a useful marker to predict its recurrence. Those patients with PA showing positive MUC1/DF3 expression should be followed up carefully.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Global PROTOMAP profiling to search for biomarkers of early-recurrent hepatocellular carcinoma.

PubMed

Taoka, Masato; Morofuji, Noriaki; Yamauchi, Yoshio; Ojima, Hidenori; Kubota, Daisuke; Terukina, Goro; Nobe, Yuko; Nakayama, Hiroshi; Takahashi, Nobuhiro; Kosuge, Tomoo; Isobe, Toshiaki; Kondo, Tadashi

2014-11-07

This study used global protein expression profiling to search for biomarkers to predict early recurrent hepatocellular carcinoma (HCC). HCC tissues surgically resected from patients with or without recurrence within 2 years (early recurrent) after surgery were compared with adjacent nontumor tissue and with normal liver tissue. We used the PROTOMAP strategy for comparative profiling, which integrates denaturing polyacrylamide gel electrophoresis migratory rates and high-resolution, semiquantitative mass-spectrometry-based identification of in-gel-digested tryptic peptides. PROTOMAP allows examination of global changes in the size, topography, and abundance of proteins in complex tissue samples. This approach identified 8438 unique proteins from 45 708 nonredundant peptides and generated a proteome-wide map of changes in expression and proteolytic events potentially induced by intrinsic apoptotic/necrotic pathways. In the early recurrent HCC tissue, 87 proteins were differentially expressed (≥20-fold) relative to the other tissues, 46 of which were up-regulated or specifically proteolyzed and 41 of which were down-regulated. This data set consisted of proteins that fell into various functional categories, including signal transduction and cell organization and, notably, the major catalytic pathways responsible for liver function, such as the urea cycle and detoxification metabolism. We found that aberrant proteolysis appeared to occur frequently during recurrence of HCC in several key signal transducers, including STAT1 and δ-catenin. Further investigation of these proteins will facilitate the development of novel clinical applications.

miRNA Profiles as a Predictor of Chemoresponsiveness in Wilms’ Tumor Blastema

PubMed Central

Watson, Jenny A.; Bryan, Kenneth; Williams, Richard; Popov, Sergey; Vujanic, Gordan; Coulomb, Aurore; Boccon-Gibod, Liliane; Graf, Norbert; Pritchard-Jones, Kathy; O’Sullivan, Maureen

2013-01-01

The current SIOP treatment protocol for Wilms’ tumor involves pre-operative chemotherapy followed by nephrectomy. Not all patients benefit equally from such chemotherapy. The aim of this study was to generate a miRNA profile of chemo resistant blastemal cells in high risk Wilms’ tumors which might serve as predictive markers of therapeutic response at the pre-treatment biopsy stage. We have shown here that unsupervised hierarchical clustering of genome-wide miRNA expression profiles can clearly separate intermediate risk tumors from high risk tumors. A total of 29 miRNAs were significantly differentially expressed between post-treatment intermediate risk and high risk groups, including miRNAs that have been previously linked to chemo resistance in other cancer types. Furthermore, 7 of these 29 miRNAs were already at the pre-treatment biopsy stage differentially expressed between cases ultimately deemed intermediate risk compared to high risk. These miRNA alterations include down-regulation in high risk cases of miR-193a.5p, miR-27a and the up-regulation of miR-483.5p, miR-628.5p, miR-590.5p, miR-302a and miR-367. The demonstration of such miRNA markers at the pre-treatment biopsy stage could permit stratification of patients to more tailored treatment regimens. PMID:23308219

Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

PubMed Central

Furge, Kyle A; Dykema, Karl; Petillo, David; Westphal, Michael; Zhang, Zhongfa; Kort, Eric J; Teh, Bin Tean

2007-01-01

Using high-throughput gene-expression profiling technology, we can now gain a better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup of the cancer cells. This abnormal genetic makeup can have profound effects on cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeutic agents and radiation. These approaches will lead to better molecular subclassification of tumours, the basis of personalized medicine. We have, to date, done whole-genome microarray gene-expression profiling on several hundreds of kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used to identify both cytogenetic abnormalities and molecular pathways that are deregulated in renal cell carcinoma (RCC). For example, we have identified the deregulation of the VHL-hypoxia pathway in clear-cell RCC, as previously known, and the c-Myc pathway in aggressive papillary RCC. Besides the more common clear-cell, papillary and chromophobe RCCs, we are currently characterizing the molecular signatures of rarer forms of renal neoplasia such as carcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosome Xp11 translocations associated with papillary RCC, renal medullary carcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response. PMID:18542781

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

RNA sequencing uncovers antisense RNAs and novel small RNAs in Streptococcus pyogenes.

PubMed

Le Rhun, Anaïs; Beer, Yan Yan; Reimegård, Johan; Chylinski, Krzysztof; Charpentier, Emmanuelle

2016-01-01

Streptococcus pyogenes is a human pathogen responsible for a wide spectrum of diseases ranging from mild to life-threatening infections. During the infectious process, the temporal and spatial expression of pathogenicity factors is tightly controlled by a complex network of protein and RNA regulators acting in response to various environmental signals. Here, we focus on the class of small RNA regulators (sRNAs) and present the first complete analysis of sRNA sequencing data in S. pyogenes. In the SF370 clinical isolate (M1 serotype), we identified 197 and 428 putative regulatory RNAs by visual inspection and bioinformatics screening of the sequencing data, respectively. Only 35 from the 197 candidates identified by visual screening were assigned a predicted function (T-boxes, ribosomal protein leaders, characterized riboswitches or sRNAs), indicating how little is known about sRNA regulation in S. pyogenes. By comparing our list of predicted sRNAs with previous S. pyogenes sRNA screens using bioinformatics or microarrays, 92 novel sRNAs were revealed, including antisense RNAs that are for the first time shown to be expressed in this pathogen. We experimentally validated the expression of 30 novel sRNAs and antisense RNAs. We show that the expression profile of 9 sRNAs including 2 predicted regulatory elements is affected by the endoribonucleases RNase III and/or RNase Y, highlighting the critical role of these enzymes in sRNA regulation.

Changes in miRNA expression profile of space-flown Caenorhabditis elegans during Shenzhou-8 mission

NASA Astrophysics Data System (ADS)

Xu, Dan; Gao, Ying; Huang, Lei; Sun, Yeqing

2014-04-01

Recent advances in the field of molecular biology have demonstrated that small non-coding microRNAs (miRNAs) have a broad effect on gene expression networks and play a key role in biological responses to environmental stressors. However, little is known about how space radiation exposure and altered gravity affect miRNA expression. The "International Space Biological Experiments" project was carried out in November 2011 by an international collaboration between China and Germany during the Shenzhou-8 (SZ-8) mission. To study the effects of spaceflight on Caenorhabditis elegans (C. elegans), we explored the expression profile miRNA changes in space-flown C. elegans. Dauer C. elegans larvae were taken by SZ-8 spacecraft and experienced the 16.5-day shuttle spaceflight. We performed miRNA microarray analysis, and the results showed that 23 miRNAs were altered in a complex space environment and different expression patterns were observed in the space synthetic and radiation environments. Most putative target genes of the altered miRNAs in the space synthetic environment were predicted to be involved in developmental processes instead of in the regulation of transcription, and the enrichment of these genes was due to space radiation. Furthermore, integration analysis of the miRNA and mRNA expression profiles confirmed that twelve genes were differently regulated by seven miRNAs. These genes may be involved in embryonic development, reproduction, transcription factor activity, oviposition in a space synthetic environment, positive regulation of growth and body morphogenesis in a space radiation environment. Specifically, we found that cel-miR-52, -55, and -56 of the miR-51 family were sensitive to space environmental stressors and could regulate biological behavioural responses and neprilysin activity through the different isoforms of T01C4.1 and F18A12.8. These findings suggest that C. elegans responded to spaceflight by altering the expression of miRNAs and some target genes that function in diverse regulatory pathways.

Electric pulses used in electrochemotherapy and electrogene therapy do not significantly change the expression profile of genes involved in the development of cancer in malignant melanoma cells

PubMed Central

2009-01-01

Background Electroporation is a versatile method for in vitro or in vivo delivery of different molecules into cells. However, no study so far has analysed the effects of electric pulses used in electrochemotherapy (ECT pulses) or electric pulses used in electrogene therapy (EGT pulses) on malignant cells. We studied the effect of ECT and EGT pulses on human malignant melanoma cells in vitro in order to understand and predict the possible effect of electric pulses on gene expression and their possible effect on cell behaviour. Methods We used microarrays with 2698 different oligonucleotides to obtain the expression profile of genes involved in apoptosis and cancer development in a malignant melanoma cell line (SK-MEL28) exposed to ECT pulses and EGT pulses. Results Cells exposed to ECT pulses showed a 68.8% average survival rate, while cells exposed to EGT pulses showed a 31.4% average survival rate. Only seven common genes were found differentially expressed in cells 16 h after exposure to ECT and EGT pulses. We found that ECT and EGT pulses induce an HSP70 stress response mechanism, repress histone protein H4, a major protein involved in chromatin assembly, and down-regulate components involved in protein synthesis. Conclusion Our results show that electroporation does not significantly change the expression profile of major tumour suppressor genes or oncogenes of the cell cycle. Moreover, electroporation also does not changes the expression of genes involved in the stability of DNA, supporting current evidence that electroporation is a safe method that does not promote tumorigenesis. However, in spite of being considered an isothermal method, it does to some extent induce stress, which resulted in the expression of the environmental stress response mechanism, HSP70. PMID:19709437

Triple-Negative or HER2-Positive Status Predicts Higher Rates of Locoregional Recurrence in Node-Positive Breast Cancer Patients After Mastectomy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Shulian; Li Yexiong, E-mail: yexiong@yahoo.com; Song Yongwen

2011-07-15

Purpose: To evaluate the prognostic value of determining estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) expression in node-positive breast cancer patients treated with mastectomy. Methods and Materials: The records of 835 node-positive breast cancer patients who had undergone mastectomy between January 2000 and December 2004 were analyzed retrospectively. Of these, 764 patients (91.5%) received chemotherapy; 68 of 398 patients (20.9%) with T1-2N1 disease and 352 of 437 patients (80.5%) with T3-4 or N2-3 disease received postoperative radiotherapy. Patients were classified into four subgroups according to hormone receptor (Rec+ or Rec-) and HER2 expression profiles:more » Rec-/HER2- (triple negative; n = 141), Rec-/HER2+ (n = 99), Rec+/HER2+ (n = 157), and Rec+/HER2- (n = 438). The endpoints were the duration of locoregional recurrence-free survival, distant metastasis-free survival, disease-free survival, and overall survival. Results: Patients with triple-negative, Rec-/HER2+, and Rec+/HER2+ expression profiles had a significantly lower 5-year locoregional recurrence-free survival than those with Rec+/HER2- profiles (86.5% vs. 93.6%, p = 0.002). Compared with those with Rec+/HER2+ and Rec+/HER2- profiles, patients with Rec-/HER2- and Rec-/HER2+ profiles had significantly lower 5-year distant metastasis-free survival (69.1% vs. 78.5%, p = 0.000), lower disease-free survival (66.6% vs. 75.6%, p = 0.000), and lower overall survival (71.4% vs. 84.2%, p = 0.000). Triple-negative or Rec-/HER2+ breast cancers had an increased likelihood of relapse and death within the first 3 years after treatment. Conclusions: Triple-negative and HER2-positive profiles are useful markers of prognosis for locoregional recurrence and survival in node-positive breast cancer patients treated with mastectomy.« less

High WT1 expression is an early predictor for relapse in patients with acute promyelocytic leukemia in first remission with negative PML-RARa after anthracycline-based chemotherapy: a single-center cohort study.

PubMed

Yoon, Jae-Ho; Kim, Hee-Je; Kwak, Dae-Hun; Park, Sung-Soo; Jeon, Young-Woo; Lee, Sung-Eun; Cho, Byung-Sik; Eom, Ki-Seong; Kim, Yoo-Jin; Lee, Seok; Min, Chang-Ki; Cho, Seok-Goo; Kim, Dong-Wook; Lee, Jong Wook; Min, Woo-Sung

2017-01-23

Wilms' tumor gene 1 (WT1) expression is a well-known predictor for relapse in acute myeloid leukemia. We monitored WT1 decrement along the treatment course to identify its significant role as a marker for residual disease in acute promyelocytic leukemia (APL) and tried to suggest its significance for relapse prediction. In this single center retrospective study, we serially measured PML-RARa and WT1 expression from 117 APL patients at diagnosis, at post-induction and post-consolidation chemotherapies, and at every 3 months after starting maintenance therapy. All 117 patients were in molecular remission after treatment of at least 2 consolidation chemotherapies. We used WT1 ProfileQuant™ kit (Ipsogen) for WT1 monitoring. High WT1 expression (>120 copies/10 4 ABL1) after consolidation and at early period (3 months) after maintenance therapy significantly predicted subsequent relapse. All paired PML-RARa RQ-PCR were not detected except for one sample with early relapse. Patients with high WT1 expression at 3 months after maintenance therapy (n = 40) showed a significantly higher relapse rate (30.5 vs. 6.9%, P < 0.001) and inferior disease free survival (62.8 vs. 91.4%, P < 0.001). Multivariate analysis revealed that high peak leukocyte counts at diagnosis (HR = 6.4, P < 0.001) and high WT1 expression at 3 months after maintenance therapy (HR = 7.1, P < 0.001) were significant factors for prediction of relapse. Our data showed high post-remission WT1 expression was a reliable marker for prediction of subsequent molecular relapse in APL. In this high-risk group, early intervention with ATRA ± ATO, anti-CD33 antibody therapy, and WT1-specific therapy may be used for relapse prevention. Clinical Research Information Service (CRIS), KCT0002079.

Predicting human genetic interactions from cancer genome evolution.

PubMed

Lu, Xiaowen; Megchelenbrink, Wout; Notebaart, Richard A; Huynen, Martijn A

2015-01-01

Synthetic Lethal (SL) genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75) for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

Predictive value of serum ALT and T-cell receptor beta variable chain for HBeAg seroconversion in chronic hepatitis B patients during tenofovir treatment.

PubMed

Yang, Jiezuan; Yan, Dong; Guo, Renyong; Chen, Jiajia; Li, Yongtao; Fan, Jun; Fu, Xuyan; Yao, Xinsheng; Diao, Hongyan; Li, Lanjuan

2017-03-01

Effective antiviral therapy plays a key role in slowing the progression of chronic hepatitis B (CHB). Identification of serum indices, including hepatitis B e antigen (HBeAg) expression and seroconversion, will facilitate evaluation of the efficacy of antiviral therapy in HBeAg-positive CHB patients. The biochemical, serological, virological parameters, and the frequency of circulating CD4CD25 regulatory T cell (Treg) in 32 patients were measured at baseline and every 12 weeks during 96 weeks of tenofovir disoproxil fumarate (TDF) treatment. The relationship between the hepatitis B virus (HBV) deoxyribonucleic acid (DNA) and Treg and alanine aminotransferase (ALT) levels was analyzed, respectively. The molecular profiles of T-cell receptor beta variable chain (TRBV) were determined using gene melting spectral pattern. For the seroconverted 12 patients, ALT declined to normal levels by week 24 and remained at this level in subsequent treatment; moreover, the predictive cutoff value of ALT for HBeAg seroconversion (SC) was 41.5 U/L at week 24. The positive correlation between HBV DNA and Treg and ALT was significant in SC patients, but not in non-SC patients. Six TRBV families (BV3, BV11, BV12, BV14, BV20, and BV24) were predominantly expressed in SC patients at baseline. The decline of ALT could be used to predict HBeAg seroconversion for CHB patients during TDF treatment. In addition, the profile of Tregs and TRBVs may be associated with HBeAg seroconversion and could also be a potential indicator for predicting HBeAg SC and treatment outcome for CHB patients.

Chemotherapy of colorectal liver metastases induces a rapid rise in intermediate blood monocytes which predicts treatment response

PubMed Central

Schauer, Dominic; Starlinger, Patrick; Alidzanovic, Lejla; Zajc, Philipp; Maier, Thomas; Feldman, Alexandra; Padickakudy, Robin; Buchberger, Elisabeth; Elleder, Vanessa; Spittler, Andreas; Stift, Judith; Pop, Lorand; Gruenberger, Birgit; Gruenberger, Thomas; Brostjan, Christine

2016-01-01

ABSTRACT We have previously reported that intermediate monocytes (CD14++/CD16+) were increased in colorectal cancer (CRC) patients, while the subset of pro-angiogenic TIE2-expressing monocytes (TEMs) was not significantly elevated. This study was designed to evaluate changes in frequency and function of intermediate monocytes and TEMs during chemotherapy and anti-angiogenic cancer treatment and their relation to treatment response. Monocyte populations were determined by flow cytometry in 60 metastasized CRC (mCRC) patients who received neoadjuvant chemotherapy with or without bevacizumab. Blood samples were taken before treatment, after two therapy cycles, at the end of neoadjuvant therapy and immediately before surgical resection of liver metastases. Neoadjuvant treatment resulted in a significant increase in circulating intermediate monocytes which was most pronounced after two cycles and positively predicted tumor response (AUC = 0.875, p = 0.005). With a cut-off value set to 1% intermediate monocytes of leukocytes, this parameter showed a predictive sensitivity and specificity of 75% and 88%. Anti-angiogenic therapy with bevacizumab had no impact on monocyte populations including TEMs. In 15 patients and six healthy controls, the gene expression profile and the migratory behavior of monocyte subsets was evaluated. The profile of intermediate monocytes suggested functions in antigen presentation, inflammatory cytokine production, chemotaxis and was remarkably stable during chemotherapy. Intermediate monocytes showed a preferential migratory response to tumor-derived signals in vitro and correlated with the level of CD14+/CD16+ monocytic infiltrates in the resected tumor tissue. In conclusion, the rapid rise of intermediate monocytes during chemotherapy may offer a simple marker for response prediction and a timely change in regimen. PMID:27471631

Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT).

PubMed

Saiag, P; Gutzmer, R; Ascierto, P A; Maio, M; Grob, J-J; Murawa, P; Dreno, B; Ross, M; Weber, J; Hauschild, A; Rutkowski, P; Testori, A; Levchenko, E; Enk, A; Misery, L; Vanden Abeele, C; Vojtek, I; Peeters, O; Brichard, V G; Therasse, P

2016-10-01

Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. An open-label prospective phase II trial ('PREDICT') in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS- populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS- patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS-). There was one complete response (GS-) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS- and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study.This study is registered at www.clinicatrials.gov NCT00942162. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

The Landscape of Circular RNA Expression Profiles in Papillary Thyroid Carcinoma Based on RNA Sequencing.

PubMed

Lan, Xiabin; Xu, Jiajie; Chen, Chao; Zheng, Chuanming; Wang, Jiafeng; Cao, Jun; Zhu, Xuhang; Ge, Minghua

2018-05-25

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, the molecular mechanisms responsible for its tumorigenesis and progression remain largely unknown. Circular RNA (circRNA) is a novel type of noncoding RNA that can serve as an ideal biomarker due to its stability. Recent evidence suggests that circRNAs play important roles in tumorigenesis. This study aims to investigate circRNA expression profiles and their potential biological functions in PTC. High-throughput RNA sequencing was used to assess circRNA expression profiles in PTC, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate dysregulated circRNAs. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of circRNAs for PTC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed circRNAs. Bioinformatic analyses were applied to predict interactions between circRNAs and microRNAs (miRNAs), and a circRNA-miRNA-mRNA network was constructed using Cytoscape software. We identified a number of differentially expressed circRNAs in PTC tissues compared with paired normal thyroid tissues, with chr5: 160757890-160763776-, chr12: 40696591-40697936+, chr7: 22330794-22357656-, and chr21: 16386665-16415895- being upregulated, and chr7: 91924203-91957214+, chr2: 179514891-179516047-, chr9: 16435553-16437522-, and chr22: 36006931-36007153- being downregulated. These findings were confirmed by qRT-PCR, and ROC curves indicated that they can serve as potential biomarkers for PTC. GO and KEGG pathway analyses showed that some of these circRNAs are related to cancers. Additionally, bioinformatic analyses revealed a potential competing-endogenous-RNA-regulating network among circRNAs, miRNAs, and mRNAs. Our study results depict the landscape of circRNA expression profiles in PTC and also provide potential biomarkers for PTC. Further functional and mechanistic studies of these circRNAs may improve our understanding of PTC tumorigenesis. © 2018 The Author(s). Published by S. Karger AG, Basel.

Global Gene Expression Profiling in PAI-1 Knockout Murine Heart and Kidney: Molecular Basis of Cardiac-Selective Fibrosis

PubMed Central

Ghosh, Asish K.; Murphy, Sheila B.; Kishore, Raj; Vaughan, Douglas E.

2013-01-01

Fibrosis is defined as an abnormal matrix remodeling due to excessive synthesis and accumulation of extracellular matrix proteins in tissues during wound healing or in response to chemical, mechanical and immunological stresses. At present, there is no effective therapy for organ fibrosis. Previous studies demonstrated that aged plasminogen activator inhibitor-1(PAI-1) knockout mice develop spontaneously cardiac-selective fibrosis without affecting any other organs. We hypothesized that differential expressions of profibrotic and antifibrotic genes in PAI-1 knockout hearts and unaffected organs lead to cardiac selective fibrosis. In order to address this prediction, we have used a genome-wide gene expression profiling of transcripts derived from aged PAI-1 knockout hearts and kidneys. The variations of global gene expression profiling were compared within four groups: wildtype heart vs. knockout heart; wildtype kidney vs. knockout kidney; knockout heart vs. knockout kidney and wildtype heart vs. wildtype kidney. Analysis of illumina-based microarray data revealed that several genes involved in different biological processes such as immune system processing, response to stress, cytokine signaling, cell proliferation, adhesion, migration, matrix organization and transcriptional regulation were affected in hearts and kidneys by the absence of PAI-1, a potent inhibitor of urokinase and tissue-type plasminogen activator. Importantly, the expressions of a number of genes, involved in profibrotic pathways including Ankrd1, Pi16, Egr1, Scx, Timp1, Timp2, Klf6, Loxl1 and Klotho, were deregulated in PAI-1 knockout hearts compared to wildtype hearts and PAI-1 knockout kidneys. While the levels of Ankrd1, Pi16 and Timp1 proteins were elevated during EndMT, the level of Timp4 protein was decreased. To our knowledge, this is the first comprehensive report on the influence of PAI-1 on global gene expression profiling in the heart and kidney and its implication in fibrogenesis and several other biological processes. The significance of these observations in the light of heart-specific profibrotic signaling and fibrogenesis are discussed. PMID:23724005

Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data.

PubMed

Racle, Julien; de Jonge, Kaat; Baumgaertner, Petra; Speiser, Daniel E; Gfeller, David

2017-11-13

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

Gene expression profiles of peripheral blood mononuclear cells reveal transcriptional signatures as novel biomarkers of cardiac remodeling in rats with aldosteronism and hypertensive heart disease.

PubMed

Gerling, Ivan C; Ahokas, Robert A; Kamalov, German; Zhao, Wenyuan; Bhattacharya, Syamal K; Sun, Yao; Weber, Karl T

2013-12-01

In searching for a noninvasive surrogate tissue mimicking the pro-oxidant/proinflammatory hypertensive heart disease (HHD) phenotype, we turned to peripheral blood mononuclear cells (PBMCs). We tested whether iterations in [Ca2+]i, [Zn2+]i, and oxidative stress in cardiomyocytes and PBMCs would complement each other, eliciting similar shifts in gene expression profiles in these tissues demonstrable during the preclinical (week 1) and pathological (week 4) stages of aldosterone/salt treatment (ALDOST). Inappropriate neurohormonal activation contributes to pathological remodeling of myocardium in HHD associated with aldosteronism. In rats receiving long-term ALDOST, evidence of reparative fibrosis replacing necrotic cardiomyocytes and coronary vasculopathy appears at week 4 associated with the induction of oxidative stress by mitochondria that overwhelms endogenous, largely Zn2+-based, antioxidant defenses. Biomarker-guided prediction of risk before the appearance of cardiac pathology would prove invaluable. In PBMCs and cardiomyocytes, quantitation of cytoplasmic free Ca2+ and Zn2+, H2O2, and 8-iosprostane levels and isolation of ribonucleic acid (RNA) and gene expression together with statistical and clustering analyses and confirmation of genes by in situ hybridization and reverse-transcription polymerase chain reaction were performed. Compared with controls, at weeks 1 and 4 of ALDOST, we found comparable increments in [Ca2+]i, [Zn2+]i, and 8-isoprotane coupled with increased H2O2 production in cardiac mitochondria and PBMCs, together with the common networks of expression profiles dominated by genes involved in oxidative stress, inflammation, and repair. These included 3 central Ingenuity pathway-linked genes: p38 mitogen-activated protein kinase, a stress-responsive protein; nuclear factor-κB, a redox-sensitive transcription factor and a proinflammatory cascade that it regulates; and transforming growth factor-β1, a fibrogenic cytokine involved in tissue repair. Significant overlapping demonstrated in the molecular mimicry of PBMCs and cardiomyocytes during preclinical and pathological stages of ALDOST implies that transcriptional signatures of PBMCs may serve as early noninvasive and novel sentinels predictive of impending pathological remodeling in HHD.

CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets

PubMed Central

Li, Yang; Liu, Jun S.; Mootha, Vamsi K.

2017-01-01

In recent years, there has been a huge rise in the number of publicly available transcriptional profiling datasets. These massive compendia comprise billions of measurements and provide a special opportunity to predict the function of unstudied genes based on co-expression to well-studied pathways. Such analyses can be very challenging, however, since biological pathways are modular and may exhibit co-expression only in specific contexts. To overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression. CLIC accepts as input a pathway consisting of two or more genes. It then uses a Bayesian partition model to simultaneously partition the input gene set into coherent co-expressed modules (CEMs), while assigning the posterior probability for each dataset in support of each CEM. CLIC then expands each CEM by scanning the transcriptome for additional co-expressed genes, quantified by an integrated log-likelihood ratio (LLR) score weighted for each dataset. As a byproduct, CLIC automatically learns the conditions (datasets) within which a CEM is operative. We implemented CLIC using a compendium of 1774 mouse microarray datasets (28628 microarrays) or 1887 human microarray datasets (45158 microarrays). CLIC analysis reveals that of 910 canonical biological pathways, 30% consist of strongly co-expressed gene modules for which new members are predicted. For example, CLIC predicts a functional connection between protein C7orf55 (FMC1) and the mitochondrial ATP synthase complex that we have experimentally validated. CLIC is freely available at www.gene-clic.org. We anticipate that CLIC will be valuable both for revealing new components of biological pathways as well as the conditions in which they are active. PMID:28719601

Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer.

PubMed

Gianni, Luca; Zambetti, Milvia; Clark, Kim; Baker, Joffre; Cronin, Maureen; Wu, Jenny; Mariani, Gabriella; Rodriguez, Jaime; Carcangiu, Marialuisa; Watson, Drew; Valagussa, Pinuccia; Rouzier, Roman; Symmans, W Fraser; Ross, Jeffrey S; Hortobagyi, Gabriel N; Pusztai, Lajos; Shak, Steven

2005-10-10

We sought to identify gene expression markers that predict the likelihood of chemotherapy response. We also tested whether chemotherapy response is correlated with the 21-gene Recurrence Score assay that quantifies recurrence risk. Patients with locally advanced breast cancer received neoadjuvant paclitaxel and doxorubicin. RNA was extracted from the pretreatment formalin-fixed paraffin-embedded core biopsies. The expression of 384 genes was quantified using reverse transcriptase polymerase chain reaction and correlated with pathologic complete response (pCR). The performance of genes predicting for pCR was tested in patients from an independent neoadjuvant study where gene expression was obtained using DNA microarrays. Of 89 assessable patients (mean age, 49.9 years; mean tumor size, 6.4 cm), 11 (12%) had a pCR. Eighty-six genes correlated with pCR (unadjusted P < .05); pCR was more likely with higher expression of proliferation-related genes and immune-related genes, and with lower expression of estrogen receptor (ER) -related genes. In 82 independent patients treated with neoadjuvant paclitaxel and doxorubicin, DNA microarray data were available for 79 of the 86 genes. In univariate analysis, 24 genes correlated with pCR with P < .05 (false discovery, four genes) and 32 genes showed correlation with P < .1 (false discovery, eight genes). The Recurrence Score was positively associated with the likelihood of pCR (P = .005), suggesting that the patients who are at greatest recurrence risk are more likely to have chemotherapy benefit. Quantitative expression of ER-related genes, proliferation genes, and immune-related genes are strong predictors of pCR in women with locally advanced breast cancer receiving neoadjuvant anthracyclines and paclitaxel.

Omic personality: implications of stable transcript and methylation profiles for personalized medicine.

PubMed

Tabassum, Rubina; Sivadas, Ambily; Agrawal, Vartika; Tian, Haozheng; Arafat, Dalia; Gibson, Greg

2015-08-13

Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes. Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness. Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression. People express an "omic personality" consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

Expression of p53 and Bcl-xL as predictive markers for larynx preservation in advanced laryngeal cancer

PubMed Central

Kumar, Bhavna; Cordell, Kitrina G.; D’Silva, Nisha; Prince, Mark E.; Adams, Meredith E.; Fisher, Susan G.; Wolf, Gregory T.; Carey, Thomas E.; Bradford, Carol R.

2012-01-01

Objective To assess tumor markers in advanced laryngeal cancer. Design Marker expression and clinical outcome. Setting Laboratory. Patients Pretreatment tumor biopsies were analyzed from patients enrolled in the Department of Veterans Affairs laryngeal cancer trial. Main Outcome Measures Expression of p53 and Bcl-xL in pretreatment biopsies was assessed for correlation with chemotherapy response, laryngeal preservation, and survival. Results Higher rates of larynx preservation were observed in patients whose tumors expressed p53 versus those that did not (73% versus 53%, p = 0.0304). Higher rates of larynx preservation were also observed in patients whose tumors expressed low levels of Bcl-xL versus those that expressed high levels (90% versus 60%, p = 0.02). Patients were then categorized into 3 risk groups (low, intermediate and high risk) based on their tumor p53 and Bcl-xL expression status. We observed that patients whose tumors had the high risk biomarker profile (low p53 and high Bcl-xL) were less likely to preserve their larynx than patients whose tumors had the intermediate risk (high p53 and low or high Bcl-xL) or low risk (low p53 and low Bcl-xL) biomarker profile. The larynx preservation rates were 100%, 76% and 54% for the low, intermediate and high risk groups respectively (Fisher exact 0.039). Conclusions Tumor expression of p53 and Bcl-xL is a strong predictor of successful organ preservation in patients treated with induction chemotherapy followed by radiation in responding tumors. PMID:18427001

Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

PubMed

Nelson, Peter T; Wang, Wang-Xia; Wilfred, Bernard R; Tang, Guiliang

2008-11-01

MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies.

Gene expression profiling in Ishikawa cells: A fingerprint for estrogen active compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boehme, Kathleen; Simon, Stephanie; Mueller, Stefan O.

2009-04-01

Several anthropogenous and naturally occurring substances, referred to as estrogen active compounds (EACs), are able to interfere with hormone and in particular estrogen receptor signaling. EACs can either cause adverse health effects in humans and wildlife populations or have beneficial effects on estrogen-dependent diseases. The aim of this study was to examine global gene expression profiles in estrogen receptor (ER)-proficient Ishikawa plus and ER-deficient Ishikawa minus endometrial cancer cells treated with selected well-known EACs (Diethylstilbestrol, Genistein, Zearalenone, Resveratrol, Bisphenol A and o,p'-DDT). We also investigated the effect of the pure antiestrogen ICI 182,780 (ICI) on the expression patterns caused bymore » these compounds. Transcript levels were quantified 24 h after compound treatment using Illumina BeadChip Arrays. We identified 87 genes with similar expression changes in response to all EAC treatments in Ishikawa plus. ICI lowered the magnitude or reversed the expression of these genes, indicating ER dependent regulation. Apart from estrogenic gene regulation, Bisphenol A, o,p'-DDT, Zearalenone, Genistein and Resveratrol displayed similarities to ICI in their expression patterns, suggesting mixed estrogenic/antiestrogenic properties. In particular, the predominant antiestrogenic expression response of Resveratrol could be clearly distinguished from the other test compounds, indicating a distinct mechanism of action. Divergent gene expression patterns of the phytoestrogens, as well as weaker estrogenic gene expression regulation determined for the anthropogenous chemicals Bisphenol A and o,p'-DDT, warrants a careful assessment of potential detrimental and/or beneficial effects of EACs. The characteristic expression fingerprints and the identified subset of putative marker genes can be used for screening chemicals with an unknown mode of action and for predicting their potential to exert endocrine disrupting effects.« less

Dexamethasone Stimulated Gene Expression in Peripheral Blood is a Sensitive Marker for Glucocorticoid Receptor Resistance in Depressed Patients

PubMed Central

Menke, Andreas; Arloth, Janine; Pütz, Benno; Weber, Peter; Klengel, Torsten; Mehta, Divya; Gonik, Mariya; Rex-Haffner, Monika; Rubel, Jennifer; Uhr, Manfred; Lucae, Susanne; Deussing, Jan M; Müller-Myhsok, Bertram; Holsboer, Florian; Binder, Elisabeth B

2012-01-01

Although gene expression profiles in peripheral blood in major depression are not likely to identify genes directly involved in the pathomechanism of affective disorders, they may serve as biomarkers for this disorder. As previous studies using baseline gene expression profiles have provided mixed results, our approach was to use an in vivo dexamethasone challenge test and to compare glucocorticoid receptor (GR)-mediated changes in gene expression between depressed patients and healthy controls. Whole genome gene expression data (baseline and following GR-stimulation with 1.5 mg dexamethasone p.o.) from two independent cohorts were analyzed to identify gene expression pattern that would predict case and control status using a training (N=18 cases/18 controls) and a test cohort (N=11/13). Dexamethasone led to reproducible regulation of 2670 genes in controls and 1151 transcripts in cases. Several genes, including FKBP5 and DUSP1, previously associated with the pathophysiology of major depression, were found to be reliable markers of GR-activation. Using random forest analyses for classification, GR-stimulated gene expression outperformed baseline gene expression as a classifier for case and control status with a correct classification of 79.1 vs 41.6% in the test cohort. GR-stimulated gene expression performed best in dexamethasone non-suppressor patients (88.7% correctly classified with 100% sensitivity), but also correctly classified 77.3% of the suppressor patients (76.7% sensitivity), when using a refined set of 19 genes. Our study suggests that in vivo stimulated gene expression in peripheral blood cells could be a promising molecular marker of altered GR-functioning, an important component of the underlying pathology, in patients suffering from depressive episodes. PMID:22237309

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

PubMed

Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

2007-07-01

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

Psmir: a database of potential associations between small molecules and miRNAs

PubMed Central

Meng, Fanlin; Wang, Jing; Dai, Enyu; Yang, Feng; Chen, Xiaowen; Wang, Shuyuan; Yu, Xuexin; Liu, Dianming; Jiang, Wei

2016-01-01

miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds can affect miRNA expression. Thus, prediction of associations between small molecules and miRNAs is important for investigation of miRNA-targeted drugs. Here, we analyzed 39 miRNA-perturbed gene expression profiles, and then calculated the similarity of transcription responses between miRNA perturbation and drug treatment to predict drug-miRNA associations. At the significance level of 0.05, we obtained 6501 candidate associations between 1295 small molecules and 25 miRNAs, which included 624 FDA approved drugs. Finally, we constructed the Psmir database to store all potential associations and the related materials. In a word, Psmir served as a valuable resource for dissecting the biological significance in small molecules’ effects on miRNA expression, which will facilitate developing novel potential therapeutic targets or treatments for human cancers. Psmir is supported by all major browsers, and is freely available at http://www.bio-bigdata.com/Psmir/. PMID:26759061

Psmir: a database of potential associations between small molecules and miRNAs.

PubMed

Meng, Fanlin; Wang, Jing; Dai, Enyu; Yang, Feng; Chen, Xiaowen; Wang, Shuyuan; Yu, Xuexin; Liu, Dianming; Jiang, Wei

2016-01-13

miRNAs are key post-transcriptional regulators of many essential biological processes, and their dysregulation has been validated in almost all human cancers. Restoring aberrantly expressed miRNAs might be a novel therapeutics. Recently, many studies have demonstrated that small molecular compounds can affect miRNA expression. Thus, prediction of associations between small molecules and miRNAs is important for investigation of miRNA-targeted drugs. Here, we analyzed 39 miRNA-perturbed gene expression profiles, and then calculated the similarity of transcription responses between miRNA perturbation and drug treatment to predict drug-miRNA associations. At the significance level of 0.05, we obtained 6501 candidate associations between 1295 small molecules and 25 miRNAs, which included 624 FDA approved drugs. Finally, we constructed the Psmir database to store all potential associations and the related materials. In a word, Psmir served as a valuable resource for dissecting the biological significance in small molecules' effects on miRNA expression, which will facilitate developing novel potential therapeutic targets or treatments for human cancers. Psmir is supported by all major browsers, and is freely available at http://www.bio-bigdata.com/Psmir/.

Identification of Transcription Factors ZmMYB111 and ZmMYB148 Involved in Phenylpropanoid Metabolism.

PubMed

Zhang, Junjie; Zhang, Shuangshuang; Li, Hui; Du, Hai; Huang, Huanhuan; Li, Yangping; Hu, Yufeng; Liu, Hanmei; Liu, Yinghong; Yu, Guowu; Huang, Yubi

2016-01-01

Maize is the leading crop worldwide in terms of both planting area and total yields, but environmental stresses cause significant losses in productivity. Phenylpropanoid compounds play an important role in plant stress resistance; however, the mechanism of their synthesis is not fully understood, especially in regard to the expression and regulation of key genes. Phenylalanine ammonia-lyase (PAL) is the first key enzyme involved in phenylpropanoid metabolism, and it has a significant effect on the synthesis of important phenylpropanoid compounds. According to the results of sequence alignments and functional prediction, we selected two conserved R2R3-MYB transcription factors as candidate genes for the regulation of phenylpropanoid metabolism. The two candidate R2R3-MYB genes, which we named ZmMYB111 and ZmMYB148, were cloned, and then their structural characteristics and phylogenetic placement were predicted and analyzed. In addition, a series of evaluations were performed, including expression profiles, subcellular localization, transcription activation, protein-DNA interaction, and transient expression in maize endosperm. Our results indicated that both ZmMYB111 and ZmMYB148 are indeed R2R3-MYB transcription factors and that they may play a regulatory role in PAL gene expression.

An efficient numerical procedure for thermohydrodynamic analysis of cavitating bearings

NASA Technical Reports Server (NTRS)

Vijayaraghavan, D.

1995-01-01

An efficient and accurate numerical procedure to determine the thermo-hydrodynamic performance of cavitating bearings is described. This procedure is based on the earlier development of Elrod for lubricating films, in which the properties across the film thickness are determined at Lobatto points and their distributions are expressed by collocated polynomials. The cavitated regions and their boundaries are rigorously treated. Thermal boundary conditions at the surfaces, including heat dissipation through the metal to the ambient, are incorporated. Numerical examples are presented comparing the predictions using this procedure with earlier theoretical predictions and experimental data. With a few points across the film thickness and across the journal and the bearing in the radial direction, the temperature profile is very well predicted.

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

PubMed Central

Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D

2007-01-01

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344

Potential of gene expression profiling in the management of childhood acute lymphoblastic leukemia.

PubMed

Bhojwani, Deepa; Moskowitz, Naomi; Raetz, Elizabeth A; Carroll, William L

2007-01-01

Childhood acute lymphoblastic leukemia (ALL) is a heterogeneous disease. Current treatment approaches are tailored according to the clinical features of the host, genotypic features of the leukemic blast, and early response to therapy. Although these approaches have been successful in dramatically improving outcomes, approximately 20% of children with ALL still relapse and many of these children do not have an identifiable adverse risk factor at presentation. Further insights into the biologic basis of the disease may contribute to novel, rational treatment strategies. Childhood ALL has served as an example for demonstrating the feasibility and potential of high-throughput technologies such as global gene expression or transcript profiling. In the last decade or so, utilization of these techniques has grown exponentially. As the methodology undergoes refinement and validation, it is plausible that microarrays may be used in the routine management of childhood ALL in the next few years. This article discusses the numerous applications to date of gene expression profiling in childhood ALL. Multiple investigators have made it evident that microarrays can be used as a single platform for the accurate classification of ALL into the various cytogenetic subtypes. Additional promising utilities include prediction of early response to therapy, overall outcome, and adverse effects. Identification of patients who are predicted to have an unfavorable outcome may allow for early intervention such as intensification of therapy or avoidance of drugs that are associated with specific secondary effects such as therapy-related acute myelogenous leukemia. Knowledge has been gained into pathways contributing to leukemogenesis and chemoresistance. Therapeutic targets have been identified, some of which are entering clinical trials following validation in additional preclinical models. These newer methods of genome analyses complemented by studies involving the proteome as well as host polymorphisms will have a profound impact on the diagnosis and management of childhood ALL.

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

Clinical utility of gene expression profiling data for clinical decision-making regarding adjuvant therapy in early stage, node-negative breast cancer: a case report.

PubMed

Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W

2012-09-10

Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.

Serum proteomic profiling for autism using magnetic bead-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry: a pilot study.

PubMed

Chen, Yan-Ni; Du, Hui-Ying; Shi, Zhuo-Yue; He, Li; He, Yu-Ying; Wang, Duan

2018-01-24

The pathogenesis of autism spectrum disorders remains elusive and currently there are no diagnostic or predictive biomarkers in autism available. Proteomic profiling has been used in a wide range of neurodevelopmental disorder studies, which could produce deeper perceptions of the molecular bases behind certain disease and potentially becomes useful in discovering biomarkers in autism spectrum disorders. Serum samples were collected from autistic children about 3 years old in age (n = 32) and healthy controls (n = 20) in similar age and gender. The samples were identified specific proteins that are differentially expressed by magnetic bead-based pre-fractionation and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS). Eight protein peaks were significantly different in autistic children from the healthy controls (P < 0.0001). The two peaks with the most significant differences were 6428 and 7758 Da in size. According to differences in serum protein profiles between the autistic children and healthy controls, this study identified a set of differentially expressed proteins those are significant for further evaluation and might function as biomarkers in autism.

Race Does Not Predict Melanocyte Heterogeneous Responses to Dermal Fibroblast-Derived Mediators

PubMed Central

Sirimahachaiyakul, Pornthep; Sood, Ravi F.; Muffley, Lara A.; Seaton, Max; Lin, Cheng-Ta; Qiao, Liang; Armaly, Jeffrey S.; Hocking, Anne M.; Gibran, Nicole S.

2015-01-01

Introduction Abnormal pigmentation following cutaneous injury causes significant patient distress and represents a barrier to recovery. Wound depth and patient characteristics influence scar pigmentation. However, we know little about the pathophysiology leading to hyperpigmentation in healed shallow wounds and hypopigmentation in deep dermal wound scars. We sought to determine whether dermal fibroblast signaling influences melanocyte responses. Methods and Materials Epidermal melanocytes from three Caucasians and three African-Americans were genotyped for single nucleotide polymorphisms (SNPs) across the entire genome. Melanocyte genetic profiles were determined using principal component analysis. We assessed melanocyte phenotype and gene expression in response to dermal fibroblast-conditioned medium and determined potential mesenchymal mediators by proteome profiling the fibroblast-conditioned medium. Results Six melanocyte samples demonstrated significant variability in phenotype and gene expression at baseline and in response to fibroblast-conditioned medium. Genetic profiling for SNPs in receptors for 13 identified soluble fibroblast-secreted mediators demonstrated considerable heterogeneity, potentially explaining the variable melanocyte responses to fibroblast-conditioned medium. Discussion Our data suggest that melanocytes respond to dermal fibroblast-derived mediators independent of keratinocytes and raise the possibility that mesenchymal-epidermal interactions influence skin pigmentation during cutaneous scarring. PMID:26418010

Honey bee (Apis mellifera) transferrin-gene structure and the role of ecdysteroids in the developmental regulation of its expression.

PubMed

do Nascimento, Adriana Mendes; Cuvillier-Hot, Virginie; Barchuk, Angel Roberto; Simões, Zilá Luz Paulino; Hartfelder, Klaus

2004-05-01

Social life is prone to invasion by microorganisms, and binding of ferric ions by transferrin is an efficient strategy to restrict their access to iron. In this study, we isolated cDNA and genomic clones encoding an Apis mellifera transferrin (AmTRF) gene. It has an open reading frame (ORF) of 2136 bp spread over nine exons. The deduced protein sequence comprises 686 amino acid residues plus a 26 residues signal sequence, giving a predicted molecular mass of 76 kDa. Comparison of the deduced AmTRF amino acid sequence with known insect transferrins revealed significant similarity extending over the entire sequence. It clusters with monoferric transferrins, with which it shares putative iron-binding residues in the N-terminal lobe. In a functional analysis of AmTRF expression in honey bee development, we monitored its expression profile in the larval and pupal stages. The negative regulation of AmTRF by ecdysteroids deduced from the developmental expression profile was confirmed by experimental treatment of spinning-stage honey bee larvae with 20-hydroxyecdysone, and of fourth instar-larvae with juvenile hormone. A juvenile hormone application to spinning-stage larvae, in contrast, had only a minor effect on AmTRF transcript levels. This is the first study implicating ecdysteroids in the developmental regulation of transferrin expression in an insect species.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

PubMed Central

2010-01-01

Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells

PubMed Central

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-01-01

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation. PMID:26838068

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells.

PubMed

Kumari, Bharti; Jain, Pratistha; Das, Shaoli; Ghosal, Suman; Hazra, Bibhabasu; Trivedi, Ashish Chandra; Basu, Anirban; Chakrabarti, Jayprokas; Vrati, Sudhanshu; Banerjee, Arup

2016-02-03

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation.

Liver protein profiles in insulin receptor-knockout mice reveal novel molecules involved in the diabetes pathophysiology.

PubMed

Capuani, Barbara; Della-Morte, David; Donadel, Giulia; Caratelli, Sara; Bova, Luca; Pastore, Donatella; De Canio, Michele; D'Aguanno, Simona; Coppola, Andrea; Pacifici, Francesca; Arriga, Roberto; Bellia, Alfonso; Ferrelli, Francesca; Tesauro, Manfredi; Federici, Massimo; Neri, Anna; Bernardini, Sergio; Sbraccia, Paolo; Di Daniele, Nicola; Sconocchia, Giuseppe; Orlandi, Augusto; Urbani, Andrea; Lauro, Davide

2015-05-01

Liver has a principal role in glucose regulation and lipids homeostasis. It is under a complex control by substrates such as hormones, nutrients, and neuronal impulses. Insulin promotes glycogen synthesis, lipogenesis, and lipoprotein synthesis and inhibits gluconeogenesis, glycogenolysis, and VLDL secretion by modifying the expression and enzymatic activity of specific molecules. To understand the pathophysiological mechanisms leading to metabolic liver disease, we analyzed liver protein patterns expressed in a mouse model of diabetes by proteomic approaches. We used insulin receptor-knockout (IR(-/-)) and heterozygous (IR(+/-)) mice as a murine model of liver metabolic dysfunction associated with diabetic ketoacidosis and insulin resistance. We evaluated liver fatty acid levels by microscopic examination and protein expression profiles by orthogonal experimental strategies using protein 2-DE MALDI-TOF/TOF and peptic nLC-MS/MS shotgun profiling. Identified proteins were then loaded into Ingenuity Pathways Analysis to find possible molecular networks. Twenty-eight proteins identified by 2-DE analysis and 24 identified by nLC-MS/MS shotgun were differentially expressed among the three genotypes. Bioinformatic analysis revealed a central role of high-mobility group box 1/2 and huntigtin never reported before in association with metabolic and related liver disease. A different modulation of these proteins in both blood and hepatic tissue further suggests their role in these processes. These results provide new insight into pathophysiology of insulin resistance and hepatic steatosis and could be useful in identifying novel biomarkers to predict risk for diabetes and its complications. Copyright © 2015 the American Physiological Society.

Gene expression profiling during asexual development of the late blight pathogen Phytophthora infestans reveals a highly dynamic transcriptome.

PubMed

Judelson, Howard S; Ah-Fong, Audrey M V; Aux, George; Avrova, Anna O; Bruce, Catherine; Cakir, Cahid; da Cunha, Luis; Grenville-Briggs, Laura; Latijnhouwers, Maita; Ligterink, Wilco; Meijer, Harold J G; Roberts, Samuel; Thurber, Carrie S; Whisson, Stephen C; Birch, Paul R J; Govers, Francine; Kamoun, Sophien; van West, Pieter; Windass, John

2008-04-01

Much of the pathogenic success of Phytophthora infestans, the potato and tomato late blight agent, relies on its ability to generate from mycelia large amounts of sporangia, which release zoospores that encyst and form infection structures. To better understand these stages, Affymetrix GeneChips based on 15,650 unigenes were designed and used to profile the life cycle. Approximately half of P. infestans genes were found to exhibit significant differential expression between developmental transitions, with approximately (1)/(10) being stage-specific and most changes occurring during zoosporogenesis. Quantitative reverse-transcription polymerase chain reaction assays confirmed the robustness of the array results and showed that similar patterns of differential expression were obtained regardless of whether hyphae were from laboratory media or infected tomato. Differentially expressed genes encode potential cellular regulators, especially protein kinases; metabolic enzymes such as those involved in glycolysis, gluconeogenesis, or the biosynthesis of amino acids or lipids; regulators of DNA synthesis; structural proteins, including predicted flagellar proteins; and pathogenicity factors, including cell-wall-degrading enzymes, RXLR effector proteins, and enzymes protecting against plant defense responses. Curiously, some stage-specific transcripts do not appear to encode functional proteins. These findings reveal many new aspects of oomycete biology, as well as potential targets for crop protection chemicals.

Aging: a portrait from gene expression profile in blood cells.

PubMed

Calabria, Elisa; Mazza, Emilia Maria Cristina; Dyar, Kenneth Allen; Pogliaghi, Silvia; Bruseghini, Paolo; Morandi, Carlo; Salvagno, Gian Luca; Gelati, Matteo; Guidi, Gian Cesare; Bicciato, Silvio; Schiaffino, Stefano; Schena, Federico; Capelli, Carlo

2016-08-01

The availability of reliable biomarkers of aging is important not only to monitor the effect of interventions and predict the timing of pathologies associated with aging but also to understand the mechanisms and devise appropriate countermeasures. Blood cells provide an easily available tissue and gene expression profiles from whole blood samples appear to mirror disease states and some aspects of the aging process itself. We report here a microarray analysis of whole blood samples from two cohorts of healthy adult and elderly subjects, aged 43±3 and 68±4 years, respectively, to monitor gene expression changes in the initial phase of the senescence process. A number of significant changes were found in the elderly compared to the adult group, including decreased levels of transcripts coding for components of the mitochondrial respiratory chain, which correlate with a parallel decline in the maximum rate of oxygen consumption (VO2max), as monitored in the same subjects. In addition, blood cells show age-related changes in the expression of several markers of immunosenescence, inflammation and oxidative stress. These findings support the notion that the immune system has a major role in tissue homeostasis and repair, which appears to be impaired since early stages of the aging process.

Early indicators of exposure to biological threat agents using host gene profiles in peripheral blood mononuclear cells

PubMed Central

Das, Rina; Hammamieh, Rasha; Neill, Roger; Ludwig, George V; Eker, Steven; Lincoln, Patrick; Ramamoorthy, Preveen; Dhokalia, Apsara; Mani, Sachin; Mendis, Chanaka; Cummings, Christiano; Kearney, Brian; Royaee, Atabak; Huang, Xiao-Zhe; Paranavitana, Chrysanthi; Smith, Leonard; Peel, Sheila; Kanesa-Thasan, Niranjan; Hoover, David; Lindler, Luther E; Yang, David; Henchal, Erik; Jett, Marti

2008-01-01

Background Effective prophylaxis and treatment for infections caused by biological threat agents (BTA) rely upon early diagnosis and rapid initiation of therapy. Most methods for identifying pathogens in body fluids and tissues require that the pathogen proliferate to detectable and dangerous levels, thereby delaying diagnosis and treatment, especially during the prelatent stages when symptoms for most BTA are indistinguishable flu-like signs. Methods To detect exposures to the various pathogens more rapidly, especially during these early stages, we evaluated a suite of host responses to biological threat agents using global gene expression profiling on complementary DNA arrays. Results We found that certain gene expression patterns were unique to each pathogen and that other gene changes occurred in response to multiple agents, perhaps relating to the eventual course of illness. Nonhuman primates were exposed to some pathogens and the in vitro and in vivo findings were compared. We found major gene expression changes at the earliest times tested post exposure to aerosolized B. anthracis spores and 30 min post exposure to a bacterial toxin. Conclusion Host gene expression patterns have the potential to serve as diagnostic markers or predict the course of impending illness and may lead to new stage-appropriate therapeutic strategies to ameliorate the devastating effects of exposure to biothreat agents. PMID:18667072

Screening of miRNA profiles and construction of regulation networks in early and late lactation of dairy goat mammary glands.

PubMed

Ji, Zhibin; Liu, Zhaohua; Chao, Tianle; Hou, Lei; Fan, Rui; He, Rongyan; Wang, Guizhi; Wang, Jianmin

2017-09-20

In recent years, studies related to the expression profiles of miRNAs in the dairy goat mammary gland were performed, but regulatory mechanisms in the physiological environment and the dynamic homeostasis of mammary gland development and lactation are not clear. In the present study, sequencing data analysis of early and late lactation uncovered a total of 1,487 unique miRNAs, including 45 novel miRNA candidates and 1,442 known and conserved miRNAs, of which 758 miRNAs were co-expressed and 378 differentially expressed with P < 0.05. Moreover, 76 non-redundant target genes were annotated in 347 GO consortiums, with 3,143 candidate target genes grouped into 33 pathways. Additionally, 18 predicted target genes of 214 miRNAs were directly annotated in mammary gland development and used to construct regulatory networks based on GO annotation and the KEGG pathway. The expression levels of seven known miRNAs and three novel miRNAs were examined using quantitative real-time PCR. The results showed that miRNAs might play important roles in early and late lactation during dairy goat mammary gland development, which will be helpful to obtain a better understanding of the genetic control of mammary gland lactation and development.

Hepatic Transcriptome Profiles of Mice with Diet-Induced Nonalcoholic Steatohepatitis Treated with Astaxanthin and Vitamin E

PubMed Central

Kobori, Masuko; Takahashi, Yumiko; Sakurai, Mutsumi; Ni, Yinhua; Chen, Guanliang; Nagashimada, Mayumi; Kaneko, Shuichi; Ota, Tsuguhito

2017-01-01

Astaxanthin alleviates hepatic lipid accumulation and peroxidation, inflammation, and fibrosis in mice with high-cholesterol, high-cholate, and high-fat (CL) diet-induced nonalcoholic steatohepatitis (NASH). It has been proposed as a potential new treatment to inhibit the progression of NASH in humans. In this study, we compared hepatic gene expression profiles after treatment with astaxanthin or the antioxidant vitamin E in mice with CL diet-induced NASH. Comprehensive gene expression analyses of the livers of mice fed a standard, CL, or CL diet containing astaxanthin or vitamin E for 12 weeks were performed using a DNA microarray. Both astaxanthin and vitamin E effectively improved gene expression associated with eukaryotic initiation factor-2 (EIF2) signaling, which is suppressed in NASH by endoplasmic reticulum (ER) stress in the liver. However, astaxanthin did not improve the expression of genes associated with mitochondrial dysfunction. Astaxanthin, but not vitamin E, was predicted to suppress the actions of ligand-dependent nuclear receptors peroxisome proliferator-activated receptors, (PPAR) α (PPARA) and PPARδ (PPARD), and to affect related molecules. Establishing a new therapy using astaxanthin will require elucidation of astaxanthin’s molecular action on the functions of PPARα and related molecules in the livers of mice with diet-induced NASH. PMID:28282876

Seasonal and latitudinal acclimatization of cardiac transcriptome responses to thermal stress in porcelain crabs, Petrolisthes cinctipes.

PubMed

Stillman, Jonathon H; Tagmount, Abderrahmane

2009-10-01

Central predictions of climate warming models include increased climate variability and increased severity of heat waves. Physiological acclimatization in populations across large-scale ecological gradients in habitat temperature fluctuation is an important factor to consider in detecting responses to climate change related increases in thermal fluctuation. We measured in vivo cardiac thermal maxima and used microarrays to profile transcriptome heat and cold stress responses in cardiac tissue of intertidal zone porcelain crabs across biogeographic and seasonal gradients in habitat temperature fluctuation. We observed acclimatization dependent induction of heat shock proteins, as well as unknown genes with heat shock protein-like expression profiles. Thermal acclimatization had the largest effect on heat stress responses of extensin-like, beta tubulin, and unknown genes. For these genes, crabs acclimatized to thermally variable sites had higher constitutive expression than specimens from low variability sites, but heat stress dramatically induced expression in specimens from low variability sites and repressed expression in specimens from highly variable sites. Our application of ecological transcriptomics has yielded new biomarkers that may represent sensitive indicators of acclimatization to habitat temperature fluctuation. Our study also has identified novel genes whose further description may yield novel understanding of cellular responses to thermal acclimatization or thermal stress.

Discovering Functions of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates

PubMed Central

Ellison, Christopher E.; Kowbel, David; Glass, N. Louise; Taylor, John W.

2014-01-01

ABSTRACT Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems. PMID:24692637

Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference

PubMed Central

Zheng, Tingting; Ni, Yueqiong; Li, Jun; Chow, Billy K. C.; Panagiotou, Gianni

2017-01-01

Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule) that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease. Methods: We performed an integrated analysis of publicly available gene expression profiles for foods, diseases and drugs, by calculating pairwise similarity scores for diet and disease gene expression signatures and characterizing their topological features in protein-protein interaction networks. Results: We identified 485 diet-disease pairs where diet could positively influence disease development and 472 pairs where specific diets should be avoided in a disease state. Multiple evidence suggests that orange, whey and coconut fat could be beneficial for psoriasis, lung adenocarcinoma and macular degeneration, respectively. On the other hand, fructose-rich diet should be restricted in patients with chronic intermittent hypoxia and ovarian cancer. Since humans normally do not consume foods in isolation, we also applied different algorithms to predict synergism; as a result, 58 food pairs were predicted. Interestingly, the diets identified as anti-correlated with diseases showed a topological proximity to the disease proteins similar to that of the corresponding drugs. Conclusions: In conclusion, we provide a computational framework for establishing diet-disease associations and additional information on the role of diet in disease development. Due to the complexity of analyzing the food composition and eating patterns of individuals our in silico analysis, using large-scale gene expression datasets and network-based topological features, may serve as a proof-of-concept in nutritional systems biology for identifying diet-disease relationships and subsequently designing dietary recommendations. PMID:29033850

MicroRNA-196a2 Biomarker and Targetome Network Analysis in Solid Tumors.

PubMed

Toraih, Eman A; Fawzy, Manal S; Mohammed, Eman A; Hussein, Mohammad H; El-Labban, Mohamad M

2016-12-01

MicroRNAs (miRNAs) have been linked to cancer development and progression. The molecular mechanisms underlying the genetic associations of the miRNA single nucleotide polymorphism with cancer vary by cancer site. As there are no previous studies on the miR-196a2 variant or expression in any type of cancer among our population, we aimed to determine the expression profile of mature miR-196a2 in various types of solid tumors and to analyze the impact of its polymorphism (rs11614913; C/T) on the expression levels. The study included 230 cancer patients (including 17 types of cancer), 26 patients with pre-cancer lesions, and 100 unrelated controls. Archived formalin-fixed, paraffin-embedded specimens (n = 197) were available for both miRNA expression analysis and single nucleotide polymorphism identification. Venous blood was collected from 59 histologically confirmed sporadic cancer patients and the study controls for single nucleotide polymorphism identification. Real-time polymerase chain reaction analysis was performed for allelic discrimination and relative quantification of miR-196a2 in the study samples. In silico target gene prediction and network analysis was performed. We found that individuals with the T variant were associated with cancer risk under all genetic association models, especially in colorectal, esophageal, skin, lung, thyroid, and renal cancer. Overall and stratified analysis showed miR-196a2 over-expression in most of the current malignant tumor samples relative to their corresponding cancer-free tissues. Carriers of the C allele had significantly higher expression levels of miR-196a2. Correlation with the clinicopathological features of cancer showed organ-specific effects. Gene enrichment analysis of predicted and validated targets speculated the putative role of miR-196a2 in cancer-associated biology. We highlighted cancer-type specific expression profiles of miR-196a2, which was correlated with the clinicopathological features in various types of cancer. Taken together, our results suggest that the miRNA signature could have promising diagnostic and prognostic significance.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.

PubMed

Elferink, M G L; Olinga, P; Draaisma, A L; Merema, M T; Bauerschmidt, S; Polman, J; Schoonen, W G; Groothuis, G M M

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

PubMed Central

Danger, Richard; Royer, Pierre-Joseph; Reboulleau, Damien; Durand, Eugénie; Loy, Jennifer; Tissot, Adrien; Lacoste, Philippe; Roux, Antoine; Reynaud-Gaubert, Martine; Gomez, Carine; Kessler, Romain; Mussot, Sacha; Dromer, Claire; Brugière, Olivier; Mornex, Jean-François; Guillemain, Romain; Dahan, Marcel; Knoop, Christiane; Botturi, Karine; Foureau, Aurore; Pison, Christophe; Koutsokera, Angela; Nicod, Laurent P.; Brouard, Sophie; Magnan, Antoine; Jougon, J.

2018-01-01

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS. PMID:29375549

Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elferink, M.G.L.; Olinga, P.; Draaisma, A.L.

2008-06-15

The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such asmore » Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl{sub 4}, fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.« less

Global proteomic analysis of two tick-borne emerging zoonotic agents: Anaplasma phagocytophilum and Ehrlichia chaffeensis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Mingqun ..; Kikuchi, Takane; Brewer, Heather M.

2011-02-17

Anaplasma phagocytophilum and Ehrlichia chaffeensis are obligatory intracellular {alpha}-proteobacteria that infect human leukocytes and cause potentially fatal emerging zoonoses. In the present study, we determined global protein expression profiles of these bacteria cultured in the human promyelocytic leukemia cell line, HL-60. Mass spectrometric (MS) analyses identified a total of 1,212 A. phagocytophilum and 1,021 E. chaffeensis proteins, representing 89.3 and 92.3% of the predicted bacterial proteomes, respectively. Nearly all bacterial proteins ({approx}99%) with known functions were expressed, whereas only approximately 80% of hypothetical proteins were detected in infected human cells. Quantitative MS/MS analyses indicated that highly expressed proteins in bothmore » bacteria included chaperones, enzymes involved in biosynthesis and metabolism, and outer membrane proteins, such as A. phagocytophilum P44 and E. chaffeensis P28/OMP-1. Among 113 A. phagocytophilum p44 paralogous genes, 110 of them were expressed and 88 of them were encoded by pseudogenes. In addition, bacterial infection of HL-60 cells up-regulated the expression of human proteins involved mostly in cytoskeleton components, vesicular trafficking, cell signaling, and energy metabolism, but down regulated some pattern recognition receptors involved in innate immunity. Our proteomics data represent a comprehensive analysis of A. phagocytophilum and E. chaffeensis proteomes, and provide a quantitative view of human host protein expression profiles regulated by bacterial infection. The availability of these proteomic data will provide new insights into biology and pathogenesis of these obligatory intracellular pathogens.« less

Long Noncoding RNAs and mRNA Regulation in Peripheral Blood Mononuclear Cells of Patients with Chronic Obstructive Pulmonary Disease

PubMed Central

Wang, Weijia; Xu, Dan

2018-01-01

Background Inflammation plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). We evaluated the lncRNA and mRNA expression profile of peripheral blood mononuclear cells (PBMCs) from healthy nonsmokers, smokers without airflow limitation, and COPD patients. Methods lncRNA and mRNA profiling of PBMCs from 17 smokers and 14 COPD subjects was detected by high-throughput microarray. The expression of dysregulated lncRNAs was validated by qPCR. The lncRNA targets in dysregulated mRNAs were predicted and the GO enrichment was analyzed. The regulatory role of lncRNA ENST00000502883.1 on CXCL16 expression and consequently the effect on PBMC recruitment were investigated by siRNA knockdown and chemotaxis analysis. Results We identified 158 differentially expressed lncRNAs in PBMCs from COPD subjects compared with smokers. The dysregulated expression of 5 selected lncRNAs NR_026891.1 (FLJ10038), ENST00000502883.1 (RP11-499E18.1), HIT000648516, XR_429541.1, and ENST00000597550.1 (CTD-2245F17.3), was validated. The GO enrichment showed that leukocyte migration, immune response, and apoptosis are the main enriched processes that previously reported to be involved in the pathogenesis of COPD. The regulatory role of ENST00000502883.1 on CXCL16 expression and consequently the effect on PBMC recruitment was confirmed. Conclusion This study may provide clues for further studies targeting lncRNAs to control inflammation in COPD. PMID:29725270

MicroRNA-326 and microRNA-200c: Two novel biomarkers for diagnosis and prognosis of pediatric acute lymphoblastic leukemia.

PubMed

Ghodousi, Elaheh S; Rahgozar, Soheila

2018-04-06

Multidrug resistance (MDR) is considered as the major obstacle for treating pediatric acute lymphoblastic leukemia (ALL). MicroRNAs (miRNAs) are small non coding RNAs which may potentially regulate response to chemotherapy. In this study, total RNA was isolated from bone marrow samples of 46 children with de novo ALL and 16 controls. Quantitative reverse transcriptase polymerase chain reaction was used to investigate the expression profile of the predicted miRNAs; miR-326 and miR-200c, and their predicted targets ABCA2, and ABCA3 transporters. The presence of minimal residual disease was studied using PCR-SSCP (single-strand conformation polymorphism) 1 year after treatment. The association between the miRNA expression and drug resistance was analyzed statistically. Results showed a significant down-regulation of both miR-326 and miR-200c expressions in ALL patients compared with non-cancer controls (P = 0.0002, AUC = 0.813 and P = 0.035, AUC = 0.79, respectively). A considerable negative association between miR-326 expression and MDR was identified which could raise the risk of chemoresistance by 4.8- fold. The expression profiles of miR-326 and ABCA2 transporter were inversely correlated. Data revealed, a novel diagnostic role for miR-326 and miR-200c as potential biomarkers of pediatric ALL. Down-regulation of miR-326 was introduced, for the first time, as a prognostic factor for drug resistance in childhood ALL. To the best of our knowledge, this is the first time that ABCA2 transporter is proposed as a target gene for miR-326, through which it can exert its impact on drug resistance. These data may provide novel approaches to new therapeutics and diagnostics. © 2018 Wiley Periodicals, Inc.

Circular RNA expression profile and potential function of hsa_circ_0045272 in systemic lupus erythematosus.

PubMed

Li, Lian-Ju; Zhu, Zhi-Wei; Zhao, Wei; Tao, Sha-Sha; Li, Bao-Zhu; Xu, Shu-Zhen; Wang, Jie-Bing; Zhang, Ming-Yue; Wu, Jun; Leng, Rui-Xue; Fan, Yin-Guang; Pan, Hai-Feng; Ye, Dong-Qing

2018-04-26

Circular RNAs (circRNAs) represent as a class of non-coding RNAs which form covalently closed RNA circles, and their extensive expression and conservation in mammals are observed. CircRNAs regulate gene expression through acting as competitive endogenous RNAs (ceRNAs) and modulating gene transcription. Accumulating evidence supports the implication of circRNAs in a variety of human diseases. Yet, study exploring the role of circRNAs in systemic lupus erythematosus (SLE) is lacking. The present study measured the circRNAs expression profiles in T cells from SLE patients and healthy controls with human circRNA microarray and identified 127 differentially expressed circRNAs in SLE patients. Downregulation of hsa_circ_0045272 in SLE T cells was verified with quantitative PCR. Jurkat cells with stable hsa_circ_0045272 knockdown were generated using specific lentiviral shRNA for functional studies. Flow cytometric analysis indicated that hsa_circ_0045272 knockdown significantly upregulated the early apoptosis of Jurkat cells. Meanwhile, enzyme-linked immunosorbent assay showed that hsa_circ_0045272 knockdown significantly enhanced IL-2 production of activated Jurkat cells. ceRNAs were then predicted for hsa_circ_0045272 and the significant downregulation of two mRNAs predicted as its ceRNAs, NM_003466 (PAX8) and NM_015177 (DTX4), but not their corresponding proteins was validated. Furthermore, dual luciferase reporter assay indicated binding of hsa_circ_0045272 with hsa-miR-6127. circRNAs-mRNAs coexpression networks showed the correlation of circRNAs with mRNAs and provided additional clues to circRNA functions. Our study demonstrated the dysregulated circRNAs in SLE and revealed function of hsa_circ_0045272 in negatively regulating apoptosis and IL-2 secretion and its potential mechanism. The implication of hsa_circ_0045272 and other abnormal circRNAs in SLE merits further investigation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Theory of Fiber Optical Bragg Grating: Revisited

NASA Technical Reports Server (NTRS)

Tai, H.

2003-01-01

The reflected signature of an optical fiber Bragg grating is analyzed using the transfer function method. This approach is capable to cast all relevant quantities into proper places and provides a better physical understanding. The relationship between reflected signal, number of periods, index of refraction, and reflected wave phase is elucidated. The condition for which the maximum reflectivity is achieved is fully examined. We also have derived an expression to predict the reflectivity minima accurately when the reflected wave is detuned. Furthermore, using the segmented potential approach, this model can handle arbitrary index of refraction profiles and compare the strength of optical reflectivity of different profiles. The condition of a non-uniform grating is also addressed.

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

RWEN: Response-Weighted Elastic Net For Prediction of Chemosensitivity of Cancer Cell Lines. | Office of Cancer Genomics

Cancer.gov

Motivation: In recent years there have been several efforts to generate sensitivity profiles of collections of genomically characterized cell lines to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based on cellular, genetic, or expression biomarkers of cancer cells. However, a remaining challenge is an efficient way to identify accurate sets of biomarkers to validate.

Defective Cell Cycle Checkpoint Functions in Melanoma Are Associated with Altered Patterns of Gene Expression

PubMed Central

Kaufmann, William K.; Nevis, Kathleen R.; Qu, Pingping; Ibrahim, Joseph G.; Zhou, Tong; Zhou, Yingchun; Simpson, Dennis A.; Helms-Deaton, Jennifer; Cordeiro-Stone, Marila; Moore, Dominic T.; Thomas, Nancy E.; Hao, Honglin; Liu, Zhi; Shields, Janiel M.; Scott, Glynis A.; Sharpless, Norman E.

2009-01-01

Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wild-type N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression. PMID:17597816

LncRNA and mRNA expression profiles of glioblastoma multiforme (GBM) reveal the potential roles of lncRNAs in GBM pathogenesis.

PubMed

Li, Qi; Jia, Hongmei; Li, Haowen; Dong, Chengya; Wang, Yajie; Zou, Zhongmei

2016-11-01

Glioblastoma multiforme (GBM) is the most common brain malignancy. Long non-coding RNAs (lncRNAs) are aberrantly expressed in many cancers and are involved in their cell proliferation, apoptosis, angiogenesis, and invasion. The functional roles of lncRNAs in GBM are less known. We analyzed a cohort of exon microarray datasets from The Cancer Genome Atlas. The differently expressed lncRNAs and mRNA were subjected to construct lncRNA-mRNA co-expression network. Probable functions for lncRNAs were predicted according to lncRNA-mRNA network and genomic adjacency by GO and pathway analysis. The expression of lncRNAs and mRNAs in GBM tissues versus normal brain tissues was examined by quantitative reverse transcription polymerase chain reaction. The 398 lncRNAs and 1995 mRNAs were identified as distinctively expressed in GBM. Probable functional roles for 98 lncRNAs were involved in 30 pathways and 32 gene functions related to tumorigenesis, development, and metastasis. The identified sets of key lncRNAs specific to GBM were subsequently verified by experiment in GBM tissues. Our reports predict the biological functions of a multitude of lncRNAs in GBM that could be potential diagnostic and prognostic biomarkers as well as therapeutic targets. Moreover, our research provides a road map for the identification and analysis of lncRNAs in tumors.

A new model for predicting moisture uptake by packaged solid pharmaceuticals.

PubMed

Chen, Y; Li, Y

2003-04-14

A novel mathematical model has been developed for predicting moisture uptake by packaged solid pharmaceutical products during storage. High density polyethylene (HDPE) bottles containing the tablet products of two new chemical entities and desiccants are investigated. Permeability of the bottles is determined at different temperatures using steady-state data. Moisture sorption isotherms of the two model drug products and desiccants at the same temperatures are determined and expressed in polynomial equations. The isotherms are used for modeling the time-humidity profile in the container, which enables the prediction of the moisture content of individual component during storage. Predicted moisture contents agree well with real time stability data. The current model could serve as a guide during packaging selection for moisture protection, so as to reduce the cost and cycle time of screening study.

Prediction of clinical behaviour and treatment for cancers.

PubMed

Futschik, Matthias E; Sullivan, Mike; Reeve, Anthony; Kasabov, Nikola

2003-01-01

Prediction of clinical behaviour and treatment for cancers is based on the integration of clinical and pathological parameters. Recent reports have demonstrated that gene expression profiling provides a powerful new approach for determining disease outcome. If clinical and microarray data each contain independent information then it should be possible to combine these datasets to gain more accurate prognostic information. Here, we have used existing clinical information and microarray data to generate a combined prognostic model for outcome prediction for diffuse large B-cell lymphoma (DLBCL). A prediction accuracy of 87.5% was achieved. This constitutes a significant improvement compared to the previously most accurate prognostic model with an accuracy of 77.6%. The model introduced here may be generally applicable to the combination of various types of molecular and clinical data for improving medical decision support systems and individualising patient care.

Comparative brain transcriptomic analyses of scouting across distinct behavioural and ecological contexts in honeybees

PubMed Central

Liang, Zhengzheng S.; Mattila, Heather R.; Rodriguez-Zas, Sandra L.; Southey, Bruce R.; Seeley, Thomas D.; Robinson, Gene E.

2014-01-01

Individual differences in behaviour are often consistent across time and contexts, but it is not clear whether such consistency is reflected at the molecular level. We explored this issue by studying scouting in honeybees in two different behavioural and ecological contexts: finding new sources of floral food resources and finding a new nest site. Brain gene expression profiles in food-source and nest-site scouts showed a significant overlap, despite large expression differences associated with the two different contexts. Class prediction and ‘leave-one-out’ cross-validation analyses revealed that a bee's role as a scout in either context could be predicted with 92.5% success using 89 genes at minimum. We also found that genes related to four neurotransmitter systems were part of a shared brain molecular signature in both types of scouts, and the two types of scouts were more similar for genes related to glutamate and GABA than catecholamine or acetylcholine signalling. These results indicate that consistent behavioural tendencies across different ecological contexts involve a mixture of similarities and differences in brain gene expression. PMID:25355476

Digital signaling decouples activation probability and population heterogeneity.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş

2015-10-21

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalra, Rajkumar S., E-mail: renu-wadhwa@aist.go.jp; Wadhwa, Renu, E-mail: renu-wadhwa@aist.go.jp

2015-02-27

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylationmore » target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein.« less

Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

PubMed

Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

2017-09-29

Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a

PubMed Central

Wu, Hsuan-Hui; Chen, Meng-Chun; Liu, Wen-Huan; Wu, Wu-Hsiung; Chang, Peter Mu-Hsin; Huang, Chi-Ying F.; Tsou, Ann-Ping; Shiao, Ming-Shi

2017-01-01

The liver is a vital organ involving in various major metabolic functions in human body. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a–/–) to infer Warburg-like effects. Elevated expression of MiR-122a target genes in Mir122a–/–mice, especially those encoding for metabolic enzymes, was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states. By definition of the similarity ratio, we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer, respectively, for hepatocytes of 2-month-old mice in normal and deficient states. The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect, and similarity of 75% to the experimental observation. We also used 2, 6, and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data. Furthermore, through a bioinformatics (LINCS program) prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells. PMID:28686599

Transcriptional maturation of the mouse auditory forebrain.

PubMed

Hackett, Troy A; Guo, Yan; Clause, Amanda; Hackett, Nicholas J; Garbett, Krassimira; Zhang, Pan; Polley, Daniel B; Mirnics, Karoly

2015-08-14

The maturation of the brain involves the coordinated expression of thousands of genes, proteins and regulatory elements over time. In sensory pathways, gene expression profiles are modified by age and sensory experience in a manner that differs between brain regions and cell types. In the auditory system of altricial animals, neuronal activity increases markedly after the opening of the ear canals, initiating events that culminate in the maturation of auditory circuitry in the brain. This window provides a unique opportunity to study how gene expression patterns are modified by the onset of sensory experience through maturity. As a tool for capturing these features, next-generation sequencing of total RNA (RNAseq) has tremendous utility, because the entire transcriptome can be screened to index expression of any gene. To date, whole transcriptome profiles have not been generated for any central auditory structure in any species at any age. In the present study, RNAseq was used to profile two regions of the mouse auditory forebrain (A1, primary auditory cortex; MG, medial geniculate) at key stages of postnatal development (P7, P14, P21, adult) before and after the onset of hearing (~P12). Hierarchical clustering, differential expression, and functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all genes. Selected genesets related to neurotransmission, developmental plasticity, critical periods and brain structure were highlighted. An accessible repository of the entire dataset was also constructed that permits extraction and screening of all data from the global through single-gene levels. To our knowledge, this is the first whole transcriptome sequencing study of the forebrain of any mammalian sensory system. Although the data are most relevant for the auditory system, they are generally applicable to forebrain structures in the visual and somatosensory systems, as well. The main findings were: (1) Global gene expression patterns were tightly clustered by postnatal age and brain region; (2) comparing A1 and MG, the total numbers of differentially expressed genes were comparable from P7 to P21, then dropped to nearly half by adulthood; (3) comparing successive age groups, the greatest numbers of differentially expressed genes were found between P7 and P14 in both regions, followed by a steady decline in numbers with age; (4) maturational trajectories in expression levels varied at the single gene level (increasing, decreasing, static, other); (5) between regions, the profiles of single genes were often asymmetric; (6) GSEA revealed that genesets related to neural activity and plasticity were typically upregulated from P7 to adult, while those related to structure tended to be downregulated; (7) GSEA and pathways analysis of selected functional networks were not predictive of expression patterns in the auditory forebrain for all genes, reflecting regional specificity at the single gene level. Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age. Maturational changes are evident at the global through single gene levels. Transcriptome profiles in A1 and MG are distinct at all ages, and differ from other brain regions. The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

Transcriptome profiles in sarcoidosis and their potential role in disease prediction.

PubMed

Schupp, Jonas C; Vukmirovic, Milica; Kaminski, Naftali; Prasse, Antje

2017-09-01

Sarcoidosis is a systemic disease defined by the presence of nonnecrotizing granuloma in the absence of any known cause. Although the heterogeneity of sarcoidosis is well characterized clinically, the transcriptome of sarcoidosis and underlying molecular mechanisms are not. The signal of all transcripts, small and long noncoding RNAs, can be detected using microarrays or RNA-Sequencing. Analyzing the transcriptome of tissues that are directly affected by granulomas is of great importance to understand biology of the disease and may be predictive of disease and treatment outcome. Multiple genome wide expression studies performed on sarcoidosis affected tissues were published in the last 11 years. Published studies focused on differences in gene expression between sarcoidosis vs. control tissues, stable vs. progressive sarcoidosis, as well as sarcoidosis vs. other diseases. Strikingly, all these transcriptomics data confirm the key role of TH1 immune response in sarcoidosis and particularly of interferon-γ (IFN-γ) and type I IFN-driven signaling pathways. The steps toward transcriptomics of sarcoidosis in precision medicine highlight the potentials of this approach. Large prospective follow-up studies are required to identify signatures predictive of disease progression and outcome.

Immunoreactivities of human nonmetastatic clone 23 and p53 products are disassociated and not good predictors of lymph node metastases in early-stage cervical cancer patients.

PubMed

Tee, Y T; Wang, P H; Ko, J L; Chen, G D; Chang, H; Lin, L Y

2007-01-01

To assess the relation between expressions of human nonmetastatic clone 23 (nm23-H1) and p53 in cervical cancer, their relationships with lymph node metastasis, and further to examine their predictive of lymph node metastases. nm23-H1 and p53 expression profiles were visualized by immunohistochemistry in early-stage cervical cancer specimens. Immunoreactivities of nm23-H1 and p53 were disassociated. The independent variables related with lymph node metastases were grade of cancer cell differentiation (p < 0.029) and stromal invasion (p < 0.039). Sensitivity, specificity, positive and negative predictive values, and accuracy for lymph node metastasis were calculated to be 91.7%, 13.5%, 25.6%, 83.3%, and 32.7% for nm23-H1 and 66.7%, 51.4%, 30.8%, 82.6%, and 55.1% for p53. Nm23-H1 and p53 are disassociated and not good predictors of lymph node metastases in early-stage cervical cancer patients. However, stromal invasion and cell differentiation can predict lymph node metastasis.

High Expression of EphA4 Predicted Lesser Degree of Tumor Regression after Neoadjuvant Chemoradiotherapy in Rectal Cancer.

PubMed

Lin, Ching-Yih; Lee, Ying-En; Tian, Yu-Feng; Sun, Ding-Ping; Sheu, Ming-Jen; Lin, Chen-Yi; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Chang, I-Wei; Wang, Chieh-Tien; He, Hong-Lin

2017-01-01

Background: Numerous transmembrane receptor tyrosine kinase pathways have been found to play an important role in tumor progression in some cancers. This study was aimed to evaluate the clinical impact of Eph receptor A4 (EphA4) in patients with rectal cancer treated with neoadjuvant concurrent chemoradiotherapy (CCRT) combined with mesorectal excision, with special emphasis on tumor regression. Methods: Analysis of the publicly available expression profiling dataset of rectal cancer disclosed that EphA4 was the top-ranking, significantly upregulated, transmembrane receptor tyrosine kinase pathway-associated gene in the non-responders to CCRT, compared with the responders. Immunohistochemical study was conducted to assess the EphA4 expression in pre-treatment biopsy specimens from 172 rectal cancer patients without distant metastasis. The relationships between EphA4 expression and various clinicopathological factors or survival were statistically analyzed. Results: EphA4 expression was significantly associated with vascular invasion ( P =0.015), post-treatment depth of tumor invasion ( P =0.006), pre-treatment and post-treatment lymph node metastasis ( P =0.004 and P =0.011, respectively). More importantly, high EphA4 expression was significantly predictive for lesser degree of tumor regression after CCRT ( P =0.031). At univariate analysis, high EphA4 expression was a negative prognosticator for disease-specific survival ( P =0.0009) and metastasis-free survival ( P =0.0001). At multivariate analysis, high expression of EphA4 still served as an independent adverse prognostic factor for disease-specific survival (HR, 2.528; 95% CI, 1.131-5.651; P =0.024) and metastasis-free survival (HR, 3.908; 95% CI, 1.590-9.601; P =0.003). Conclusion: High expression of EphA4 predicted lesser degree of tumor regression after CCRT and served as an independent negative prognostic factor in patients with rectal cancer.

Prediction of Clinical Outcomes by Chemokine and Cytokine Profiling In CSF from Radiation Treated Breast Cancer Primary with Brain Metastases

NASA Astrophysics Data System (ADS)

Lok, Edwin

Whole brain radiation is the standard treatment for patients with brain metastasis but unfortunately tumors can recover from radiation-induced damage with the help of the immune system. The hypothesis that differences in immunokines in the cerebrospinal fluid (CSF) pre- and post-irradiation could reveal tumor biology and correlate with outcome of patients with metastatic breast cancer to the brain is tested. Collected CSF samples were analyzed using Luminex's multiplexing assays to survey global immunokine levels while Enzyme-Linked Immunosorbent Assays were used to quantify each individual immunokines. Cluster analysis was performed to segregate patients based on their common immunokine profile and each cluster was correlated with survival and other clinical parameters. Breast cancer brain metastasis was found to have altered immunokine profiles in the CSF, and that Interleukin-1α expression was elevated after irradiation. Therefore, immunokine profiling in the CSF could enable cancer physicians to monitor the status of brain metastases.

Global Gene Expression Change Induced by Major Thoracoabdominal Surgery.

PubMed

Allen, Casey J; Griswold, Anthony J; Schulman, Carl I; Sleeman, Danny; Levi, Joe U; Livingstone, Alan S; Proctor, Kenneth G

2017-12-01

To test the hypothesis that major thoracoabdominal surgery induces gene expression changes associated with adverse outcomes. Widely different traumatic injuries evoke surprisingly similar gene expression profiles, but there is limited information on whether the iatrogenic injury caused by major surgery is associated with similar patterns. With informed consent, blood samples were obtained from 50 patients before and after open transhiatal esophagectomy or pancreaticoduodenectomy. Twelve cases with complicated recoveries (death, infection, venous thromboembolism) were matched with 12 cases with uneventful recoveries. Global gene expression was assayed using human microarray chips. A 2-fold change with a corrected P < 0.05 was considered differentially expressed. In these 24 patients, 522 genes were differentially expressed after surgery; 248 (48%) were upregulated (innate immunity and inflammation) and 274 (52%) were downregulated [adaptive immunity (antigen presentation, T-cell function)]. Hierarchical clustering of the profile reliably predicted pre- and postoperative status. The within-patient change was 3.08 ± 0.91-fold. There was no measurable association with age, malignancy, procedure, surgery length, operative blood loss, or transfusion requirements, but was positively associated with postoperative infection (3.81 ± 0.97 vs 2.79 ± 0.73; P = 0.009) and hospital length of stay (r = 0.583, P = 0.003). Venous thromboembolism and mortality each occurred in one patient, thus no associations were possible. Major surgery induces a quantifiable pattern of gene expression change that is associated with adverse outcome. This could reflect early impaired adaptive immunity and suggests potential therapeutic targets to improve postoperative recovery.

Integrative analysis of long non-coding RNAs and messenger RNA expression profiles in systemic lupus erythematosus.

PubMed

Luo, Qing; Li, Xue; Xu, Chuxin; Zeng, Lulu; Ye, Jianqing; Guo, Yang; Huang, Zikun; Li, Junming

2018-03-01

Thousands of long noncoding RNAs (lncRNAs) have been reported and represent an important subset of pervasive genes associated with a broad range of biological functions. Abnormal expression levels of lncRNAs have been demonstrated in multiple types of human disease. However, the role of lncRNAs in systemic lupus erythematosus (SLE) remains poorly understood. In the present study, the expression patterns of lncRNAs and messenger RNAs (mRNAs) were investigated in peripheral blood mononuclear cells (PBMCs) in SLE using Human lncRNA Array v3.0 (8x60 K; Arraystar, Inc., Rockville, MD, USA). The microarray results indicated that 8,868 lncRNAs (3,657 upregulated and 5,211 downregulated) and 6,876 mRNAs (2,862 upregulated and 4,014 downregulated) were highly differentially expressed in SLE samples compared with the healthy group. Gene ontology (GO) analysis of lncRNA target prediction indicated the presence of 474 matched lncRNA‑mRNA pairs for 293 differentially expressed lncRNAs (fold change, ≥3.0) and 381 differentially expressed mRNAs (fold change, ≥3.0). The most enriched pathways were 'Transcriptional misregulation in cancer' and 'Valine, leucine and isoleucine degradation'. Furthermore, reverse transcription‑quantitative polymerase chain reaction data verified six abnormal lncRNAs and mRNAs in SLE. The results indicate that the lncRNA expression profile in SLE was significantly changed. In addition, a range of SLE‑associated lncRNAs were identified. Thus, the present results provide important insights regarding lncRNAs in the pathogenesis of SLE.

Circular RNA expression profiles in placental villi from women with gestational diabetes mellitus.

PubMed

Yan, Linping; Feng, Jie; Cheng, Feng; Cui, Xianwei; Gao, Lingjuan; Chen, Yajun; Wang, Fei; Zhong, Tianying; Li, Yun; Liu, Lan

2018-04-15

Circular RNAs (circRNAs) have recently been shown to exert their effects on multiple pathological processes by acting as microRNA (miRNA) sponges. However, the roles of circRNAs in gestational diabetes mellitus (GDM) are largely unknown. This study aimed to identify the circRNAs involved in GDM and predict their potential biological functions. We first performed next-generation sequencing (NGS) to generate unbiased placental villi circRNA expression profiles of GDM and normal controls. In total, 48,270 circRNAs from the placental villi of the two groups were sequenced. Of these, 227 circRNAs were significantly up-regulated and 255 circRNAs were significantly down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses demonstrated that glycometabolism and lipometabolism processes, which are important in GDM development, were significantly enriched. Further analysis showed that most of the circRNAs harbored miRNA binding sites, and some were associated with GDM. These results showed that circRNAs are aberrantly expressed in the placental villi of GDM patients and play potential roles in the development of GDM. Copyright © 2018 Elsevier Inc. All rights reserved.

The microRNA-218~Survivin axis regulates migration, invasion, and lymph node metastasis in cervical cancer

PubMed Central

Kogo, Ryunosuke; How, Christine; Chaudary, Naz; Bruce, Jeff; Shi, Wei; Hill, Richard P.; Zahedi, Payam; Yip, Kenneth W.; Liu, Fei-Fei

2015-01-01

Cervical cancer is the third most common cancer in women worldwide. In the present study, global microRNA profiling for 79 cervical cancer patient samples led to the identification of miR-218 down-regulation in cervical cancer tissues compared to normal cervical tissues. Lower miR-218 expression was associated significantly with worse overall survival (OS), disease-free survival (DFS), and pelvic/aortic lymph node recurrence. In vitro, miR-218 over-expression decreased clonogenicity, migration, and invasion. Survivin (BIRC5) was subsequently identified as an important cervical cancer target of miR-218 using in silico prediction, mRNA profiling, and quantitative real-time PCR (qRT-PCR). Concordant with miR-218 over-expression, survivin knockdown by siRNA decreased clonogenicity, migration, and invasion. YM155, a small molecule survivin inhibitor, significantly suppressed tumor growth and lymph node metastasis in vivo. Our findings demonstrate that the miR-218~survivin axis inhibits cervical cancer progression by regulating clonogenicity, migration, and invasion, and suggest that the inhibition of survivin could be a potential therapeutic strategy to improve outcome in this disease. PMID:25473903

Distinct gene expression profiles characterize the histopathological stages of disease in Helicobacter-induced mucosa-associated lymphoid tissue lymphoma

PubMed Central

Mueller, Anne; O'Rourke, Jani; Grimm, Jan; Guillemin, Karen; Dixon, Michael F.; Lee, Adrian; Falkow, Stanley

2003-01-01

Long-term colonization of humans with Helicobacter pylori can cause the development of gastric B cell mucosa-associated lymphoid tissue lymphoma, yet little is known about the sequence of molecular steps that accompany disease progression. We used microarray analysis and laser microdissection to identify gene expression profiles characteristic and predictive of the various histopathological stages in a mouse model of the disease. The initial step in lymphoma development is marked by infiltration of reactive lymphocytes into the stomach and the launching of a mucosal immune response. Our analysis uncovered molecular markers of both of these processes, including genes coding for the immunoglobulins and the small proline-rich protein Sprr 2A. The subsequent step is characterized histologically by the antigen-driven proliferation and aggregation of B cells and the gradual appearance of lymphoepithelial lesions. In tissues of this stage, we observed increased expression of genes previously associated with malignancy, including the laminin receptor-1 and the multidrug-resistance channel MDR-1. Finally, we found that the transition to destructive lymphoepithelial lesions and malignant lymphoma is marked by an increase in transcription of a single gene encoding calgranulin A/Mrp-8. PMID:12552104

Circular RNA expression in basal cell carcinoma.

PubMed

Sand, Michael; Bechara, Falk G; Sand, Daniel; Gambichler, Thilo; Hahn, Stephan A; Bromba, Michael; Stockfleth, Eggert; Hessam, Schapoor

2016-05-01

Circular RNAs (circRNAs), are nonprotein coding RNAs consisting of a circular loop with multiple miRNA, binding sites called miRNA response elements (MREs), functioning as miRNA sponges. This study was performed to identify differentially expressed circRNAs and their MREs in basal cell carcinoma (BCC). Microarray circRNA expression profiles were acquired from BCC and control followed by qRT-PCR validation. Bioinformatical target prediction revealed multiple MREs. Sequence analysis was performed concerning MRE interaction potential with the BCC miRNome. We identified 23 upregulated and 48 downregulated circRNAs with 354 miRNA response elements capable of sequestering miRNA target sequences of the BCC miRNome. The present study describes a variety of circRNAs that are potentially involved in the molecular pathogenesis of BCC.

How to normalize metatranscriptomic count data for differential expression analysis.

PubMed

Klingenberg, Heiner; Meinicke, Peter

2017-01-01

Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it has not been clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscriptomics. We propose a model for differential expression in metatranscriptomics that explicitly accounts for variations in the taxonomic composition of transcripts across different samples. As a main consequence the correct normalization of metatranscriptomic count data under this model requires the taxonomic separation of the data into organism-specific bins. Then the taxon-specific scaling of organism profiles yields a valid normalization and allows us to recombine the scaled profiles into a metatranscriptomic count matrix. This matrix can then be analyzed with statistical tools for transcriptomic count data. For taxon-specific scaling and recombination of scaled counts we provide a simple R script. When applying transcriptomic tools for differential expression analysis directly to metatranscriptomic data with an organism-independent (global) scaling of counts the resulting differences may be difficult to interpret. The differences may correspond to changing functional profiles of the contributing organisms but may also result from a variation of taxonomic abundances. Taxon-specific scaling eliminates this variation and therefore the resulting differences actually reflect a different behavior of organisms under changing conditions. In simulation studies we show that the divergence between results from global and taxon-specific scaling can be drastic. In particular, the variation of organism abundances can imply a considerable increase of significant differences with global scaling. Also, on real metatranscriptomic data, the predictions from taxon-specific and global scaling can differ widely. Our studies indicate that in real data applications performed with global scaling it might be impossible to distinguish between differential expression in terms of transcriptomic changes and differential composition in terms of changing taxonomic proportions. As in transcriptomics, a proper normalization of count data is also essential for differential expression analysis in metatranscriptomics. Our model implies a taxon-specific scaling of counts for normalization of the data. The application of taxon-specific scaling consequently removes taxonomic composition variations from functional profiles and therefore provides a clear interpretation of the observed functional differences.

Global Analysis of Transcriptome Responses and Gene Expression Profiles to Cold Stress of Jatropha curcas L.

PubMed Central

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Background Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. Results In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. Conclusions This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas. PMID:24349370

Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

PubMed

Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance in J. curcas.

Global Gene Expression Profiling in Omental Adipose Tissue of Morbidly Obese Diabetic African Americans.

PubMed

Doumatey, Ayo P; Xu, Huichun; Huang, Hanxia; Trivedi, Niraj S; Lei, Lin; Elkahloun, Abdel; Adeyemo, Adebowale; Rotimi, Charles N

2015-06-01

Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D. Twenty morbidly obese (mean BMI: about 54 kg/m 2 ) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals. At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase ( HNRNPA1, TNKS2 ), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified. This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.

Molecular Phenotypes Distinguish Patients with Relatively Stable from Progressive Idiopathic Pulmonary Fibrosis (IPF)

PubMed Central

Boon, Kathy; Bailey, Nathaniel W.; Yang, Jun; Steel, Mark P.; Groshong, Steve; Kervitsky, Dolly; Brown, Kevin K.; Schwarz, Marvin I.; Schwartz, David A.

2009-01-01

Background Idiopathic pulmonary fibrosis (IPF) is a progressive, chronic interstitial lung disease that is unresponsive to current therapy and often leads to death. However, the rate of disease progression differs among patients. We hypothesized that comparing the gene expression profiles between patients with stable disease and those in which the disease progressed rapidly will lead to biomarker discovery and contribute to the understanding of disease pathogenesis. Methodology and Principal Findings To begin to address this hypothesis, we applied Serial Analysis of Gene Expression (SAGE) to generate lung expression profiles from diagnostic surgical lung biopsies in 6 individuals with relatively stable (or slowly progressive) IPF and 6 individuals with progressive IPF (based on changes in DLCO and FVC over 12 months). Our results indicate that this comprehensive lung IPF SAGE transcriptome is distinct from normal lung tissue and other chronic lung diseases. To identify candidate markers of disease progression, we compared the IPF SAGE profiles in stable and progressive disease, and identified a set of 102 transcripts that were at least 5-fold up regulated and a set of 89 transcripts that were at least 5-fold down regulated in the progressive group (P-value≤0.05). The over expressed genes included surfactant protein A1, two members of the MAPK-EGR-1-HSP70 pathway that regulate cigarette-smoke induced inflammation, and Plunc (palate, lung and nasal epithelium associated), a gene not previously implicated in IPF. Interestingly, 26 of the up regulated genes are also increased in lung adenocarcinomas and have low or no expression in normal lung tissue. More importantly, we defined a SAGE molecular expression signature of 134 transcripts that sufficiently distinguished relatively stable from progressive IPF. Conclusions These findings indicate that molecular signatures from lung parenchyma at the time of diagnosis could prove helpful in predicting the likelihood of disease progression or possibly understanding the biological activity of IPF. PMID:19347046

Digital sorting of complex tissues for cell type-specific gene expression profiles.

PubMed

Zhong, Yi; Wan, Ying-Wooi; Pang, Kaifang; Chow, Lionel M L; Liu, Zhandong

2013-03-07

Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations. Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies. The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.

Clinical Value of miR-101-3p and Biological Analysis of its Prospective Targets in Breast Cancer: A Study Based on The Cancer Genome Atlas (TCGA) and Bioinformatics.

PubMed

Li, Chun-Yao; Xiong, Dan-Dan; Huang, Chun-Qin; He, Rong-Quan; Liang, Hai-Wei; Pan, Deng-Hua; Wang, Han-Lin; Wang, Yi-Wen; Zhu, Hua-Wei; Chen, Gang

2017-04-18

BACKGROUND MiR-101-3p can promote apoptosis and inhibit proliferation, invasion, and metastasis in breast cancer (BC) cells. However, its mechanisms in BC are not fully understood. Therefore, a comprehensive analysis of the target genes, pathways, and networks of miR-101-3p in BC is necessary. MATERIAL AND METHODS The miR-101 profiles for 781 patients with BC from The Cancer Genome Atlas (TCGA) were analyzed. Gene expression profiling of GSE31397 with miR-101-3p transfected MCF-7 cells and scramble control cells was downloaded from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified. The potential genes targeted by miR-101-3p were also predicted. Gene Ontology (GO) and pathway and network analyses were constructed for the DEGs and predicted genes. RESULTS In the TCGA data, a low level of miR-101-2 expression might represent a diagnostic (AUC: 0.63) marker, and the miR-101-1 was a prognostic (HR=1.79) marker. MiR-101-1 was linked to the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), and miR-101-2 was associated with the tumor (T), lymph node (N), and metastasis (M) stages of BC. Moreover, 427 genes were selected from the 921 DEGs in GEO and the 7924 potential target genes from the prediction databases. These genes were related to transcription, metabolism, biosynthesis, and proliferation. The results were also significantly enriched in the VEGF, mTOR, focal adhesion, Wnt, and chemokine signaling pathways. CONCLUSIONS MiR-101-1 and miR-101-2 may be prospective biomarkers for the prognosis and diagnosis of BC, respectively, and are associated with diverse clinical parameters. The target genes of miR-101-3p regulate the development and progression of BC. These results provide insight into the pathogenic mechanism and potential therapies for BC.

An RNA-Seq based gene expression atlas of the common bean.

PubMed

O'Rourke, Jamie A; Iniguez, Luis P; Fu, Fengli; Bucciarelli, Bruna; Miller, Susan S; Jackson, Scott A; McClean, Philip E; Li, Jun; Dai, Xinbin; Zhao, Patrick X; Hernandez, Georgina; Vance, Carroll P

2014-10-06

Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.

Claudin-2 is an independent negative prognostic factor in breast cancer and specifically predicts early liver recurrences.

PubMed

Kimbung, Siker; Kovács, Anikó; Bendahl, Pär-Ola; Malmström, Per; Fernö, Mårten; Hatschek, Thomas; Hedenfalk, Ingrid

2014-02-01

Predicting any future metastatic site of early-stage breast cancer is important as it significantly influences the prognosis of advanced disease. This study aimed at investigating the potential of claudin-2, over-expressed in breast cancer liver metastases, as a biomarker for predicting liver metastatic propensity in primary breast cancer. Claudin-2 expression was analyzed in two independent cohorts. Cohort 1 included 304 women with metastatic breast cancer diagnosed between 2002 and 2007, while cohort 2 included 237 premenopausal women with early-stage node-negative breast cancer diagnosed between 1991 and 1994. Global transcriptional profiling of fine-needle aspirates from metastases was performed, followed by immunohistochemical analyses in archival primary tumor tissue. Associations between claudin-2 expression and relapse site were assessed by univariable and multivariable Cox regression models including conventional prognostic factors. Two-sided statistical tests were used. CLDN2 was significantly up-regulated (P < 0.001) in liver metastases compared to other metastatic sites. Claudin-2 protein was more frequently expressed in primary tumors from patients who subsequently developed liver metastases (P = 0.02) and high expression was associated with a shorter metastasis-free interval (cohort 1, HR = 1.4, 95% CI = 1.0-1.9; cohort 2, HR = 2.2, 95% CI = 1.3-3.5). Specifically, a significantly shorter interval between primary tumor diagnosis and liver-specific recurrence was observed among patients with high levels of claudin-2 expression in the primary tumor (cohort 1, HR = 2.3, 95% CI = 1.3-3.9). These results suggest a novel role for claudin-2 as a prognostic biomarker with the ability to predict not only the likelihood of a breast cancer recurrence, but more interestingly, the liver metastatic potential of the primary tumor. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Ribosome profiling reveals pervasive and regulated stop codon readthrough in Drosophila melanogaster

PubMed Central

Dunn, Joshua G; Foo, Catherine K; Belletier, Nicolette G; Gavis, Elizabeth R; Weissman, Jonathan S

2013-01-01

Ribosomes can read through stop codons in a regulated manner, elongating rather than terminating the nascent peptide. Stop codon readthrough is essential to diverse viruses, and phylogenetically predicted to occur in a few hundred genes in Drosophila melanogaster, but the importance of regulated readthrough in eukaryotes remains largely unexplored. Here, we present a ribosome profiling assay (deep sequencing of ribosome-protected mRNA fragments) for Drosophila melanogaster, and provide the first genome-wide experimental analysis of readthrough. Readthrough is far more pervasive than expected: the vast majority of readthrough events evolved within D. melanogaster and were not predicted phylogenetically. The resulting C-terminal protein extensions show evidence of selection, contain functional subcellular localization signals, and their readthrough is regulated, arguing for their importance. We further demonstrate that readthrough occurs in yeast and humans. Readthrough thus provides general mechanisms both to regulate gene expression and function, and to add plasticity to the proteome during evolution. DOI: http://dx.doi.org/10.7554/eLife.01179.001 PMID:24302569

Two members of the mouse mdr gene family confer multidrug resistance with overlapping but distinct drug specificities.

PubMed Central

Devault, A; Gros, P

1990-01-01

We report the cloning and functional analysis of a complete clone for the third member of the mouse mdr gene family, mdr3. Nucleotide and predicted amino acid sequence analyses showed that the three mouse mdr genes encode highly homologous membrane glycoproteins, which share the same length (1,276 residues), the same predicted functional domains, and overall structural arrangement. Regions of divergence among the three proteins are concentrated in discrete segments of the predicted polypeptides. Sequence comparison indicated that the three mouse mdr genes were created from a common ancestor by two independent gene duplication events, the most recent one producing mdr1 and mdr3. When transfected and overexpressed in otherwise drug-sensitive cells, the mdr3 gene, like mdr1 and unlike mdr2, conferred multidrug resistance to these cells. In independently derived transfected cell clones expressing similar amounts of either MDR1 or MDR3 protein, the drug resistance profile conferred by mdr3 was distinct from that conferred by mdr1. Cells transfected with and expressing MDR1 showed a marked 7- to 10-fold preferential resistance to colchicine and Adriamycin compared with cells expressing equivalent amounts of MDR3. Conversely, cells transfected with and expressing MDR3 showed a two- to threefold preferential resistance to actinomycin D over their cellular counterpart expressing MDR1. These results suggest that MDR1 and MDR3 are membrane-associated efflux pumps which, in multidrug-resistant cells and perhaps normal tissues, have overlapping but distinct substrate specificities. Images PMID:1969610

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

PubMed

Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

2015-03-01

A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice.

PubMed

Yu, Aiping; Wang, Ying; Yin, Jianhai; Zhang, Jing; Cao, Shengkui; Cao, Jianping; Shen, Yujuan

2018-05-30

Cystic echinococcosis is a worldwide chronic zoonotic disease caused by infection with the larval stage of Echinococcus granulosus. Previously, we found significant accumulation of myeloid-derived suppressor cells (MDSCs) in E. granulosus infection mouse models and that they play a key role in immunosuppressing T lymphocytes. Here, we compared the long non-coding RNA (lncRNA) and mRNA expression patterns between the splenic monocytic MDSCs (M-MDSCs) of E. granulosus protoscoleces-infected mice and normal mice using microarray analysis. LncRNA functions were predicted using Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Cis- and trans-regulation analyses revealed potential relationships between the lncRNAs and their target genes or related transcription factors. We found that 649 lncRNAs were differentially expressed (fold change ≥ 2, P < 0.05): 582 lncRNAs were upregulated and 67 lncRNAs were downregulated; respectively, 28 upregulated mRNAs and 1043 downregulated mRNAs were differentially expressed. The microarray data was validated by quantitative reverse transcription-PCR. The results indicated that mRNAs co-expressed with the lncRNAs are mainly involved in regulating the actin cytoskeleton, Salmonella infection, leishmaniasis, and the vascular endothelial growth factor (VEGF) signaling pathway. The lncRNA NONMMUT021591 was predicted to cis-regulate the retinoblastoma gene (Rb1), whose expression is associated with abnormal M-MDSCs differentiation. We found that 372 lncRNAs were predicted to interact with 60 transcription factors; among these, C/EBPβ (CCAAT/enhancer binding protein beta) was previously demonstrated to be a transcription factor of MDSCs. Our study identified dysregulated lncRNAs in the M-MDSCs of E. granulosus infection mouse models; they might be involved in M-MDSC-derived immunosuppression in related diseases.

Long Noncoding RNA Profiling from Fasciola Gigantica Excretory/Secretory Product-Induced M2 to M1 Macrophage Polarization.

PubMed

Luo, Honglin; Zhang, Yaoyao; Sheng, Zhaoan; Luo, Tao; Chen, Jie; Liu, Junjie; Wang, Huifeng; Chen, Miao; Shi, Yunliang; Li, Lequn

2018-05-22

Long noncoding RNAs (lncRNAs) are well known regulators of gene expression that play essential roles in macrophage activation and polarization. However, the role of lncRNA in Fasciola gigantica excretory/secretory products (ESP)-induced M2 polarization into M1 macrophages is unclear. Herein, we performed lncRNA profiling of lncRNAs and mRNAs during the ESP-induced macrophage polarization process. F. gigantica ESP was used to induce peritoneal cavity M2 macrophages in BALB/c mice (5-6 weeks old) in vivo, and these cells were subsequently isolated and stimulated with IFN-γ + LPS to induce M1 cells in vitro. LncRNA and mRNA profiling was performed via microarray at the end of both polarization stages. In total, 2,844 lncRNAs (1,579 upregulated and 1,265 downregulated) and 1,782 mRNAs (789 upregulated and 993 downregulated) were differentially expressed in M2 macrophages compared to M1 macrophages, and six lncRNAs were identified during polarization. We selected 34 differentially expressed lncRNAs and mRNAs to validate the results of microarray analysis using quantitative real-time PCR (qPCR). Pathway and Gene Ontology (GO) analyses demonstrated that these altered transcripts were involved in multiple biological processes, particularly peptidase activity and carbohydrate metabolism. Furthermore, coding and non-coding gene (CNC) and mRNA-related ceRNA network analyses were conducted to predict lncRNA expression trends and the potential target genes of these lncRNAs and mRNAs. Moreover, we determined that four lncRNAs and four mRNAs might participate in F. gigantica ESP-induced M2 polarization into M1 macrophages. This study illustrates the basic profiling of lncRNAs and mRNAs during F. gigantica ESP-induced M2 polarization into M1 macrophages and deepens our understanding of the mechanism underlying this process. © 2018 The Author(s). Published by S. Karger AG, Basel.

Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

PubMed Central

Racle, Julien; de Jonge, Kaat; Baumgaertner, Petra; Speiser, Daniel E

2017-01-01

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org). PMID:29130882

Expression Profiling Analysis Reveals Key MicroRNA-mRNA Interactions in Early Retinal Degeneration in Retinitis Pigmentosa.

PubMed

Anasagasti, Ander; Ezquerra-Inchausti, Maitane; Barandika, Olatz; Muñoz-Culla, Maider; Caffarel, María M; Otaegui, David; López de Munain, Adolfo; Ruiz-Ederra, Javier

2018-05-01

The aim of this study was to identify differentially expressed microRNAs (miRNAs) that might play an important role in the etiology of retinal degeneration in a genetic mouse model of retinitis pigmentosa (rd10 mice) at initial stages of the disease. miRNAs-mRNA interaction networks were generated for analysis of biological pathways involved in retinal degeneration. Of more than 1900 miRNAs analyzed, we selected 19 miRNAs on the basis of (1) a significant differential expression in rd10 retinas compared with control samples and (2) an inverse expression relationship with predicted mRNA targets involved in biological pathways relevant to retinal biology and/or degeneration. Seven of the selected miRNAs have been associated with retinal dystrophies, whereas, to our knowledge, nine have not been previously linked to any disease. This study contributes to our understanding of the etiology and progression of retinal degeneration.

Analysis of microRNA and gene expression profiling in triazole fungicide-treated HepG2 cell line.

PubMed

An, Yu Ri; Kim, Seung Jun; Oh, Moon-Ju; Kim, Hyun-Mi; Shim, Il-Seob; Kim, Pil-Je; Choi, Kyunghee; Hwang, Seung Yong

2013-01-07

MicroRNA (miRNA) plays an important role in various diseases and in cellular and molecular responses to toxicants. In the present study, we investigated differential expression of miRNAs in response to three triazole fungicides (myclobutanil, propiconazole, and triadimefon). The human hepatoma cell line (HepG2) was treated with the above triazoles for 3 h or 48 h. miRNA-based microarray experiments were carried out using the Agilent human miRNA v13 array. At early exposure (3h), six miRNAs were differentially expressed and at late exposure (48 h), three miRNAs were significantly expressed. Overall, this study provides an array of potential biomarkers for the above triazole fungicides. Furthermore, these miRNAs induced by triazoles could be the foundation for the development of a miRNA-based toxic biomarker library that can predict environmental toxicity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Immunohistochemical expression of mucin antigens in gallbladder adenocarcinoma: MUC1-positive and MUC2-negative expression Is associated with vessel invasion and shortened survival.

PubMed

Hiraki, Tsubasa; Yamada, Sohsuke; Higashi, Michiyo; Hatanaka, Kazuhito; Yokoyama, Seiya; Kitazono, Ikumi; Goto, Yuko; Kirishima, Mari; Batra, Surinder K; Yonezawa, Suguru; Tanimoto, Akihide

2017-06-01

Mucins play pivotal roles in influencing cancer biology, for example affecting carcinoma invasion, aggressiveness and/or metastatic potential. Our aim is to investigate the significance of expression profiles of two mucins in particular, MUC1 and MUC2, their correlations with various clinicopathological features, and prognosis in gallbladder adenocarcinoma (GBAC). We performed immunohistochemistry from patients with surgically resected GBAC, using antibodies against mucin core proteins MUC1/DF3 and MUC2/Ccp58 in 81 paraffin-embedded tumor samples. MUC1 or MUC2 expression was considered to be high when ≥ 20% or 10% of the GBAC cells showed positive staining, respectively. High MUC1 expression was revealed to have a significant relationship to the presence of pathologically lymphatic and vascular invasion, and regional lymph node metastasis. By contrast, high MUC2 expression showed a significant correlation with pathologically perineural invasion, T stage ≥ 3, and post-operative recurrence. Moreover, MUC1 showed significantly positive co-expression and potentially complementary correlations with MUC2. Multivariate analyses demonstrated that the high MUC1 expression group had significantly shorter disease-specific survival times. However, the combination of both high MUC1 and MUC2 expression did not predict worse outcome in GBACs. Therefore, although each mucin has a somewhat important role in the pathogenesis of GBAC progression, MUC1 can independently predict vessel invasion and poor prognosis in patients with GBAC. The detection of MUC1 might well offer a useful parameter for providing clinical management and treatment against postsurgical GBACs.

Correlation between lower balance of Th2 helper T-cells and expression of PD-L1/PD-1 axis genes enables prognostic prediction in patients with glioblastoma.

PubMed

Takashima, Yasuo; Kawaguchi, Atsushi; Kanayama, Tomohiko; Hayano, Azusa; Yamanaka, Ryuya

2018-04-10

Common cancer treatments include radiation therapy, chemotherapy including molecular targeted drugs and anticancer drugs, and surgical treatment. Recent studies have focused on investigating the mechanisms by which immune cells attack cancer cells and produce immune tolerance-suppressing cytokines, as well as on their potential application in cancer immunotherapy. We conducted expression profiling of CD274 ( PD-L1 ), GATA3, IFNG, IL12R, IL12RB2, IL4, PDCD1 ( PD-1 ), PDCD1LG2 ( PD-L2 ), and TBX21 ( T-bet ) using data of 158 glioblastoma multiforme (GBM) patients with clinical information available at The Cancer Genome Atlas. Principal component analysis of the expression profiling data was used to derive an equation for evaluating the status of Th1 and Th2 cells. GBM specimens were divided based on the median of the Th scores. The results revealed that Th1 High Th2 Low and Th1 Low Th2 Low statuses indicated better prognosis than Th1 High Th2 High , and were evaluated based on the downregulation of PD-L1, PD-L2, and PD-1. Furthermore, Th2 Low divided based on the threshold, as well as CD274 Low and PDCD1 Low , were associated with good prognosis. In the Th2 Low subgroup, 14 genes were identified as potential prognostic markers. Of these, SLC11A1 Low , TNFRSF1B Low , and LTBR Low also indicated good prognosis. These results suggest that low Th2 balance and low activity of the PD-L1/PD-1 axis predict good prognosis in GBM. The set of genes identified in the present study could reliably predict survival in GBM patients and serve as useful molecular markers. Furthermore, this set of genes could prove to be novel targets for cancer immunotherapy.

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

PubMed

Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan; Kim, Hoon; Barthel, Floris; Jiang, Tao; Hess, Kenneth R; Verhaak, Roel G W

2017-06-01

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Heterogeneity of (18)F-FDG PET combined with expression of EGFR may improve the prognostic stratification of advanced oropharyngeal carcinoma.

PubMed

Wang, Hung-Ming; Cheng, Nai-Ming; Lee, Li-Yu; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Liao, Chun-Ta; Yang, Lan-Yan; Yen, Tzu-Chen

2016-02-01

The Ang's risk profile (based on p16, smoking and cancer stage) is a well-known prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC). Whether heterogeneity in (18)F-fluorodeoxyglucose (FDG) positron emission tomographic (PET) images and epidermal growth factor receptor (EGFR) expression could provide additional information on clinical outcomes in advanced-stage OPSCC was investigated. Patients with stage III-IV OPSCC who completed primary therapy were eligible. Zone-size nonuniformity (ZSNU) extracted from pretreatment FDG PET scans was used as an index of image heterogeneity. EGFR and p16 expression were examined by immunohistochemistry. Disease-specific survival (DSS) and overall survival (OS) served as outcome measures. Kaplan-Meier estimates and Cox proportional hazards regression models were used for survival analysis. A bootstrap resampling technique was applied to investigate the stability of outcomes. Finally, a recursive partitioning analysis (RPA)-based model was constructed. A total of 113 patients were included, of which 28 were p16-positive. Multivariate analysis identified the Ang's profile, EGFR and ZSNU as independent predictors of both DSS and OS. Using RPA, the three risk factors were used to devise a prognostic scoring system that successfully predicted DSS in both p16-positive and -negative cases. The c-statistic of the prognostic index for DSS was 0.81, a value which was significantly superior to both AJCC stage (0.60) and the Ang's risk profile (0.68). In patients showing an Ang's high-risk profile (N = 77), the use of our scoring system clearly identified three distinct prognostic subgroups. It was concluded that a novel index may improve the prognostic stratification of patients with advanced-stage OPSCC. © 2015 UICC.

A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.

PubMed

He, Xu-Jiang; Jiang, Wu-Jun; Zhou, Mi; Barron, Andrew B; Zeng, Zhi-Jiang

2017-11-06

Honeybees (Apis mellifera) have haplodiploid sex determination: males develop from unfertilized eggs and females develop from fertilized ones. The differences in larval food also determine the development of females. Here we compared the total somatic gene expression profiles of 2-day and 4-day-old drone, queen and worker larvae by RNA-Seq. The results from a co-expression network analysis on all expressed genes showed that 2-day-old drone and worker larvae were closer in gene expression profiles than 2-day-old queen larvae. This indicated that for young larvae (2-day-old) environmental factors such as larval diet have a greater effect on gene expression profiles than ploidy or sex determination. Drones had the most distinct gene expression profiles at the 4-day larval stage, suggesting that haploidy, or sex dramatically affects the gene expression of honeybee larvae. Drone larvae showed fewer differences in gene expression profiles at the 2-day and 4-day time points than the worker and queen larval comparisons (598 against 1190 and 1181), suggesting a different pattern of gene expression regulation during the larval development of haploid males compared to diploid females. This study indicates that early in development the queen caste has the most distinct gene expression profile, perhaps reflecting the very rapid growth and morphological specialization of this caste compared to workers and drones. Later in development the haploid male drones have the most distinct gene expression profile, perhaps reflecting the influence of ploidy or sex determination on gene expression. © 2017 Institute of Zoology, Chinese Academy of Sciences.

RNA-seq analysis of the gonadal transcriptome during Alligator mississippiensis temperature-dependent sex determination and differentiation.

PubMed

Yatsu, Ryohei; Miyagawa, Shinichi; Kohno, Satomi; Parrott, Benjamin B; Yamaguchi, Katsushi; Ogino, Yukiko; Miyakawa, Hitoshi; Lowers, Russell H; Shigenobu, Shuji; Guillette, Louis J; Iguchi, Taisen

2016-01-25

The American alligator (Alligator mississippiensis) displays temperature-dependent sex determination (TSD), in which incubation temperature during embryonic development determines the sexual fate of the individual. However, the molecular mechanisms governing this process remain a mystery, including the influence of initial environmental temperature on the comprehensive gonadal gene expression patterns occurring during TSD. Our characterization of transcriptomes during alligator TSD allowed us to identify novel candidate genes involved in TSD initiation. High-throughput RNA sequencing (RNA-seq) was performed on gonads collected from A. mississippiensis embryos incubated at both a male and a female producing temperature (33.5 °C and 30 °C, respectively) in a time series during sexual development. RNA-seq yielded 375.2 million paired-end reads, which were mapped and assembled, and used to characterize differential gene expression. Changes in the transcriptome occurring as a function of both development and sexual differentiation were extensively profiled. Forty-one differentially expressed genes were detected in response to incubation at male producing temperature, and included genes such as Wnt signaling factor WNT11, histone demethylase KDM6B, and transcription factor C/EBPA. Furthermore, comparative analysis of development- and sex-dependent differential gene expression revealed 230 candidate genes involved in alligator sex determination and differentiation, and early details of the suspected male-fate commitment were profiled. We also discovered sexually dimorphic expression of uncharacterized ncRNAs and other novel elements, such as unique expression patterns of HEMGN and ARX. Twenty-five of the differentially expressed genes identified in our analysis were putative transcriptional regulators, among which were MYBL2, MYCL, and HOXC10, in addition to conventional sex differentiation genes such as SOX9, and FOXL2. Inferred gene regulatory network was constructed, and the gene-gene and temperature-gene interactions were predicted. Gonadal global gene expression kinetics during sex determination has been extensively profiled for the first time in a TSD species. These findings provide insights into the genetic framework underlying TSD, and expand our current understanding of the developmental fate pathways during vertebrate sex determination.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

Early diffusion of gene expression profiling in breast cancer patients associated with areas of high income inequality.

PubMed

Ponce, Ninez A; Ko, Michelle; Liang, Su-Ying; Armstrong, Joanne; Toscano, Michele; Chanfreau-Coffinier, Catherine; Haas, Jennifer S

2015-04-01

With the Affordable Care Act reducing coverage disparities, social factors could prominently determine where and for whom innovations first diffuse in health care markets. Gene expression profiling is a potentially cost-effective innovation that guides chemotherapy decisions in early-stage breast cancer, but adoption has been uneven across the United States. Using a sample of commercially insured women, we evaluated whether income inequality in metropolitan areas was associated with receipt of gene expression profiling during its initial diffusion in 2006-07. In areas with high income inequality, gene expression profiling receipt was higher than elsewhere, but it was associated with a 10.6-percentage-point gap between high- and low-income women. In areas with low rates of income inequality, gene expression profiling receipt was lower, with no significant differences by income. Even among insured women, income inequality may indirectly shape diffusion of gene expression profiling, with benefits accruing to the highest-income patients in the most unequal places. Policies reducing gene expression profiling disparities should address low-inequality areas and, in unequal places, practice settings serving low-income patients. Project HOPE—The People-to-People Health Foundation, Inc.

MicroRNA Expression Profiling to Identify and Validate Reference Genes for the Relative Quantification of microRNA in Rectal Cancer.

PubMed

Eriksen, Anne Haahr Mellergaard; Andersen, Rikke Fredslund; Pallisgaard, Niels; Sørensen, Flemming Brandt; Jakobsen, Anders; Hansen, Torben Frøstrup

2016-01-01

MicroRNAs (miRNAs) play important roles in regulating biological processes at the post-transcriptional level. Deregulation of miRNAs has been observed in cancer, and miRNAs are being investigated as potential biomarkers regarding diagnosis, prognosis and prediction in cancer management. Real-time quantitative polymerase chain reaction (RT-qPCR) is commonly used, when measuring miRNA expression. Appropriate normalisation of RT-qPCR data is important to ensure reliable results. The aim of the present study was to identify stably expressed miRNAs applicable as normaliser candidates in future studies of miRNA expression in rectal cancer. We performed high-throughput miRNA profiling (OpenArray®) on ten pairs of laser micro-dissected rectal cancer tissue and adjacent stroma. A global mean expression normalisation strategy was applied to identify the most stably expressed miRNAs for subsequent validation. In the first validation experiment, a panel of miRNAs were analysed on 25 pairs of micro dissected rectal cancer tissue and adjacent stroma. Subsequently, the same miRNAs were analysed in 28 pairs of rectal cancer tissue and normal rectal mucosa. From the miRNA profiling experiment, miR-645, miR-193a-5p, miR-27a and let-7g were identified as stably expressed, both in malignant and stromal tissue. In addition, NormFinder confirmed high expression stability for the four miRNAs. In the RT-qPCR based validation experiments, no significant difference between tumour and stroma/normal rectal mucosa was detected for the mean of the normaliser candidates miR-27a, miR-193a-5p and let-7g (first validation P = 0.801, second validation P = 0.321). MiR-645 was excluded from the data analysis, because it was undetected in 35 of 50 samples (first validation) and in 24 of 56 samples (second validation), respectively. Significant difference in expression level of RNU6B was observed between tumour and adjacent stromal (first validation), and between tumour and normal rectal mucosa (second validation). We recommend the mean expression of miR-27a, miR-193a-5p and let-7g as normalisation factor, when performing miRNA expression analyses by RT-qPCR on rectal cancer tissue.

Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: A report from the International DLBCL Rituximab-CHOP Consortium Program Study

PubMed Central

Visco, Carlo; Li, Yan; Xu-Monette, Zijun Y.; Miranda, Roberto N.; Green, Tina M.; Li, Yong; Tzankov, Alexander; Wen, Wei; Liu, Wei-min; Kahl, Brad S.; d’Amore, Emanuele S. G.; Montes-Moreno, Santiago; Dybkær, Karen; Chiu, April; Tam, Wayne; Orazi, Attilio; Zu, Youli; Bhagat, Govind; Winter, Jane N.; Wang, Huan-You; O’Neill, Stacey; Dunphy, Cherie H.; Hsi, Eric D.; Zhao, X. Frank; Go, Ronald S.; Choi, William W. L.; Zhou, Fan; Czader, Magdalena; Tong, Jiefeng; Zhao, Xiaoying; van Krieken, J. Han; Huang, Qing; Ai, Weiyun; Etzell, Joan; Ponzoni, Maurilio; Ferreri, Andres J. M.; Piris, Miguel A.; Møller, Michael B.; Bueso-Ramos, Carlos E.; Medeiros, L. Jeffrey; Wu, Lin; Young, Ken H.

2013-01-01

Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development - namely germinal center B-cell-like and activated B-cell-like. This classification has prognostic significance, but GEP is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1, and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B-cells. Cutoffs for each marker were obtained using receiver operating characteristic curves, obviating the need for any arbitrary method. An algorithm based on the expression of CD10, FOXP1, and BCL6 was developed that had a simpler structure than other recently proposed algorithms and 92.6% concordance with GEP. In multivariate analysis, both the International Prognostic Index and our proposed algorithm were significant independent predictors of progression-free and overall survival. In conclusion, this algorithm effectively predicts prognosis of DLBCL patients matching GEP subgroups in the era of rituximab therapy. PMID:22437443