Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

NASA Astrophysics Data System (ADS)

Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

Data-adaptive test statistics for microarray data.

PubMed

Mukherjee, Sach; Roberts, Stephen J; van der Laan, Mark J

2005-09-01

An important task in microarray data analysis is the selection of genes that are differentially expressed between different tissue samples, such as healthy and diseased. However, microarray data contain an enormous number of dimensions (genes) and very few samples (arrays), a mismatch which poses fundamental statistical problems for the selection process that have defied easy resolution. In this paper, we present a novel approach to the selection of differentially expressed genes in which test statistics are learned from data using a simple notion of reproducibility in selection results as the learning criterion. Reproducibility, as we define it, can be computed without any knowledge of the 'ground-truth', but takes advantage of certain properties of microarray data to provide an asymptotically valid guide to expected loss under the true data-generating distribution. We are therefore able to indirectly minimize expected loss, and obtain results substantially more robust than conventional methods. We apply our method to simulated and oligonucleotide array data. By request to the corresponding author.

Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

PubMed Central

von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

2005-01-01

Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method

PubMed Central

Takahashi, Hiro; Nemoto, Takeshi; Yoshida, Teruhiko; Honda, Hiroyuki; Hasegawa, Tadashi

2006-01-01

Background Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis and selection of treatment. To accomplish this objective, it is important to establish a sophisticated algorithm that can deal with large quantities of data such as gene expression profiles obtained by DNA microarray analysis. Results Previously, we developed the projective adaptive resonance theory (PART) filtering method as a gene filtering method. This is one of the clustering methods that can select specific genes for each subtype. In this study, we applied the PART filtering method to analyze microarray data that were obtained from soft tissue sarcoma (STS) patients for the extraction of subtype-specific genes. The performance of the filtering method was evaluated by comparison with other widely used methods, such as signal-to-noise, significance analysis of microarrays, and nearest shrunken centroids. In addition, various combinations of filtering and modeling methods were used to extract essential subtype-specific genes. The combination of the PART filtering method and boosting – the PART-BFCS method – showed the highest accuracy. Seven genes among the 15 genes that are frequently selected by this method – MIF, CYFIP2, HSPCB, TIMP3, LDHA, ABR, and RGS3 – are known prognostic marker genes for other tumors. These genes are candidate marker genes for the diagnosis of STS. Correlation analysis was performed to extract marker genes that were not selected by PART-BFCS. Sixteen genes among those extracted are also known prognostic marker genes for other tumors, and they could be candidate marker genes for the diagnosis of STS. Conclusion The procedure that consisted of two steps, such as the PART-BFCS and the correlation analysis, was proposed. The results suggest that novel diagnostic and therapeutic targets for STS can be extracted by a procedure that includes the PART filtering method. PMID:16948864

Methodological Challenges in Protein Microarray and Immunohistochemistry for the Discovery of Novel Autoantibodies in Paediatric Acute Disseminated Encephalomyelitis

PubMed Central

Peschl, Patrick; Ramberger, Melanie; Höftberger, Romana; Jöhrer, Karin; Baumann, Matthias; Rostásy, Kevin; Reindl, Markus

2017-01-01

Acute disseminated encephalomyelitis (ADEM) is a rare autoimmune-mediated demyelinating disease affecting mainly children and young adults. Differentiation to multiple sclerosis is not always possible, due to overlapping clinical symptoms and recurrent and multiphasic forms. Until now, immunoglobulins reactive to myelin oligodendrocyte glycoprotein (MOG antibodies) have been found in a subset of patients with ADEM. However, there are still patients lacking autoantibodies, necessitating the identification of new autoantibodies as biomarkers in those patients. Therefore, we aimed to identify novel autoantibody targets in ADEM patients. Sixteen ADEM patients (11 seronegative, 5 seropositive for MOG antibodies) were analysed for potential new biomarkers, using a protein microarray and immunohistochemistry on rat brain tissue to identify antibodies against intracellular and surface neuronal and glial antigens. Nine candidate antigens were identified in the protein microarray analysis in at least two patients per group. Immunohistochemistry on rat brain tissue did not reveal new target antigens. Although no new autoantibody targets could be found here, future studies should aim to identify new biomarkers for therapeutic and prognostic purposes. The microarray analysis and immunohistochemistry methods used here have several limitations, which should be considered in future searches for biomarkers. PMID:28327523

Soy consumption and histopathologic markers in breast tissue using tissue microarrays.

PubMed

Maskarinec, Gertraud; Erber, Eva; Verheus, Martijn; Hernandez, Brenda Y; Killeen, Jeffrey; Cashin, Suzanne; Cline, J Mark

2009-01-01

This study examined the relation of soy intake with hormonal and proliferation markers in benign and malignant breast tissue using tissue microarrays (TMAs). TMAs with up to 4 malignant and 4 benign tissue samples for 268 breast cancer cases were constructed. Soy intake in early life and in adulthood was assessed by questionnaire. The TMAs were stained for estrogen receptor (ER) alpha, ERbeta, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2/neu), proliferating cell nuclear antigen (PCNA), and Ki-67 using standard immunohistochemical methods. Logistic regression was applied for statistical analysis. A higher percentage of women showed positive marker expression in malignant than in benign tissue. With one exception, HER2/neu, no significant associations between soy intake and pathologic markers were observed. Early life soy intake was associated with lower HER2/neu and PCNA staining of malignant tissue. In benign tissue, early life soy intake showed higher ER and PR expression, but no difference in proliferation markers. The results of this investigation provide some assurance that soy intake does not adversely affect markers of proliferation. TMAs were shown to be a useful tool for epidemiologic research.

Optimised laser microdissection of the human ocular surface epithelial regions for microarray studies

PubMed Central

2013-01-01

Background The most important challenge of performing insitu transcriptional profiling of the human ocular surface epithelial regions is obtaining samples in sufficient amounts, without contamination from adjacent tissue, as the region of interest is microscopic and closely apposed to other tissues regions. We have effectively collected ocular surface (OS) epithelial tissue samples from the Limbal Epithelial Crypt (LEC), limbus, cornea and conjunctiva of post-mortem cadaver eyes with laser microdissection (LMD) technique for gene expression studies with spotted oligonucleotide microarrays and Gene 1.0 ST arrays. Methods Human donor eyes (4 pairs for spotted oligonucleotide microarrays, 3 pairs for Gene 1.0 ST arrays) consented for research were included in this study with due ethical approval of the Nottingham Research Ethics Committee. Eye retrieval was performed within 36 hours of post-mortem period. The dissected corneoscleral buttons were immersed in OCT media and frozen in liquid nitrogen and stored at −80°C till further use. Microscopic tissue sections of interest were taken on PALM slides and stained with Toluidine Blue for laser microdissection with PALM microbeam systems. Optimisation of the laser microdissection technique was crucial for efficient and cost effective sample collection. Results The starting concentration of RNA as stipulated by the protocol of microarray platforms was taken as the cut-off concentration of RNA samples in our studies. The area of LMD tissue processed for spotted oligonucleotide microarray study ranged from 86,253 μm2 in LEC to 392,887 μm2 in LEC stroma. The RNA concentration of the LMD samples ranged from 22 to 92 pg/μl. The recommended starting concentration of the RNA samples used for Gene 1.0 ST arrays was 6 ng/5 μl. To achieve the desired RNA concentration the area of ocular surface epithelial tissue sample processed for the Gene 1.0 ST array experiments was approximately 100,0000 μm2 to 130,0000 μm2. RNA concentration of these samples ranged from 10.88 ng/12 μl to 25.8 ng/12 μl, with the RNA integrity numbers (RIN) for these samples from 3.3 to 7.9. RNA samples with RIN values below 2, that had failed to amplify satisfactorily were discarded. Conclusions The optimised protocol for sample collection and laser microdissection improved the RNA yield of the insitu ocular surface epithelial regions for effective microarray studies on spotted oligonucleotide and affymetrix platforms. PMID:24160452

Multiple immunofluorescence labelling of formalin-fixed paraffin-embedded (FFPE) tissue

PubMed Central

Robertson, David; Savage, Kay; Reis-Filho, Jorge S; Isacke, Clare M

2008-01-01

Background Investigating the expression of candidate genes in tissue samples usually involves either immunohistochemical labelling of formalin-fixed paraffin-embedded (FFPE) sections or immunofluorescence labelling of cryosections. Although both of these methods provide essential data, both have important limitations as research tools. Consequently, there is a demand in the research community to be able to perform routine, high quality immunofluorescence labelling of FFPE tissues. Results We present here a robust optimised method for high resolution immunofluorescence labelling of FFPE tissues, which involves the combination of antigen retrieval, indirect immunofluorescence and confocal laser scanning microscopy. We demonstrate the utility of this method with examples of immunofluorescence labelling of human kidney, human breast and a tissue microarray of invasive human breast cancers. Finally, we demonstrate that stained slides can be stored in the short term at 4°C or in the longer term at -20°C prior to images being collected. This approach has the potential to unlock a large in vivo database for immunofluorescence investigations and has the major advantages over immunohistochemistry in that it provides higher resolution imaging of antigen localization and the ability to label multiple antigens simultaneously. Conclusion This method provides a link between the cell biology and pathology communities. For the cell biologist, it will enable them to utilise the vast archive of pathology specimens to advance their in vitro data into in vivo samples, in particular archival material and tissue microarrays. For the pathologist, it will enable them to utilise multiple antibodies on a single section to characterise particular cell populations or to test multiple biomarkers in limited samples and define with greater accuracy cellular heterogeneity in tissue samples. PMID:18366689

ROKU: a novel method for identification of tissue-specific genes.

PubMed

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-06-12

One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

Tissue microarray immunohistochemical detection of brachyury is not a prognostic indicator in chordoma.

PubMed

Zhang, Linlin; Guo, Shang; Schwab, Joseph H; Nielsen, G Petur; Choy, Edwin; Ye, Shunan; Zhang, Zhan; Mankin, Henry; Hornicek, Francis J; Duan, Zhenfeng

2013-01-01

Brachyury is a marker for notochord-derived tissues and neoplasms, such as chordoma. However, the prognostic relevance of brachyury expression in chordoma is still unknown. The improvement of tissue microarray technology has provided the opportunity to perform analyses of tumor tissues on a large scale in a uniform and consistent manner. This study was designed with the use of tissue microarray to determine the expression of brachyury. Brachyury expression in chordoma tissues from 78 chordoma patients was analyzed by immunohistochemical staining of tissue microarray. The clinicopathologic parameters, including gender, age, location of tumor and metastatic status were evaluated. Fifty-nine of 78 (75.64%) tumors showed nuclear staining for brachyury, and among them, 29 tumors (49.15%) showed 1+ (<30% positive cells) staining, 15 tumors (25.42%) had 2+ (31% to 60% positive cells) staining, and 15 tumors (25.42%) demonstrated 3+ (61% to 100% positive cells) staining. Brachyury nuclear staining was detected more frequently in sacral chordomas than in chordomas of the mobile spine. However, there was no significant relationship between brachyury expression and other clinical variables. By Kaplan-Meier analysis, brachyury expression failed to produce any significant relationship with the overall survival rate. In conclusion, brachyury expression is not a prognostic indicator in chordoma.

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

NASA Astrophysics Data System (ADS)

Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

Extraction and labeling methods for microarrays using small amounts of plant tissue.

PubMed

Stimpson, Alexander J; Pereira, Rhea S; Kiss, John Z; Correll, Melanie J

2009-03-01

Procedures were developed to maximize the yield of high-quality RNA from small amounts of plant biomass for microarrays. Two disruption techniques (bead milling and pestle and mortar) were compared for the yield and the quality of RNA extracted from 1-week-old Arabidopsis thaliana seedlings (approximately 0.5-30 mg total biomass). The pestle and mortar method of extraction showed enhanced RNA quality at the smaller biomass samples compared with the bead milling technique, although the quality in the bead milling could be improved with additional cooling steps. The RNA extracted from the pestle and mortar technique was further tested to determine if the small quantity of RNA (500 ng-7 microg) was appropriate for microarray analyses. A new method of low-quantity RNA labeling for microarrays (NuGEN Technologies, Inc.) was used on five 7-day-old seedlings (approximately 2.5 mg fresh weight total) of Arabidopsis that were grown in the dark and exposed to 1 h of red light or continued dark. Microarray analyses were performed on a small plant sample (five seedlings; approximately 2.5 mg) using these methods and compared with extractions performed with larger biomass samples (approximately 500 roots). Many well-known light-regulated genes between the small plant samples and the larger biomass samples overlapped in expression changes, and the relative expression levels of selected genes were confirmed with quantitative real-time polymerase chain reaction, suggesting that these methods can be used for plant experiments where the biomass is extremely limited (i.e. spaceflight studies).

Using pathway modules as targets for assay development in xenobiotic screening

EPA Science Inventory

Toxicology and pharmaceutical research is increasingly making use of high throughout-screening (HTS) methods to assess the effects of chemicals on molecular pathways, cells and tissues. Whole-genome microarray analysis provides broad information on the response of biological syst...

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed Central

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-01-01

Background Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Results Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. Conclusion In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects. PMID:12962547

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-09-08

Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.

Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

PubMed

Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

2015-06-01

White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

PubMed

Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

2012-01-01

Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

Cruella: developing a scalable tissue microarray data management system.

PubMed

Cowan, James D; Rimm, David L; Tuck, David P

2006-06-01

Compared with DNA microarray technology, relatively little information is available concerning the special requirements, design influences, and implementation strategies of data systems for tissue microarray technology. These issues include the requirement to accommodate new and different data elements for each new project as well as the need to interact with pre-existing models for clinical, biological, and specimen-related data. To design and implement a flexible, scalable tissue microarray data storage and management system that could accommodate information regarding different disease types and different clinical investigators, and different clinical investigation questions, all of which could potentially contribute unforeseen data types that require dynamic integration with existing data. The unpredictability of the data elements combined with the novelty of automated analysis algorithms and controlled vocabulary standards in this area require flexible designs and practical decisions. Our design includes a custom Java-based persistence layer to mediate and facilitate interaction with an object-relational database model and a novel database schema. User interaction is provided through a Java Servlet-based Web interface. Cruella has become an indispensable resource and is used by dozens of researchers every day. The system stores millions of experimental values covering more than 300 biological markers and more than 30 disease types. The experimental data are merged with clinical data that has been aggregated from multiple sources and is available to the researchers for management, analysis, and export. Cruella addresses many of the special considerations for managing tissue microarray experimental data and the associated clinical information. A metadata-driven approach provides a practical solution to many of the unique issues inherent in tissue microarray research, and allows relatively straightforward interoperability with and accommodation of new data models.

Comparing transformation methods for DNA microarray data

PubMed Central

Thygesen, Helene H; Zwinderman, Aeilko H

2004-01-01

Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method. PMID:15202953

Comparing transformation methods for DNA microarray data.

PubMed

Thygesen, Helene H; Zwinderman, Aeilko H

2004-06-17

When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

Recursive feature selection with significant variables of support vectors.

PubMed

Tsai, Chen-An; Huang, Chien-Hsun; Chang, Ching-Wei; Chen, Chun-Houh

2012-01-01

The development of DNA microarray makes researchers screen thousands of genes simultaneously and it also helps determine high- and low-expression level genes in normal and disease tissues. Selecting relevant genes for cancer classification is an important issue. Most of the gene selection methods use univariate ranking criteria and arbitrarily choose a threshold to choose genes. However, the parameter setting may not be compatible to the selected classification algorithms. In this paper, we propose a new gene selection method (SVM-t) based on the use of t-statistics embedded in support vector machine. We compared the performance to two similar SVM-based methods: SVM recursive feature elimination (SVMRFE) and recursive support vector machine (RSVM). The three methods were compared based on extensive simulation experiments and analyses of two published microarray datasets. In the simulation experiments, we found that the proposed method is more robust in selecting informative genes than SVMRFE and RSVM and capable to attain good classification performance when the variations of informative and noninformative genes are different. In the analysis of two microarray datasets, the proposed method yields better performance in identifying fewer genes with good prediction accuracy, compared to SVMRFE and RSVM.

Microarray expression profiling in adhesion and normal peritoneal tissues.

PubMed

Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

2012-05-01

To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Cell and tissue microarray technologies for protein and nucleic acid expression profiling.

PubMed

Cardano, Marina; Diaferia, Giuseppe R; Falavigna, Maurizio; Spinelli, Chiara C; Sessa, Fausto; DeBlasio, Pasquale; Biunno, Ida

2013-02-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform.

Biomarkers of Selenium Action in Prostate Cancer

DTIC Science & Technology

2005-01-01

secretory by conventional methods according to published literature. In addition, we have determined the similarities and differences in global gene...transition zone tissue of a 42-year-old man ac- arrays in the resulting data tables were ordered by their cording to previously described methods [4]. The pre...hundred fifteen genes identified by ELISA method . Replicating the conditions used for the SAM analysis showed significant differential expres- microarray

ROKU: a novel method for identification of tissue-specific genes

PubMed Central

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-01-01

Background One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. Results We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. Conclusion ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes. PMID:16764735

Finding Patterns of Emergence in Science and Technology

DTIC Science & Technology

2012-09-24

formal evaluation scheduled – Case Studies, Eight Examples: Tissue Engineering, Cold Fusion, RF Metamaterials, DNA Microarrays, Genetic Algorithms, RNAi...emerging capabilities Case Studies, Eight Examples: • Tissue Engineering, Cold Fusion, RF Metamaterials, DNA Microarrays, Genetic Algorithms...Evidence Quality (i.e., the rubric ) and deliver comprehensible evidential support for nomination • Demonstrate proof-of-concept nomination for Chinese

Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

NASA Astrophysics Data System (ADS)

Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan

2016-03-01

Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non-epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin-eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long-term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04-4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84-3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99-3.88, AUC 0.61). As a conclusion, a deep-learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.

Recurrent pregnancy loss evaluation combined with 24-chromosome microarray of miscarriage tissue provides a probable or definite cause of pregnancy loss in over 90% of patients.

PubMed

Popescu, F; Jaslow, C R; Kutteh, W H

2018-04-01

Will the addition of 24-chromosome microarray analysis on miscarriage tissue combined with the standard American Society for Reproductive Medicine (ASRM) evaluation for recurrent miscarriage explain most losses? Over 90% of patients with recurrent pregnancy loss (RPL) will have a probable or definitive cause identified when combining genetic testing on miscarriage tissue with the standard ASRM evaluation for recurrent miscarriage. RPL is estimated to occur in 2-4% of reproductive age couples. A probable cause can be identified in approximately 50% of patients after an ASRM recommended workup including an evaluation for parental chromosomal abnormalities, congenital and acquired uterine anomalies, endocrine imbalances and autoimmune factors including antiphospholipid syndrome. Single-center, prospective cohort study that included 100 patients seen in a private RPL clinic from 2014 to 2017. All 100 women had two or more pregnancy losses, a complete evaluation for RPL as defined by the ASRM, and miscarriage tissue evaluated by 24-chromosome microarray analysis after their second or subsequent miscarriage. Frequencies of abnormal results for evidence-based diagnostic tests considered definite or probable causes of RPL (karyotyping for parental chromosomal abnormalities, and 24-chromosome microarray evaluation for products of conception (POC); pelvic sonohysterography, hysterosalpingogram, or hysteroscopy for uterine anomalies; immunological tests for lupus anticoagulant and anticardiolipin antibodies; and blood tests for thyroid stimulating hormone (TSH), prolactin and hemoglobin A1c) were evaluated. We excluded cases where there was maternal cell contamination of the miscarriage tissue or if the ASRM evaluation was incomplete. A cost analysis for the evaluation of RPL was conducted to determine whether a proposed procedure of 24-chromome microarray evaluation followed by an ASRM RPL workup (for those RPL patients who had a normal 24-chromosome microarray evaluation) was more cost-efficient than conducting ASRM RPL workups on RPL patients followed by 24-chromosome microarray analysis (for those RPL patients who had a normal RPL workup). A definite or probable cause of pregnancy loss was identified in the vast majority (95/100; 95%) of RPL patients when a 24-chromosome pair microarray evaluation of POC testing is combined with the standard ASRM RPL workup evaluation at the time of the second or subsequent loss. The ASRM RPL workup identified an abnormality and a probable explanation for pregnancy loss in only 45/100 or 45% of all patients. A definite abnormality was identified in 67/100 patients or 67% when initial testing was performed using 24-chromosome microarray analyses on the miscarriage tissue. Only 5/100 (5%) patients, who had a euploid loss and a normal ASRM RPL workup, had a pregnancy loss without a probable or definitive cause identified. All other losses were explained by an abnormal 24-chromosome microarray analysis of the miscarriage tissue, an abnormal finding of the RPL workup, or a combination of both. Results from the cost analysis indicated that an initial approach of using a 24-chromosome microarray analysis on miscarriage tissue resulted in a 50% savings in cost to the health care system and to the patient. This is a single-center study on a small group of well-characterized women with RPL. There was an incomplete follow-up on subsequent pregnancy outcomes after evaluation, however this should not affect our principal results. The maternal age of patients varied from 26 to 45 years old. More aneuploid pregnancy losses would be expected in older women, particularly over the age of 35 years old. Evaluation of POC using 24-chromosome microarray analysis adds significantly to the ASRM recommended evaluation of RPL. Genetic evaluation on miscarriage tissue obtained at the time of the second and subsequent pregnancy losses should be offered to all couples with two or more consecutive pregnancy losses. The combination of a genetic evaluation on miscarriage tissue with an evidence-based evaluation for RPL will identify a probable or definitive cause in over 90% of miscarriages. No funding was received for this study and there are no conflicts of interest to declare. Not applicable.

Cell and Tissue Microarray Technologies for Protein and Nucleic Acid Expression Profiling

PubMed Central

Cardano, Marina; Diaferia, Giuseppe R.; Falavigna, Maurizio; Spinelli, Chiara C.; Sessa, Fausto; DeBlasio, Pasquale

2013-01-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform. PMID:23172795

ModuleMiner - improved computational detection of cis-regulatory modules: are there different modes of gene regulation in embryonic development and adult tissues?

PubMed Central

Van Loo, Peter; Aerts, Stein; Thienpont, Bernard; De Moor, Bart; Moreau, Yves; Marynen, Peter

2008-01-01

We present ModuleMiner, a novel algorithm for computationally detecting cis-regulatory modules (CRMs) in a set of co-expressed genes. ModuleMiner outperforms other methods for CRM detection on benchmark data, and successfully detects CRMs in tissue-specific microarray clusters and in embryonic development gene sets. Interestingly, CRM predictions for differentiated tissues exhibit strong enrichment close to the transcription start site, whereas CRM predictions for embryonic development gene sets are depleted in this region. PMID:18394174

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

The tissue microarray data exchange specification: Extending TMA DES to provide flexible scoring and incorporate virtual slides

PubMed Central

Wright, Alexander; Lyttleton, Oliver; Lewis, Paul; Quirke, Philip; Treanor, Darren

2011-01-01

Background: Tissue MicroArrays (TMAs) are a high throughput technology for rapid analysis of protein expression across hundreds of patient samples. Often, data relating to TMAs is specific to the clinical trial or experiment it is being used for, and not interoperable. The Tissue Microarray Data Exchange Specification (TMA DES) is a set of eXtensible Markup Language (XML)-based protocols for storing and sharing digitized Tissue Microarray data. XML data are enclosed by named tags which serve as identifiers. These tag names can be Common Data Elements (CDEs), which have a predefined meaning or semantics. By using this specification in a laboratory setting with increasing demands for digital pathology integration, we found that the data structure lacked the ability to cope with digital slide imaging in respect to web-enabled digital pathology systems and advanced scoring techniques. Materials and Methods: By employing user centric design, and observing behavior in relation to TMA scoring and associated data, the TMA DES format was extended to accommodate the current limitations. This was done with specific focus on developing a generic tool for handling any given scoring system, and utilizing data for multiple observations and observers. Results: DTDs were created to validate the extensions of the TMA DES protocol, and a test set of data containing scores for 6,708 TMA core images was generated. The XML was then read into an image processing algorithm to utilize the digital pathology data extensions, and scoring results were easily stored alongside the existing multiple pathologist scores. Conclusions: By extending the TMA DES format to include digital pathology data and customizable scoring systems for TMAs, the new system facilitates the collaboration between pathologists and organizations, and can be used in automatic or manual data analysis. This allows complying systems to effectively communicate complex and varied scoring data. PMID:21572508

Equalizer reduces SNP bias in Affymetrix microarrays.

PubMed

Quigley, David

2015-07-30

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

Implementation of spectral clustering with partitioning around medoids (PAM) algorithm on microarray data of carcinoma

NASA Astrophysics Data System (ADS)

Cahyaningrum, Rosalia D.; Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Technology of microarray became one of the imperative tools in life science to observe the gene expression levels, one of which is the expression of the genes of people with carcinoma. Carcinoma is a cancer that forms in the epithelial tissue. These data can be analyzed such as the identification expressions hereditary gene and also build classifications that can be used to improve diagnosis of carcinoma. Microarray data usually served in large dimension that most methods require large computing time to do the grouping. Therefore, this study uses spectral clustering method which allows to work with any object for reduces dimension. Spectral clustering method is a method based on spectral decomposition of the matrix which is represented in the form of a graph. After the data dimensions are reduced, then the data are partitioned. One of the famous partition method is Partitioning Around Medoids (PAM) which is minimize the objective function with exchanges all the non-medoid points into medoid point iteratively until converge. Objectivity of this research is to implement methods spectral clustering and partitioning algorithm PAM to obtain groups of 7457 genes with carcinoma based on the similarity value. The result in this study is two groups of genes with carcinoma.

A microarray analysis of sexual dimorphism of adipose tissues in high-fat-diet-induced obese mice

PubMed Central

Grove, KL; Fried, SK; Greenberg, AS; Xiao, XQ; Clegg, DJ

2013-01-01

Objective A sexual dimorphism exists in body fat distribution; females deposit relatively more fat in subcutaneous/inguinal depots whereas males deposit more fat in the intra-abdominal/gonadal depot. Our objective was to systematically document depot- and sex-related differences in the accumulation of adipose tissue and gene expression, comparing differentially expressed genes in diet-induced obese mice with mice maintained on a chow diet. Research Design and Methods We used a microarray approach to determine whether there are sexual dimorphisms in gene expression in age-matched male, female or ovariectomized female (OVX) C57/BL6 mice maintained on a high-fat (HF) diet. We then compared expression of validated genes between the sexes on a chow diet. Results After exposure to a high fat diet for 12 weeks, females gained less weight than males. The microarray analyses indicate in intra-abdominal/gonadal adipose tissue in females 1642 genes differ by at least twofold between the depots, whereas 706 genes differ in subcutaneous/inguinal adipose tissue when compared with males. Only 138 genes are commonly regulated in both sexes and adipose tissue depots. Inflammatory genes (cytokine–cytokine receptor interactions and acute-phase protein synthesis) are upregulated in males when compared with females, and there is a partial reversal after OVX, where OVX adipose tissue gene expression is more ′male-like′. This pattern is not observed in mice maintained on chow. Histology of male gonadal white adipose tissue (GWAT) shows more crown-like structures than females, indicative of inflammation and adipose tissue remodeling. In addition, genes related to insulin signaling and lipid synthesis are higher in females than males, regardless of dietary exposure. Conclusions These data suggest that male and female adipose tissue differ between the sexes regardless of diet. Moreover, HF diet exposure elicits a much greater inflammatory response in males when compared with females. This data set underscores the importance of analyzing depot-, sex- and steroid-dependent regulation of adipose tissue distribution and function. PMID:20157318

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

PubMed

Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Laser capture microdissection of embryonic cells and preparation of RNA for microarray assays.

PubMed

Redmond, Latasha C; Pang, Christopher J; Dumur, Catherine; Haar, Jack L; Lloyd, Joyce A

2014-01-01

In order to compare the global gene expression profiles of different embryonic cell types, it is first necessary to isolate the specific cells of interest. The purpose of this chapter is to provide a step-by-step protocol to perform laser capture microdissection (LCM) on embryo samples and obtain sufficient amounts of high-quality RNA for microarray hybridizations. Using the LCM/microarray strategy on mouse embryo samples has some challenges, because the cells of interest are available in limited quantities. The first step in the protocol is to obtain embryonic tissue, and immediately cryoprotect and freeze it in a cryomold containing Optimal Cutting Temperature freezing media (Sakura Finetek), using a dry ice-isopentane bath. The tissue is then cryosectioned, and the microscope slides are processed to fix, stain, and dehydrate the cells. LCM is employed to isolate specific cell types from the slides, identified under the microscope by virtue of their morphology. Detailed protocols are provided for using the currently available ArcturusXT LCM instrument and CapSure(®) LCM Caps, to which the selected cells adhere upon laser capture. To maintain RNA integrity, upon removing a slide from the final processing step, or attaching the first cells on the LCM cap, LCM is completed within 20 min. The cells are then immediately recovered from the LCM cap using a denaturing solution that stabilizes RNA integrity. RNA is prepared using standard methods, modified for working with small samples. To ensure the validity of the microarray data, the quality of the RNA is assessed using the Agilent bioanalyzer. Only RNA that is of sufficient integrity and quantity is used to perform microarray assays. This chapter provides guidance regarding troubleshooting and optimization to obtain high-quality RNA from cells of limited availability, obtained from embryo samples by LCM.

Laser Capture Microdissection of Embryonic Cells and Preparation of RNA for Microarray Assays

PubMed Central

Redmond, Latasha C.; Pang, Christopher J.; Dumur, Catherine; Haar, Jack L.; Lloyd, Joyce A.

2014-01-01

In order to compare the global gene expression profiles of different embryonic cell types, it is first necessary to isolate the specific cells of interest. The purpose of this chapter is to provide a step-by-step protocol to perform laser capture microdissection (LCM) on embryo samples and obtain sufficient amounts of high-quality RNA for microarray hybridizations. Using the LCM/microarray strategy on mouse embryo samples has some challenges, because the cells of interest are available in limited quantities. The first step in the protocol is to obtain embryonic tissue, and immediately cryoprotect and freeze it in a cryomold containing Optimal Cutting Temperature freezing media (Sakura Finetek), using a dry ice–isopentane bath. The tissue is then cryosectioned, and the microscope slides are processed to fix, stain, and dehydrate the cells. LCM is employed to isolate specific cell types from the slides, identified under the microscope by virtue of their morphology. Detailed protocols are provided for using the currently available ArcturusXT LCM instrument and CapSure® LCM Caps, to which the selected cells adhere upon laser capture. To maintain RNA integrity, upon removing a slide from the final processing step, or attaching the first cells on the LCM cap, LCM is completed within 20 min. The cells are then immediately recovered from the LCM cap using a denaturing solution that stabilizes RNA integrity. RNA is prepared using standard methods, modified for working with small samples. To ensure the validity of the microarray data, the quality of the RNA is assessed using the Agilent bioanalyzer. Only RNA that is of sufficient integrity and quantity is used to perform microarray assays. This chapter provides guidance regarding troubleshooting and optimization to obtain high-quality RNA from cells of limited availability, obtained from embryo samples by LCM. PMID:24318813

A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics.

PubMed

Chen, Wenjin; Reiss, Michael; Foran, David J

2004-06-01

The tissue microarray (TMA) technique enables researchers to extract small cylinders of tissue from histological sections and arrange them in a matrix configuration on a recipient paraffin block such that hundreds can be analyzed simultaneously. TMA offers several advantages over traditional specimen preparation by maximizing limited tissue resources and providing a highly efficient means for visualizing molecular targets. By enabling researchers to reliably determine the protein expression profile for specific types of cancer, it may be possible to elucidate the mechanism by which healthy tissues are transformed into malignancies. Currently, the primary methods used to evaluate arrays involve the interactive review of TMA samples while they are viewed under a microscope, subjectively evaluated, and scored by a technician. This process is extremely slow, tedious, and prone to error. In order to facilitate large-scale, multi-institutional studies, a more automated and reliable means for analyzing TMAs is needed. We report here a web-based prototype which features automated imaging, registration, and distributed archiving of TMAs in multiuser network environments. The system utilizes a principal color decomposition approach to identify and characterize the predominant staining signatures of specimens in color space. This strategy was shown to be reliable for detecting and quantifying the immunohistochemical expression levels for TMAs.

NF2 tumor suppressor gene: a comprehensive and efficient detection of somatic mutations by denaturing HPLC and microarray-CGH.

PubMed

Szijan, Irene; Rochefort, Daniel; Bruder, Carl; Surace, Ezequiel; Machiavelli, Gloria; Dalamon, Viviana; Cotignola, Javier; Ferreiro, Veronica; Campero, Alvaro; Basso, Armando; Dumanski, Jan P; Rouleau, Guy A

2003-01-01

The NF2 tumor suppressor gene, located in chromosome 22q12, is involved in the development of multiple tumors of the nervous system, either associated with neurofibromatosis 2 or sporadic ones, mainly schwannomas and meningiomas. In order to evaluate the role of the NF2 gene in sporadic central nervous system (CNS) tumors, we analyzed NF2 mutations in 26 specimens: 14 meningiomas, 4 schwannomas, 4 metastases, and 4 other histopathological types of neoplasms. Denaturing high performance liquid chromatography (denaturing HPLC) and comparative genomic hybridization on a DNA microarray (microarray- CGH) were used as scanning methods for small mutations and gross rearrangements respectively. Small mutations were identified in six out of seventeen meningiomas and schwannomas, one mutation was novel. Large deletions were detected in six meningiomas. All mutations were predicted to result in truncated protein or in the absence of a large protein domain. No NF2 mutations were found in other histopathological types of CNS tumors. These results provide additional evidence that mutations in the NF2 gene play an important role in the development of sporadic meningiomas and schwannomas. Denaturing HPLC analysis of small mutations and microarray-CGH of large deletions are complementary, fast, and efficient methods for the detection of mutations in tumor tissues.

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

PubMed Central

Zlobec, Inti; Suter, Guido; Perren, Aurel; Lugli, Alessandro

2014-01-01

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research. PMID:25285857

Rapid Spoligotyping of Mycobacterium tuberculosis Complex Bacteria by Use of a Microarray System with Automatic Data Processing and Assignment

PubMed Central

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf

2012-01-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability. PMID:22553239

Rapid spoligotyping of Mycobacterium tuberculosis complex bacteria by use of a microarray system with automatic data processing and assignment.

PubMed

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf; Sachse, Konrad

2012-07-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability.

A DNA microarray for identification of selected Korean birds based on mitochondrial cytochrome c oxidase I gene sequences.

PubMed

Chung, In-Hyuk; Yoo, Hye Sook; Eah, Jae-Yong; Yoon, Hyun-Kyu; Jung, Jin-Wook; Hwang, Seung Yong; Kim, Chang-Bae

2010-10-01

DNA barcoding with the gene encoding cytochrome c oxidase I (COI) in the mitochondrial genome has been proposed as a standard marker to identify and discover animal species. Some migratory wild birds are suspected of transmitting avian influenza and pose a threat to aircraft safety because of bird strikes. We have previously reported the COI gene sequences of 92 Korean bird species. In the present study, we developed a DNA microarray to identify 17 selected bird species on the basis of nucleotide diversity. We designed and synthesized 19 specific oligonucleotide probes; these probes were arrayed on a silylated glass slide. The length of the probes was 19-24 bps. The COI sequences amplified from the tissues of the selected birds were labeled with a fluorescent probe for microarray hybridization, and unique hybridization patterns were detected for each selected species. These patterns may be considered diagnostic patterns for species identification. This microarray system will provide a sensitive and a high-throughput method for identification of Korean birds.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

PubMed

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

PubMed Central

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

2016-01-01

Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

Interlaboratory comparison of immunohistochemical testing for HER2: results of the 2004 and 2005 College of American Pathologists HER2 Immunohistochemistry Tissue Microarray Survey.

PubMed

Fitzgibbons, Patrick L; Murphy, Douglas A; Dorfman, David M; Roche, Patrick C; Tubbs, Raymond R

2006-10-01

Correct assessment of human epidermal growth factor receptor 2 (HER2) status is essential in managing patients with invasive breast carcinoma, but few data are available on the accuracy of laboratories performing HER2 testing by immunohistochemistry (IHC). To review the results of the 2004 and 2005 College of American Pathologists HER2 Immunohistochemistry Tissue Microarray Survey. The HER2 survey is designed for laboratories performing immunohistochemical staining and interpretation for HER2. The survey uses tissue microarrays, each consisting of ten 3-mm tissue cores obtained from different invasive breast carcinomas. All cases are also analyzed by fluorescence in situ hybridization. Participants receive 8 tissue microarrays (80 cases) with instructions to perform immunostaining for HER2 using the laboratory's standard procedures. The laboratory interprets the stained slides and returns results to the College of American Pathologists for analysis. In 2004 and 2005, a core was considered "graded" when at least 90% of laboratories agreed on the result--negative (0, 1+) versus positive (2+, 3+). This interlaboratory comparison survey included 102 laboratories in 2004 and 141 laboratories in 2005. Of the 160 cases in both surveys, 111 (69%) achieved 90% consensus (graded). All 43 graded cores scored as IHC-positive were fluorescence in situ hybridization-positive, whereas all but 3 of the 68 IHC-negative graded cores were fluorescence in situ hybridization-negative. Ninety-seven (95%) of 102 laboratories in 2004 and 129 (91%) of 141 laboratories in 2005 correctly scored at least 90% of the graded cores. Performance among laboratories performing HER2 IHC in this tissue microarray-based survey was excellent. Cores found to be IHC-positive or IHC-negative by participant consensus can be used as validated benchmarks for interlaboratory comparison, allowing laboratories to assess their performance and determine if improvements are needed.

The role of metalloendopeptidases in oropharyngeal carcinomas assessed by tissue microarray.

PubMed

Ribeiro, Daniel A; Nascimento, Fabio D; Fracalossi, Ana Carolina C; Noguti, Juliana; Oshima, Celina T F; Ihara, Silvia S M; Franco, Marcello F

2011-01-01

The goal of this study was to investigate the expression of some metalloendopeptidases in squamous cell carcinomas of the oropharynx as well as its relation to histological differentiation, staging of disease, and prognosis. Paraffin blocks from 21 primary tumors were obtained from archives of the Department of Pathology, Paulista Medical School, Federal University of Sao Paulo, UNIFESP/EPM. Immunohistochemistry was used to detect the expression of EP24.15 and EP24.16 by means of tissue microarrays. Expression of EP24.15 or EP24.16 was not correlated with the stage of disease, histopathological grading or recurrence in squamous cell carcinomas of the oropharynx. In summary, our results support the notion that EP24.15 and EP24.16 are expressed in carcinoma of the oropharynx; however, these do not appear to be suitable biomarkers for histological grading, disease stage or recurrence as depicted by tissue microarrays and immunohistochemistry.

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

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

He, Fei; Maslov, Sergei; Yoo, Shinjae

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

DOE PAGES

He, Fei; Maslov, Sergei; Yoo, Shinjae; ...

2016-05-25

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset andmore » found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.« less

Comparison of Dorsocervical With Abdominal Subcutaneous Adipose Tissue in Patients With and Without Antiretroviral Therapy–Associated Lipodystrophy

PubMed Central

Sevastianova, Ksenia; Sutinen, Jussi; Greco, Dario; Sievers, Meline; Salmenkivi, Kaisa; Perttilä, Julia; Olkkonen, Vesa M.; Wågsäter, Dick; Lidell, Martin E.; Enerbäck, Sven; Eriksson, Per; Walker, Ulrich A.; Auvinen, Petri; Ristola, Matti; Yki-Järvinen, Hannele

2011-01-01

OBJECTIVE Combination antiretroviral therapy (cART) is associated with lipodystrophy, i.e., loss of subcutaneous adipose tissue in the abdomen, limbs, and face and its accumulation intra-abdominally. No fat is lost dorsocervically and it can even accumulate in this region (buffalo hump). It is unknown how preserved dorsocervical fat differs from abdominal subcutaneous fat in HIV-1–infected cART-treated patients with (cART+LD+) and without (cART+LD−) lipodystrophy. RESEARCH DESIGN AND METHODS We used histology, microarray, PCR, and magnetic resonance imaging to compare dorsocervical and abdominal subcutaneous adipose tissue in cART+LD+ (n = 21) and cART+LD− (n = 11). RESULTS Albeit dorsocervical adipose tissue in cART+LD+ seems spared from lipoatrophy, its mitochondrial DNA (mtDNA; copies/cell) content was significantly lower (by 62%) than that of the corresponding tissue in cART+LD−. Expression of CD68 mRNA, a marker of macrophages, and numerous inflammatory genes in microarray were significantly lower in dorsocervical versus abdominal subcutaneous adipose tissue. Genes with the greatest difference in expression between the two depots were those involved in regulation of transcription and regionalization (homeobox genes), irrespective of lipodystrophy status. There was negligible mRNA expression of uncoupling protein 1, a gene characteristic of brown adipose tissue, in either depot. CONCLUSIONS Because mtDNA is depleted even in the nonatrophic dorsocervical adipose tissue, it is unlikely that the cause of lipoatrophy is loss of mtDNA. Dorsocervical adipose tissue is less inflamed than lipoatrophic adipose tissue. It does not resemble brown adipose tissue. The greatest difference in gene expression between dorsocervical and abdominal subcutaneous adipose tissue is in expression of homeobox genes. PMID:21602514

A novel surface modification approach for protein and cell microarrays

NASA Astrophysics Data System (ADS)

Kurkuri, Mahaveer D.; Driever, Chantelle; Thissen, Helmut W.; Voelcker, Nicholas H.

2007-01-01

Tissue engineering and stem cell technologies have led to a rapidly increasing interest in the control of the behavior of mammalian cells growing on tissue culture substrates. Multifunctional polymer coatings can assist research in this area in many ways, for example, by providing low non-specific protein adsorption properties and reactive functional groups at the surface. The latter can be used for immobilization of specific biological factors that influence cell behavior. In this study, glass slides were coated with copolymers of glycidyl methacrylate (GMA) and poly(ethylene glycol) methacrylate (PEGMA). The coatings were prepared by three different methods based on dip and spin coating as well as polymer grafting procedures. Coatings were characterized by X-ray photoelectron spectroscopy, surface sensitive infrared spectroscopy, ellipsometry and contact angle measurements. A fluorescently labelled protein was deposited onto reactive coatings using a contact microarrayer. Printing of a model protein (fluorescein labeled bovine serum albumin) was performed at different protein concentrations, pH, temperature, humidity and using different micropins. The arraying of proteins was studied with a microarray scanner. Arrays printed at a protein concentration above 50 μg/mL prepared in pH 5 phosphate buffer at 10°C and 65% relative humidity gave the most favourable results in terms of the homogeneity of the printed spots and the fluorescence intensity.

Semantically enabled and statistically supported biological hypothesis testing with tissue microarray databases

PubMed Central

2011-01-01

Background Although many biological databases are applying semantic web technologies, meaningful biological hypothesis testing cannot be easily achieved. Database-driven high throughput genomic hypothesis testing requires both of the capabilities of obtaining semantically relevant experimental data and of performing relevant statistical testing for the retrieved data. Tissue Microarray (TMA) data are semantically rich and contains many biologically important hypotheses waiting for high throughput conclusions. Methods An application-specific ontology was developed for managing TMA and DNA microarray databases by semantic web technologies. Data were represented as Resource Description Framework (RDF) according to the framework of the ontology. Applications for hypothesis testing (Xperanto-RDF) for TMA data were designed and implemented by (1) formulating the syntactic and semantic structures of the hypotheses derived from TMA experiments, (2) formulating SPARQLs to reflect the semantic structures of the hypotheses, and (3) performing statistical test with the result sets returned by the SPARQLs. Results When a user designs a hypothesis in Xperanto-RDF and submits it, the hypothesis can be tested against TMA experimental data stored in Xperanto-RDF. When we evaluated four previously validated hypotheses as an illustration, all the hypotheses were supported by Xperanto-RDF. Conclusions We demonstrated the utility of high throughput biological hypothesis testing. We believe that preliminary investigation before performing highly controlled experiment can be benefited. PMID:21342584

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

Validation of the Swine Protein-Annotated Oligonucleotide Microarray

USDA-ARS?s Scientific Manuscript database

The specificity and utility of the Swine Protein-Annotated Oligonucleotide Microarray, or Pigoligoarray (www.pigoligoarray.org), has been evaluated by profiling the expression of transcripts from four porcine tissues. Tools for comparative analyses of expression on the Pigoligoarray were developed i...

Overexpression of Plasminogen Activator Inhibitor-1 in Advanced Gastric Cancer with Aggressive Lymph Node Metastasis

PubMed Central

Suh, Yun-Suhk; Yu, Jieun; Kim, Byung Chul; Choi, Boram; Han, Tae-Su; Ahn, Hye Seong; Kong, Seong-Ho; Lee, Hyuk-Joon; Kim, Woo Ho; Yang, Han-Kwang

2015-01-01

Purpose The purpose of this study is to investigate differentially expressed genes using DNA microarray between advanced gastric cancer (AGC) with aggressive lymph node (LN) metastasis and that with a more advanced tumor stage but without LN metastasis. Materials and Methods Five sample pairs of gastric cancer tissue and normal gastric mucosa were taken from three patients with T3N3 stage (highN) and two with T4N0 stage (lowN). Data from triplicate DNA microarray experiments were analyzed, and candidate genes were identified using a volcano plot that showed ≥ 2-fold differential expression and were significant by Welch's t test (p < 0.05) between highN and lowN. Those selected genes were validated independently by reverse-transcriptase–polymerase chain reaction (RT-PCR) using five AGC patients, and tissue-microarray (TMA) comprising 47 AGC patients. Results CFTR, LAMC2, SERPINE2, F2R, MMP7, FN1, TIMP1, plasminogen activator inhibitor-1 (PAI-1), ITGB8, SDS, and TMPRSS4 were commonly up-regulated over 2-fold in highN. REG3A, CD24, ITLN1, and WBP5 were commonly down-regulated over 2-fold in lowN. Among these genes, overexpression of PAI-1 was validated by RT-PCR, and TMA showed 16.7% (7/42) PAI-1 expression in T3N3, but none (0/5) in T4N0 (p=0.393). Conclusion DNA microarray analysis and validation by RT-PCR and TMA showed that overexpression of PAI-1 is related to aggressive LN metastasis in AGC. PMID:25687870

Successful Application of Microarray Technology to Microdissected Formalin-Fixed, Paraffin-Embedded Tissue

PubMed Central

Coudry, Renata A.; Meireles, Sibele I.; Stoyanova, Radka; Cooper, Harry S.; Carpino, Alan; Wang, Xianqun; Engstrom, Paul F.; Clapper, Margie L.

2007-01-01

The establishment of a reliable method for using RNA from formalin-fixed, paraffin-embedded (FFPE) tissue would provide an opportunity to obtain novel gene expression data from the vast amounts of archived tissue. A custom-designed 22,000 oligonucleotide array was used in the present study to compare the gene expression profile of colonic epithelial cells isolated by laser capture microdissection from FFPE-archived samples with that of the same cell population from matched frozen samples, the preferred source of RNA. Total RNA was extracted from FFPE tissues, amplified, and labeled using the Paradise Reagent System. The quality of the input RNA was assessed by the Bioanalyzer profile, reverse transcriptase-polymerase chain reaction, and agarose gel electrophoresis. The results demonstrate that it is possible to obtain reliable microarray data from FFPE samples using RNA acquired by laser capture microdissection. The concordance between matched FFPE and frozen samples was evaluated and expressed as a Pearson’s correlation coefficient, with values ranging from 0.80 to 0.97. The presence of ribosomal RNA peaks in FFPE-derived RNA was reflected by a high correlation with paired frozen samples. A set of practical recommendations for evaluating the RNA integrity and quality in FFPE samples is reported. PMID:17251338

Quality Control of RNA Preservation and Extraction from Paraffin-Embedded Tissue: Implications for RT-PCR and Microarray Analysis

PubMed Central

Pichler, Martin; Zatloukal, Kurt

2013-01-01

Analysis of RNA isolated from fixed and paraffin-embedded tissues is widely used in biomedical research and molecular pathological diagnostics. We have performed a comprehensive and systematic investigation of the impact of factors in the pre-analytical workflow, such as different fixatives, fixation time, RNA extraction method and storage of tissues in paraffin blocks, on several downstream reactions including complementary DNA (cDNA) synthesis, quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray hybridization. We compared the effects of routine formalin fixation with the non-crosslinking, alcohol-based Tissue Tek Xpress Molecular Fixative (TTXMF, Sakura Finetek), and cryopreservation as gold standard for molecular analyses. Formalin fixation introduced major changes into microarray gene expression data and led to marked gene-to-gene variations in delta-ct values of qRT-PCR. We found that qRT-PCR efficiency and gene-to-gene variations were mainly attributed to differences in the efficiency of cDNA synthesis as the most sensitive step. These differences could not be reliably detected by quality assessment of total RNA isolated from formalin-fixed tissues by electrophoresis or spectrophotometry. Although RNA from TTXMF fixed samples was as fragmented as RNA from formalin fixed samples, much higher cDNA yield and lower ct-values were obtained in qRT-PCR underlining the negative impact of crosslinking by formalin. In order to better estimate the impact of pre-analytical procedures such as fixation on the reliability of downstream analysis, we applied a qRT-PCR-based assay using amplicons of different length and an assay measuring the efficiency of cDNA generation. Together these two assays allowed better quality assessment of RNA extracted from fixed and paraffin-embedded tissues and should be used to supplement quality scores derived from automated electrophoresis. A better standardization of the pre-analytical workflow, application of additional quality controls and detailed sample information would markedly improve the comparability and reliability of molecular studies based on formalin-fixed and paraffin-embedded tissue samples. PMID:23936242

Micatu Tissue Arrayer | NCI Technology Transfer Center | TTC

Cancer.gov

An NCI researcher recognized a critical need to create a low-cost, easy-to-use tissue microarrayer (TMA), an instrument used by researchers and pathologists to accurately examine tissue samples from patients.

[Transciptome among Mexicans: a large scale methodology to analyze the genetics expression profile of simultaneous samples in muscle, adipose tissue and lymphocytes obtained from the same individual].

PubMed

Bastarrachea, Raúl A; López-Alvarenga, Juan Carlos; Kent, Jack W; Laviada-Molina, Hugo A; Cerda-Flores, Ricardo M; Calderón-Garcidueñas, Ana Laura; Torres-Salazar, Amada; Torres-Salazar, Amanda; Nava-González, Edna J; Solis-Pérez, Elizabeth; Gallegos-Cabrales, Esther C; Cole, Shelley A; Comuzzie, Anthony G

2008-01-01

We describe the methodology used to analyze multiple transcripts using microarray techniques in simultaneous biopsies of muscle, adipose tissue and lymphocytes obtained from the same individual as part of the standard protocol of the Genetics of Metabolic Diseases in Mexico: GEMM Family Study. We recruited 4 healthy male subjects with BM1 20-41, who signed an informed consent letter. Subjects participated in a clinical examination that included anthropometric and body composition measurements, muscle biopsies (vastus lateralis) subcutaneous fat biopsies anda blood draw. All samples provided sufficient amplified RNA for microarray analysis. Total RNA was extracted from the biopsy samples and amplified for analysis. Of the 48,687 transcript targets queried, 39.4% were detectable in a least one of the studied tissues. Leptin was not detectable in lymphocytes, weakly expressed in muscle, but overexpressed and highly correlated with BMI in subcutaneous fat. Another example was GLUT4, which was detectable only in muscle and not correlated with BMI. Expression level concordance was 0.7 (p< 0.001) for the three tissues studied. We demonstrated the feasibility of carrying out simultaneous analysis of gene expression in multiple tissues, concordance of genetic expression in different tissues, and obtained confidence that this method corroborates the expected biological relationships among LEPand GLUT4. TheGEMM study will provide a broad and valuable overview on metabolic diseases, including obesity and type 2 diabetes.

Standardized Scalp Massage Results in Increased Hair Thickness by Inducing Stretching Forces to Dermal Papilla Cells in the Subcutaneous Tissue

PubMed Central

Kobayashi, Kazuhiro; Hama, Takanori; Murakami, Kasumi; Ogawa, Rei

2016-01-01

Objective: In this study, we evaluated the effect of scalp massage on hair in Japanese males and the effect of stretching forces on human dermal papilla cells in vitro. Methods: Nine healthy men received 4 minutes of standardized scalp massage per day for 24 weeks using a scalp massage device. Total hair number, hair thickness, and hair growth rate were evaluated. The mechanical effect of scalp massage on subcutaneous tissue was analyzed using a finite element method. To evaluate the effect of mechanical forces, human dermal papilla cells were cultured using a 72-hour stretching cycle. Gene expression change was analyzed using DNA microarray analyses. In addition, expression of hair cycle-related genes including IL6, NOGGIN, BMP4, and SMAD4 were evaluated using real-time reverse transcription-polymerase chain reaction. Results: Standardized scalp massage resulted in increased hair thickness 24 weeks after initiation of massage (0.085 ± 0.003 mm vs 0.092 ± 0.001 mm). Finite element method showed that scalp massage caused z-direction displacement and von Mises stress on subcutaneous tissue. In vitro, DNA microarray showed gene expression change significantly compared with nonstretching human dermal papilla cells. A total of 2655 genes were upregulated and 2823 genes were downregulated. Real-time reverse transcription-polymerase chain reaction demonstrated increased expression of hair cycle–related genes such as NOGGIN, BMP4, SMAD4, and IL6ST and decrease in hair loss–related genes such as IL6. Conclusions: Stretching forces result in changes in gene expression in human dermal papilla cells. Standardized scalp massage is a way to transmit mechanical stress to human dermal papilla cells in subcutaneous tissue. Hair thickness was shown to increase with standardized scalp massage. PMID:26904154

Transcriptome-Wide Mega-Analyses Reveal Joint Dysregulation of Immunologic Genes and Transcription Regulators in Brain and Blood in Schizophrenia

PubMed Central

Hess, Jonathan L.; Tylee, Daniel S.; Barve, Rahul; de Jong, Simone; Ophoff, Roel A.; Kumarasinghe, Nishantha; Tooney, Paul; Schall, Ulrich; Gardiner, Erin; Beveridge, Natalie Jane; Scott, Rodney J.; Yasawardene, Surangi; Perera, Antionette; Mendis, Jayan; Carr, Vaughan; Kelly, Brian; Cairns, Murray; Tsuang, Ming T.; Glatt, Stephen J.

2016-01-01

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia. PMID:27450777

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia.

PubMed

Hess, Jonathan L; Tylee, Daniel S; Barve, Rahul; de Jong, Simone; Ophoff, Roel A; Kumarasinghe, Nishantha; Tooney, Paul; Schall, Ulrich; Gardiner, Erin; Beveridge, Natalie Jane; Scott, Rodney J; Yasawardene, Surangi; Perera, Antionette; Mendis, Jayan; Carr, Vaughan; Kelly, Brian; Cairns, Murray; Tsuang, Ming T; Glatt, Stephen J

2016-10-01

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n=315) and from ex-vivo blood tissues (n=578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia. Published by Elsevier B.V.

Image microarrays (IMA): Digital pathology's missing tool

PubMed Central

Hipp, Jason; Cheng, Jerome; Pantanowitz, Liron; Hewitt, Stephen; Yagi, Yukako; Monaco, James; Madabhushi, Anant; Rodriguez-canales, Jaime; Hanson, Jeffrey; Roy-Chowdhuri, Sinchita; Filie, Armando C.; Feldman, Michael D.; Tomaszewski, John E.; Shih, Natalie NC.; Brodsky, Victor; Giaccone, Giuseppe; Emmert-Buck, Michael R.; Balis, Ulysses J.

2011-01-01

Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. PMID:22200030

Immunohistochemical evidence of ubiquitous distribution of the metalloendoprotease insulin-degrading enzyme (IDE; insulysin) in human non-malignant tissues and tumor cell lines.

PubMed

Weirich, Gregor; Mengele, Karin; Yfanti, Christina; Gkazepis, Apostolos; Hellmann, Daniela; Welk, Anita; Giersig, Cecylia; Kuo, Wen-Liang; Rosner, Marsha Rich; Tang, Wei-Jen; Schmitt, Manfred

2008-11-01

Immunohistochemical evidence of ubiquitous distribution of the metalloprotease insulin-degrading enzyme (IDE; insulysin) in human non-malignant tissues and tumor cells is presented. Immunohistochemical staining was performed on a multi-organ tissue microarray (pancreas, lung, kidney, central/peripheral nervous system, liver, breast, placenta, myocardium, striated muscle, bone marrow, thymus, and spleen) and on a cell microarray of 31 tumor cell lines of different origin, as well as trophoblast cells and normal blood lymphocytes and granulocytes. IDE protein was expressed in all the tissues assessed and all the tumor cell lines except for Raji and HL-60. Trophoblast cells and granulocytes, but not normal lymphocytes, were also IDE-positive.

Immunohistochemical evidence for ubiquitous distribution of metalloendoprotease insulin-degrading enzyme (IDE; insulysin) in human non-malignant tissues and tumor cell lines

PubMed Central

Weirich, Gregor; Mengele, Karin; Yfanti, Christina; Gkazepis, Apostolos; Hellmann, Daniela; Welk, Anita; Giersig, Cecylia; Kuo, Wen-Liang; Rosner, Marsha Rich; Tang, Wei-Jen; Schmitt, Manfred

2013-01-01

Immunohistochemical evidence for ubiquitous distribution of metalloprotease insulin-degrading enzyme (IDE; insulysin) in human non-malignant tissues and tumor cells is presented. Immunohistochemical staining was performed on a multi-organ tissue microarray (pancreas, lung, kidney, central/peripheral nervous system, liver, breast, placenta, myocardium, striated muscle, bone marrow, thymus, spleen) and on a cell microarray encompassing 31 tumor cell lines of different origin plus trophoblast cells, and normal blood lymphocytes and granulocytes. IDE protein is expressed by all of the tissues assessed and in all of the tumor cell lines except Raji and HL-60; trophoblast cells and granulocytes but not normal lymphocytes are also IDE-positive. PMID:18783335

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2017-01-25

With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

PubMed

Ryge, Jesper; Westerdahl, Ann-Charlotte; Alstrøm, Preben; Kiehn, Ole

2008-01-01

In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

Gene Expression Profiling of Two Distinct Neuronal Populations in the Rodent Spinal Cord

PubMed Central

Alstrøm, Preben; Kiehn, Ole

2008-01-01

Background In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. Methodology/Principal Findings We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50–250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. Conclusions/Significance We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord. PMID:18923679

Speckle-type POZ (pox virus and zinc finger protein) protein gene deletion in ovarian cancer: Fluorescence in situ hybridization analysis of a tissue microarray.

PubMed

Hu, Xiaoyu; Yang, Zhu; Zeng, Manman; Liu, Y I; Yang, Xiaotao; Li, Yanan; Li, X U; Yu, Qiubo

2016-07-01

The aim of the present study was to investigate the status of speckle-type POZ (pox virus and zinc finger protein) protein (SPOP) gene located on chromosome 17q21 in ovarian cancer (OC). The present study evaluated a tissue microarray, which contained 90 samples of ovarian cancer and 10 samples of normal ovarian tissue, using fluorescence in situ hybridization (FISH). FISH is a method where a SPOP-specific DNA red fluorescence probe was used for the experimental group and a centromere-specific DNA green fluorescence probe for chromosome 17 was used for the control group. The present study demonstrated that a deletion of the SPOP gene was observed in 52.27% (46/88) of the ovarian cancer tissues, but was not identified in normal ovarian tissues. Simultaneously, monosomy 17 was frequently identified in the ovarian cancer tissues, but not in the normal ovarian tissues. Furthermore, the present data revealed that the ovarian cancer histological subtype and grade were significantly associated with a deletion of the SPOP gene, which was assessed by the appearance of monosomy 17 in the ovarian cancer samples; the deletion of the SPOP gene was observed in a large proportion of serous epithelial ovarian cancer (41/61; 67.21%), particularly in grade 3 (31/37; 83.78%). In conclusion, deletion of the SPOP gene on chromosome 17 in ovarian cancer samples, which results from monosomy 17, indicates that the SPOP gene may serve as a tumor suppressor gene in ovarian cancer.

Expression profiling of cell cycle regulatory proteins in oropharyngeal carcinomas using tissue microarrays.

PubMed

Ribeiro, Daniel A; Nascimento, Fabio D; Fracalossi, Ana Carolina C; Gomes, Thiago S; Oshima, Celina T F; Franco, Marcello F

2010-01-01

The aim of this study was to investigate the expressions of cell cycle regulatory proteins such as p53, p16, p21, and Rb in squamous cell carcinoma of the oropharynx and their relation to histological differentiation, staging of disease, and prognosis. Paraffin blocks from 21 primary tumors were obtained from archives of the Department of Pathology, Paulista Medical School, Federal University of Sao Paulo, UNIFESP/EPM. Immunohistochemistry was used to detect the expression of p53, p16, p21, and Rb by means of tissue microarrays. Expression of p53, p21, p16 and Rb was not correlated with the stage of disease, histopathological grading or recurrence in squamous cell carcinoma of the oropharynx. Taken together, our results suggest that p53, p16, p21 and Rb are not reliable biomarkers for prognosis of the tumor severity or recurrence in squamous cell carcinoma of the oropharynx as depicted by tissue microarrays and immunohistochemistry.

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

Expression profiling of peroxisome proliferator-activated receptor-delta (PPAR-delta) in mouse tissues using tissue microarray.

PubMed

Higashiyama, Hiroyuki; Billin, Andrew N; Okamoto, Yuji; Kinoshita, Mine; Asano, Satoshi

2007-05-01

Peroxisome proliferator-activated receptor-delta (PPAR-delta) is known as a transcription factor involved in the regulation of fatty acid oxidation and mitochondrial biogenesis in several tissues, such as skeletal muscle, liver and adipose tissues. In this study, to elucidate systemic physiological functions of PPAR-delta, we examined the tissue distribution and localization of PPAR-delta in adult mouse tissues using tissue microarray (TMA)-based immunohistochemistry. PPAR-delta positive signals were observed on variety of tissues/cells in multiple systems including cardiovascular, urinary, respiratory, digestive, endocrine, nervous, hematopoietic, immune, musculoskeletal, sensory and reproductive organ systems. In these organs, PPAR-delta immunoreactivity was generally localized on the nucleus, although cytoplasmic localization was observed on several cell types including neurons in the nervous system and cells of the islet of Langerhans. These expression profiling data implicate various physiological roles of PPAR-delta in multiple organ systems. TMA-based immunohistochemistry enables to profile comprehensive protein localization and distribution in a high-throughput manner.

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

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Microarrays for Undergraduate Classes

ERIC Educational Resources Information Center

Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

2006-01-01

A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data

PubMed Central

Berman, Jules J; Edgerton, Mary E; Friedman, Bruce A

2003-01-01

Background Tissue Microarrays (TMAs) allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API) hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification. Methods A draft tissue microarray data exchange specification was developed through workshop meetings. The first workshop confirmed community support for the effort and urged the creation of an open XML-based specification. This was to evolve in steps with approval for each step coming from the stakeholders in the user community during open workshops. By the fourth workshop, held October, 2002, a set of Common Data Elements (CDEs) was established as well as a basic strategy for organizing TMA data in self-describing XML documents. Results The TMA data exchange specification is a well-formed XML document with four required sections: 1) Header, containing the specification Dublin Core identifiers, 2) Block, describing the paraffin-embedded array of tissues, 3)Slide, describing the glass slides produced from the Block, and 4) Core, containing all data related to the individual tissue samples contained in the array. Eighty CDEs, conforming to the ISO-11179 specification for data elements constitute XML tags used in the TMA data exchange specification. A set of six simple semantic rules describe the complete data exchange specification. Anyone using the data exchange specification can validate their TMA files using a software implementation written in Perl and distributed as a supplemental file with this publication. Conclusion The TMA data exchange specification is now available in a draft form with community-approved Common Data Elements and a community-approved general file format and data structure. The specification can be freely used by the scientific community. Efforts sponsored by the Association for Pathology Informatics to refine the draft TMA data exchange specification are expected to continue for at least two more years. The interested public is invited to participate in these open efforts. Information on future workshops will be posted at (API we site). PMID:12769826

ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

PubMed

Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

2018-04-19

Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We developed a novel de-arraying approach for TMA analysis. By combining wavelet-based detection, active contour segmentation, and thin-plate spline interpolation, our approach is able to handle TMA images with high dynamic, poor signal-to-noise ratio, complex background and non-linear deformation of TMA grid. In addition, the deformation estimation produces quantitative information to asset the manufacturing quality of TMAs.

A New Microarray Substrate for Ultra-Sensitive Genotyping of KRAS and BRAF Gene Variants in Colorectal Cancer

PubMed Central

Pinzani, Pamela; Mancini, Irene; Vinci, Serena; Chiari, Marcella; Orlando, Claudio; Cremonesi, Laura; Ferrari, Maurizio

2013-01-01

Molecular diagnostics of human cancers may increase accuracy in prognosis, facilitate the selection of the optimal therapeutic regimen, improve patient outcome, reduce costs of treatment and favour development of personalized approaches to patient care. Moreover sensitivity and specificity are fundamental characteristics of any diagnostic method. We developed a highly sensitive microarray for the detection of common KRAS and BRAF oncogenic mutations. In colorectal cancer, KRAS and BRAF mutations have been shown to identify a cluster of patients that does not respond to anti-EGFR therapies; the identification of these mutations is therefore clinically extremely important. To verify the technical characteristics of the microarray system for the correct identification of the KRAS mutational status at the two hotspot codons 12 and 13 and of the BRAFV600E mutation in colorectal tumor, we selected 75 samples previously characterized by conventional and CO-amplification at Lower Denaturation temperature-PCR (COLD-PCR) followed by High Resolution Melting analysis and direct sequencing. Among these samples, 60 were collected during surgery and immediately steeped in RNAlater while the 15 remainders were formalin-fixed and paraffin-embedded (FFPE) tissues. The detection limit of the proposed method was different for the 7 KRAS mutations tested and for the V600E BRAF mutation. In particular, the microarray system has been able to detect a minimum of about 0.01% of mutated alleles in a background of wild-type DNA. A blind validation displayed complete concordance of results. The excellent agreement of the results showed that the new microarray substrate is highly specific in assigning the correct genotype without any enrichment strategy. PMID:23536897

The CD117 immunohistochemistry tissue microarray survey for quality assurance and interlaboratory comparison: a College of American Pathologists Cell Markers Committee Study.

PubMed

Dorfman, David M; Bui, Marilyn M; Tubbs, Raymond R; Hsi, Eric D; Fitzgibbons, Patrick L; Linden, Michael D; Rickert, Robert R; Roche, Patrick C

2006-06-01

We have developed tissue microarray-based surveys to allow laboratories to compare their performance in staining predictive immunohistochemical markers, including proto-oncogene CD117 (c-kit), which is characteristically expressed in gastrointestinal stromal tumors (GISTs). GISTs exhibit activating mutations in the c-kit proto-oncogene, which render them amenable to treatment with imatinib mesylate. Consequently, correct identification of c-Kit expression is important for the diagnosis and treatment of GISTs. To analyze CD117 immunohistochemical staining performance by a large number of clinical laboratories. A mechanical device was used to construct tissue microarrays consisting of 3 x 1-mm cores of 10 tumor samples, which can be used to generate hundreds of tissue sections from the arrayed cases, suitable for large-scale interlaboratory comparison of immunohistochemical staining. An initial survey of 63 laboratories and a second survey of 90 laboratories, performed in 2004 and 2005, exhibited >81% concordance for 7 of 10 cores, including all 4 GIST cases, which were immunoreactive for CD117 with >95% staining concordance. Three of the cores achieved less than 81% concordance of results, possibly due to the presence of foci of necrosis in one core and CD117-positive mast cells in 2 cores of CD117-negative neoplasms. There was good performance among a large number of laboratories performing CD117 immunohistochemical staining, with consistently higher concordance of results for CD117-positive GIST cases than for nonimmunoreactive cases. Tissue microarrays for CD117 and other predictive markers should be useful for interlaboratory comparisons, quality assurance, and education of participants regarding staining nuances such as the expression of CKIT by nonneoplastic mast cells.

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

A preliminary result of three-dimensional microarray technology to gene analysis with endoscopic ultrasound-guided fine-needle aspiration specimens and pancreatic juices

PubMed Central

2010-01-01

Background Analysis of gene expression and gene mutation may add information to be different from ordinary pathological tissue diagnosis. Since samples obtained endoscopically are very small, it is desired that more sensitive technology is developed for gene analysis. We investigated whether gene expression and gene mutation analysis by newly developed ultra-sensitive three-dimensional (3D) microarray is possible using small amount samples from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens and pancreatic juices. Methods Small amount samples from 17 EUS-FNA specimens and 16 pancreatic juices were obtained. After nucleic acid extraction, the samples were amplified with labeling and analyzed by the 3D microarray. Results The analyzable rate with the microarray was 46% (6/13) in EUS-FNA specimens of RNAlater® storage, and RNA degradations were observed in all the samples of frozen storage. In pancreatic juices, the analyzable rate was 67% (4/6) in frozen storage samples and 20% (2/10) in RNAlater® storage. EUS-FNA specimens were classified into cancer and non-cancer by gene expression analysis and K-ras codon 12 mutations were also detected using the 3D microarray. Conclusions Gene analysis from small amount samples obtained endoscopically was possible by newly developed 3D microarray technology. High quality RNA from EUS-FNA samples were obtained and remained in good condition only using RNA stabilizer. In contrast, high quality RNA from pancreatic juice samples were obtained only in frozen storage without RNA stabilizer. PMID:20416107

Pro-oncogene Pokemon promotes breast cancer progression by upregulating survivin expression

PubMed Central

2011-01-01

Introduction Pokemon is an oncogenic transcription factor involved in cell growth, differentiation and oncogenesis, but little is known about its role in human breast cancer. In this study, we aimed to reveal the role of Pokemon in breast cancer progression and patient survival and to understand its underlying mechanisms. Methods Tissue microarray analysis of breast cancer tissues from patients with complete clinicopathological data and more than 20 years of follow-up were used to evaluate Pokemon expression and its correlation with the progression and prognosis of the disease. DNA microarray analysis of MCF-7 cells that overexpress Pokemon was used to identify Pokemon target genes. Chromatin immunoprecipitation (ChIP) and site-directed mutagenesis were utilized to determine how Pokemon regulates survivin expression, a target gene. Results Pokemon was found to be overexpressed in 158 (86.8%) of 182 breast cancer tissues, and its expression was correlated with tumor size (P = 0.0148) and lymph node metastasis (P = 0.0014). Pokemon expression led to worse overall (n = 175, P = 0.01) and disease-related (n = 79, P = 0.0134) patient survival. DNA microarray analyses revealed that in MCF-7 breast cancer cells, Pokemon regulates the expression of at least 121 genes involved in several signaling and metabolic pathways, including anti-apoptotic survivin. In clinical specimens, Pokemon and survivin expression were highly correlated (n = 49, r = 0.6799, P < 0.0001). ChIP and site-directed mutagenesis indicated that Pokemon induces survivin expression by binding to the GT boxes in its promoter. Conclusions Pokemon promotes breast cancer progression by upregulating survivin expression and thus may be a potential target for the treatment of this malignancy. PMID:21392388

Toxicity of Doxorubicin on Pig Liver After Chemoembolization with Doxorubicin-loaded Microspheres: A Pilot DNA-microarrays and Histology Study

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

Verret, Valentin, E-mail: valentin.verret@archimmed.com; Namur, Julien; Ghegediban, Saieda Homayra

The potential mechanisms accounting for the hepatotoxicity of doxorubicin-loaded microspheres in chemoembolization were examined by combining histology and DNA-microarray techniques.The left hepatic arteries of two pigs were embolized with 1 mL of doxorubicin-loaded (25 mg; (DoxMS)) or non-loaded (BlandMS) microspheres. The histopathological effects of the embolization were analyzed at 1 week. RNAs extracted from both the embolized and control liver areas were hybridized onto Agilent porcine microarrays. Genes showing significantly different expression (p < 0.01; fold-change > 2) between two groups were classified by biological process. At 1 week after embolization, DoxMS caused arterial and parenchymal necrosis in 51 andmore » 38 % of embolized vessels, respectively. By contrast, BlandMS did not cause any tissue damage. Up-regulated genes following embolization with DoxMS (vs. BlandMS, n = 353) were mainly involved in cell death, apoptosis, and metabolism of doxorubicin. Down-regulated genes (n = 120) were mainly related to hepatic functions, including enzymes of lipid and carbohydrate metabolisms. Up-regulated genes included genes related to cell proliferation (growth factors and transcription factors), tissue remodeling (MMPs and several collagen types), inflammatory reaction (interleukins and chemokines), and angiogenesis (angiogenic factors and HIF1a pathway), all of which play an important role in liver healing and regeneration. DoxMS caused lesions to the liver, provoked cell death, and disturbed liver metabolism. An inflammatory repair process with cell proliferation, tissue remodeling, and angiogenesis was rapidly initiated during the first week after chemoembolization. This pilot study provides a comprehensive method to compare different types of DoxMS in healthy animals or tumor models.« less

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

PubMed Central

Ramirez, Lisa S.; Wang, Jun

2016-01-01

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications. PMID:26780370

Paraffin tissue microarrays constructed with a cutting board and cutting board arrayer.

PubMed

Vogel, Ulrich Felix

2010-05-01

Paraffin tissue microarrays (PTMAs) are blocks of paraffin containing up to 1300 paraffin tissue core biopsies (PTCBs). Normally, these PTCBs are punched from routine paraffin tissue blocks, which contain tissues of differing thicknesses. Therefore, the PTCBs are of different lengths. In consequence, the sections of the deeper portions of the PTMA do not contain all of the desired PTCBs. To overcome this drawback, cutting boards were constructed from panels of plastic with a thickness of 4 mm. Holes were drilled into the plastic and filled completely with at least one PTCB per hole. After being trimmed to a uniform length of 4 mm, these PTCBs were pushed from the cutting board into corresponding holes in a recipient block by means of a plate with steel pins. Up to 1000 sections per PTMA were cut without any significant loss of PTCBs, thereby increasing the efficacy of the PTMA technique.

Lumen-based detection of prostate cancer via convolutional neural networks

NASA Astrophysics Data System (ADS)

Kwak, Jin Tae; Hewitt, Stephen M.

2017-03-01

We present a deep learning approach for detecting prostate cancers. The approach consists of two steps. In the first step, we perform tissue segmentation that identifies lumens within digitized prostate tissue specimen images. Intensity- and texture-based image features are computed at five different scales, and a multiview boosting method is adopted to cooperatively combine the image features from differing scales and to identify lumens. In the second step, we utilize convolutional neural networks (CNN) to automatically extract high-level image features of lumens and to predict cancers. The segmented lumens are rescaled to reduce computational complexity and data augmentation by scaling, rotating, and flipping the rescaled image is applied to avoid overfitting. We evaluate the proposed method using two tissue microarrays (TMA) - TMA1 includes 162 tissue specimens (73 Benign and 89 Cancer) and TMA2 comprises 185 tissue specimens (70 Benign and 115 Cancer). In cross-validation on TMA1, the proposed method achieved an AUC of 0.95 (CI: 0.93-0.98). Trained on TMA1 and tested on TMA2, CNN obtained an AUC of 0.95 (CI: 0.92-0.98). This demonstrates that the proposed method can potentially improve prostate cancer pathology.

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

Assessing the impact of Benzo[a]pyrene on Marine Mussels: Application of a novel targeted low density microarray complementing classical biomarker responses

PubMed Central

Sforzini, Susanna; Arlt, Volker M.; Barranger, Audrey; Dallas, Lorna J.; Oliveri, Caterina; Aminot, Yann; Pacchioni, Beniamina; Millino, Caterina; Lanfranchi, Gerolamo; Readman, James W.; Moore, Michael N.; Viarengo, Aldo; Jha, Awadhesh N.

2017-01-01

Despite the increasing use of mussels in environmental monitoring and ecotoxicological studies, their genomes and gene functions have not been thoroughly explored. Several cDNA microarrays were recently proposed for Mytilus spp., but putatively identified partial transcripts have rendered the generation of robust transcriptional responses difficult in terms of pathway identification. We developed a new low density oligonucleotide microarray with 465 probes covering the same number of genes. Target genes were selected to cover most of the well-known biological processes in the stress response documented over the last decade in bivalve species at the cellular and tissue levels. Our new ‘STressREsponse Microarray’ (STREM) platform consists of eight sub-arrays with three replicates for each target in each sub-array. To assess the potential use of the new array, we tested the effect of the ubiquitous environmental pollutant benzo[a]pyrene (B[a]P) at 5, 50, and 100 μg/L on two target tissues, the gills and digestive gland, of Mytilus galloprovincialis exposed invivo for three days. Bioaccumulation of B[a]P was also determined demonstrating exposure in both tissues. In addition to the well-known effects of B[a]P on DNA metabolism and oxidative stress, the new array data provided clues about the implication of other biological processes, such as cytoskeleton, immune response, adhesion to substrate, and mitochondrial activities. Transcriptional data were confirmed using qRT-PCR. We further investigated cellular functions and possible alterations related to biological processes highlighted by the microarray data using oxidative stress biomarkers (Lipofuscin content) and the assessment of genotoxicity. DNA damage, as measured by the alkaline comet assay, increased as a function of dose.DNA adducts measurements using 32P-postlabeling method also showed the presence of bulky DNA adducts (i.e. dG-N2-BPDE). Lipofiscin content increased significantly in B[a]P exposed mussels. Immunohistochemical analysis of tubulin and actin showed changes in cytoskeleton organisation. Our results adopting an integrated approach confirmed that the combination of newly developed transcriptomic approcah, classical biomarkers along with chemical analysis of water and tissue samples should be considered for environmental bioimonitoring and ecotoxicological studies to obtain holistic information to assess the impact of contaminants on the biota. PMID:28651000

Decentralized Data Sharing of Tissue Microarrays for Investigative Research in Oncology

PubMed Central

Chen, Wenjin; Schmidt, Cristina; Parashar, Manish; Reiss, Michael; Foran, David J.

2007-01-01

Tissue microarray technology (TMA) is a relatively new approach for efficiently and economically assessing protein and gene expression across large ensembles of tissue specimens. Tissue microarray technology holds great potential for reducing the time and cost associated with conducting research in tissue banking, proteomics, and outcome studies. However, the sheer volume of images and other data generated from even limited studies involving tissue microarrays quickly approach the processing capacity and resources of a division or department. This challenge is compounded by the fact that large-scale projects in several areas of modern research rely upon multi-institutional efforts in which investigators and resources are spread out over multiple campuses, cities, and states. To address some of the data management issues several leading institutions have begun to develop their own “in-house” systems, independently, but such data will be only minimally useful if it isn’t accessible to others in the scientific community. Investigators at different institutions studying the same or related disorders might benefit from the synergy of sharing results. To facilitate sharing of TMA data across different database implementations, the Technical Standards Committee of the Association for Pathology Informatics organized workshops in efforts to establish a standardized TMA data exchange specification. The focus of our research does not relate to the establishment of standards for exchange, but rather builds on these efforts and concentrates on the design, development and deployment of a decentralized collaboratory for the unsupervised characterization, and seamless and secure discovery and sharing of TMA data. Specifically, we present a self-organizing, peer-to-peer indexing and discovery infrastructure for quantitatively assessing digitized TMA’s. The system utilizes a novel, optimized decentralized search engine that supports flexible querying, while guaranteeing that once information has been stored in the system, it will be found with bounded costs. PMID:19081778

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

PubMed Central

2010-01-01

Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

PubMed

Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

PubMed

Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction.

PubMed

Patel, Palak G; Selvarajah, Shamini; Boursalie, Suzanne; How, Nathan E; Ejdelman, Joshua; Guerard, Karl-Philippe; Bartlett, John M; Lapointe, Jacques; Park, Paul C; Okello, John B A; Berman, David M

2016-08-21

Formalin-fixed paraffin embedded tissue (FFPET) represents a valuable, well-annotated substrate for molecular investigations. The utility of FFPET in molecular analysis is complicated both by heterogeneous tissue composition and low yields when extracting nucleic acids. A literature search revealed a paucity of protocols addressing these issues, and none that showed a validated method for simultaneous extraction of RNA and DNA from regions of interest in FFPET. This method addresses both issues. Tissue specificity was achieved by mapping cancer areas of interest on microscope slides and transferring annotations onto FFPET blocks. Tissue cores were harvested from areas of interest using 0.6 mm microarray punches. Nucleic acid extraction was performed using a commercial FFPET extraction system, with modifications to homogenization, deparaffinization, and Proteinase K digestion steps to improve tissue digestion and increase nucleic acid yields. The modified protocol yields sufficient quantity and quality of nucleic acids for use in a number of downstream analyses, including a multi-analyte gene expression platform, as well as reverse transcriptase coupled real time PCR analysis of mRNA expression, and methylation-specific PCR (MSP) analysis of DNA methylation.

A tissue microarray study of toll-like receptor 4, decoy receptor 3, and external signal regulated kinase 1/2 expressions in astrocytoma.

PubMed

Lin, Chih-Kung; Ting, Chun-Chieh; Tsai, Wen-Chiuan; Chen, Yuan-Wu; Hueng, Dueng-Yuan

2016-01-01

Decoy receptor 3 (DcR3) functions as a death decoy inhibiting apoptosis mediated by the tumor necrosis factor receptor family. It is highly expressed in many tumors and its expression can be regulated by the MAPK/ERK signaling pathway and ERK is a vital member of this pathway. Toll-like receptor 4 (TLR4) is expressed on immune cells. Increased TLR4 expression has been associated with various types of cancers. The study was conducted to investigate the expression of DcR3, ERK1/2, and TLR4 in astrocytomas and evaluate if they are validating markers for discriminating glioblastoma from anaplastic astrocytoma in limited surgical specimen. Expression of DcR3, ERK1/2, and TLR4 was determined by immunohistochemical staining of tissue microarray from 48 paraffin-embedded tissues. A binary logistic regression method was used to generate functions that discriminate between anaplastic astrocytomas and glioblastomas. The expression of TLR4 and DcR3 was significantly higher in glioblastomas than in anaplastic astrocytomas. DcR3 could discriminate anaplastic astrocytomas from glioblastomas with high sensitivity (93.8%), specificity (90%), and accuracy (92.3%). Our results suggest that DcR3 may be a useful marker for discriminating anaplastic astrocytomas from glioblastomas.

Vitamin D Receptor gene (VDR) transcripts in bone, cartilage, muscles and blood and microarray analysis of vitamin D responsive genes expression in paravertebral muscles of Juvenile and Adolescent Idiopathic Scoliosis patients

PubMed Central

2012-01-01

Background VDR may be considered as a candidate gene potentially related to Idiopathic Scoliosis susceptibility and natural history. Transcriptional profile of VDR mRNA isoforms might be changed in the structural tissues of the scoliotic spine and potentially influence the expression of VDR responsive genes. The purpose of the study was to determine differences in mRNA abundance of VDR isoforms in bone, cartilage and paravertebral muscles between tissues from curve concavity and convexity, between JIS and AIS and to identify VDR responsive genes differentiating Juvenile and Adolescent Idiopathic Scoliosis in paravertebral muscles. Methods In a group of 29 patients with JIS and AIS, specimens of bone, cartilage, paravertebral muscles were harvested at the both sides of the curve apex together with peripheral blood samples. Extracted total RNA served as a matrix for VDRs and VDRl mRNA quantification by QRT PCR. Subsequent microarray analysis of paravertebral muscular tissue samples was performed with HG U133A chips (Affymetrix). Quantitative data were compared by a nonparametric Mann Whitney U test. Microarray results were analyzed with GeneSpring 11GX application. Matrix plot of normalized log-intensities visualized the degree of differentiation between muscular tissue transcriptomes of JIS and AIS group. Fold Change Analysis with cutoff of Fold Change ≥2 identified differentially expressed VDR responsive genes in paravertebral muscles of JIS and AIS. Results No significant differences in transcript abundance of VDR isoforms between tissues of the curve concavity and convexity were found. Statistically significant difference between JIS and AIS group in mRNA abundance of VDRl isoform was found in paravertebral muscles of curve concavity. Higher degree of muscular transcriptome differentiation between curve concavity and convexity was visualized in JIS group. In paravertebral muscles Tob2 and MED13 were selected as genes differentially expressed in JIS and AIS group. Conclusions In Idiopathic Scolioses transcriptional activity and alternative splicing of VDR mRNA in osseous, cartilaginous, and paravertebral muscular tissues are tissue specific and equal on both sides of the curve. The number of mRNA copies of VDRl izoform in concave paravertebral muscles might be one of the factors differentiating JIS and AIS. In paravertebral muscles Tob2 and Med13 genes differentiate Adolescent and Juvenile type of Idiopathic Scoliosis. PMID:23259508

Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

PubMed

Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

2015-11-10

IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

Microarray profiles reveal that circular RNA hsa_circ_0007385 functions as an oncogene in non-small cell lung cancer tumorigenesis.

PubMed

Jiang, Ming-Ming; Mai, Zhi-Tao; Wan, Shan-Zhi; Chi, Yu-Min; Zhang, Xin; Sun, Bao-Hua; Di, Qing-Guo

2018-04-01

Circular RNAs (circRNAs) are a novel class of non-protein-coding RNA. Emerging evidence indicates that circRNAs participate in the regulation of many pathophysiological processes. This study aims to explore the expression profiles and pathological effects of circRNAs in non-small cell lung cancer (NSCLC). Human circRNAs microarray analysis was performed to screen the expression profile of circRNAs in NSCLC tissue. Expressions of circRNA and miRNA in NSCLC tissues and cells were quantified by qRTPCR. Functional experiments were performed to investigate the biological functions of circRNA, including CCK-8 assay, colony formation assay, transwell assay and xenograft in vivo assay. Human circRNAs microarray revealed a total 957 abnormally expressed circRNAs (> twofold, P < 0.05) in NSCLC tissue compared with adjacent normal tissue. In further studies, hsa_circ_0007385 was significantly up regulated in NSCLC tissue and cells. In vitro experiments with hsa_circ_0007385 knockdown resulted in significant suppression of the proliferation, migration and invasion of NSCLC cells. In vivo xenograft assay using hsa_circ_0007385 knockdown, significantly reduced tumor growth. Bioinformatics analysis and luciferase reporter assay verified the potential target miR-181, suggesting a possible regulatory pathway for hsa_circ_0007385. In summary, results suggest hsa_circ_0007385 plays a role in NSCLC tumorigenesis, providing a potential therapeutic target for NSCLC.

Karyotype versus microarray testing for genetic abnormalities after stillbirth.

PubMed

Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn

2012-12-06

Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications.

PubMed

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-09-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

Biofunctionalization of surfaces by energetic ion implantation: Review of progress on applications in implantable biomedical devices and antibody microarrays

NASA Astrophysics Data System (ADS)

Bilek, Marcela M. M.

2014-08-01

Despite major research efforts in the field of biomaterials, rejection, severe immune responses, scar tissue and poor integration continue to seriously limit the performance of today's implantable biomedical devices. Implantable biomaterials that interact with their host via an interfacial layer of active biomolecules to direct a desired cellular response to the implant would represent a major and much sought after improvement. Another, perhaps equally revolutionary, development that is on the biomedical horizon is the introduction of cost-effective microarrays for fast, highly multiplexed screening for biomarkers on cell membranes and in a variety of analyte solutions. Both of these advances will rely on effective methods of functionalizing surfaces with bioactive molecules. After a brief introduction to other methods currently available, this review will describe recently developed approaches that use energetic ions extracted from plasma to facilitate simple, one-step covalent surface immobilization of bioactive molecules. A kinetic theory model of the immobilization process by reactions with long-lived, mobile, surface-embedded radicals will be presented. The roles of surface chemistry and microstructure of the ion treated layer will be discussed. Early progress on applications of this technology to create diagnostic microarrays and to engineer bioactive surfaces for implantable biomedical devices will be reviewed.

Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications

PubMed Central

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-01-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell based drug-screening models, which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell based drug screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds a great potential to provide repeatable 3D cell based constructs with high temporal, spatial control and versatility. PMID:21725152

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

Symptomatic and asymptomatic benign prostatic hyperplasia: Molecular differentiation by using microarrays

NASA Astrophysics Data System (ADS)

Prakash, Kulkarni; Pirozzi, Gregorio; Elashoff, Michael; Munger, William; Waga, Iwao; Dhir, Rajiv; Kakehi, Yoshiyuki; Getzenberg, Robert H.

2002-05-01

Benign prostatic hyperplasia (BPH) is a disease of unknown etiology that significantly affects the quality of life in aging men. Histologic BPH may present itself either as symptomatic or asymptomatic in nature. To elucidate the molecular differences underlying BPH, gene expression profiles from the prostate transition zone tissue have been analyzed by using microarrays. A set of 511 differentially expressed genes distinguished symptomatic and asymptomatic BPH. This genetic signature separates BPH from normal tissue but does not seem to change with age. These data could provide novel approaches for alleviating symptoms and hyperplasia in BPH.

Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

PubMed Central

Kennedy, Laura; Vass, J. Keith; Haggart, D. Ross; Moore, Steve; Burczynski, Michael E.; Crowther, Dan; Miele, Gino

2008-01-01

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies. PMID:19578521

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

HOXB9 Expression Correlates with Histological Grade and Prognosis in LSCC

PubMed Central

2017-01-01

The purpose of this study was to investigate the HOX gene expression profile in laryngeal squamous cell carcinoma (LSCC) and assess whether some genes are associated with the clinicopathological features and prognosis in LSCC patients. The HOX gene levels were tested by microarray and validated by qRT-PCR in paired cancerous and adjacent noncancerous LSCC tissue samples. The microarray testing data of 39 HOX genes revealed 15 HOX genes that were at least 2-fold upregulated and 2 that were downregulated. After qRT-PCR evaluation, the three most upregulated genes (HOXB9, HOXB13, and HOXD13) were selected for tissue microarray (TMA) analysis. The correlations between the HOXB9, HOXB13, and HOXD13 expression levels and both clinicopathological features and prognosis were analyzed. Three HOX gene expression levels were markedly increased in LSCC tissues compared with adjacent noncancerous tissues (P < 0.001). HOXB9 was found to correlate with histological grade (P < 0.01) and prognosis (P < 0.01) in LSCC. In conclusion, this study revealed that HOXB9, HOXB13, and HOXD13 were upregulated and may play important roles in LSCC. Moreover, HOXB9 may serve as a novel marker of poor prognosis and a potential therapeutic target in LSCC patients. PMID:28808656

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP

PubMed Central

Coutinho, Rita; Clear, Andrew J.; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G.

2015-01-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. PMID:25425693

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP.

PubMed

Coutinho, Rita; Clear, Andrew J; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G

2015-03-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. Copyright© Ferrata Storti Foundation.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Fluorescence-based bioassays for the detection and evaluation of food materials.

PubMed

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-10-13

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials.

Fluorescence-Based Bioassays for the Detection and Evaluation of Food Materials

PubMed Central

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-01-01

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials. PMID:26473869

Radiation Fibrosis of the Vocal Fold: From Man to Mouse

PubMed Central

Johns, Michael M.; Kolachala, Vasantha; Berg, Eric; Muller, Susan; Creighton, Frances X.; Branski, Ryan C.

2013-01-01

Objectives To characterize fundamental late tissue effects in the human vocal fold following radiation therapy. To develop a murine model of radiation fibrosis to ultimately develop both treatment and prevention paradigms. Design Translational study using archived human and fresh murine irradiated vocal fold tissue. Methods 1) Irradiated vocal fold tissue from patients undergoing laryngectomy for loss of function from radiation fibrosis were identified from pathology archives. Histomorphometry, immunohistochemistry, and whole-genome microarray as well as real-time transcriptional analyses was performed. 2) Focused radiation to the head and neck was delivered to mice in a survival fashion. One month following radiation, vocal fold tissue was analyzed with histomorphometry, immunohistochemistry, and real-time PCR transcriptional analysis for selected markers of fibrosis. Results Human irradiated vocal folds demonstrated increased collagen transcription with increased deposition and disorganization of collagen in both the thyroarytenoid muscle and the superficial lamina propria. Fibronectin were increased in the superficial lamina propria. Laminin decreased in the thyroarytenoid muscle. Whole genome microarray analysis demonstrated increased transcription of markers for fibrosis, oxidative stress, inflammation, glycosaminoglycan production and apoptosis. Irradiated murine vocal folds demonstrated increases in collagen and fibronectin transcription and deposition in the lamina propria. Transforming growth factor (TGF)-β increased in the lamina propria. Conclusion Human irradiated vocal folds demonstrate molecular changes leading to fibrosis that underlie loss of vocal fold pliability that occurs in patients following laryngeal irradiation. Irradiated murine tissue demonstrates similar findings, and this mouse model may have utility in creating prevention and treatment strategies for vocal fold radiation fibrosis. PMID:23242839

Combining Evidence of Preferential Gene-Tissue Relationships from Multiple Sources

PubMed Central

Guo, Jing; Hammar, Mårten; Öberg, Lisa; Padmanabhuni, Shanmukha S.; Bjäreland, Marcus; Dalevi, Daniel

2013-01-01

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity. PMID:23950964

The Prostate Cancer Biorepository Network (PCBN)

DTIC Science & Technology

2016-10-01

site includes blood (serum, plasma, and buffy coat), prostatectomy tissues (frozen), biopsies and metastatic tissue from rapid autopsies (paraffin...embedded material and tissue microarrays (TMAs)), prostate cancer patient derived xenografts (PDX) and derived specimens (DNA and RNA) from prostate...Genitourinary Cancer Biorepository set up a rapid autopsy program to provide access to metastatic tissue and create patient derived xenograft (PDX

The Role of the Immune Response in the Pathogenesis of Thyroid Eye Disease: A Reassessment

PubMed Central

Rosenbaum, James T.; Choi, Dongseok; Wong, Amanda; Wilson, David J.; Grossniklaus, Hans E.; Harrington, Christina A.; Dailey, Roger A.; Ng, John D.; Steele, Eric A.; Czyz, Craig N.; Foster, Jill A.; Tse, David; Alabiad, Chris; Dubovy, Sander; Parekh, Prashant K.; Harris, Gerald J.; Kazim, Michael; Patel, Payal J.; White, Valerie A.; Dolman, Peter J.; Edward, Deepak P.; Alkatan, Hind M.; al Hussain, Hailah; Selva, Dinesh; Yeatts, R. Patrick; Korn, Bobby S.; Kikkawa, Don O.; Stauffer, Patrick; Planck, Stephen R.

2015-01-01

Background Although thyroid eye disease is a common complication of Graves’ disease, the pathogenesis of the orbital disease is poorly understood. Most authorities implicate the immune response as an important causal factor. We sought to clarify pathogenesis by using gene expression microarray. Methods An international consortium of ocular pathologists and orbital surgeons contributed formalin fixed orbital biopsies. RNA was extracted from orbital tissue from 20 healthy controls, 25 patients with thyroid eye disease (TED), 25 patients with nonspecific orbital inflammation (NSOI), 7 patients with sarcoidosis and 6 patients with granulomatosis with polyangiitis (GPA). Tissue was divided into a discovery set and a validation set. Gene expression was quantified using Affymetrix U133 Plus 2.0 microarrays which include 54,000 probe sets. Results Principal component analysis showed that gene expression from tissue from patients with TED more closely resembled gene expression from healthy control tissue in comparison to gene expression characteristic of sarcoidosis, NSOI, or granulomatosis with polyangiitis. Unsupervised cluster dendrograms further indicated the similarity between TED and healthy controls. Heat maps based on gene expression for cytokines, chemokines, or their receptors showed that these inflammatory markers were associated with NSOI, sarcoidosis, or GPA much more frequently than with TED. Conclusion This is the first study to compare gene expression in TED to gene expression associated with other causes of exophthalmos. The juxtaposition shows that inflammatory markers are far less characteristic of TED relative to other orbital inflammatory diseases. PMID:26371757

Expression of BMI-1 and Mel-18 in breast tissue - a diagnostic marker in patients with breast cancer

PubMed Central

2010-01-01

Background Polycomb Group (PcG) proteins are epigenetic silencers involved in maintaining cellular identity, and their deregulation can result in cancer. Expression of Mel-18 and Bmi-1 has been studied in tumor tissue, but not in adjacent non-cancerous breast epithelium. Our study compares the expression of the two genes in normal breast epithelium of cancer patients and relates it to the level of expression in the corresponding tumors as well as in breast epithelium of healthy women. Methods A total of 79 tumors, of which 71 malignant tumors of the breast, 6 fibroadenomas, and 2 DCIS were studied and compared to the reduction mammoplastic specimens of 11 healthy women. In addition there was available adjacent cancer free tissue for 23 of the malignant tumors. The tissue samples were stored in RNAlater, RNA was isolated to create expression microarray profile. These two genes were then studied more closely first on mRNA transcription level by microarrays (Agilent 44 K) and quantitative RT-PCR (TaqMan) and then on protein expression level using immunohistochemistry. Results Bmi-1 mRNA is significantly up-regulated in adjacent normal breast tissue in breast cancer patients compared to normal breast tissue from noncancerous patients. Conversely, mRNA transcription level of Mel-18 is lower in normal breast from patients operated for breast cancer compared to breast tissue from mammoplasty. When protein expression of these two genes was evaluated, we observed that most of the epithelial cells were positive for Bmi-1 in both groups of tissue samples, although the expression intensity was stronger in normal tissue from cancer patients compared to mammoplasty tissue samples. Protein expression of Mel-18 showed inversely stronger intensity in tissue samples from mammoplasty compared to normal breast tissue from patients operated for breast cancer. Conclusion Bmi-1 mRNA level is consistently increased and Mel-18 mRNA level is consistently decreased in adjacent normal breast tissue of cancer patients as compared to normal breast tissue in women having had reduction mammoplasties. Bmi-1/Mel-18 ratio can be potentially used as a tool for stratifying women at risk of developing malignancy. PMID:21162745

Recent progress in making protein microarray through BioLP

NASA Astrophysics Data System (ADS)

Yang, Rusong; Wei, Lian; Feng, Ying; Li, Xiujian; Zhou, Quan

2017-02-01

Biological laser printing (BioLP) is a promising biomaterial printing technique. It has the advantage of high resolution, high bioactivity, high printing frequency and small transported liquid amount. In this paper, a set of BioLP device is design and made, and protein microarrays are printed by this device. It's found that both laser intensity and fluid layer thickness have an influence on the microarrays acquired. Besides, two kinds of the fluid layer coating methods are compared, and the results show that blade coating method is better than well-coating method in BioLP. A microarray of 0.76pL protein microarray and a "NUDT" patterned microarray are printed to testify the printing ability of BioLP.

Systematic gene microarray analysis of the lncRNA expression profiles in human uterine cervix carcinoma.

PubMed

Chen, Jie; Fu, Ziyi; Ji, Chenbo; Gu, Pingqing; Xu, Pengfei; Yu, Ningzhu; Kan, Yansheng; Wu, Xiaowei; Shen, Rong; Shen, Yan

2015-05-01

The human uterine cervix carcinoma is one of the most well-known malignancy reproductive system cancers, which threatens women health globally. However, the mechanisms of the oncogenesis and development process of cervix carcinoma are not yet fully understood. Long non-coding RNAs (lncRNAs) have been proved to play key roles in various biological processes, especially development of cancer. The function and mechanism of lncRNAs on cervix carcinoma is still rarely reported. We selected 3 cervix cancer and normal cervix tissues separately, then performed lncRNA microarray to detect the differentially expressed lncRNAs. Subsequently, we explored the potential function of these dysregulated lncRNAs through online bioinformatics databases. Finally, quantity real-time PCR was carried out to confirm the expression levels of these dysregulated lncRNAs in cervix cancer and normal tissues. We uncovered the profiles of differentially expressed lncRNAs between normal and cervix carcinoma tissues by using the microarray techniques, and found 1622 upregulated and 3026 downregulated lncRNAs (fold-change>2.0) in cervix carcinoma compared to the normal cervical tissue. Furthermore, we found HOXA11-AS might participate in cervix carcinogenesis by regulating HOXA11, which is involved in regulating biological processes of cervix cancer. This study afforded expression profiles of lncRNAs between cervix carcinoma tissue and normal cervical tissue, which could provide database for further research about the function and mechanism of key-lncRNAs in cervix carcinoma, and might be helpful to explore potential diagnosis factors and therapeutic targets for cervix carcinoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Transcriptomic responses to wounding: meta-analysis of gene expression microarray data.

PubMed

Sass, Piotr Andrzej; Dąbrowski, Michał; Charzyńska, Agata; Sachadyn, Paweł

2017-11-07

A vast amount of microarray data on transcriptomic response to injury has been collected so far. We designed the analysis in order to identify the genes displaying significant changes in expression after wounding in different organisms and tissues. This meta-analysis is the first study to compare gene expression profiles in response to wounding in as different tissues as heart, liver, skin, bones, and spinal cord, and species, including rat, mouse and human. We collected available microarray transcriptomic profiles obtained from different tissue injury experiments and selected the genes showing a minimum twofold change in expression in response to wounding in prevailing number of experiments for each of five wound healing stages we distinguished: haemostasis & early inflammation, inflammation, early repair, late repair and remodelling. During the initial phases after wounding, haemostasis & early inflammation and inflammation, the transcriptomic responses showed little consistency between different tissues and experiments. For the later phases, wound repair and remodelling, we identified a number of genes displaying similar transcriptional responses in all examined tissues. As revealed by ontological analyses, activation of certain pathways was rather specific for selected phases of wound healing, such as e.g. responses to vitamin D pronounced during inflammation. Conversely, we observed induction of genes encoding inflammatory agents and extracellular matrix proteins in all wound healing phases. Further, we selected several genes differentially upregulated throughout different stages of wound response, including established factors of wound healing in addition to those previously unreported  in this context such as PTPRC and AQP4. We found that transcriptomic responses to wounding showed similar traits in a diverse selection of tissues including skin, muscles, internal organs and nervous system. Notably, we distinguished transcriptional induction of inflammatory genes not only in the initial response to wounding, but also later, during wound repair and tissue remodelling.

Comparison of gene expression responses to hypoxia in viviparous (Xiphophorus) and oviparous (Oryzias) fishes using a medaka microarray.

PubMed

Boswell, Mikki G; Wells, Melissa C; Kirk, Lyndsey M; Ju, Zhenlin; Zhang, Ziping; Booth, Rachell E; Walter, Ronald B

2009-03-01

Gene expression profiling using DNA microarray technology is a useful tool for assessing gene transcript level responses after an organism is exposed to environmental stress. Herein, we detail results from studies using an 8 k medaka (Oryzias latipes) microarray to assess modulated gene expression patterns upon hypoxia exposure of the live-bearing aquaria fish, Xiphophorus maculatus. To assess the reproducibility and reliability of using the medaka array in cross-genus hybridization, a two-factor ANOVA analysis of gene expression was employed. The data show the tissue source of the RNA used for array hybridization contributed more to the observed response of modulated gene targets than did the species source of the RNA. In addition, hierarchical clustering via heat map analyses of groupings of tissues and species (Xiphophorus and medaka) suggests that hypoxia induced similar responses in the same tissues from these two diverse aquatic model organisms. Our Xiphophorus results indicate 206 brain, 37 liver, and 925 gill gene targets exhibit hypoxia induced expression changes. Analysis of the Xiphophorus data to determine those features exhibiting a significant (p<0.05)+/-3 fold change produced only two gene targets within brain tissue and 80 features within gill tissue. Of these 82 characterized features, 39 were identified via homology searching (cut-off E-value of 1 x 10(-5)) and placed into one or more biological process gene ontology groups. Among these 39 genes, metabolic energy changes and manipulation was the most affected biological pathway (13 genes).

Tumor Acquisition for Biomarker Research in Lung Cancer

PubMed Central

Stevenson, Marvaretta; Christensen, Jared; Shoemaker, Debra; Foster, Traci; Barry, William T.; Tong, Betty C.; Wahidi, Momen; Shofer, Scott; Datto, Michael; Ginsburg, Geoffrey; Crawford, Jeffrey; D’Amico, Thomas; Ready, Neal

2015-01-01

The biopsy collection data from two lung cancer trials that required fresh tumor samples be obtained for microarray analysis were reviewed. In the trial for advanced disease, microarray data were obtained on 50 patient samples, giving an overall success rate of 60.2%. The majority of the specimens were obtained through CT-guided lung biopsies (N=30). In the trial for early-stage patients, 28 tissue specimens were collected from excess tumor after surgical resection with a success rate of 85.7%. This tissue procurement program documents the feasibility in obtaining fresh tumor specimens prospectively that could be used for molecular testing. PMID:24810245

Next-generation sequencing for endocrine cancers: Recent advances and challenges.

PubMed

Suresh, Padmanaban S; Venkatesh, Thejaswini; Tsutsumi, Rie; Shetty, Abhishek

2017-05-01

Contemporary molecular biology research tools have enriched numerous areas of biomedical research that address challenging diseases, including endocrine cancers (pituitary, thyroid, parathyroid, adrenal, testicular, ovarian, and neuroendocrine cancers). These tools have placed several intriguing clues before the scientific community. Endocrine cancers pose a major challenge in health care and research despite considerable attempts by researchers to understand their etiology. Microarray analyses have provided gene signatures from many cells, tissues, and organs that can differentiate healthy states from diseased ones, and even show patterns that correlate with stages of a disease. Microarray data can also elucidate the responses of endocrine tumors to therapeutic treatments. The rapid progress in next-generation sequencing methods has overcome many of the initial challenges of these technologies, and their advantages over microarray techniques have enabled them to emerge as valuable aids for clinical research applications (prognosis, identification of drug targets, etc.). A comprehensive review describing the recent advances in next-generation sequencing methods and their application in the evaluation of endocrine and endocrine-related cancers is lacking. The main purpose of this review is to illustrate the concepts that collectively constitute our current view of the possibilities offered by next-generation sequencing technological platforms, challenges to relevant applications, and perspectives on the future of clinical genetic testing of patients with endocrine tumors. We focus on recent discoveries in the use of next-generation sequencing methods for clinical diagnosis of endocrine tumors in patients and conclude with a discussion on persisting challenges and future objectives.

Oligonucleotide microarray analysis reveals dysregulation of energy-related metabolism in insulin-sensitive tissues of type 2 diabetes patients.

PubMed

Wang, M; Wang, X C; Zhao, L; Zhang, Y; Yao, L L; Lin, Y; Peng, Y D; Hu, R M

2014-06-17

Impaired insulin action within skeletal muscle, adipose tissue, and the liver is an important characteristic of type 2 diabetes (T2D). In order to identify common underlying defects in insulin-sensitive tissues that may be involved in the pathogenesis of T2D, the gene expression profiles of skeletal muscle, visceral adipose tissue, and liver from autopsy donors with or without T2D were examined using oligonucleotide microarrays and quantitative reverse transcriptase-PCR. Compared with controls, 691 genes were commonly dysregulated in these three insulin-sensitive tissues of humans with T2D. These co-expressed genes were enriched within the mitochondrion, with suggested involvement in energy metabolic processes such as glycolysis and gluconeogenesis, fatty acid beta oxidative, tricarboxylic acid cycle, and electron transport. Genes related to energy metabolism were mostly downregulated in diabetic skeletal muscle and visceral adipose tissue, while they were upregulated in the diabetic liver. This observed dysregulation in energy-related metabolism may be the underlying factor leading to the molecular mechanisms responsible for the insulin resistance of patients with T2D.

A curated collection of tissue microarray images and clinical outcome data of prostate cancer patients

PubMed Central

Zhong, Qing; Guo, Tiannan; Rechsteiner, Markus; Rüschoff, Jan H.; Rupp, Niels; Fankhauser, Christian; Saba, Karim; Mortezavi, Ashkan; Poyet, Cédric; Hermanns, Thomas; Zhu, Yi; Moch, Holger; Aebersold, Ruedi; Wild, Peter J.

2017-01-01

Microscopy image data of human cancers provide detailed phenotypes of spatially and morphologically intact tissues at single-cell resolution, thus complementing large-scale molecular analyses, e.g., next generation sequencing or proteomic profiling. Here we describe a high-resolution tissue microarray (TMA) image dataset from a cohort of 71 prostate tissue samples, which was hybridized with bright-field dual colour chromogenic and silver in situ hybridization probes for the tumour suppressor gene PTEN. These tissue samples were digitized and supplemented with expert annotations, clinical information, statistical models of PTEN genetic status, and computer source codes. For validation, we constructed an additional TMA dataset for 424 prostate tissues, hybridized with FISH probes for PTEN, and performed survival analysis on a subset of 339 radical prostatectomy specimens with overall, disease-specific and recurrence-free survival (maximum 167 months). For application, we further produced 6,036 image patches derived from two whole slides. Our curated collection of prostate cancer data sets provides reuse potential for both biomedical and computational studies. PMID:28291248

TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.

PubMed

Chitturi, Neelima; Balagannavar, Govindkumar; Chandrashekar, Darshan S; Abinaya, Sadashivam; Srini, Vasan S; Acharya, Kshitish K

2013-12-27

Standard 3' Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No resource can currently identify expression pattern of specific mRNA forms using these microarray data, even though it is possible to do this. We report a web server for expression profiling of alternatively spliced transcripts using microarray data sets from 31 standard 3' Affymetrix arrays for human, mouse and rat species. The tool has been experimentally validated for mRNAs transcribed or not-detected in a human disease condition (non-obstructive azoospermia, a male infertility condition). About 4000 gene expression datasets were downloaded from a public repository. 'Good probes' with complete coverage and identity to latest reference transcript sequences were first identified. Using them, 'Transcript specific probe-clusters' were derived for each platform and used to identify expression status of possible transcripts. The web server can lead the user to datasets corresponding to specific tissues, conditions via identifiers of the microarray studies or hybridizations, keywords, official gene symbols or reference transcript identifiers. It can identify, in the tissues and conditions of interest, about 40% of known transcripts as 'transcribed', 'not-detected' or 'differentially regulated'. Corresponding additional information for probes, genes, transcripts and proteins can be viewed too. We identified the expression of transcripts in a specific clinical condition and validated a few of these transcripts by experiments (using reverse transcription followed by polymerase chain reaction). The experimental observations indicated higher agreements with the web server results, than contradictions. The tool is accessible at http://resource.ibab.ac.in/TIPMaP. The newly developed online tool forms a reliable means for identification of alternatively spliced transcript-isoforms that may be differentially expressed in various tissues, cell types or physiological conditions. Thus, by making better use of existing data, TIPMaP avoids the dependence on precious tissue-samples, in experiments with a goal to establish expression profiles of alternative splice forms--at least in some cases.

Larger core size has superior technical and analytical accuracy in bladder tissue microarray.

PubMed

Eskaros, Adel Rh; Egloff, Shanna A Arnold; Boyd, Kelli L; Richardson, Joyce E; Hyndman, M Eric; Zijlstra, Andries

2017-03-01

The construction of tissue microarrays (TMAs) with cores from a large number of paraffin-embedded tissues (donors) into a single paraffin block (recipient) is an effective method of analyzing samples from many patient specimens simultaneously. For the TMA to be successful, the cores within it must capture the correct histologic areas from the donor blocks (technical accuracy) and maintain concordance with the tissue of origin (analytical accuracy). This can be particularly challenging for tissues with small histological features such as small islands of carcinoma in situ (CIS), thin layers of normal urothelial lining of the bladder, or cancers that exhibit intratumor heterogeneity. In an effort to create a comprehensive TMA of a bladder cancer patient cohort that accurately represents the tumor heterogeneity and captures the small features of normal and CIS, we determined how core size (0.6 vs 1.0 mm) impacted the technical and analytical accuracy of the TMA. The larger 1.0 mm core exhibited better technical accuracy for all tissue types at 80.9% (normal), 94.2% (tumor), and 71.4% (CIS) compared with 58.6%, 85.9%, and 63.8% for 0.6 mm cores. Although the 1.0 mm core provided better tissue capture, increasing the number of replicates from two to three allowed with the 0.6 mm core compensated for this reduced technical accuracy. However, quantitative image analysis of proliferation using both Ki67+ immunofluorescence counts and manual mitotic counts demonstrated that the 1.0 mm core size also exhibited significantly greater analytical accuracy (P=0.004 and 0.035, respectively, r 2 =0.979 and 0.669, respectively). Ultimately, our findings demonstrate that capturing two or more 1.0 mm cores for TMA construction provides superior technical and analytical accuracy over the smaller 0.6 mm cores, especially for tissues harboring small histological features or substantial heterogeneity.

A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

PubMed Central

Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

2016-01-01

A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids released via lipolysis of white adipose tissue. PMID:27187182

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

PubMed Central

2009-01-01

Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment. PMID:20025723

Effect of Fixatives and Tissue Processing on the Content and Integrity of Nucleic Acids

PubMed Central

Srinivasan, Mythily; Sedmak, Daniel; Jewell, Scott

2002-01-01

Clinical and molecular medicines are undergoing a revolution based on the accelerated advances in biotechnology such as DNA microarrays and proteomics. Answers to fundamental questions such as how does the DNA sequence differ between individuals and what makes one individual more prone for a certain disease are eagerly being sought in this postgenomic era. Several government and nonprofit organizations provide the researchers access to human tissues for molecular studies. The tissues procured by the different organizations may differ with respect to fixation and processing parameters that may affect significantly the molecular profile of the tissues. It is imperative that a prospective investigator be aware of the potential contributing factors before designing a project. The purpose of this review is to provide an overview of the methods of human tissue acquisition, fixation, and preservation. In addition, the parameters of procurement and fixation that affect the quality of the tissues at the molecular level are discussed. PMID:12466110

A New Way to Introduce Microarray Technology in a Lecture/Laboratory Setting by Studying the Evolution of This Modern Technology

ERIC Educational Resources Information Center

Rowland-Goldsmith, Melissa

2009-01-01

DNA microarray is an ordered grid containing known sequences of DNA, which represent many of the genes in a particular organism. Each DNA sequence is unique to a specific gene. This technology enables the researcher to screen many genes from cells or tissue grown in different conditions. We developed an undergraduate lecture and laboratory…

High SPDEF May Identify Patients Who Will Have a Prolonged Response to Androgen Deprivation Therapy

PubMed Central

Haller, Andrew C.; Tan, Wei; Payne-Ondracek, Rochelle; Underwood, Willie; Tian, Lili; Morrison, Carl; Li, Fengzhi

2015-01-01

Background Due to the indolent nature of prostate cancer, new prognostic measures are needed to identify patients with life threatening disease. SAM pointed domain-containing Ets transcription factor (SPDEF) has been associated with good prognosis and demonstrates an intimate relationship with the androgen receptor (AR), however its role in prostate cancer progression remains unclear. Methods A tissue microarray constructed from cores of 713 consecutive radical prostatectomy specimens were immunohistochemically stained for SPDEF and correlated with progression free and metastatic free survival. In vitro studies assessed growth rate, migration, and sensitivity to bicalutamide to explore mechanisms behind the tissue microarray observations. Results Patients with high SPDEF demonstrate longer metastases free survival after receiving the standard of care (HR = 9.80, P = 0.006). SPDEF expression corresponded with bicalutamide growth inhibition and apoptosis induction in all cell lines studied. In addition, a feed-forward loop of AR-SPEF expression regulation is observed. Conclusions SPDEF may be clinically useful to identify patients who will have extended benefits from androgen deprivation therapy. In vitro observations suggest SPDEF mediates initial sensitivity to androgen deprivation therapy through both AR regulation and downstream events. PMID:24375440

Intratumoral concentration of estrogens and clinicopathological changes in ductal carcinoma in situ following aromatase inhibitor letrozole treatment

PubMed Central

Takagi, K; Ishida, T; Miki, Y; Hirakawa, H; Kakugawa, Y; Amano, G; Ebata, A; Mori, N; Nakamura, Y; Watanabe, M; Amari, M; Ohuchi, N; Sasano, H; Suzuki, T

2013-01-01

Background: Estrogens have important roles in ductal carcinoma in situ (DCIS) of the breast. However, the significance of presurgical aromatase inhibitor treatment remains unclear. Therefore, we examined intratumoral concentration of estrogens and changes of clinicopathological factors in DCIS after letrozole treatment. Methods: Ten cases of postmenopausal oestrogen receptor (ER)-positive DCIS were examined. They received oral letrozole before the surgery, and the tumour size was evaluated by ultrasonography. Surgical specimens and corresponding biopsy samples were used for immunohistochemistry. Snap-frozen specimens were also available in a subset of cases, and used for hormone assays and microarray analysis. Results: Intratumoral oestrogen levels were significantly lower in DCIS treated with letrozole compared with that in those without the therapy. A great majority of oestrogen-induced genes showed low expression levels in DCIS treated with letrozole by microarray analysis. Moreover, letrozole treatment reduced the greatest dimension of DCIS, and significantly decreased Ki-67 and progesterone receptor immunoreactivity in DCIS tissues. Conclusion: These results suggest that estrogens are mainly produced by aromatase in DCIS tissues, and aromatase inhibitors potently inhibit oestrogen actions in postmenopausal ER-positive DCIS through rapid deprivation of intratumoral estrogens. PMID:23756858

Myogenin, AP2β, NOS-1, and HMGA2 are surrogate markers of fusion status in rhabdomyosarcoma: a report from the soft tissue sarcoma committee of the children's oncology group.

PubMed

Rudzinski, Erin R; Anderson, James R; Lyden, Elizabeth R; Bridge, Julia A; Barr, Frederic G; Gastier-Foster, Julie M; Bachmeyer, Karen; Skapek, Stephen X; Hawkins, Douglas S; Teot, Lisa A; Parham, David M

2014-05-01

Pediatric rhabdomyosarcoma (RMS) is traditionally classified on the basis of the histologic appearance into alveolar (ARMS) and embryonal (ERMS) subtypes. The majority of ARMS contain a PAX3-FOXO1 or PAX7-FOXO1 gene fusion, but about 20% do not. Intergroup Rhabdomyosarcoma Study stage-matched and group-matched ARMS typically behaves more aggressively than ERMS, but recent studies have shown that it is, in fact, the fusion status that drives the outcome for RMS. Gene expression microarray data indicate that several genes discriminate between fusion-positive and fusion-negative RMS with high specificity. Using tissue microarrays containing a series of both ARMS and ERMS, we identified a panel of 4 immunohistochemical markers-myogenin, AP2β, NOS-1, and HMGA2-which can be used as surrogate markers of fusion status in RMS. These antibodies provide an alternative to molecular methods for identification of fusion-positive RMS, particularly in cases in which there is scant or poor-quality material. In addition, these antibodies may be useful in fusion-negative ARMS as an indicator that a variant gene fusion may be present.

Intratumoral immune cells expressing PD-1/PD-L1 and their prognostic implications in cancer: a meta-analysis.

PubMed

Kim, Younghoon; Wen, Xianyu; Cho, Nam Yun; Kang, Gyeong Hoon

2018-05-01

The prognostic value of immune cells expressing programmed cell death 1 (PD-1) and PD-1 ligand 1 (PD-L1) in cancer are controversial, and the potential differential impact of using tissue microarrays and whole tissue sections to assess the positivity of immune cells has not been addressed. The current study included 30 eligible studies with 7251 patients that evaluated the relationship between tumor-infiltrating lymphocytes expressing PD-1/PD-L1 and overall survival and disease-free survival, or progression-free survival. Subgroup analysis was based on the tissue type of cancer and the type of tissue sampling (tissue microarray or whole tissue section). In the meta-analysis, PD-1-positive and PD-L1-positive tumor-infiltrating lymphocytes had a positive effect on disease-free survival or progression-free survival (hazard ratio [HR] 0.732; 95% confidence interval [CI] 0.565, 0.947; and HR 0.727; 95% CI 0.584, 0.905, respectively). PD-L1-positive tumor-infiltrating lymphocytes had a positive impact on overall survival in studies using tissue microarray (HR 0.586; 95% CI 0.476, 0.721), but had a poor impact when only whole tissue sections were considered (HR 1.558; 95% CI 1.232, 1.969). Lung cancer was associated with good overall survival and disease-free survival (HR 0.639; 95% CI 0.491, 0.831; and HR 0.693; 95% CI 0.538, 0.891, respectively) for PD-1-positive tumor-infiltrating lymphocytes, and colorectal cancer showed favorable disease-free survival (HR 0.471; 95% CI 0.308, 0.722) for PD-L1-positive tumor-infiltrating lymphocytes. Immune cells expressing PD-1 and PD-L1 within tumors are associated with the prognosis. However, the correlation may vary among different tumor types and by the type of tissue sampling used for the assessment.

Cancer testis antigen OY-TES-1: analysis of protein expression in ovarian cancer with tissue microarrays.

PubMed

Fan, R; Huang, W; Luo, B; Zhang, Q M; Xiao, S W; Xie, X X

2015-01-01

Revised manuscript accepted for publication March 5, Objectives: The purpose of this study was to determine the potential of cancer testis antigen OY-TES-1 as a vaccine for ovarian cancer (OC). A tissue microarray (TMA) containing 107 samples from OC tissues and 48 samples from OC adjacent tissues was analyzed by immunohistochemistry with the OY-TES-1 polyclonal antibody. The correlation between OY-TES-1 and clinic pathological traits of OC was statistically analyzed. The expression of OY-TES-1 protein was found in 81% (87/107) of OC tissues and 56% (27/48) of OC adjacent tissues. The immunostaining intensity of OY-TES-1 in OC tissues was significantly higher than that in OC adjacent tissues tested (p = 0.040). OC adjacent tissues only demonstrated lower immunostaining intensity, whereas some of OC tissues presented higher immunostaining intensity and majority showed the heterogeneity of protein distribution. There was no statistically significant correlation found between OY-TES-1 expression and any other clinicopathological traits such as age, FIGO stage, pathological grade, and histological type. OY-TES-1 was expressed in OC tissues with a high proportion, and some of OC tissues presented OY-TES-1 expression in high level vs OC adjacent tissues. OY-TES-1 could be an attractive target for immunotherapy for OC in the future.

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

Comprehensive analysis of differentially expressed profiles of lncRNAs and construction of miR-133b mediated ceRNA network in colorectal cancer.

PubMed

Wu, Hao; Wu, Runliu; Chen, Miao; Li, Daojiang; Dai, Jing; Zhang, Yi; Gao, Kai; Yu, Jun; Hu, Gui; Guo, Yihang; Lin, Changwei; Li, Xiaorong

2017-03-28

Growing evidence suggests that long non-coding RNAs (lncRNAs) play a key role in tumorigenesis. However, the mechanism remains largely unknown. Thousands of significantly dysregulated lncRNAs and mRNAs were identified by microarray. Furthermore, a miR-133b-meditated lncRNA-mRNA ceRNA network was revealed, a subset of which was validated in 14 paired CRC patient tumor/non-tumor samples. Gene set enrichment analysis (GSEA) results demonstrated that lncRNAs ENST00000520055 and ENST00000535511 shared KEGG pathways with miR-133b target genes. We used microarrays to survey the lncRNA and mRNA expression profiles of colorectal cancer and para-cancer tissues. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed to explore the functions of the significantly dysregulated genes. An innovate method was employed that combined analyses of two microarray data sets to construct a miR-133b-mediated lncRNA-mRNA competing endogenous RNAs (ceRNA) network. Quantitative RT-PCR analysis was used to validate part of this network. GSEA was used to predict the potential functions of these lncRNAs. This study identifies and validates a new method to investigate the miR-133b-mediated lncRNA-mRNA ceRNA network and lays the foundation for future investigation into the role of lncRNAs in colorectal cancer.

Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

PubMed

Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

2011-10-11

Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

Microfluidic microarray systems and methods thereof

DOEpatents

West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

2009-04-28

Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

MicroRNA-301a-3p promotes pancreatic cancer progression via negative regulation of SMAD4

PubMed Central

Zhang, Kundong; Cen, Gang; Jiang, Tao; Cao, Jun; Huang, Kejian; Zhao, Qian; Qiu, Zhengjun

2015-01-01

Background Aim to determine the clinicopathological and prognostic role of miR-301a-3p in pancreatic ductal adenocarcinoma(PDAC), to investigate the biological mechanism of miR-301a-3p in vitro and in vivo. Methods By tissue microarray analysis, we studied miR-301a-3p expression in PDAC patients and its clinicopathological correlations as well as prognostic significance. qRT-PCR was used to test miR-301a-3p expression in PDAC tissues and cell lines. Functional experiments including in vitro and in vivo were performed. Results Significantly higher expression of miR-301a-3p were found in PDAC patients with lymph node metastasis and advanced pathological stages and identified as an independent prognostic factor for worse survival. In PDAC samples and cell lines, miR-301a-3p was significantly up-regulated compared with matched non-tumor tissues and normal pancreatic ductal cells, respectively. Overexpression of miR-301a-3p enhanced PDAC cells colony, invasion and migration abilities in vitro as well as tumorigenicity in vivo. Furthermore, SMAD4 was identified as a target gene of miR-301a-3p by cell as well as mice xenograft experiments. In PDAC tissue microarray, a significantly inverse correlation between miR-301a-3p ISH scores and SMAD4 IHC scores were observed in both tumor and corresponding non-tumor tissues. Conclusion MiR-301a-3p functions as a novel oncogene in PDAC and the oncogenic activity may involve its inhibition of the target gene SMAD4. PMID:26019136

Functional proteomic analysis reveals the involvement of KIAA1199 in breast cancer growth, motility and invasiveness

PubMed Central

2014-01-01

Background KIAA1199 is a recently identified novel gene that is up-regulated in human cancer with poor survival. Our proteomic study on signaling polarity in chemotactic cells revealed KIAA1199 as a novel protein target that may be involved in cellular chemotaxis and motility. In the present study, we examined the functional significance of KIAA1199 expression in breast cancer growth, motility and invasiveness. Methods We validated the previous microarray observation by tissue microarray immunohistochemistry using a TMA slide containing 12 breast tumor tissue cores and 12 corresponding normal tissues. We performed the shRNA-mediated knockdown of KIAA1199 in MDA-MB-231 and HS578T cells to study the role of this protein in cell proliferation, migration and apoptosis in vitro. We studied the effects of KIAA1199 knockdown in vivo in two groups of mice (n = 5). We carried out the SILAC LC-MS/MS based proteomic studies on the involvement of KIAA1199 in breast cancer. Results KIAA1199 mRNA and protein was significantly overexpressed in breast tumor specimens and cell lines as compared with non-neoplastic breast tissues from large-scale microarray and studies of breast cancer cell lines and tumors. To gain deeper insights into the novel role of KIAA1199 in breast cancer, we modulated KIAA1199 expression using shRNA-mediated knockdown in two breast cancer cell lines (MDA-MB-231 and HS578T), expressing higher levels of KIAA1199. The KIAA1199 knockdown cells showed reduced motility and cell proliferation in vitro. Moreover, when the knockdown cells were injected into the mammary fat pads of female athymic nude mice, there was a significant decrease in tumor incidence and growth. In addition, quantitative proteomic analysis revealed that knockdown of KIAA1199 in breast cancer (MDA-MB-231) cells affected a broad range of cellular functions including apoptosis, metabolism and cell motility. Conclusions Our findings indicate that KIAA1199 may play an important role in breast tumor growth and invasiveness, and that it may represent a novel target for biomarker development and a novel therapeutic target for breast cancer. PMID:24628760

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Transcriptional profiling of the parr–smolt transformation in Atlantic salmon

USGS Publications Warehouse

Robertson, Laura S.; McCormick, Stephen D.

2012-01-01

The parr–smolt transformation in Atlantic salmon (Salmo salar) is a complex developmental process that culminates in the ability to migrate to and live in seawater. We used GRASP 16K cDNA microarrays to identify genes that are differentially expressed in the liver, gill, hypothalamus, pituitary, and olfactory rosettes of smolts compared to parr. Smolts had higher levels of gill Na+/K+-ATPase activity, plasma cortisol and plasma thyroid hormones relative to parr. Across all five tissues, stringent microarray analyses identified 48 features that were differentially expressed in smolts compared to parr. Using a less stringent method we found 477 features that were differentially expressed at least 1.2-fold in smolts, including 172 features in the gill. Smolts had higher mRNA levels of genes involved in transcription, protein biosynthesis and folding, electron transport, oxygen transport, and sensory perception and lower mRNA levels for genes involved in proteolysis. Quantitative RT-PCR was used to confirm differential expression in select genes identified by microarray analyses and to quantify expression of other genes known to be involved in smolting. This study expands our understanding of the molecular processes that underlie smolting in Atlantic salmon and identifies genes for further investigation.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

The clinicopathologic association of c-MET overexpression in Iranian gastric carcinomas; an immunohistochemical study of tissue microarrays

PubMed Central

2012-01-01

Background c-MET is an oncogene protein that plays important role in gastric carcinogenesis and has been introduced as a prognostic marker and potential therapeutic target. The aim of this study was to evaluate the frequency of c-MET overexpression and its relationship with clinicopathological variables in gastric cancer of Iranian population using tissue microarray. Methods In a cross sectional study, representative paraffin blocks of 130 patients with gastric carcinoma treated by curative gastrectomy during a 2 years period of 2008–2009 in two university hospitals in Tehran-Iran were collected in tissue microarray and c-MET expression was studied by immunohistochemical staining. Results Finally 124 cases were evaluated, constituted of 99 male and 25 female with the average age of 61.5 years. In 71% (88/124) of tumors, c-MET high expression was found. c-MET high expression was more associated with intestinal than diffuse tumor type (P = 0.04), deeper tumor invasion, pT3 and pT4 versus pT1 and pT2 (P = 0.014), neural invasion (P = 0.002) and advanced TNM staging, stage 3 and 4 versus stage 1 and2 (P = 0.044). The c-MET high expression was not associated with age, sex, tumor location, differentiation grade and distant metastasis, but relative associations with lymph node metastasis (P = 0.065) and vascular invasion (P = 0.078) were observed. Conclusions c-MET oncogene protein was frequently overexpressed in Iranian gastric carcinomas and it was related to clinicopathological characteristics such as tumor type, depth of invasion, neural invasion and TNM staging. It can also support the idea that c-MET is a potential marker for target therapy in Iranian gastric cancer. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9744598757151429 PMID:22640970

Informatic selection of a neural crest-melanocyte cDNA set for microarray analysis

PubMed Central

Loftus, S. K.; Chen, Y.; Gooden, G.; Ryan, J. F.; Birznieks, G.; Hilliard, M.; Baxevanis, A. D.; Bittner, M.; Meltzer, P.; Trent, J.; Pavan, W.

1999-01-01

With cDNA microarrays, it is now possible to compare the expression of many genes simultaneously. To maximize the likelihood of finding genes whose expression is altered under the experimental conditions, it would be advantageous to be able to select clones for tissue-appropriate cDNA sets. We have taken advantage of the extensive sequence information in the dbEST expressed sequence tag (EST) database to identify a neural crest-derived melanocyte cDNA set for microarray analysis. Analysis of characterized genes with dbEST identified one library that contained ESTs representing 21 neural crest-expressed genes (library 198). The distribution of the ESTs corresponding to these genes was biased toward being derived from library 198. This is in contrast to the EST distribution profile for a set of control genes, characterized to be more ubiquitously expressed in multiple tissues (P < 1 × 10−9). From library 198, a subset of 852 clustered ESTs were selected that have a library distribution profile similar to that of the 21 neural crest-expressed genes. Microarray analysis demonstrated the majority of the neural crest-selected 852 ESTs (Mel1 array) were differentially expressed in melanoma cell lines compared with a non-neural crest kidney epithelial cell line (P < 1 × 10−8). This was not observed with an array of 1,238 ESTs that was selected without library origin bias (P = 0.204). This study presents an approach for selecting tissue-appropriate cDNAs that can be used to examine the expression profiles of developmental processes and diseases. PMID:10430933

An 80-year experience with optic nerve glioma cases at the Armed Forces Institute of Pathology: evolution from museum to molecular evaluation suggests possibe interventions in the cellular senescence and microglial pathways (an American Ophthalmological Society thesis).

PubMed

Cameron, J Douglas; Rodriguez, Fausto J; Rushing, Elisabeth; Horkayne-Szakaly, Iren; Eberhart, Charles

2014-01-01

To determine whether p16, a molecular marker of cellular senescence, and CD68, a microglial marker, are detectible in optic nerve glioma tissue stored for decades, thus providing potential targets for pharmacologic intervention. Cases were retrieved from the Armed Forces Institute of Pathology Registry of Ophthalmic Pathology. Clinical information was tabulated. In specimens with sufficient tissue, a tissue microarray was constructed to conduct molecular studies. Ninety-two cases were included: gender distribution was in a ratio of one male to 1.6 females, and age range was 2 months to 50 years (average age, 10.8 years). Neurofibromatosis type 1 was identified in 10 cases (10.8%). The majority presented with decreased vision and exophthalmos. Forty-eight cases were studied by a tissue microarray construction. Glial fibrillary acidic protein, a control for immunoreactivity, was positive in 46 cases (96%). Immunoreactivity for p16 protein was seen in 36 cases (75%) and CD68-positive cells in 34 (71%). Limitations include referral bias, limited clinical information, limited amount of tissue, and extended period of tissue preservation. Optic nerve glioma is a tumor of the visual axis in young individuals, which is generally indolent but with a variable clinical course. Traditional histopathologic techniques have not been reliably predictive of clinical course. This microarray contains tumors with representative demographic, clinical, and histologic characteristics for optic nerve glioma. Immunoreactivity for p16 protein and CD68 is positive in the majority. These findings suggest a possible explanation for the variable clinical course and identify therapeutic targets in the cell senescence and microglial pathways.

Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

PubMed Central

Hu, Wenchao; Liu, Yuting; Yan, Jun

2014-01-01

Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

Expression Comparison of Oil Biosynthesis Genes in Oil Palm Mesocarp Tissue Using Custom Array

PubMed Central

Wong, Yick Ching; Kwong, Qi Bin; Lee, Heng Leng; Ong, Chuang Kee; Mayes, Sean; Chew, Fook Tim; Appleton, David R.; Kulaveerasingam, Harikrishna

2014-01-01

Gene expression changes that occur during mesocarp development are a major research focus in oil palm research due to the economic importance of this tissue and the relatively rapid increase in lipid content to very high levels at fruit ripeness. Here, we report the development of a transcriptome-based 105,000-probe oil palm mesocarp microarray. The expression of genes involved in fatty acid (FA) and triacylglycerol (TAG) assembly, along with the tricarboxylic acid cycle (TCA) and glycolysis pathway at 16 Weeks After Anthesis (WAA) exhibited significantly higher signals compared to those obtained from a cross-species hybridization to the Arabidopsis (p-value < 0.01), and rice (p-value < 0.01) arrays. The oil palm microarray data also showed comparable correlation of expression (r2 = 0.569, p < 0.01) throughout mesocarp development to transcriptome (RNA sequencing) data, and improved correlation over quantitative real-time PCR (qPCR) (r2 = 0.721, p < 0.01) of the same RNA samples. The results confirm the advantage of the custom microarray over commercially available arrays derived from model species. We demonstrate the utility of this custom microarray to gain a better understanding of gene expression patterns in the oil palm mesocarp that may lead to increasing future oil yield. PMID:27600348

Expression Comparison of Oil Biosynthesis Genes in Oil Palm Mesocarp Tissue Using Custom Array.

PubMed

Wong, Yick Ching; Kwong, Qi Bin; Lee, Heng Leng; Ong, Chuang Kee; Mayes, Sean; Chew, Fook Tim; Appleton, David R; Kulaveerasingam, Harikrishna

2014-11-13

Gene expression changes that occur during mesocarp development are a major research focus in oil palm research due to the economic importance of this tissue and the relatively rapid increase in lipid content to very high levels at fruit ripeness. Here, we report the development of a transcriptome-based 105,000-probe oil palm mesocarp microarray. The expression of genes involved in fatty acid (FA) and triacylglycerol (TAG) assembly, along with the tricarboxylic acid cycle (TCA) and glycolysis pathway at 16 Weeks After Anthesis (WAA) exhibited significantly higher signals compared to those obtained from a cross-species hybridization to the Arabidopsis (p-value < 0.01), and rice (p-value < 0.01) arrays. The oil palm microarray data also showed comparable correlation of expression (r² = 0.569, p < 0.01) throughout mesocarp development to transcriptome (RNA sequencing) data, and improved correlation over quantitative real-time PCR (qPCR) (r² = 0.721, p < 0.01) of the same RNA samples. The results confirm the advantage of the custom microarray over commercially available arrays derived from model species. We demonstrate the utility of this custom microarray to gain a better understanding of gene expression patterns in the oil palm mesocarp that may lead to increasing future oil yield.

Gene profiling, biomarkers and pathways characterizing HCV-related hepatocellular carcinoma

PubMed Central

De Giorgi, Valeria; Monaco, Alessandro; Worchech, Andrea; Tornesello, MariaLina; Izzo, Francesco; Buonaguro, Luigi; Marincola, Francesco M; Wang, Ena; Buonaguro, Franco M

2009-01-01

Background Hepatitis C virus (HCV) infection is a major cause of hepatocellular carcinoma (HCC) worldwide. The molecular mechanisms of HCV-induced hepatocarcinogenesis are not yet fully elucidated. Besides indirect effects as tissue inflammation and regeneration, a more direct oncogenic activity of HCV can be postulated leading to an altered expression of cellular genes by early HCV viral proteins. In the present study, a comparison of gene expression patterns has been performed by microarray analysis on liver biopsies from HCV-positive HCC patients and HCV-negative controls. Methods Gene expression profiling of liver tissues has been performed using a high-density microarray containing 36'000 oligos, representing 90% of the human genes. Samples were obtained from 14 patients affected by HCV-related HCC and 7 HCV-negative non-liver-cancer patients, enrolled at INT in Naples. Transcriptional profiles identified in liver biopsies from HCC nodules and paired non-adjacent non-HCC liver tissue of the same HCV-positive patients were compared to those from HCV-negative controls by the Cluster program. The pathway analysis was performed using the BRB-Array- Tools based on the "Ingenuity System Database". Significance threshold of t-test was set at 0.001. Results Significant differences were found between the expression patterns of several genes falling into different metabolic and inflammation/immunity pathways in HCV-related HCC tissues as well as the non-HCC counterpart compared to normal liver tissues. Only few genes were found differentially expressed between HCV-related HCC tissues and paired non-HCC counterpart. Conclusion In this study, informative data on the global gene expression pattern of HCV-related HCC and non-HCC counterpart, as well as on their difference with the one observed in normal liver tissues have been obtained. These results may lead to the identification of specific biomarkers relevant to develop tools for detection, diagnosis, and classification of HCV-related HCC. PMID:19821982

Improvement in the amine glass platform by bubbling method for a DNA microarray

PubMed Central

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

Improvement in the amine glass platform by bubbling method for a DNA microarray.

PubMed

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

Overcoming confounded controls in the analysis of gene expression data from microarray experiments.

PubMed

Bhattacharya, Soumyaroop; Long, Dang; Lyons-Weiler, James

2003-01-01

A potential limitation of data from microarray experiments exists when improper control samples are used. In cancer research, comparisons of tumour expression profiles to those from normal samples is challenging due to tissue heterogeneity (mixed cell populations). A specific example exists in a published colon cancer dataset, in which tissue heterogeneity was reported among the normal samples. In this paper, we show how to overcome or avoid the problem of using normal samples that do not derive from the same tissue of origin as the tumour. We advocate an exploratory unsupervised bootstrap analysis that can reveal unexpected and undesired, but strongly supported, clusters of samples that reflect tissue differences instead of tumour versus normal differences. All of the algorithms used in the analysis, including the maximum difference subset algorithm, unsupervised bootstrap analysis, pooled variance t-test for finding differentially expressed genes and the jackknife to reduce false positives, are incorporated into our online Gene Expression Data Analyzer ( http:// bioinformatics.upmc.edu/GE2/GEDA.html ).

Molecular profiles of pre- and postoperative breast cancer tumours reveal differentially expressed genes.

PubMed

Riis, Margit L H; Lüders, Torben; Markert, Elke K; Haakensen, Vilde D; Nesbakken, Anne-Jorun; Kristensen, Vessela N; Bukholm, Ida R K

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.

Molecular Profiles of Pre- and Postoperative Breast Cancer Tumours Reveal Differentially Expressed Genes

PubMed Central

Riis, Margit L. H.; Lüders, Torben; Markert, Elke K.; Haakensen, Vilde D.; Nesbakken, Anne-Jorun; Kristensen, Vessela N.; Bukholm, Ida R. K.

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology. PMID:23227362

The prognostic implication of the expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in primary locally advanced oral squamous cell carcinoma cases: a tissue microarray study.

PubMed

Solomon, Monica Charlotte; Vidyasagar, M S; Fernandes, Donald; Guddattu, Vasudev; Mathew, Mary; Shergill, Ankur Kaur; Carnelio, Sunitha; Chandrashekar, Chetana

2016-12-01

Oral squamous cell carcinomas comprise a heterogeneous tumor cell population with varied molecular characteristics, which makes prognostication of these tumors a complex and challenging issue. Thus, molecular profiling of these tumors is advantageous for an accurate prognostication and treatment planning. This is a retrospective study on a cohort of primary locally advanced oral squamous cell carcinomas (n = 178) of an Indian rural population. The expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in a cohort of primary locally advanced oral squamous cell carcinomas was evaluated. A potential biomarker that can predict the tumor response to treatment was identified. Formalin-fixed paraffin-embedded tumor blocks of (n = 178) of histopathologically diagnosed cases of locally advanced oral squamous cell carcinomas were selected. Tissue microarray blocks were constructed with 2 cores of 2 mm diameter from each tumor block. Four-micron-thick sections were cut from these tissue microarray blocks. These tissue microarray sections were immunohistochemically stained for EGFR, p53, Bcl-2, cyclin D1 and p16. In this cohort, EGFR was the most frequently expressed 150/178 (84%) biomarker of the cases. Kaplan-Meier analysis showed a significant association (p = 0.038) between expression of p53 and a poor prognosis. A Poisson regression analysis showed that tumors that expressed p53 had a two times greater chance of recurrence (unadjusted IRR-95% CI 2.08 (1.03, 4.5), adjusted IRR-2.29 (1.08, 4.8) compared with the tumors that did not express this biomarker. Molecular profiling of oral squamous cell carcinomas will enable us to categorize our patients into more realistic risk groups. With biologically guided tumor characterization, personalized treatment protocols can be designed for individual patients, which will improve the quality of life of these patients.

Unique Chemokine Profiles of Lung Tissues Distinguish Post-chemotherapeutic Persistent and Chronic Tuberculosis in a Mouse Model.

PubMed

Park, Soomin; Baek, Seung-Hun; Cho, Sang-Nae; Jang, Young-Saeng; Kim, Ahreum; Choi, In-Hong

2017-01-01

There is a substantial need for biomarkers to distinguish latent stage from active Mycobacterium tuberculosis infections, for predicting disease progression. To induce the reactivation of tuberculosis, we present a new experimental animal model modified based on the previous model established by our group. In the new model, the reactivation of tuberculosis is induced without administration of immunosuppressive agents, which might disturb immune responses. To identify the immunological status of the persistent and chronic stages, we analyzed immunological genes in lung tissues from mice infected with M. tuberculosis . Gene expression was screened using cDNA microarray analysis and confirmed by quantitative RT-PCR. Based on the cDNA microarray results, 11 candidate cytokines genes, which were obviously up-regulated during the chronic stage compared with those during the persistent stage, were selected and clustered into three groups: (1) chemokine genes, except those of monocyte chemoattractant proteins (MCPs; CXCL9, CXCL10, CXCL11, CCL5, CCL19); (2) MCP genes (CCL2, CCL7, CCL8, CCL12); and (3) TNF and IFN-γ genes. Results from the cDNA microarray and quantitative RT-PCR analyses revealed that the mRNA expression of the selected cytokine genes was significantly higher in lung tissues of the chronic stage than of the persistent stage. Three chemokines (CCL5, CCL19, and CXCL9) and three MCPs (CCL7, CCL2, and CCL12) were noticeably increased in the chronic stage compared with the persistent stage by cDNA microarray ( p < 0.01, except CCL12) or RT-PCR ( p < 0.01). Therefore, these six significantly increased cytokines in lung tissue from the mouse tuberculosis model might be candidates for biomarkers to distinguish the two disease stages. This information can be combined with already reported potential biomarkers to construct a network of more efficient tuberculosis markers.

Differential Adipose Tissue Gene Expression Profiles in Abacavir Treated Patients That May Contribute to the Understanding of Cardiovascular Risk: A Microarray Study

PubMed Central

Shahmanesh, Mohsen; Phillips, Kenneth; Boothby, Meg; Tomlinson, Jeremy W.

2015-01-01

Objective To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC), tenofovir (TDF) or zidovidine (AZT). Design Subcutaneous fat biopsies were obtained before, at 6- and 18–24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis. Results There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18–24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18–24 months (adjusted p<0.05) and focal adhesions and tight junction at 6 months (p<0.5). Genes controlling leukocyte transendothelial migration (p<0.05) and ECM-receptor interactions (p = 0.04) were over-expressed in ABC compared to TDF and AZT at 6 months but not at 18–24 months. Enrichment of pathways and individual genes controlling cell adhesion and environmental information processing were specifically dysregulated in the ABC group in comparison with other treatments. There was little difference between AZT and TDF. Conclusion After initiating treatment, there is divergence in the expression of genes controlling cell adhesion and environmental information processing between ABC and both TDF and AZT in subcutaneous adipose tissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens. PMID:25617630

High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples.

PubMed

Reiser, Vladimír; Smith, Ryan C; Xue, Jiyan; Kurtz, Marc M; Liu, Rong; Legrand, Cheryl; He, Xuanmin; Yu, Xiang; Wong, Peggy; Hinchcliffe, John S; Tanen, Michael R; Lazar, Gloria; Zieba, Renata; Ichetovkin, Marina; Chen, Zhu; O'Neill, Edward A; Tanaka, Wesley K; Marton, Matthew J; Liao, Jason; Morris, Mark; Hailman, Eric; Tokiwa, George Y; Plump, Andrew S

2011-11-01

With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma.

PubMed

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong; Li, Ning

2016-12-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma

PubMed Central

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong

2016-01-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC (n = 65) and healthy control subjects (n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC. PMID:27885040

Advances in cell-free protein array methods.

PubMed

Yu, Xiaobo; Petritis, Brianne; Duan, Hu; Xu, Danke; LaBaer, Joshua

2018-01-01

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Loss of Smad4 in colorectal cancer induces resistance to 5-fluorouracil through activating Akt pathway

PubMed Central

Zhang, B; Zhang, B; Chen, X; Bae, S; Singh, K; Washington, M K; Datta, P K

2014-01-01

Background: Higher frequency of Smad4 inactivation or loss of expression is observed in metastasis of colorectal cancer (CRC) leading to unfavourable survival and contributes to chemoresistance. However, the molecular mechanism of how Smad4 regulates chemosensitivity of CRC is unknown. Methods: We evaluated how the loss of Smad4 in CRC enhanced chemoresistance to 5-fluorouracil (5-FU) using two CRC cell lines in vitro and in vivo. Immunoblotting with cell and tumour lysates and immunohistochemical analyses with tissue microarray were performed. Results: Knockdown or loss of Smad4 induced tumorigenicity, migration, invasion, angiogenesis, metastasis, and 5-FU resistance. Smad4 expression in mouse tumours regulated cell-cycle regulatory proteins leading to Rb phosphorylation. Loss of Smad4 activated Akt pathway that resulted in upregulation of anti-apoptotic proteins, Bcl-2 and Bcl-w, and Survivin. Suppression of phosphatidylinositol-3-kinase (PI3K)/Akt pathway by LY294002 restored chemosensitivity of Smad4-deficient cells to 5-FU. Vascular endothelial growth factor-induced angiogenesis in Smad4-deficient cells might also lead to chemoresistance. Low levels of Smad4 expression in CRC tissues correlated with higher levels of Bcl-2 and Bcl-w and with poor overall survival as observed in immunohistochemical staining of tissue microarrays. Conclusion: Loss of Smad4 in CRC patients induces resistance to 5-FU-based therapy through activation of Akt pathway and inhibitors of this pathway may sensitise these patients to 5-FU. PMID:24384683

Multi-Tissue Computational Modeling Analyzes Pathophysiology of Type 2 Diabetes in MKR Mice

PubMed Central

Kumar, Amit; Harrelson, Thomas; Lewis, Nathan E.; Gallagher, Emily J.; LeRoith, Derek; Shiloach, Joseph; Betenbaugh, Michael J.

2014-01-01

Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM) can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL) multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective. PMID:25029527

Genetic and Epigenetic Biomarkers for Recurrent Prostate Cancer After Radiotherapy

DTIC Science & Technology

2015-07-01

several distinct advantages over surgical treatment, such as no complications from surgery, and a low risk of urinary incontinence , RT treatment takes...Khorana, Tissue factor and VEGF expression in prostate carcinoma: a tissue microarray study. Cancer Invest, 2009. 27(4): p. 430-4. 7. Crawford, E.D

Genomic expression patterns of cardiac tissues from dogs with dilated cardiomyopathy.

PubMed

Oyama, Mark A; Chittur, Sridar

2005-07-01

To evaluate global genome expression patterns of left ventricular tissues from dogs with dilated cardiomyopathy (DCM). Tissues obtained from the left ventricle of 2 Doberman Pinschers with end-stage DCM and 5 healthy control dogs. Transcriptional activities of 23,851 canine DNA sequences were determined by use of an oligonucleotide microarray. Genome expression patterns of DCM tissue were evaluated by measuring the relative amount of complementary RNA hybridization to the microarray probes and comparing it with gene expression for tissues from 5 healthy control dogs. 478 transcripts were differentially expressed (> or = 2.5-fold change). In DCM tissue, expression of 173 transcripts was upregulated and expression of 305 transcripts was downregulated, compared with expression for control tissues. Of the 478 transcripts, 167 genes could be specifically identified. These genes were grouped into 1 of 8 categories on the basis of their primary physiologic function. Grouping revealed that pathways involving cellular energy production, signaling and communication, and cell structure were generally downregulated, whereas pathways involving cellular defense and stress responses were upregulated. Many previously unreported genes that may contribute to the pathophysiologic aspects of heart disease were identified. Evaluation of global expression patterns provides a molecular portrait of heart failure, yields insights into the pathophysiologic aspects of DCM, and identifies intriguing genes and pathways for further study.

Biologically relevant effects of mRNA amplification on gene expression profiles.

PubMed

van Haaften, Rachel I M; Schroen, Blanche; Janssen, Ben J A; van Erk, Arie; Debets, Jacques J M; Smeets, Hubert J M; Smits, Jos F M; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris T A

2006-04-11

Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other.Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways.

Biologically relevant effects of mRNA amplification on gene expression profiles

PubMed Central

van Haaften, Rachel IM; Schroen, Blanche; Janssen, Ben JA; van Erk, Arie; Debets, Jacques JM; Smeets, Hubert JM; Smits, Jos FM; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris TA

2006-01-01

Background Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Results Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other. Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. Conclusion This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways. PMID:16608515

DNA microarrays: a powerful genomic tool for biomedical and clinical research

PubMed Central

Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A.

2007-01-01

Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, reveal differences in genetic makeup, regulatory mechanisms and subtle variations are approaching the era of personalized medicine. To understand this powerful tool, its versatility and how it is dramatically changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to integrate multidisciplinary teams, to take advantage of this technology and its expanding applications that in a slide reveals our genetic inheritance and destiny. PMID:17660860

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology

USGS Publications Warehouse

Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Zawada, David G.; Andersen, Gary L.

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease.

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology.

PubMed

Kellogg, Christina A; Piceno, Yvette M; Tom, Lauren M; DeSantis, Todd Z; Zawada, David G; Andersen, Gary L

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease. Published by Elsevier B.V.

Validation of Biomarker Proteins Using Reverse Capture Protein Microarrays.

PubMed

Jozwik, Catherine; Eidelman, Ofer; Starr, Joshua; Pollard, Harvey B; Srivastava, Meera

2017-01-01

Genomics has revolutionized large-scale and high-throughput sequencing and has led to the discovery of thousands of new proteins. Protein chip technology is emerging as a miniaturized and highly parallel platform that is suited to rapid, simultaneous screening of large numbers of proteins and the analysis of various protein-binding activities, enzyme substrate relationships, and posttranslational modifications. Specifically, reverse capture protein microarrays provide the most appropriate platform for identifying low-abundance, disease-specific biomarker proteins in a sea of high-abundance proteins from biological fluids such as blood, serum, plasma, saliva, urine, and cerebrospinal fluid as well as tissues and cells obtained by biopsy. Samples from hundreds of patients can be spotted in serial dilutions on many replicate glass slides. Each slide can then be probed with one specific antibody to the biomarker of interest. That antibody's titer can then be determined quantitatively for each patient, allowing for the statistical assessment and validation of the diagnostic or prognostic utility of that particular antigen. As the technology matures and the availability of validated, platform-compatible antibodies increases, the platform will move further into the desirable realm of discovery science for detecting and quantitating low-abundance signaling proteins. In this chapter, we describe methods for the successful application of the reverse capture protein microarray platform for which we have made substantial contributions to the development and application of this method, particularly in the use of body fluids other than serum/plasma.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.

PubMed

Boskamp, Tobias; Lachmund, Delf; Oetjen, Janina; Cordero Hernandez, Yovany; Trede, Dennis; Maass, Peter; Casadonte, Rita; Kriegsmann, Jörg; Warth, Arne; Dienemann, Hendrik; Weichert, Wilko; Kriegsmann, Mark

2017-07-01

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

Novel green tissue-specific synthetic promoters and cis-regulatory elements in rice.

PubMed

Wang, Rui; Zhu, Menglin; Ye, Rongjian; Liu, Zuoxiong; Zhou, Fei; Chen, Hao; Lin, Yongjun

2015-12-11

As an important part of synthetic biology, synthetic promoter has gradually become a hotspot in current biology. The purposes of the present study were to synthesize green tissue-specific promoters and to discover green tissue-specific cis-elements. We first assembled several regulatory sequences related to tissue-specific expression in different combinations, aiming to obtain novel green tissue-specific synthetic promoters. GUS assays of the transgenic plants indicated 5 synthetic promoters showed green tissue-specific expression patterns and different expression efficiencies in various tissues. Subsequently, we scanned and counted the cis-elements in different tissue-specific promoters based on the plant cis-elements database PLACE and the rice cDNA microarray database CREP for green tissue-specific cis-element discovery, resulting in 10 potential cis-elements. The flanking sequence of one potential core element (GEAT) was predicted by bioinformatics. Then, the combination of GEAT and its flanking sequence was functionally identified with synthetic promoter. GUS assays of the transgenic plants proved its green tissue-specificity. Furthermore, the function of GEAT flanking sequence was analyzed in detail with site-directed mutagenesis. Our study provides an example for the synthesis of rice tissue-specific promoters and develops a feasible method for screening and functional identification of tissue-specific cis-elements with their flanking sequences at the genome-wide level in rice.

Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

PubMed

Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

2014-08-01

The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Hybrid feature selection algorithm using symmetrical uncertainty and a harmony search algorithm

NASA Astrophysics Data System (ADS)

Salameh Shreem, Salam; Abdullah, Salwani; Nazri, Mohd Zakree Ahmad

2016-04-01

Microarray technology can be used as an efficient diagnostic system to recognise diseases such as tumours or to discriminate between different types of cancers in normal tissues. This technology has received increasing attention from the bioinformatics community because of its potential in designing powerful decision-making tools for cancer diagnosis. However, the presence of thousands or tens of thousands of genes affects the predictive accuracy of this technology from the perspective of classification. Thus, a key issue in microarray data is identifying or selecting the smallest possible set of genes from the input data that can achieve good predictive accuracy for classification. In this work, we propose a two-stage selection algorithm for gene selection problems in microarray data-sets called the symmetrical uncertainty filter and harmony search algorithm wrapper (SU-HSA). Experimental results show that the SU-HSA is better than HSA in isolation for all data-sets in terms of the accuracy and achieves a lower number of genes on 6 out of 10 instances. Furthermore, the comparison with state-of-the-art methods shows that our proposed approach is able to obtain 5 (out of 10) new best results in terms of the number of selected genes and competitive results in terms of the classification accuracy.

Development of a DNA Microarray-Based Assay for the Detection of Sugar Beet Root Rot Pathogens.

PubMed

Liebe, Sebastian; Christ, Daniela S; Ehricht, Ralf; Varrelmann, Mark

2016-01-01

Sugar beet root rot diseases that occur during the cropping season or in storage are accompanied by high yield losses and a severe reduction of processing quality. The vast diversity of microorganism species involved in rot development requires molecular tools allowing simultaneous identification of many different targets. Therefore, a new microarray technology (ArrayTube) was applied in this study to improve diagnosis of sugar beet root rot diseases. Based on three marker genes (internal transcribed spacer, translation elongation factor 1 alpha, and 16S ribosomal DNA), 42 well-performing probes enabled the identification of prevalent field pathogens (e.g., Aphanomyces cochlioides), storage pathogens (e.g., Botrytis cinerea), and ubiquitous spoilage fungi (e.g., Penicillium expansum). All probes were proven for specificity with pure cultures from 73 microorganism species as well as for in planta detection of their target species using inoculated sugar beet tissue. Microarray-based identification of root rot pathogens in diseased field beets was successfully confirmed by classical detection methods. The high discriminatory potential was proven by Fusarium species differentiation based on a single nucleotide polymorphism. The results demonstrate that the ArrayTube constitute an innovative tool allowing a rapid and reliable detection of plant pathogens particularly when multiple microorganism species are present.

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

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

PubMed Central

2010-01-01

Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

Cardiac mesenchymal progenitors from postmortem cardiac tissues retained cellular characterization.

PubMed

Kami, D; Kitani, T; Nakata, M; Gojo, S

2014-05-01

Currently, cells for transplantation in regenerative medicine are derived from either autologous or allogeneic tissue. The former has the drawbacks that the quality of donor cells may depend on the condition of the patient, while the quantity of the cells may also be limited. To solve these problems, we investigated the potential of allogeneic cardiac mesenchymal progenitors (CMPs) derived from postmortem hearts, which may be immunologically privileged similar to bone marrow-derived mesenchymal progenitors. We examined whether viable CMPs could be isolated from C57/B6 murine cardiac tissues harvested at 24 hours postmortem. After 2- to 3-week propagation with a high dose of basic fibroblast growth factor, we performed cellular characteristics analyses, which included proliferation and differentiation property flow cytometry and microarray analyses. Postmortem CMPs had a longer lag phase after seeding than CMPs obtained from living tissues, but otherwise had similar characteristics in all the analyses. In addition, global gene expression analysis by microarray showed that cells derived from postmortem and living tissues had similar characteristics. These results indicate that allogeneic postmortem CMPs have potential for cell transplantation because they circumvent the issue of both the quality and quantity of donor cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Microarray analysis of subcutaneous adipose tissue from mature cows with divergent body weight gain after feed restriction and realimentation

USDA-ARS?s Scientific Manuscript database

Body weight response to periods of feed restriction and realimentation is critical and relevant to the agricultural industry. The purpose of this study was to evaluate differentially expressed genes identified in subcutaneous adipose tissue collected from cows divergent in body weight (BW) gain afte...

A metadata-aware application for remote scoring and exchange of tissue microarray images

PubMed Central

2013-01-01

Background The use of tissue microarrays (TMA) and advances in digital scanning microscopy has enabled the collection of thousands of tissue images. There is a need for software tools to annotate, query and share this data amongst researchers in different physical locations. Results We have developed an open source web-based application for remote scoring of TMA images, which exploits the value of Microsoft Silverlight Deep Zoom to provide a intuitive interface for zooming and panning around digital images. We use and extend existing XML-based standards to ensure that the data collected can be archived and that our system is interoperable with other standards-compliant systems. Conclusion The application has been used for multi-centre scoring of TMA slides composed of tissues from several Phase III breast cancer trials and ten different studies participating in the International Breast Cancer Association Consortium (BCAC). The system has enabled researchers to simultaneously score large collections of TMA and export the standardised data to integrate with pathological and clinical outcome data, thereby facilitating biomarker discovery. PMID:23635078

Prognostic value of matrix metalloproteinase 9 expression in patients with juvenile nasopharyngeal angiofibroma: tissue microarray analysis.

PubMed

Sun, Xicai; Guo, Limin; Wang, Jingjing; Wang, Huan; Liu, Zhuofu; Liu, Juan; Yu, Huapeng; Hu, Li; Li, Han; Wang, Dehui

2014-08-01

Although JNA is a benign neoplasm histopathologically, it has a propensity for locally destructive growth and remains a higher postoperative recurrence rate. The aim of this study was to analyze the expression and localization of MMP-9 in JNA using tissue microarray to elucidate its correlation with clinicopathological features and recurrence. The expression of MMP-9 was assessed by immunohistochemistry in a tissue microarray from 70 patients with JNA and 10 control subjects. Correlation between the levels of MMP-9 expression and clinicopathologic variables, as well as tumor recurrence, were analyzed. MMP-9 was detected in perivascular and extravascular less differentiated cells and stromal cells of patients with JNA but not in the matured vascular endothelial cells of these patients. The presence of MMP-9 expression in JNA was correlated with patient's age (p=0.001). Spearman correlation analysis suggested that high expression of MMP-9 in JNA had negative correlation with patient's age (r=-0.412, p<0.001). The recurrence rate in JNA patients with high MMP-9 expression was significantly higher than those with low MMP-9 expression (p=0.002). In multivariate and ROC curve analysis, MMP-9 was a good prognostic factor for tumor recurrence of JNA. Higher MMP-9 expression is a poor prognostic factor for patients with JNA who have been surgically treated. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Expression profile of circular RNAs in human gastric cancer tissues

PubMed Central

Huang, You-Sheng; Jie, Na; Zou, Ke-Jian; Weng, Yang

2017-01-01

Circular RNAs (circRNAs) represent a newly identified class of non-coding RNA molecules, which interfere with gene transcription by adsorbing microRNAs (miRNAs). CircRNAs serve important roles in disease development and have the potential to serve as a novel class of biomarkers for clinical diagnosis. However, the role of circRNAs in the occurrence and development of gastric cancer (GC) remains unclear. In the present study, the expression profiles of circRNAs were compared between GC and adjacent normal tissues using a circRNA microarray, following which quantitative polymerase chain reaction (qPCR) was used to confirm the results of the circRNA microarray. Compared with the adjacent, normal mucosal tissues, 16 circRNAs were upregulated and 84 circRNAs were downregulated in GC. A total of 10 circRNAs were selected for validation in three pairs of GC and adjacent noncancerous tissues. The qPCR results were consistent with the findings of the microarray-based expression analysis. Of the circRNAs studied, only circRNA-0026 (hsa_circ_0000026) exhibited significantly different expression in GC (2.8-fold, P=0.001). Furthermore, online Database for Annotation, Visualization and Integrated Discovery annotation was used to predict circRNA-targeted miRNA-gene interactions. The analysis revealed that circRNA-0026 may regulate RNA transcription, RNA metabolism, gene expression, gene silencing and other biological functions in GC. In conclusion, differential expression of circRNAs may be associated with GC tumorigenesis, and circRNA-0026 is a promising biomarker for GC diagnosis and targeted therapy. PMID:28737829

EST resources and establishment and validation of a 16k cDNA microarray from Atlantic cod (Gadus morhua).

PubMed

Edvardsen, Rolf B; Malde, Ketil; Mittelholzer, Christian; Taranger, Geir Lasse; Nilsen, Frank

2011-03-01

The Atlantic cod, Gadus morhua, is an important species both for traditional fishery and increasingly also in fish farming. The Atlantic cod is also under potential threat from various environmental changes such as pollution and climate change, but the biological impact of such changes are not well known, in particular when it comes to sublethal effects that can be difficult to assert. Modern molecular and genomic approaches have revolutionized biological research during the last decade, and offer new avenues to study biological functions and e.g. the impact of anthropogenic activities at different life-stages for a given organism. In order to develop genomic data and genomic tools for Atlantic cod we conducted a program were we constructed 20 cDNA libraries, and produced and analyzed 44006 expressed sequence tags (ESTs) from these. Several tissues are represented in the multiple cDNA libraries, that differ in either sexual maturation or immulogical stimulation. This approach allowed us to identify genes that are expressed in particular tissues, life-stages or in response to specific stimuli, and also gives us information about potential functions of the transcripts. The ESTs were used to construct a 16k cDNA microarray to further investigate the cod transcriptome. Microarray analyses were preformed on pylorus, pituitary gland, spleen and testis of sexually maturing male cod. The four different tissues displayed tissue specific transcriptomes demonstrating that the cDNA array is working as expected and will prove to be a powerful tool in further experiments. Copyright © 2010 Elsevier Inc. All rights reserved.

Microarray profiling of human white adipose tissue after exogenous leptin injection.

PubMed

Taleb, S; Van Haaften, R; Henegar, C; Hukshorn, C; Cancello, R; Pelloux, V; Hanczar, B; Viguerie, N; Langin, D; Evelo, C; Zucker, J; Clément, K; Saris, W H M

2006-03-01

Leptin is a secreted adipocyte hormone that plays a key role in the regulation of body weight homeostasis. The leptin effect on human white adipose tissue (WAT) is still debated. The aim of this study was to assess whether the administration of polyethylene glycol-leptin (PEG-OB) in a single supraphysiological dose has transcriptional effects on genes of WAT and to identify its target genes and functional pathways in WAT. Blood samples and WAT biopsies were obtained from 10 healthy nonobese men before treatment and 72 h after the PEG-OB injection, leading to an approximate 809-fold increase in circulating leptin. The WAT gene expression profile before and after the PEG-OB injection was compared using pangenomic microarrays. Functional gene annotations based on the gene ontology of the PEG-OB regulated genes were performed using both an 'in house' automated procedure and GenMAPP (Gene Microarray Pathway Profiler), designed for viewing and analyzing gene expression data in the context of biological pathways. Statistical analysis of microarray data revealed that PEG-OB had a major down-regulated effect on WAT gene expression, as we obtained 1,822 and 100 down- and up-regulated genes, respectively. Microarray data were validated using reverse transcription quantitative PCR. Functional gene annotations of PEG-OB regulated genes revealed that the functional class related to immunity and inflammation was among the most mobilized PEG-OB pathway in WAT. These genes are mainly expressed in the cell of the stroma vascular fraction in comparison with adipocytes. Our observations support the hypothesis that leptin could act on WAT, particularly on genes related to inflammation and immunity, which may suggest a novel leptin target pathway in human WAT.

Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis.

PubMed

Vukmirovic, Milica; Herazo-Maya, Jose D; Blackmon, John; Skodric-Trifunovic, Vesna; Jovanovic, Dragana; Pavlovic, Sonja; Stojsic, Jelena; Zeljkovic, Vesna; Yan, Xiting; Homer, Robert; Stefanovic, Branko; Kaminski, Naftali

2017-01-12

Idiopathic Pulmonary Fibrosis (IPF) is a lethal lung disease of unknown etiology. A major limitation in transcriptomic profiling of lung tissue in IPF has been a dependence on snap-frozen fresh tissues (FF). In this project we sought to determine whether genome scale transcript profiling using RNA Sequencing (RNA-Seq) could be applied to archived Formalin-Fixed Paraffin-Embedded (FFPE) IPF tissues. We isolated total RNA from 7 IPF and 5 control FFPE lung tissues and performed 50 base pair paired-end sequencing on Illumina 2000 HiSeq. TopHat2 was used to map sequencing reads to the human genome. On average ~62 million reads (53.4% of ~116 million reads) were mapped per sample. 4,131 genes were differentially expressed between IPF and controls (1,920 increased and 2,211 decreased (FDR < 0.05). We compared our results to differentially expressed genes calculated from a previously published dataset generated from FF tissues analyzed on Agilent microarrays (GSE47460). The overlap of differentially expressed genes was very high (760 increased and 1,413 decreased, FDR < 0.05). Only 92 differentially expressed genes changed in opposite directions. Pathway enrichment analysis performed using MetaCore confirmed numerous IPF relevant genes and pathways including extracellular remodeling, TGF-beta, and WNT. Gene network analysis of MMP7, a highly differentially expressed gene in both datasets, revealed the same canonical pathways and gene network candidates in RNA-Seq and microarray data. For validation by NanoString nCounter® we selected 35 genes that had a fold change of 2 in at least one dataset (10 discordant, 10 significantly differentially expressed in one dataset only and 15 concordant genes). High concordance of fold change and FDR was observed for each type of the samples (FF vs FFPE) with both microarrays (r = 0.92) and RNA-Seq (r = 0.90) and the number of discordant genes was reduced to four. Our results demonstrate that RNA sequencing of RNA obtained from archived FFPE lung tissues is feasible. The results obtained from FFPE tissue are highly comparable to FF tissues. The ability to perform RNA-Seq on archived FFPE IPF tissues should greatly enhance the availability of tissue biopsies for research in IPF.

Upregulation of long non-coding RNA M26317 correlates with tumor progression and poor prognosis in gastric cancer.

PubMed

Li, Li; Wang, Yuan-Yu; Mou, Xiao Zhou; Ye, Zai-Yuan; Zhao, Zhong-Sheng

2018-04-23

To investigate the expression and clinical significance of long non-coding RNA (lnc RNA) in gastric cancer, we applied microarray analysis to obtain expression profiles of protein coding genes and lncRNAs in tumor and paired adjacent non-tumor tissues. We found that 41 lncRNAs were upregulated and 31 lncRNAs were downregulated more than 2-fold in gastric cancer versus noncancerous tissues (ratio>2.0, P<.01). We established a co-expression network of the differentially expressed lncRNAs and targeted coding genes that included 17 lncRNAs and 16 coding genes. As the results of microarray analysis showed that lncRNA M26317 was upregulated in gastric cancer tissues we examined the expression level of M26317 in 103 gastric cancer tissues by RT-PCR and 436 gastric cancer tissues by in situ hybridization. Our data confirmed that M26317 was upregulated in gastric cancer tissues. Moreover, expression of M26317 correlated with patient age, size of tumor, Lauren's classification, depth of invasion, lymph node and distant metastasis, TNM stage and poor prognosis (P<.05), but was not associated with gender, location of tumor, and differentiation (P>.05). M26317 may have an important role in malignant transformation and metastasis of gastric cancer. Copyright © 2018. Published by Elsevier Inc.

Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray

PubMed Central

Carter, Mark G; Sharov, Alexei A; VanBuren, Vincent; Dudekula, Dawood B; Carmack, Condie E; Nelson, Charlie; Ko, Minoru SH

2005-01-01

The ability to quantitatively measure the expression of all genes in a given tissue or cell with a single assay is an exciting promise of gene-expression profiling technology. An in situ-synthesized 60-mer oligonucleotide microarray designed to detect transcripts from all mouse genes was validated, as well as a set of exogenous RNA controls derived from the yeast genome (made freely available without restriction), which allow quantitative estimation of absolute endogenous transcript abundance. PMID:15998450

Therapeutic potential of Dickkopf-1 in wild-type BRAF papillary thyroid cancer via regulation of β-catenin/E-cadherin signaling.

PubMed

Cho, Sun Wook; Kim, Young A; Sun, Hyun Jin; Ahn, Hwa Young; Lee, Eun Kyung; Yi, Ka Hee; Oh, Byung-Chul; Park, Do Joon; Cho, Bo Youn; Park, Young Joo

2014-09-01

Aberrant activation of the Wnt/β-catenin pathway is a common pathogenesis of various human cancers. We investigated the role of the Wnt inhibitor, Dkk-1, in papillary thyroid cancer (PTC). Immunohistochemical β-catenin staining was performed in tissue microarray containing 148 PTCs and five normal thyroid tissues. In vivo effects of Dkk-1 were explored using ectopic tumors with BHP10-3SC cells. In 27 PTC patients, 60% of patients showed β-catenin up-regulation and Dkk-1 down-regulation in tumor vs normal tissues. Tissue microarray analysis showed that 14 of 148 PTC samples exhibited cytoplasmic-dominant β-catenin expression compared to membranous-dominant expression in normal tissues. Aberrant β-catenin expression was significantly correlated with higher rates of the loss of membranous E-cadherin expression and poor disease-free survival than that in the normal membranous expression group over a median follow-up period of 14 years. Implantation of Dkk-1-overexpressing BHP10-3SC cells revealed delayed tumor growth, resulting from the rescue of membranous β-catenin and E-cadherin expressions. Furthermore, tissue microarray analysis demonstrated that BRAF(WT) patients had higher rates of aberrant expressions of β-catenin and E-cadherin than BRAF(V600E) patients. Indeed, the inhibitory effects of Dkk-1 on cell survival were more sensitive in BRAF(WT) (BHP10-3SC and TPC-1) than in BRAF(V600E) (SNU-790 and BCPAP) cells. Overexpression of BRAF(V600E) in normal thyroid epithelial (H tori) cells also reduced the effects of Dkk-1 on cell survival. A subset of PTC patients showed aberrant expression of β-catenin/E-cadherin signaling and poor disease-free survival. Dkk-1 might have a therapeutic role, particularly in BRAF(WT) patients.

Evaluating concentration estimation errors in ELISA microarray experiments

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

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

Cytokine-related genes and oxidation-related genes detected in preeclamptic placentas.

PubMed

Lee, Gui Se Ra; Joe, Yoon Seong; Kim, Sa Jin; Shin, Jong Chul

2010-10-01

To investigate cytokine- and oxidation-related genes for preeclampsia using DNA microarray analysis. Placentas were collected from 13 normal pregnancies and 13 patients with preeclampsia. Gene expression was studied using DNA microarray. Among significantly expressed genes, we focused on genes associated with cytokines and oxidation, and the results were confirmed using quantitative real time-polymerase chain reaction (QRT-PCR). 415 genes out of 30,940 genes were altered by > or =2-fold in the microarray analysis. 121 up-regulated genes and 294 down-regulated genes were found to be in preeclamptic placenta. Six cytokine-related genes and 5 oxidation-related genes were found from among the 121 up-regulated genes. The cytokine-related genes studied included oncostatin M (OSM), fms-related tyrosine kinase (FLT1) and vascular endothelial growth factor A (VEGFA), and the oxidation-related genes studied included spermine oxidase (SMOX), l cytochrome P450, family 26, subfamily A, polypeptide 1 (CYP26A1), acetate dehydrogenase A (LDHA). These six genes were also significantly higher in placentas from patients with preeclampsia than in those from women with normal pregnancies. The placental tissue of patients with preeclampsia showed significantly higher mRNA expression of these six genes than the normal group, using QRT-PCR. DNA microarray analysis is one of the great methods for simultaneously detecting the functionally associated genes of preeclampsia. The cytokine-related genes such as OSM, FLT1 and VEGFA, and the oxidation-related genes such as LDHA, CYP26A1 and SMOX might prove to be the starting point in the elucidation of the pathogenesis of preeclampsia.

Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays

PubMed Central

Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

2017-01-01

Background: Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples. Methods: We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. Results: We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). Conclusions: These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains. PMID:27959886

Multiview boosting digital pathology analysis of prostate cancer.

PubMed

Kwak, Jin Tae; Hewitt, Stephen M

2017-04-01

Various digital pathology tools have been developed to aid in analyzing tissues and improving cancer pathology. The multi-resolution nature of cancer pathology, however, has not been fully analyzed and utilized. Here, we develop an automated, cooperative, and multi-resolution method for improving prostate cancer diagnosis. Digitized tissue specimen images are obtained from 5 tissue microarrays (TMAs). The TMAs include 70 benign and 135 cancer samples (TMA1), 74 benign and 89 cancer samples (TMA2), 70 benign and 115 cancer samples (TMA3), 79 benign and 82 cancer samples (TMA4), and 72 benign and 86 cancer samples (TMA5). The tissue specimen images are segmented using intensity- and texture-based features. Using the segmentation results, a number of morphological features from lumens and epithelial nuclei are computed to characterize tissues at different resolutions. Applying a multiview boosting algorithm, tissue characteristics, obtained from differing resolutions, are cooperatively combined to achieve accurate cancer detection. In segmenting prostate tissues, the multiview boosting method achieved≥ 0.97 AUC using TMA1. For detecting cancers, the multiview boosting method achieved an AUC of 0.98 (95% CI: 0.97-0.99) as trained on TMA2 and tested on TMA3, TMA4, and TMA5. The proposed method was superior to single-view approaches, utilizing features from a single resolution or merging features from all the resolutions. Moreover, the performance of the proposed method was insensitive to the choice of the training dataset. Trained on TMA3, TMA4, and TMA5, the proposed method obtained an AUC of 0.97 (95% CI: 0.96-0.98), 0.98 (95% CI: 0.96-0.99), and 0.97 (95% CI: 0.96-0.98), respectively. The multiview boosting method is capable of integrating information from multiple resolutions in an effective and efficient fashion and identifying cancers with high accuracy. The multiview boosting method holds a great potential for improving digital pathology tools and research. Copyright © 2017 Elsevier B.V. All rights reserved.

The Choice of the Filtering Method in Microarrays Affects the Inference Regarding Dosage Compensation of the Active X-Chromosome

PubMed Central

Zeller, Tanja; Wild, Philipp S.; Truong, Vinh; Trégouët, David-Alexandre; Munzel, Thomas; Ziegler, Andreas; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2011-01-01

Background The hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays. Methodology/Principal Findings To investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels than autosomes. We compared the ratio of expression levels of X-linked to autosomal transcripts (X∶AA) using two different filtering methods: 1. gene expressions were filtered out using a detection threshold irrespective of gene chromosomal location (the standard method in microarrays); 2. equal proportions of genes were filtered out separately on the X and on autosomes. For a wide range of filtering proportions, the X∶AA ratio estimated with the first method was not significantly different from 1, the value expected if dosage compensation was achieved, whereas it was significantly lower than 1 with the second method, leading to the rejection of the hypothesis of dosage compensation. We further showed in simulated data that the choice of the most appropriate method was dependent on biological assumptions regarding the proportion of actively expressed genes on the X chromosome comparative to the autosomes and the extent of dosage compensation. Conclusion/Significance This study shows that the method used for filtering out lowly expressed genes in microarrays may have a major impact according to the hypothesis investigated. The hypothesis of dosage compensation of X-linked genes cannot be firmly accepted or rejected using microarray-based data. PMID:21912656

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

PubMed

Zhang, Wensheng; Edwards, Andrea; Fan, Wei; Zhu, Dongxiao; Zhang, Kun

2010-06-22

Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering. svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.

Database construction for PromoterCAD: synthetic promoter design for mammals and plants.

PubMed

Nishikata, Koro; Cox, Robert Sidney; Shimoyama, Sayoko; Yoshida, Yuko; Matsui, Minami; Makita, Yuko; Toyoda, Tetsuro

2014-03-21

Synthetic promoters can control a gene's timing, location, and expression level. The PromoterCAD web server ( http://promotercad.org ) allows the design of synthetic promoters to control plant gene expression, by novel arrangement of cis-regulatory elements. Recently, we have expanded PromoterCAD's scope with additional plant and animal data: (1) PLACE (Plant Cis-acting Regulatory DNA Elements), including various sized sequence motifs; (2) PEDB (Mammalian Promoter/Enhancer Database), including gene expression data for mammalian tissues. The plant PromoterCAD data now contains 22 000 Arabidopsis thaliana genes, 2 200 000 microarray measurements in 20 growth conditions and 79 tissue organs and developmental stages, while the new mammalian PromoterCAD data contains 679 Mus musculus genes and 65 000 microarray measurements in 96 tissue organs and cell types ( http://promotercad.org/mammal/ ). This work presents step-by-step instructions for adding both regulatory motif and gene expression data to PromoterCAD, to illustrate how users can expand PromoterCAD functionality for their own applications and organisms.

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Diffuse myogenin expression by immunohistochemistry is an independent marker of poor survival in pediatric rhabdomyosarcoma: a tissue microarray study of 71 primary tumors including correlation with molecular phenotype.

PubMed

Heerema-McKenney, Amy; Wijnaendts, Liliane C D; Pulliam, Joseph F; Lopez-Terrada, Dolores; McKenney, Jesse K; Zhu, Shirley; Montgomery, Kelli; Mitchell, Janet; Marinelli, Robert J; Hart, Augustinus A M; van de Rijn, Matt; Linn, Sabine C

2008-10-01

The pathologic classification of rhabdomyosarcoma (RMS) into embryonal or alveolar subtype is an important prognostic factor guiding the therapeutic protocol chosen for an individual patient. Unfortunately, this classification is not always straightforward, and the diagnostic criteria are controversial in a subset of cases. Ancillary studies are used to aid in the classification, but their potential use as independent prognostic factors is rarely studied. The aim of this study is to identify immunohistochemical markers of potential prognostic significance in pediatric RMS and to correlate their expression with PAX-3/FKHR and PAX-7/FKHR fusion status. A single tissue microarray containing 71 paraffin-embedded pediatric RMSs was immunostained with antibodies against p53, bcl-2, Ki-67, CD44, myogenin, and MyoD1. The tissue microarray and whole paraffin blocks were studied for PAX-3/FKHR and PAX-7/FKHR gene fusions by fluorescence in situ hybridization and reverse transcription-polymerase chain reaction. Clinical follow-up data were available for each patient. Immunohistochemical staining results and translocation status were correlated with recurrence-free interval (RFI) and overall survival (OS) using the Kaplan-Meier method, the log-rank test, and Cox proportional hazard regression. The minimum clinical follow-up interval was 24 months (median follow-up=57 mo). On univariable analysis, immunohistochemical expression of myogenin, bcl-2, and identification of a gene fusion were associated with decreased 5-year RFI and 10-year OS (myogenin RFI P=0.0028, OS P=0.0021; bcl-2 RFI P=0.037, OS P=0.032; gene fusion RFI P=0.0001, OS P=0.0058). After adjustment for Intergroup Rhabdomyosarcoma Study-TNM stage, tumor site, age, tumor histology, and translocation status by multivariable analysis, only myogenin retained an independent association with RFI (P=0.034) and OS (P=0.0069). In this retrospective analysis, diffuse immunohistochemical reactivity for myogenin in RMS correlates with decreased RFI and OS, independent of histologic subtype, translocation status, tumor site, or stage.

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

PubMed Central

2011-01-01

Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A-bomb radiation may affect the increased amount of CNA as a hallmark of GIN and, subsequently, be associated with a higher histologic grade in breast cancer found in A-bomb survivors. PMID:22152285

Prostate Cancer Pathology Resource Network

DTIC Science & Technology

2012-07-01

microarrays (TMAs), serum, plasma , buffy coat, prostatic fluid, and derived specimens (DNA and RNA); these specimens are linked to clinical and...research community. The specimens in the PCBN include tissues from prostatectomies, serum, plasma , buffy coat, prostatic fluid, derived specimens such...prostatectomy, seminal vesicles), body fluids (serum, plasma , buffy coat, prostatic fluid; most can be matched to tumor and benign tissue), and

Identification of methylated genes in salivary gland adenoid cystic carcinoma xenografts using global demethylation and methylation microarray screening

PubMed Central

LING, SHIZHANG; RETTIG, ELENI M.; TAN, MARIETTA; CHANG, XIAOFEI; WANG, ZHIMING; BRAIT, MARIANA; BISHOP, JUSTIN A.; FERTIG, ELANA J.; CONSIDINE, MICHAEL; WICK, MICHAEL J.; HA, PATRICK K.

2016-01-01

Salivary gland adenoid cystic carcinoma (ACC) is a rare head and neck malignancy without molecular biomarkers that can be used to predict the chemotherapeutic response or prognosis of ACC. The regulation of gene expression of oncogenes and tumor suppressor genes (TSGs) through DNA promoter methylation may play a role in the carcinogenesis of ACC. To identify differentially methylated genes in ACC, a global demethylating agent, 5-aza-2′-deoxycytidine (5-AZA) was utilized to unmask putative TSG silencing in ACC xenograft models in mice. Fresh xenografts were passaged, implanted in triplicate in mice that were treated with 5-AZA daily for 28 days. These xenografts were then evaluated for genome-wide DNA methylation patterns using the Illumina Infinium HumanMethylation27 BeadChip array. Validation of the 32 candidate genes was performed by bisulfite sequencing (BS-seq) in a separate cohort of 6 ACC primary tumors and 6 normal control salivary gland tissues. Hypermethylation was identified in the HCN2 gene promoter in all 6 control tissues, but hypomethylation was found in all 6 ACC tumor tissues. Quantitative validation of HCN2 promoter methylation level in the region detected by BS-seq was performed in a larger cohort of primary tumors (n=32) confirming significant HCN2 hypomethylation in ACCs compared with normal samples (n=10; P=0.04). HCN2 immunohistochemical staining was performed on an ACC tissue microarray. HCN2 staining intensity and H-score, but not percentage of the positively stained cells, were significantly stronger in normal tissues than those of ACC tissues. With our novel screening and sequencing methods, we identified several gene candidates that were methylated. The most significant of these genes, HCN2, was actually hypomethylated in tumors. However, promoter methylation status does not appear to be a major determinant of HCN2 expression in normal and ACC tissues. HCN2 hypomethylation is a biomarker of ACC and may play an important role in the carcinogenesis of ACC. PMID:27212063

Testing an aflatoxin B1 gene signature in rat archival tissues.

PubMed

Merrick, B Alex; Auerbach, Scott S; Stockton, Patricia S; Foley, Julie F; Malarkey, David E; Sills, Robert C; Irwin, Richard D; Tice, Raymond R

2012-05-21

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced tumors. We conclude that an evaluation of gene signatures in archival tissues can be an important toxicological tool for evaluating critical molecular events associated with chemical exposures.

HPASubC: A suite of tools for user subclassification of human protein atlas tissue images

PubMed Central

Cornish, Toby C.; Chakravarti, Aravinda; Kapoor, Ashish; Halushka, Marc K.

2015-01-01

Background: The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented. Materials and Methods: To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest. Results: We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs. Conclusions: The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology. PMID:26167380

Population effect model identifies gene expression predictors of survival outcomes in lung adenocarcinoma for both Caucasian and Asian patients

PubMed Central

Cai, Guoshuai; Xiao, Feifei; Cheng, Chao; Li, Yafang; Amos, Christopher I.; Whitfield, Michael L.

2017-01-01

Background We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied. PMID:28426704

A molecular analysis by gene expression profiling reveals Bik/NBK overexpression in sporadic breast tumor samples of Mexican females

PubMed Central

García, Normand; Salamanca, Fabio; Astudillo-de la Vega, Horacio; Curiel-Quesada, Everardo; Alvarado, Isabel; Peñaloza, Rosenda; Arenas, Diego

2005-01-01

Background Breast cancer is one of the most frequent causes of death in Mexican women over 35 years of age. At molecular level, changes in many genetic networks have been reported as associated with this neoplasia. To analyze these changes, we determined gene expression profiles of tumors from Mexican women with breast cancer at different stages and compared these with those of normal breast tissue samples. Methods 32P-radiolabeled cDNA was synthesized by reverse transcription of mRNA from fresh sporadic breast tumor biopsies, as well as normal breast tissue. cDNA probes were hybridized to microarrays and expression levels registered using a phosphorimager. Expression levels of some genes were validated by real time RT-PCR and immunohistochemical assays. Results We identified two subgroups of tumors according to their expression profiles, probably related with cancer progression. Ten genes, unexpressed in normal tissue, were turned on in some tumors. We found consistent high expression of Bik gene in 14/15 tumors with predominant cytoplasmic distribution. Conclusion Recently, the product of the Bik gene has been associated with tumoral reversion in different neoplasic cell lines, and was proposed as therapy to induce apoptosis in cancers, including breast tumors. Even though a relationship among genes, for example those from a particular pathway, can be observed through microarrays, this relationship might not be sufficient to assign a definitive role to Bik in development and progression of the neoplasia. The findings herein reported deserve further investigation. PMID:16060964

Association of tumor-infiltrating T-cell density with molecular subtype, racial ancestry and clinical outcomes in prostate cancer.

PubMed

Kaur, Harsimar B; Guedes, Liana B; Lu, Jiayun; Maldonado, Laneisha; Reitz, Logan; Barber, John R; De Marzo, Angelo M; Tosoian, Jeffrey J; Tomlins, Scott A; Schaeffer, Edward M; Joshu, Corinne E; Sfanos, Karen S; Lotan, Tamara L

2018-05-30

The inflammatory microenvironment plays an important role in the pathogenesis and progression of tumors and may be associated with somatic genomic alterations. We examined the association of tumor-infiltrating T-cell density with clinical-pathologic variables, tumor molecular subtype, and oncologic outcomes in surgically treated primary prostate cancer occurring in patients of European-American or African-American ancestry. We evaluated 312 primary prostate tumors, enriched for patients with African-American ancestry and high grade disease. Tissue microarrays were immunostained for CD3, CD8, and FOXP3 and were previously immunostained for ERG and PTEN using genetically validated protocols. Image analysis for quantification of T-cell density in tissue microarray tumor spots was performed. Automated quantification of T-cell densities in tumor-containing regions of tissue microarray spots and standard histologic sections were correlated (r = 0.73, p < 0.00001) and there was good agreement between visual and automated T-cell density counts on tissue microarray spots (r = 0.93, p < 0.00001). There was a significant correlation between CD3+, CD8+, and FOXP3+ T-cell densities (p < 0.00001), but these were not associated with most clinical or pathologic variables. Increased T-cell density was significantly associated with ERG positivity (median 309 vs. 188 CD3+ T cells/mm 2 ; p = 0.0004) and also with PTEN loss (median 317 vs. 192 CD3+ T cells/mm 2 ; p = 0.001) in the combined cohort of matched European-American and African-American ancestry patients. The same association or a similar trend was present in patients of both ancestries when analyzed separately. When the African-American patients from the matched race set were combined with a separate high grade set of African-American cases, there was a weak association of increased FOXP3+ T-cell densities with increased risk of metastasis in multivariable analysis. Though high T-cell density is associated with specific molecular subclasses of prostate cancer, we did not find an association of T-cell density with racial ancestry.

Rapid Characterization of Candidate Biomarkers for Pancreatic Cancer Using Cell Microarrays (CMAs)

PubMed Central

Kim, Min-Sik; Kuppireddy, Sarada V.; Sakamuri, Sruthi; Singal, Mukul; Getnet, Derese; Harsha, H. C.; Goel, Renu; Balakrishnan, Lavanya; Jacob, Harrys K. C.; Kashyap, Manoj K.; Tankala, Shantal G.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Jaffee, Elizabeth; Goggins, Michael G.; Velculescu, Victor E.; Hruban, Ralph H.; Pandey, Akhilesh

2013-01-01

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research. PMID:22985314

Image Analysis Algorithms for Immunohistochemical Assessment of Cell Death Events and Fibrosis in Tissue Sections

PubMed Central

Krajewska, Maryla; Smith, Layton H.; Rong, Juan; Huang, Xianshu; Hyer, Marc L.; Zeps, Nikolajs; Iacopetta, Barry; Linke, Steven P.; Olson, Allen H.; Reed, John C.; Krajewski, Stan

2009-01-01

Cell death is of broad physiological and pathological importance, making quantification of biochemical events associated with cell demise a high priority for experimental pathology. Fibrosis is a common consequence of tissue injury involving necrotic cell death. Using tissue specimens from experimental mouse models of traumatic brain injury, cardiac fibrosis, and cancer, as well as human tumor specimens assembled in tissue microarray (TMA) format, we undertook computer-assisted quantification of specific immunohistochemical and histological parameters that characterize processes associated with cell death. In this study, we demonstrated the utility of image analysis algorithms for color deconvolution, colocalization, and nuclear morphometry to characterize cell death events in tissue specimens: (a) subjected to immunostaining for detecting cleaved caspase-3, cleaved poly(ADP-ribose)-polymerase, cleaved lamin-A, phosphorylated histone H2AX, and Bcl-2; (b) analyzed by terminal deoxyribonucleotidyl transferase–mediated dUTP nick end labeling assay to detect DNA fragmentation; and (c) evaluated with Masson's trichrome staining. We developed novel algorithm-based scoring methods and validated them using TMAs as a high-throughput format. The proposed computer-assisted scoring methods for digital images by brightfield microscopy permit linear quantification of immunohistochemical and histochemical stainings. Examples are provided of digital image analysis performed in automated or semiautomated fashion for successful quantification of molecular events associated with cell death in tissue sections. (J Histochem Cytochem 57:649–663, 2009) PMID:19289554

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Unconventional microarray design reveals the response to obesity is largely tissue specific: analysis of common and divergent responses to diet-induced obesity in insulin-sensitive tissues.

PubMed

Lee, Robyn K; Hittel, Dustin S; Nyamandi, Vongai Z; Kang, Li; Soh, Jung; Sensen, Christoph W; Shearer, Jane

2012-04-01

Obesity is a chronic condition involving the excessive accumulation of adipose tissue that adversely affects all systems in the body. The aim of the present study was to employ an unbiased, genome-wide assessment of transcript abundance in order to identify common gene expression pathways within insulin-sensitive tissues in response to dietary-induced diabetes. Following 20 weeks of chow or high-fat feeding (60% kcal), age-matched mice underwent a euglycemic-hyperinsulinemic clamp to assess insulin sensitivity. High-fat-fed animals were obese and highly insulin resistant, disposing of ∼75% less glucose compared with their chow-fed counterparts. Tissues were collected, and gene expression was examined by microarray in 4 tissues known to exhibit obesity-related metabolic disturbances: white adipose tissue, skeletal muscle, liver, and heart. A total of 463 genes were differentially expressed between diets. Analysis of individual tissues showed skeletal muscle to exhibit the largest number of differentially expressed genes (191) in response to high-fat feeding, followed by adipose tissue (169), liver (115), and heart (65). Analyses revealed that the response of individual genes to obesity is distinct and largely tissue specific, with less than 10% of transcripts being shared among tissues. Although transcripts are largely tissue specific, a systems approach shows numerous commonly activated pathways, including those involved in signal transduction, inflammation, oxidative stress, substrate transport, and metabolism. This suggests a coordinated attempt by tissues to limit metabolic perturbations occurring in early-stage obesity. Many identified genes were associated with a variety of disorders, thereby serving as potential links between obesity and its related health risks.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Expression analysis of URI/RMP gene in endometrioid adenocarcinoma by tissue microarray immunohistochemistry.

PubMed

Gu, Junxia; Liang, Yuting; Qiao, Longwei; Li, Xiaoyun; Li, Xingang; Lu, Yaojuan; Zheng, Qiping

2013-01-01

Multiple studies have recently demonstrated the oncogenic property of URI (or RMP, a member of the prefoldin family of molecular chaperones) during progression of hepatocellular carcinoma, ovarian cancer, and possibly prostate cancer. Most recently, we have shown that URI/RMP is up-regulated in cervical cancer, another reproductive system tumor beside ovarian and prostate cancers. To investigate if URI/RMP also plays a role in other reproductive system tumors, especially in endometrioid adenocarcinoma, we analyzed URI/RMP expression in a TMA (tissue microarray) containing tissues from 30 cases of endometrioid adenocarcinoma (which covers tumor tissues from Grade I through Grade III) and adjacent endometrium by immunohistochemistry (IHC) and densitometry analysis using image-pro plus 6.0 software. Our results showed that the mean density of URI/RMP expression in cancerous tissue is slightly higher than that of the adjacent endometrial tissue, though not statistically significant (p>0.05). There is no significant difference either between the mean density of Grade III cancerous tissue and that of Grade I and II cancers. Notably, we detected significantly higher signal intensity in cancerous tissue of all 7 Grade III cases than that of their adjacent endometrial tissue (p<0.05), suggesting a correlation of URI/RMP expression with the differentiation and pathological classification of endometrioid adenocarcinoma. Together, our results demonstrate the heterogeneous expression of URI/RMP in endometrioid adenocarcinoma. The higher level of URI/RMP expression in high-grade endometrioid adenocarcinomas compared to tissues of adjacent endometrium or gland suggests a diagnostic and possibly, a prognostic value of URI/RMP in endometrioid adenocarcinoma.

Expression analysis of URI/RMP gene in endometrioid adenocarcinoma by tissue microarray immunohistochemistry

PubMed Central

Gu, Junxia; Liang, Yuting; Qiao, Longwei; Li, Xiaoyun; Li, Xingang; Lu, Yaojuan; Zheng, Qiping

2013-01-01

Multiple studies have recently demonstrated the oncogenic property of URI (or RMP, a member of the prefoldin family of molecular chaperones) during progression of hepatocellular carcinoma, ovarian cancer, and possibly prostate cancer. Most recently, we have shown that URI/RMP is up-regulated in cervical cancer, another reproductive system tumor beside ovarian and prostate cancers. To investigate if URI/RMP also plays a role in other reproductive system tumors, especially in endometrioid adenocarcinoma, we analyzed URI/RMP expression in a TMA (tissue microarray) containing tissues from 30 cases of endometrioid adenocarcinoma (which covers tumor tissues from Grade I through Grade III) and adjacent endometrium by immunohistochemistry (IHC) and densitometry analysis using image-pro plus 6.0 software. Our results showed that the mean density of URI/RMP expression in cancerous tissue is slightly higher than that of the adjacent endometrial tissue, though not statistically significant (p>0.05). There is no significant difference either between the mean density of Grade III cancerous tissue and that of Grade I and II cancers. Notably, we detected significantly higher signal intensity in cancerous tissue of all 7 Grade III cases than that of their adjacent endometrial tissue (p<0.05), suggesting a correlation of URI/RMP expression with the differentiation and pathological classification of endometrioid adenocarcinoma. Together, our results demonstrate the heterogeneous expression of URI/RMP in endometrioid adenocarcinoma. The higher level of URI/RMP expression in high-grade endometrioid adenocarcinomas compared to tissues of adjacent endometrium or gland suggests a diagnostic and possibly, a prognostic value of URI/RMP in endometrioid adenocarcinoma. PMID:24228101

Microarray technology for major chemical contaminants analysis in food: current status and prospects.

PubMed

Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

2012-01-01

Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

PubMed Central

Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

2012-01-01

Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

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

Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

PubMed Central

Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

2009-01-01

Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles. PMID:19123946

Src kinases in chondrosarcoma chemoresistance and migration: dasatinib sensitises to doxorubicin in TP53 mutant cells

PubMed Central

van Oosterwijk, J G; van Ruler, M A J H; Briaire-de Bruijn, I H; Herpers, B; Gelderblom, H; van de Water, B; Bovée, J V M G

2013-01-01

Background: Chondrosarcomas are malignant cartilage-forming tumours of bone. Because of their resistance to conventional chemotherapy and radiotherapy, currently no treatment strategies exist for unresectable and metastatic chondrosarcoma. Previously, PI3K/AKT/GSK3β and Src kinase pathways were shown to be activated in chondrosarcoma cell lines. Our aim was to investigate the role of these kinases in chemoresistance and migration in chondrosarcoma in relation to TP53 mutation status. Methods: We used five conventional and three dedifferentiated chondrosarcoma cell lines and investigated the effect of PI3K/AKT/GSK3β pathway inhibition (enzastaurin) and Src pathway inhibition (dasatinib) in chemoresistance using WST assay and live cell imaging with AnnexinV staining. Immunohistochemistry on tissue microarrays (TMAs) containing 157 cartilaginous tumours was performed for Src family members. Migration assays were performed with the RTCA xCelligence System. Results: Src inhibition was found to overcome chemoresistance, to induce apoptosis and to inhibit migration. Cell lines with TP53 mutations responded better to combination therapy than wild-type cell lines (P=0.002). Tissue microarray immunohistochemistry confirmed active Src (pSrc) signalling, with Fyn being most abundantly expressed (76.1%). Conclusion: These results strongly indicate Src family kinases, in particular Fyn, as a potential target for the treatment of inoperable and metastatic chondrosarcomas, and to sensitise for doxorubicin especially in the presence of TP53 mutations. PMID:23922104

Generation of Viable Cell and Biomaterial Patterns by Laser Transfer

NASA Astrophysics Data System (ADS)

Ringeisen, Bradley

2001-03-01

In order to fabricate and interface biological systems for next generation applications such as biosensors, protein recognition microarrays, and engineered tissues, it is imperative to have a method of accurately and rapidly depositing different active biomaterials in patterns or layered structures. Ideally, the biomaterial structures would also be compatible with many different substrates including technologically relevant platforms such as electronic circuits or various detection devices. We have developed a novel laser-based technique, termed matrix assisted pulsed laser evaporation direct write (MAPLE DW), that is able to direct write patterns and three-dimensional structures of numerous biologically active species ranging from proteins and antibodies to living cells. Specifically, we have shown that MAPLE DW is capable of forming mesoscopic patterns of living prokaryotic cells (E. coli bacteria), living mammalian cells (Chinese hamster ovaries), active proteins (biotinylated bovine serum albumin, horse radish peroxidase), and antibodies specific to a variety of classes of cancer related proteins including intracellular and extracellular matrix proteins, signaling proteins, cell cycle proteins, growth factors, and growth factor receptors. In addition, patterns of viable cells and active biomolecules were deposited on different substrates including metals, semiconductors, nutrient agar, and functionalized glass slides. We will present an explanation of the laser-based transfer mechanism as well as results from our recent efforts to fabricate protein recognition microarrays and tissue-based microfluidic networks.

Feasibility of using tissue microarray cores of paraffin-embedded breast cancer tissue for measurement of gene expression: a proof-of-concept study.

PubMed

Drury, Suzanne; Salter, Janine; Baehner, Frederick L; Shak, Steven; Dowsett, Mitch

2010-06-01

To determine whether 0.6 mm cores of formalin-fixed paraffin-embedded (FFPE) tissue, as commonly used to construct immunohistochemical tissue microarrays, may be a valid alternative to tissue sections as source material for quantitative real-time PCR-based transcriptional profiling of breast cancer. Four matched 0.6 mm cores of invasive breast tumour and two 10 microm whole sections were taken from eight FFPE blocks. RNA was extracted and reverse transcribed, and TaqMan assays were performed on the 21 genes of the Oncotype DX Breast Cancer assay. Expression of the 16 recurrence-related genes was normalised to the set of five reference genes, and the recurrence score (RS) was calculated. RNA yield was lower from 0.6 mm cores than from 10 microm whole sections, but was still more than sufficient to perform the assay. RS and single gene data from cores were highly comparable with those from whole sections (RS p=0.005). Greater variability was seen between cores than between sections. FFPE sections are preferable to 0.6 mm cores for RNA profiling in order to maximise RNA yield and to allow for standard histopathological assessment. However, 0.6 mm cores are sufficient and would be appropriate to use for large cohort studies.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

TMA Navigator: network inference, patient stratification and survival analysis with tissue microarray data

PubMed Central

Lubbock, Alexander L. R.; Katz, Elad; Harrison, David J.; Overton, Ian M.

2013-01-01

Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan–Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management. PMID:23761446

GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor.

PubMed

Davis, Sean; Meltzer, Paul S

2007-07-15

Microarray technology has become a standard molecular biology tool. Experimental data have been generated on a huge number of organisms, tissue types, treatment conditions and disease states. The Gene Expression Omnibus (Barrett et al., 2005), developed by the National Center for Bioinformatics (NCBI) at the National Institutes of Health is a repository of nearly 140,000 gene expression experiments. The BioConductor project (Gentleman et al., 2004) is an open-source and open-development software project built in the R statistical programming environment (R Development core Team, 2005) for the analysis and comprehension of genomic data. The tools contained in the BioConductor project represent many state-of-the-art methods for the analysis of microarray and genomics data. We have developed a software tool that allows access to the wealth of information within GEO directly from BioConductor, eliminating many the formatting and parsing problems that have made such analyses labor-intensive in the past. The software, called GEOquery, effectively establishes a bridge between GEO and BioConductor. Easy access to GEO data from BioConductor will likely lead to new analyses of GEO data using novel and rigorous statistical and bioinformatic tools. Facilitating analyses and meta-analyses of microarray data will increase the efficiency with which biologically important conclusions can be drawn from published genomic data. GEOquery is available as part of the BioConductor project.

SYMBIOmatics: synergies in Medical Informatics and Bioinformatics--exploring current scientific literature for emerging topics.

PubMed

Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan

2007-03-08

The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.

SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics

PubMed Central

Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan

2007-01-01

Background The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to ). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science. PMID:17430562

Status of epigenetic chromatin modification enzymes and esophageal squamous cell carcinoma risk in northeast Indian population.

PubMed

Singh, Virendra; Singh, Laishram C; Singh, Avninder P; Sharma, Jagannath; Borthakur, Bibhuti B; Debnath, Arundhati; Rai, Avdhesh K; Phukan, Rup K; Mahanta, Jagadish; Kataki, Amal C; Kapur, Sujala; Saxena, Sunita

2015-01-01

Esophageal cancer incidence is reported in high frequency in northeast India. The etiology is different from other population at India due to wide variations in dietary habits or nutritional factors, tobacco/betel quid chewing and alcohol habits. Since DNA methylation, histone modification and miRNA-mediated epigenetic processes alter the gene expression, the involvement of these processes might be useful to find out epigenetic markers of esophageal cancer risk in northeast Indian population. The present investigation was aimed to carryout differential expression profiling of chromatin modification enzymes in tumor and normal tissue collected from esophageal squamous cell carcinoma (ESCC) patients. Differential mRNA expression profiling and their validation was done by quantitative real time PCR and tissue microarray respectively. Univariate and multiple logistic regression analysis were used to analyze the epidemiological data. mRNA expression data was analyzed by Student t-test. Fisher exact test was used for tissue microarray data analysis. Higher expression of enzymes regulating methylation (DOT1L and PRMT1) and acetylation (KAT7, KAT8, KAT2A and KAT6A) of histone was found associated with ESCC risk. Tissue microarray done in independent cohort of 75 patients revealed higher nuclear protein expression of KAT8 and PRMT1 in tumor similar to mRNA expression. Expression status of PRMT1 and KAT8 was found declined as we move from low grade to high grade tumor. Betel nut chewing, alcohol drinking and dried fish intake were significantly associated with increased risk of esophageal cancer among the study subject. Study suggests the association of PRMT1 and KAT8 with esophageal cancer risk and its involvement in the transition process of low to high grade tumor formation. The study exposes the differential status of chromatin modification enzymes between tumor and normal tissue and points out that relaxed state of chromatin facilitates more transcriptionally active genome in esophageal carcinogenesis.

A Modified Protocol for High-Quality RNA Extraction from Oleoresin-Producing Adult Pines.

PubMed

de Lima, Júlio César; Füller, Thanise Nogueira; de Costa, Fernanda; Rodrigues-Corrêa, Kelly C S; Fett-Neto, Arthur G

2016-01-01

RNA extraction resulting in good yields and quality is a fundamental step for the analyses of transcriptomes through high-throughput sequencing technologies, microarray, and also northern blots, RT-PCR, and RTqPCR. Even though many specific protocols designed for plants with high content of secondary metabolites have been developed, these are often expensive, time consuming, and not suitable for a wide range of tissues. Here we present a modification of the method previously described using the commercially available Concert™ Plant RNA Reagent (Invitrogen) buffer for field-grown adult pine trees with high oleoresin content.

Development of a low-cost detection method for miRNA microarray.

PubMed

Li, Wei; Zhao, Botao; Jin, Youxin; Ruan, Kangcheng

2010-04-01

MicroRNA (miRNA) microarray is a powerful tool to explore the expression profiling of miRNA. The current detection method used in miRNA microarray is mainly fluorescence based, which usually requires costly detection system such as laser confocal scanner of tens of thousands of dollars. Recently, we developed a low-cost yet sensitive detection method for miRNA microarray based on enzyme-linked assay. In this approach, the biotinylated miRNAs were captured by the corresponding oligonucleotide probes immobilized on microarray slide; and then the biotinylated miRNAs would capture streptavidin-conjugated alkaline phosphatase. A purple-black precipitation on each biotinylated miRNA spot was produced by the enzyme catalytic reaction. It could be easily detected by a charge-coupled device digital camera mounted on a microscope, which lowers the detection cost more than 100 fold compared with that of fluorescence method. Our data showed that signal intensity of the spot correlates well with the biotinylated miRNA concentration and the detection limit for miRNAs is at least 0.4 fmol and the detection dynamic range spans about 2.5 orders of magnitude, which is comparable to that of fluorescence method.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis*

PubMed Central

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-01-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. PMID:24687888

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

PubMed

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-06-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Clustering-based spot segmentation of cDNA microarray images.

PubMed

Uslan, Volkan; Bucak, Ihsan Ömür

2010-01-01

Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.

In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics

PubMed Central

Grundberg, Ida; Kiflemariam, Sara; Mignardi, Marco; Imgenberg-Kreuz, Juliana; Edlund, Karolina; Micke, Patrick; Sundström, Magnus; Sjöblom, Tobias

2013-01-01

Current assays for somatic mutation analysis are based on extracts from tissue sections that often contain morphologically heterogeneous neoplastic regions with variable contents of genetically normal stromal and inflammatory cells, obscuring the results of the assays. We have developed an RNA-based in situ mutation assay that targets oncogenic mutations in a multiplex fashion that resolves the heterogeneity of the tissue sample. Activating oncogenic mutations are targets for a new generation of cancer drugs. For anti-EGFR therapy prediction, we demonstrate reliable in situ detection of KRAS mutations in codon 12 and 13 in colon and lung cancers in three different types of routinely processed tissue materials. High-throughput screening of KRAS mutation status was successfully performed on a tissue microarray. Moreover, we show how the patterns of expressed mutated and wild-type alleles can be studied in situ in tumors with complex combinations of mutated EGFR, KRAS and TP53. This in situ method holds great promise as a tool to investigate the role of somatic mutations during tumor progression and for prediction of response to targeted therapy. PMID:24280411

Application of laser-capture microdissection to analysis of gene expression in the testis.

PubMed

Sluka, Pavel; O'Donnell, Liza; McLachlan, Robert I; Stanton, Peter G

2008-01-01

The isolation and molecular analysis of highly purified cell populations from complex, heterogeneous tissues has been a challenge for many years. Spermatogenesis in the testis is a particularly difficult process to study given the unique multiple cellular associations within the seminiferous epithelium, making the isolation of specific cell types difficult. Laser-capture microdissection (LCM) is a recently developed technique that enables the isolation of individual cell populations from complex tissues. This technology has enhanced our ability to directly examine gene expression in enriched testicular cell populations by routine methods of gene expression analysis, such as real-time RT-PCR, differential display, and gene microarrays. The application of LCM has however introduced methodological hurdles that have not been encountered with more conventional molecular analyses of whole tissue. In particular, tissue handling (i.e. fixation, storage, and staining), consumables (e.g. slide choice), staining reagents (conventional H&E vs. fluorescence), extraction methods, and downstream applications have all required re-optimisation to facilitate differential gene expression analysis using the small amounts of material obtained using LCM. This review will discuss three critical issues that are essential for successful procurement of cells from testicular tissue sections; tissue morphology, capture success, and maintenance of molecular integrity. The importance of these issues will be discussed with specific reference to the two most commonly used LCM systems; the Arcturus PixCell IIe and PALM systems. The rat testis will be used as a model, and emphasis will be placed on issues of tissue handling, processing, and staining methods, including the application of fluorescence techniques to assist in the identification of cells of interest for the purposes of mRNA expression analysis.

[Expression of cell adhesion molecules in acute leukemia cell].

PubMed

Ju, Xiaoping; Peng, Min; Xu, Xiaoping; Lu, Shuqing; Li, Yao; Ying, Kang; Xie, Yi; Mao, Yumin; Xia, Fang

2002-11-01

To investigate the role of cell adhesion molecule in the development and extramedullary infiltration (EI) of acute leukemia. The expressions of neural cell adhesion molecule (NCAM) gene, intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule (VCAM-1) genes in 25 acute leukemia patients bone marrow cells were detected by microarray and reverse transcriptase-polymerase chain reaction (RT-PCR). The expressions of NCAM, ICAM-1 and VCAM-1 gene were significantly higher in acute leukemia cells and leukemia cells with EI than in normal tissues and leukemia cells without EI, respectively, both by cDNA microarray and by RT-PCR. The cDNA microarray is a powerful technique in analysis of acute leukemia cells associated genes. High expressions of cell adhesion molecule genes might be correlated with leukemia pathogenesis and infiltration of acute leukemia cell.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Tissue-enriched expression profiles in Aedes aegypti identify hemocyte-specific transcriptome responses to infection

PubMed Central

Choi, Young-Jun; Fuchs, Jeremy F.; Mayhew, George F.; Yu, Helen E.; Christensen, Bruce M.

2012-01-01

Hemocytes are integral components of mosquito immune mechanisms such as phagocytosis, melanization, and production of antimicrobial peptides. However, our understanding of hemocyte-specific molecular processes and their contribution to shaping the host immune response remains limited. To better understand the immunophysiological features distinctive of hemocytes, we conducted genome-wide analysis of hemocyte-enriched transcripts, and examined how tissue-enriched expression patterns change with the immune status of the host. Our microarray data indicate that the hemocyte-enriched trascriptome is dynamic and context-dependent. Analysis of transcripts enriched after bacterial challenge in circulating hemocytes with respect to carcass added a dimension to evaluating infection-responsive genes and immune-related gene families. We resolved patterns of transcriptional change unique to hemocytes from those that are likely shared by other immune responsive tissues, and identified clusters of genes preferentially induced in hemocytes, likely reflecting their involvement in cell type specific functions. In addition, the study revealed conserved hemocyte-enriched molecular repertoires which might be implicated in core hemocyte function by cross-species meta-analysis of microarray expression data from Anopheles gambiae and Drosophila melanogaster. PMID:22796331

Role of Macrophage-Induced Inflammation in Mesothelioma

DTIC Science & Technology

2010-07-01

in human mesothelioma tumors and correlate immune cell infiltration with histopathologic subtype (months 1-6). Using tumor tissue microarrays of... histopathologic subtype (months 1-6). • Acquired 71 fixed and paraffin-embedded mesothelioma tumor samples • Prepared mesothelioma tumor tissue...Biol., 2008. 84: p. 1-8. 5. Dave, S.S., et al., Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating

Tissue microarrays and digital image analysis.

PubMed

Ryan, Denise; Mulrane, Laoighse; Rexhepaj, Elton; Gallagher, William M

2011-01-01

Tissue microarrays (TMAs) have recently emerged as very valuable tools for high-throughput pathological assessment, especially in the cancer research arena. This important technology, however, has yet to fully penetrate into the area of toxicology. Here, we describe the creation of TMAs representative of samples produced from conventional toxicology studies within a large-scale, multi-institutional pan-European project, PredTox. PredTox, short for Predictive Toxicology, formed part of an EU FP6 Integrated Project, Innovative Medicines for Europe (InnoMed), and aimed to study pre-clinically 16 compounds of known liver and/or kidney toxicity. In more detail, TMAs were constructed from materials corresponding to the full face sections of liver and kidney from rats treated with different drug candidates by members of the consortium. We also describe the process of digital slide scanning of kidney and liver sections, in the context of creating an online resource of histopathological data.

Delayed inflammatory mRNA and protein expression after spinal cord injury

PubMed Central

2011-01-01

Background Spinal cord injury (SCI) induces secondary tissue damage that is associated with inflammation. We have previously demonstrated that inflammation-related gene expression after SCI occurs in two waves - an initial cluster that is acutely and transiently up-regulated within 24 hours, and a more delayed cluster that peaks between 72 hours and 7 days. Here we extend the microarray analysis of these gene clusters up to 6 months post-SCI. Methods Adult male rats were subjected to mild, moderate or severe spinal cord contusion injury at T9 using a well-characterized weight-drop model. Tissue from the lesion epicenter was obtained 4 hours, 24 hours, 7 days, 28 days, 3 months or 6 months post-injury and processed for microarray analysis and protein expression. Results Anchor gene analysis using C1qB revealed a cluster of genes that showed elevated expression through 6 months post-injury, including galectin-3, p22PHOX, gp91PHOX, CD53 and progranulin. The expression of these genes occurred primarily in microglia/macrophage cells and was confirmed at the protein level using both immunohistochemistry and western blotting. As p22PHOX and gp91PHOX are components of the NADPH oxidase enzyme, enzymatic activity and its role in SCI were assessed and NADPH oxidase activity was found to be significantly up-regulated through 6 months post-injury. Further, treating rats with the nonspecific, irreversible NADPH oxidase inhibitor diphenylene iodinium (DPI) reduced both lesion volume and expression of chronic gene cluster proteins one month after trauma. Conclusions These data demonstrate that inflammation-related genes are chronically up-regulated after SCI and may contribute to further tissue loss. PMID:21975064

Aberrant expressions of c-KIT and DOG-1 in mucinous and nonmucinous colorectal carcinomas and relation to clinicopathologic features and prognosis.

PubMed

Foda, Abd Al-Rahman Mohammad; Mohamed, Mie Ali

2015-10-01

c-KIT and DOG-1 are 2 highly expressed proteins in gastrointestinal stromal tumors. Few studies had investigated c-KIT, but not DOG-1, expression in colorectal carcinoma (CRC). This study aims to investigate expressions of c-KIT and DOG-1 in colorectal mucinous carcinoma and nonmucinous carcinoma using manual tissue microarray technique. In this work, we studied tumor tissue specimens from 150 patients with colorectal mucinous (MA) and nonmucinous adenocarcinoma (NMA). High-density manual tissue microarrays were constructed using modified mechanical pencil tip technique, and immunohistochemistry for c-KIT and DOG-1 was done. We found that aberrant c-KIT expression was detected in 12 cases (8%); 6 cases (4%) showed strong expression. Aberrant DOG-1 expression was detected in 15 cases (10%); among them, only 4 cases (2.7%) showed strong expression. Nonmucinous adenocarcinoma showed a significantly high expression of c-KIT, but not DOG-1, than MA. Aberrant c-KIT and DOG-1 expressions were significantly unrelated but were associated with excessive microscopic abscess formation. Neither c-KIT nor DOG-1 expression showed a significant impact on disease-free survival or overall survival. In conclusion, aberrant c-KIT and DOG-1 expressions in CRC are rare events, either in NMA or MA. Nonmucinous adenocarcinoma showed a significantly higher expression of c-KIT, but not DOG-1, than MA. The expressions of both in CRC are significantly unrelated but are associated with microscopic abscess formation. Neither c-KIT nor DOG-1 expression showed a significant impact on disease-free survival or overall survival. So, c-KIT and DOG-1 immunostaining is not a cost-effective method of identifying patients with CRC who may benefit from treatment with tyrosine kinase inhibitors. Copyright © 2015 Elsevier Inc. All rights reserved.

Highly Tissue Substructure-Specific Effects of Human Papilloma Virus in Mucosa of HIV-Infected Patients Revealed by Laser-Dissection Microscopy-Assisted Gene Expression Profiling

PubMed Central

Baumgarth, Nicole; Szubin, Richard; Dolganov, Greg M.; Watnik, Mitchell R.; Greenspan, Deborah; Da Costa, Maria; Palefsky, Joel M.; Jordan, Richard; Roederer, Mario; Greenspan, John S.

2004-01-01

Human papilloma virus (HPV) causes focal infections of epithelial layers in skin and mucosa. HIV-infected patients on highly active antiretroviral therapy (HAART) appear to be at increased risk of developing HPV-induced oral warts. To identify the mechanisms that allow long-term infection of oral epithelial cells in these patients, we used a combination of laser-dissection microscopy (LDM) and highly sensitive and quantitative, non-biased, two-step multiplex real-time RT-PCR to study pathogen-induced alterations of specific tissue subcompartments. Expression of 166 genes was compared in three distinct epithelial and subepithelial compartments isolated from biopsies of normal mucosa from HIV-infected and non-infected patients and of HPV32-induced oral warts from HIV-infected patients. In contrast to the underlying HIV infection and/or HAART, which did not significantly elaborate tissue substructure-specific effects, changes in oral warts were strongly tissue substructure-specific. HPV 32 seems to establish infection by selectively enhancing epithelial cell growth and differentiation in the stratum spinosum and to evade the immune system by actively suppressing inflammatory responses in adjacent underlying tissues. With this highly sensitive and quantitative method tissue-specific expression of hundreds of genes can be studied simultaneously in a few cells. Because of its large dynamic measurement range it could also become a method of choice to confirm and better quantify results obtained by microarray analysis. PMID:15331396

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

MicroRNA expression in melanocytic nevi: the usefulness of formalin-fixed, paraffin-embedded material for miRNA microarray profiling.

PubMed

Glud, Martin; Klausen, Mikkel; Gniadecki, Robert; Rossing, Maria; Hastrup, Nina; Nielsen, Finn C; Drzewiecki, Krzysztof T

2009-05-01

MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate cellular differentiation, proliferation, and apoptosis. MiRNAs are expressed in a developmentally regulated and tissue-specific manner. Aberrant expression may contribute to pathological processes such as cancer, and miRNA may therefore serve as biomarkers that may be useful in a clinical environment for diagnosis of various diseases. Most miRNA profiling studies have used fresh tissue samples. However, in some types of cancer, including malignant melanoma, fresh material is difficult to obtain from primary tumors, and most surgical specimens are formalin fixed and paraffin embedded (FFPE). To explore whether FFPE material would be suitable for miRNA profiling in melanocytic lesions, we compared miRNA expression patterns in FFPE versus fresh frozen samples, obtained from 15 human melanocytic nevi. Out of microarray data, we identified 84 miRNAs that were expressed in both types of samples and represented an miRNA profile of melanocytic nevi. Our results showed a high correlation in miRNA expression (Spearman r-value of 0.80) between paired FFPE and fresh frozen material. The data were further validated by quantitative RT-PCR. In conclusion, FFPE specimens of melanocytic lesions are suitable as a source for miRNA microarray profiling.

Microarray-based identification of differentially expressed genes in extramammary Paget’s disease

PubMed Central

Lin, Jin-Ran; Liang, Jun; Zhang, Qiao-An; Huang, Qiong; Wang, Shang-Shang; Qin, Hai-Hong; Chen, Lian-Jun; Xu, Jin-Hua

2015-01-01

Extramammary Paget’s disease (EMPD) is a rare cutaneous malignancy accounting for approximately 1-2% of vulvar cancers. The rarity of this disease has caused difficulties in characterization and the molecular mechanism underlying EMPD development remains largely unclear. Here we used microarray analysis to identify differentially expressed genes in EMPD of the scrotum comparing with normal epithelium from healthy donors. Agilent single-channel microarray was used to compare the gene expression between 6 EMPD specimens and 6 normal scrotum epithelium samples. A total of 799 up-regulated genes and 723 down-regulated genes were identified in EMPD tissues. Real-time PCR was conducted to verify the differential expression of some representative genes, including ERBB4, TCF3, PAPSS2, PIK3R3, PRLR, SULT1A1, TCF7L1, and CREB3L4. Generally, the real-time PCR results were consistent with microarray data, and the expression of ERBB4, PRLR, TCF3, PIK3R3, SULT1A1, and TCF7L1 was significantly overexpressed in EMPD (P<0.05). Moreover, the overexpression of PRLR in EMPD, a receptor for the anterior pituitary hormone prolactin (PRL), was confirmed by immunohistochemistry. These data demonstrate that the differentially expressed genes from the microarray-based identification are tightly associated with EMPD occurrence. PMID:26221264

Image processing in digital pathology: an opportunity to solve inter-batch variability of immunohistochemical staining

NASA Astrophysics Data System (ADS)

van Eycke, Yves-Rémi; Allard, Justine; Salmon, Isabelle; Debeir, Olivier; Decaestecker, Christine

2017-02-01

Immunohistochemistry (IHC) is a widely used technique in pathology to evidence protein expression in tissue samples. However, this staining technique is known for presenting inter-batch variations. Whole slide imaging in digital pathology offers a possibility to overcome this problem by means of image normalisation techniques. In the present paper we propose a methodology to objectively evaluate the need of image normalisation and to identify the best way to perform it. This methodology uses tissue microarray (TMA) materials and statistical analyses to evidence the possible variations occurring at colour and intensity levels as well as to evaluate the efficiency of image normalisation methods in correcting them. We applied our methodology to test different methods of image normalisation based on blind colour deconvolution that we adapted for IHC staining. These tests were carried out for different IHC experiments on different tissue types and targeting different proteins with different subcellular localisations. Our methodology enabled us to establish and to validate inter-batch normalization transforms which correct the non-relevant IHC staining variations. The normalised image series were then processed to extract coherent quantitative features characterising the IHC staining patterns.

Image processing in digital pathology: an opportunity to solve inter-batch variability of immunohistochemical staining

PubMed Central

Van Eycke, Yves-Rémi; Allard, Justine; Salmon, Isabelle; Debeir, Olivier; Decaestecker, Christine

2017-01-01

Immunohistochemistry (IHC) is a widely used technique in pathology to evidence protein expression in tissue samples. However, this staining technique is known for presenting inter-batch variations. Whole slide imaging in digital pathology offers a possibility to overcome this problem by means of image normalisation techniques. In the present paper we propose a methodology to objectively evaluate the need of image normalisation and to identify the best way to perform it. This methodology uses tissue microarray (TMA) materials and statistical analyses to evidence the possible variations occurring at colour and intensity levels as well as to evaluate the efficiency of image normalisation methods in correcting them. We applied our methodology to test different methods of image normalisation based on blind colour deconvolution that we adapted for IHC staining. These tests were carried out for different IHC experiments on different tissue types and targeting different proteins with different subcellular localisations. Our methodology enabled us to establish and to validate inter-batch normalization transforms which correct the non-relevant IHC staining variations. The normalised image series were then processed to extract coherent quantitative features characterising the IHC staining patterns. PMID:28220842

Ewing's Sarcoma: An Analysis of miRNA Expression Profiles and Target Genes in Paraffin-Embedded Primary Tumor Tissue.

PubMed

Parafioriti, Antonina; Bason, Caterina; Armiraglio, Elisabetta; Calciano, Lucia; Daolio, Primo Andrea; Berardocco, Martina; Di Bernardo, Andrea; Colosimo, Alessia; Luksch, Roberto; Berardi, Anna C

2016-04-30

The molecular mechanism responsible for Ewing's Sarcoma (ES) remains largely unknown. MicroRNAs (miRNAs), a class of small non-coding RNAs able to regulate gene expression, are deregulated in tumors and may serve as a tool for diagnosis and prediction. However, the status of miRNAs in ES has not yet been thoroughly investigated. This study compared global miRNAs expression in paraffin-embedded tumor tissue samples from 20 ES patients, affected by primary untreated tumors, with miRNAs expressed in normal human mesenchymal stromal cells (MSCs) by microarray analysis. A miRTarBase database was used to identify the predicted target genes for differentially expressed miRNAs. The miRNAs microarray analysis revealed distinct patterns of miRNAs expression between ES samples and normal MSCs. 58 of the 954 analyzed miRNAs were significantly differentially expressed in ES samples compared to MSCs. Moreover, the qRT-PCR analysis carried out on three selected miRNAs showed that miR-181b, miR-1915 and miR-1275 were significantly aberrantly regulated, confirming the microarray results. Bio-database analysis identified BCL-2 as a bona fide target gene of the miR-21, miR-181a, miR-181b, miR-29a, miR-29b, miR-497, miR-195, miR-let-7a, miR-34a and miR-1915. Using paraffin-embedded tissues from ES patients, this study has identified several potential target miRNAs and one gene that might be considered a novel critical biomarker for ES pathogenesis.

Elucidation of the effect of brain cortex tetrapeptide Cortagen on gene expression in mouse heart by microarray.

PubMed

Anisimov, Sergey V; Khavinson, Vladimir Kh; Anisimov, Vladimir N

2004-01-01

Aging is associated with significant alterations in gene expression in numerous organs and tissues. Anti-aging therapy with peptide bioregulators holds much promise for the correction of age-associated changes, making a screening for their molecular targets in tissues an important question of modern gerontology. The synthetic tetrapeptide Cortagen (Ala-Glu-Asp-Pro) was obtained by directed synthesis based on amino acid analysis of natural brain cortex peptide preparation Cortexin. In humans, Cortagen demonstrated a pronounced therapeutic effect upon the structural and functional posttraumatic recovery of peripheral nerve tissue. Importantly, other effects were also observed in cardiovascular and cerebrovascular parameters. Based on these latter observations, we hypothesized that acute course of Cortagen treatment, large-scale transcriptome analysis, and identification of transcripts with altered expression in heart would facilitate our understanding of the mechanisms responsible for this peptide biological effects. We therefore analyzed the expression of 15,247 transcripts in the heart of female 6-months CBA mice receiving injections of Cortagen for 5 consecutive days was studied by cDNA microarrays. Comparative analysis of cDNA microarray hybridisation with heart samples from control and experimental group revealed 234 clones (1,53% of the total number of clones) with significant changes of expression that matched 110 known genes belonging to various functional categories. Maximum up- and down-regulation was +5.42 and -2.86, respectively. Intercomparison of changes in cardiac expression profile induced by synthetic peptides (Cortagen, Vilon, Epitalon) and pineal peptide hormone melatonin revealed both common and specific effects of Cortagen upon gene expression in heart.

Loss of Nuclear Localized and Tyrosine Phosphorylated Stat5 in Breast Cancer Predicts Poor Clinical Outcome and Increased Risk of Antiestrogen Therapy Failure

PubMed Central

Peck, Amy R.; Witkiewicz, Agnieszka K.; Liu, Chengbao; Stringer, Ginger A.; Klimowicz, Alexander C.; Pequignot, Edward; Freydin, Boris; Tran, Thai H.; Yang, Ning; Rosenberg, Anne L.; Hooke, Jeffrey A.; Kovatich, Albert J.; Nevalainen, Marja T.; Shriver, Craig D.; Hyslop, Terry; Sauter, Guido; Rimm, David L.; Magliocco, Anthony M.; Rui, Hallgeir

2011-01-01

Purpose To investigate nuclear localized and tyrosine phosphorylated Stat5 (Nuc-pYStat5) as a marker of prognosis in node-negative breast cancer and as a predictor of response to antiestrogen therapy. Patients and Methods Levels of Nuc-pYStat5 were analyzed in five archival cohorts of breast cancer by traditional diaminobenzidine-chromogen immunostaining and pathologist scoring of whole tissue sections or by immunofluorescence and automated quantitative analysis (AQUA) of tissue microarrays. Results Nuc-pYStat5 was an independent prognostic marker as measured by cancer-specific survival (CSS) in patients with node-negative breast cancer who did not receive systemic adjuvant therapy, when adjusted for common pathology parameters in multivariate analyses both by standard chromogen detection with pathologist scoring of whole tissue sections (cohort I; n = 233) and quantitative immunofluorescence of a tissue microarray (cohort II; n = 291). Two distinct monoclonal antibodies gave concordant results. A progression array (cohort III; n = 180) revealed frequent loss of Nuc-pYStat5 in invasive carcinoma compared to normal breast epithelia or ductal carcinoma in situ, and general loss of Nuc-pYStat5 in lymph node metastases. In cohort IV (n = 221), loss of Nuc-pYStat5 was associated with increased risk of antiestrogen therapy failure as measured by univariate CSS and time to recurrence (TTR). More sensitive AQUA quantification of Nuc-pYStat5 in antiestrogen-treated patients (cohort V; n = 97) identified by multivariate analysis patients with low Nuc-pYStat5 at elevated risk for therapy failure (CSS hazard ratio [HR], 21.55; 95% CI, 5.61 to 82.77; P < .001; TTR HR, 7.30; 95% CI, 2.34 to 22.78; P = .001). Conclusion Nuc-pYStat5 is an independent prognostic marker in node-negative breast cancer. If confirmed in prospective studies, Nuc-pYStat5 may become a useful predictive marker of response to adjuvant hormone therapy. PMID:21576635

MicroRNA-20a-5p promotes colorectal cancer invasion and metastasis by downregulating Smad4

PubMed Central

Zhang, Dongyuan; Sun, Hongcheng; Yu, Fudong; Yue, Ben; Wang, Jingtao; Zhang, Meng; Yu, Yang; Liu, Xisheng; Sun, Xiaofeng; Zhou, Zongguang; Qin, Xuebin; Zhang, Xin; Yan, Dongwang; Wen, Yugang; Peng, Zhihai

2016-01-01

Background Tumor metastasis is one of the leading causes of poor prognosis for colorectal cancer (CRC) patients. Loss of Smad4 contributes to aggression process in many human cancers. However, the underlying precise mechanism of aberrant Smad4 expression in CRC development is still little known. Results miR-20a-5p negatively regulated Smad4 by directly targeting its 3′UTR in human colorectal cancer cells. miR-20a-5p not only promoted CRC cells aggression capacity in vitro and liver metastasis in vivo, but also promoted the epithelial-to-mesenchymal transition process by downregulating Smad4 expression. In addition, tissue microarray analysis obtained from 544 CRC patients’ clinical characters showed that miR-20a-5p was upregulated in human CRC tissues, especially in the tissues with metastasis. High level of miR-20a-5p predicted poor prognosis in CRC patients. Methods Five miRNA target prediction programs were applied to identify potential miRNA(s) that target(s) Smad4 in CRC. Luciferase reporter assay and transfection technique were used to validate the correlation between miR-20a-5p and Smad4 in CRC. Wound healing, transwell and tumorigenesis assays were used to explore the function of miR-20a-5p and Smad4 in CRC progression in vitro and in vivo. The association between miR-20a-5p expression and the prognosis of CRC patients was evaluated by Kaplan–Meier analysis and multivariate cox proportional hazard analyses based on tissue microarray data. Conclusions miR-20a-5p, as an onco-miRNA, promoted the invasion and metastasis ability by suppressing Smad4 expression in CRC cells, and high miR-20a-5p predicted poor prognosis for CRC patients, providing a novel and promising therapeutic target in human colorectal cancer. PMID:27286257

MicroRNA-320 family is downregulated in colorectal adenoma and affects tumor proliferation by targeting CDK6

PubMed Central

Tadano, Toshihiro; Kakuta, Yoichi; Hamada, Shin; Shimodaira, Yosuke; Kuroha, Masatake; Kawakami, Yoko; Kimura, Tomoya; Shiga, Hisashi; Endo, Katsuya; Masamune, Atsushi; Takahashi, Seiichi; Kinouchi, Yoshitaka; Shimosegawa, Tooru

2016-01-01

AIM: To investigate the microRNA (miRNA) expression during histological progression from colorectal normal mucosa through adenoma to carcinoma within a lesion. METHODS: Using microarray, the sequential changes in miRNA expression profiles were compared in colonic lesions from matched samples; histologically, non-neoplastic mucosa, adenoma, and submucosal invasive carcinoma were microdissected from a tissue sample. Cell proliferation assay was performed to observe the effect of miRNA, and its target genes were predicted using bioinformatics approaches and the expression profile of SW480 transfected with the miRNA mimics. mRNA and protein levels of the target gene in colon cancer cell lines with a mimic control or miRNA mimics were measured using qRT-PCR and Western blotting. The expression levels of miRNA and target gene in colorectal tissue samples were also measured. RESULTS: Microarray analysis identified that the miR-320 family, including miR-320a, miR-320b, miR-320c, miR-320d and miR-320e, were differentially expressed in adenoma and submucosal invasive carcinoma. The miR-320 family, which inhibits cell proliferation, is frequently downregulated in colorectal adenoma and submucosal invasive carcinoma tissues. Seven genes including CDK6 were identified to be common in the results of gene expression array and bioinformatics analyses performed to find the target gene of the miR-320 family. We confirmed that mRNA and protein levels of CDK6 were significantly suppressed in colon cancer cell lines with miR-320 family mimics. CDK6 expression was found to increase from non-neoplastic mucosa through adenoma to submucosal invasive carcinoma tissues and showed an inverse correlation with miR-320 family expression. CONCLUSION: MiR-320 family affects colorectal tumor proliferation by targeting CDK6, plays important role in its growth, and is considered to be a biomarker for its early detection. PMID:27559432

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Double stranded nucleic acid biochips

DOEpatents

Chernov, Boris; Golova, Julia

2006-05-23

This invention describes a new method of constructing double-stranded DNA (dsDNA) microarrays based on the use of pre-synthesized or natural DNA duplexes without a stem-loop structure. The complementary oligonucleotide chains are bonded together by a novel connector that includes a linker for immobilization on a matrix. A non-enzymatic method for synthesizing double-stranded nucleic acids with this novel connector enables the construction of inexpensive and robust dsDNA/dsRNA microarrays. DNA-DNA and DNA-protein interactions are investigated using the microarrays.

Unusual Intron Conservation near Tissue-Regulated Exons Found by Splicing Microarrays

PubMed Central

Sugnet, Charles W; Srinivasan, Karpagam; Clark, Tyson A; O'Brien, Georgeann; Cline, Melissa S; Wang, Hui; Williams, Alan; Kulp, David; Blume, John E; Haussler, David; Ares, Manuel

2006-01-01

Alternative splicing contributes to both gene regulation and protein diversity. To discover broad relationships between regulation of alternative splicing and sequence conservation, we applied a systems approach, using oligonucleotide microarrays designed to capture splicing information across the mouse genome. In a set of 22 adult tissues, we observe differential expression of RNA containing at least two alternative splice junctions for about 40% of the 6,216 alternative events we could detect. Statistical comparisons identify 171 cassette exons whose inclusion or skipping is different in brain relative to other tissues and another 28 exons whose splicing is different in muscle. A subset of these exons is associated with unusual blocks of intron sequence whose conservation in vertebrates rivals that of protein-coding exons. By focusing on sets of exons with similar regulatory patterns, we have identified new sequence motifs implicated in brain and muscle splicing regulation. Of note is a motif that is strikingly similar to the branchpoint consensus but is located downstream of the 5′ splice site of exons included in muscle. Analysis of three paralogous membrane-associated guanylate kinase genes reveals that each contains a paralogous tissue-regulated exon with a similar tissue inclusion pattern. While the intron sequences flanking these exons remain highly conserved among mammalian orthologs, the paralogous flanking intron sequences have diverged considerably, suggesting unusually complex evolution of the regulation of alternative splicing in multigene families. PMID:16424921

Altered Molecular Expression of the TLR4/NF-κB Signaling Pathway in Mammary Tissue of Chinese Holstein Cattle with Mastitis

PubMed Central

Wu, Jie; Li, Lian; Sun, Yu; Huang, Shuai; Tang, Juan; Yu, Pan; Wang, Genlin

2015-01-01

Toll-like receptor 4 (TLR4) mediated activation of the nuclear transcription factor κB (NF-κB) signaling pathway by mastitis initiates expression of genes associated with inflammation and the innate immune response. In this study, the profile of mastitis-induced differential gene expression in the mammary tissue of Chinese Holstein cattle was investigated by Gene-Chip microarray and bioinformatics. The microarray results revealed that 79 genes associated with the TLR4/NF-κB signaling pathway were differentially expressed. Of these genes, 19 were up-regulated and 29 were down-regulated in mastitis tissue compared to normal, healthy tissue. Statistical analysis of transcript and protein level expression changes indicated that 10 genes, namely TLR4, MyD88, IL-6, and IL-10, were up-regulated, while, CD14, TNF-α, MD-2, IL-β, NF-κB, and IL-12 were significantly down-regulated in mastitis tissue in comparison with normal tissue. Analyses using bioinformatics database resources, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the Gene Ontology Consortium (GO) for term enrichment analysis, suggested that these differently expressed genes implicate different regulatory pathways for immune function in the mammary gland. In conclusion, our study provides new evidence for better understanding the differential expression and mechanisms of the TLR4 /NF-κB signaling pathway in Chinese Holstein cattle with mastitis. PMID:25706977

Altered molecular expression of the TLR4/NF-κB signaling pathway in mammary tissue of Chinese Holstein cattle with mastitis.

PubMed

Wu, Jie; Li, Lian; Sun, Yu; Huang, Shuai; Tang, Juan; Yu, Pan; Wang, Genlin

2015-01-01

Toll-like receptor 4 (TLR4) mediated activation of the nuclear transcription factor κB (NF-κB) signaling pathway by mastitis initiates expression of genes associated with inflammation and the innate immune response. In this study, the profile of mastitis-induced differential gene expression in the mammary tissue of Chinese Holstein cattle was investigated by Gene-Chip microarray and bioinformatics. The microarray results revealed that 79 genes associated with the TLR4/NF-κB signaling pathway were differentially expressed. Of these genes, 19 were up-regulated and 29 were down-regulated in mastitis tissue compared to normal, healthy tissue. Statistical analysis of transcript and protein level expression changes indicated that 10 genes, namely TLR4, MyD88, IL-6, and IL-10, were up-regulated, while, CD14, TNF-α, MD-2, IL-β, NF-κB, and IL-12 were significantly down-regulated in mastitis tissue in comparison with normal tissue. Analyses using bioinformatics database resources, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the Gene Ontology Consortium (GO) for term enrichment analysis, suggested that these differently expressed genes implicate different regulatory pathways for immune function in the mammary gland. In conclusion, our study provides new evidence for better understanding the differential expression and mechanisms of the TLR4 /NF-κB signaling pathway in Chinese Holstein cattle with mastitis.

TAMEE: data management and analysis for tissue microarrays.

PubMed

Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

2007-03-07

With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from http://genome.tugraz.at/Software/TAMEE.

Improved microarray methods for profiling the yeast knockout strain collection

PubMed Central

Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.

2005-01-01

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

Simplified Microarray Technique for Identifying mRNA in Rare Samples

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

Two simplified methods of identifying messenger ribonucleic acid (mRNA), and compact, low-power apparatuses to implement the methods, are at the proof-of-concept stage of development. These methods are related to traditional methods based on hybridization of nucleic acid, but whereas the traditional methods must be practiced in laboratory settings, these methods could be practiced in field settings. Hybridization of nucleic acid is a powerful technique for detection of specific complementary nucleic acid sequences, and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes. A traditional microarray study entails at least the following six steps: 1. Purification of cellular RNA, 2. Amplification of complementary deoxyribonucleic acid [cDNA] by polymerase chain reaction (PCR), 3. Labeling of cDNA with fluorophores of Cy3 (a green cyanine dye) and Cy5 (a red cyanine dye), 4. Hybridization to a microarray chip, 5. Fluorescence scanning the array(s) with dual excitation wavelengths, and 6. Analysis of the resulting images. This six-step procedure must be performed in a laboratory because it requires bulky equipment.

HPASubC: A suite of tools for user subclassification of human protein atlas tissue images.

PubMed

Cornish, Toby C; Chakravarti, Aravinda; Kapoor, Ashish; Halushka, Marc K

2015-01-01

The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented. To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest. We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs. The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology.

A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition

NASA Astrophysics Data System (ADS)

Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

2013-10-01

Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors.Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors. Electronic supplementary information (ESI) available: Four-probe method for determining the conductivity of the hybrid crystal (Fig. S1); stability comparisons of the hybrid films (Fig. S2); FESEM images of the hybrid microarray (Fig. S3); electrochemical characterizations of the hybrid films (Fig. S4); DFT simulations (Fig. S5); cross-sectional FESEM image of the hybrid microarray (Fig. S6); regeneration and stability tests of the DNA biosensor (Fig. S7). See DOI: 10.1039/c3nr03097k

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster

PubMed Central

Robinson, Scott W.; Herzyk, Pawel; Dow, Julian A. T.; Leader, David P.

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25—17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13 250 Drosophila genes, detecting 12 533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax ‘autosuggest’ facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues. PMID:23203866

FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster.

PubMed

Robinson, Scott W; Herzyk, Pawel; Dow, Julian A T; Leader, David P

2013-01-01

The FlyAtlas resource contains data on the expression of the genes of Drosophila melanogaster in different tissues (currently 25-17 adult and 8 larval) obtained by hybridization of messenger RNA to Affymetrix Drosophila Genome 2 microarrays. The microarray probe sets cover 13,250 Drosophila genes, detecting 12,533 in an unambiguous manner. The data underlying the original web application (http://flyatlas.org) have been restructured into a relational database and a Java servlet written to provide a new web interface, FlyAtlas 2 (http://flyatlas.gla.ac.uk/), which allows several additional queries. Users can retrieve data for individual genes or for groups of genes belonging to the same or related ontological categories. Assistance in selecting valid search terms is provided by an Ajax 'autosuggest' facility that polls the database as the user types. Searches can also focus on particular tissues, and data can be retrieved for the most highly expressed genes, for genes of a particular category with above-average expression or for genes with the greatest difference in expression between the larval and adult stages. A novel facility allows the database to be queried with a specific gene to find other genes with a similar pattern of expression across the different tissues.

Up-regulation of CD44 in the development of metastasis, recurrence and drug resistance of ovarian cancer

PubMed Central

Gao, Yan; Foster, Rosemary; Yang, Xiaoqian; Feng, Yong; Shen, Jacson K.; Mankin, Henry J.; Hornicek, Francis J.; Amiji, Mansoor M.; Duan, Zhenfeng

2015-01-01

The clinical significance of Cluster of Differentiation 44 (CD44) remains controversial in human ovarian cancer. The aim of this study is to evaluate the clinical significance of CD44 expression by using a unique tissue microarray, and then to determine the biological functions of CD44 in ovarian cancer. In this study, a unique ovarian cancer tissue microarray (TMA) was constructed with paired primary, metastatic, and recurrent tumor tissues from 26 individual patients. CD44 expression in TMA was assessed by immunohistochemistry. Both the metastatic and recurrent ovarian cancer tissues expressed higher level of CD44 than the patient-matched primary tumor. A significant association has been shown between CD44 expression and both the disease free survival and overall survival. A strong increase of CD44 was found in the tumor recurrence of mouse model. Finally, when CD44 was knocked down, proliferation, migration/invasion activity, and spheroid formation were significantly suppressed, while drug sensitivity was enhanced. Thus, up-regulation of CD44 represents a crucial event in the development of metastasis, recurrence, and drug resistance to current treatments in ovarian cancer. Developing strategies to target CD44 may prevent metastasis, recurrence, and drug resistance in ovarian cancer. PMID:25823654

Up-regulation of CD44 in the development of metastasis, recurrence and drug resistance of ovarian cancer.

PubMed

Gao, Yan; Foster, Rosemary; Yang, Xiaoqian; Feng, Yong; Shen, Jacson K; Mankin, Henry J; Hornicek, Francis J; Amiji, Mansoor M; Duan, Zhenfeng

2015-04-20

The clinical significance of Cluster of Differentiation 44 (CD44) remains controversial in human ovarian cancer. The aim of this study is to evaluate the clinical significance of CD44 expression by using a unique tissue microarray, and then to determine the biological functions of CD44 in ovarian cancer. In this study, a unique ovarian cancer tissue microarray (TMA) was constructed with paired primary, metastatic, and recurrent tumor tissues from 26 individual patients. CD44 expression in TMA was assessed by immunohistochemistry. Both the metastatic and recurrent ovarian cancer tissues expressed higher level of CD44 than the patient-matched primary tumor. A significant association has been shown between CD44 expression and both the disease free survival and overall survival. A strong increase of CD44 was found in the tumor recurrence of mouse model. Finally, when CD44 was knocked down, proliferation, migration/invasion activity, and spheroid formation were significantly suppressed, while drug sensitivity was enhanced. Thus, up-regulation of CD44 represents a crucial event in the development of metastasis, recurrence, and drug resistance to current treatments in ovarian cancer. Developing strategies to target CD44 may prevent metastasis, recurrence, and drug resistance in ovarian cancer.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Circular RNA profiles in mouse lung tissue induced by radon.

PubMed

Pei, Weiwei; Tao, Lijing; Zhang, Leshuai W; Zhang, Shuyu; Cao, Jianping; Jiao, Yang; Tong, Jian; Nie, Jihua

2017-04-07

Radon is a known human lung carcinogen, whose underlying carcinogenic mechanism remains unclear. Recently, circular RNA (circRNA), a class of endogenous non-protein coding RNAs that contain a circular loop, was found to exhibit multiple biological effects. In this study, circRNA profiles in mouse lung tissues between control and radon exposure were analyzed. Six mice were exposed to radon at concentration of 100,000 Bq/m 3 , 12 h/d, for up to cumulative doses of 60 working level months (WLM). H&E staining and immunohistochemistry of caspase-3 were used to detect the damages in lung tissue. The lung tissue of control and exposed group were selected for circRNA microarray study. The circRNA/microRNA interaction was analyzed by starBase prediction software. 5 highest expressing circRNAs were selected by real-time PCR to validate the consistency in mouse lung tissue exposed to radon. Inflammatory reaction was found in mouse lung tissue exposed to radon, and caspase-3 expression was significantly increased. Microarray screening revealed 107 up-regulated and 83 down-regulated circRNAs, among which top 30 circRNAs with the highest fold changes were chosen for further analysis, with 5 microRNAs binding sites listed for each circRNA. Consistency of the top 5 circRNAs with the highest expressions were confirmed in mice exposed with 60WLM of radon. Mouse lung tissue was severely injured when exposed to radon through pathological diagnosis and immunohistochemical analysis. A series of differentially expressed circRNAs demonstrated that they may play an important role in pulmonary toxicity induced by radon.

Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals.

PubMed

Fricano, Meagan M; Ditewig, Amy C; Jung, Paul M; Liguori, Michael J; Blomme, Eric A G; Yang, Yi

2011-01-01

Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 μL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per μL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total RNA samples were further processed using the NuGEN Ovation Whole Blood Solution system and cDNA was hybridized to Affymetrix Rat Genome 230 2.0 Arrays. The microarray QC parameters using RNA isolated with the QSI method were within the acceptable range for microarray analysis. The transcriptomic profiles were highly correlated with those using RNA isolated with the PAXgene method and were consistent with expected LPS-induced inflammatory responses. The present study demonstrated that the QSI method coupled with NuGEN Ovation Whole Blood Solution system is cost-effective and particularly suitable for transcriptomic profiling of minimal volumes of whole blood, typical of those obtained with small animal species.

Highly sensitive molecular diagnosis of prostate cancer using surplus material washed off from biopsy needles

PubMed Central

Bermudo, R; Abia, D; Mozos, A; García-Cruz, E; Alcaraz, A; Ortiz, Á R; Thomson, T M; Fernández, P L

2011-01-01

Introduction: Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment. Methods: Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT–PCR (qRT–PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis. Results: Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT–PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity. Conclusion: Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis. PMID:22009027

Robust Segmentation of Overlapping Cells in Histopathology Specimens Using Parallel Seed Detection and Repulsive Level Set

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Automated image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of breast cancer. Automated segmentation of the cells comprising imaged tissue microarrays (TMA) is a prerequisite for any subsequent quantitative analysis. Unfortunately, crowding and overlapping of cells present significant challenges for most traditional segmentation algorithms. In this paper, we propose a novel algorithm which can reliably separate touching cells in hematoxylin stained breast TMA specimens which have been acquired using a standard RGB camera. The algorithm is composed of two steps. It begins with a fast, reliable object center localization approach which utilizes single-path voting followed by mean-shift clustering. Next, the contour of each cell is obtained using a level set algorithm based on an interactive model. We compared the experimental results with those reported in the most current literature. Finally, performance was evaluated by comparing the pixel-wise accuracy provided by human experts with that produced by the new automated segmentation algorithm. The method was systematically tested on 234 image patches exhibiting dense overlap and containing more than 2200 cells. It was also tested on whole slide images including blood smears and tissue microarrays containing thousands of cells. Since the voting step of the seed detection algorithm is well suited for parallelization, a parallel version of the algorithm was implemented using graphic processing units (GPU) which resulted in significant speed-up over the C/C++ implementation. PMID:22167559

A novel monoclonal antibody targeting carboxymethyllysine, an advanced glycation end product in atherosclerosis and pancreatic cancer.

PubMed

Wendel, Ulrika; Persson, Nina; Risinger, Christian; Bengtsson, Eva; Nodin, Björn; Danielsson, Lena; Welinder, Charlotte; Nordin Fredrikson, Gunilla; Jansson, Bo; Blixt, Ola

2018-01-01

Advanced glycation end products are formed by non-enzymatic reactions between proteins and carbohydrates, causing irreversible lysine and arginine alterations that severely affect protein structure and function. The resulting modifications induce inflammation by binding to scavenger receptors. An increase in advanced glycation end products is observed in a number of diseases e.g. atherosclerosis and cancer. Since advanced glycation end products also are present in healthy individuals, their detection and quantification are of great importance for usage as potential biomarkers. Current methods for advanced glycation end product detection are though limited and solely measure total glycation. This study describes a new epitope-mapped single chain variable fragment, D1-B2, against carboxymethyllysine, produced from a phage library that was constructed from mouse immunizations. The phage library was selected against advanced glycation end product targets using a phage display platform. Characterization of its binding pattern was performed using large synthetic glycated peptide and protein libraries displayed on microarray slides. D1-B2 showed a preference for an aspartic acid, three positions N-terminally from a carboxymethyllysine residue and also bound to a broad collection of glycated proteins. Positive immunohistochemical staining of mouse atherosclerotic plaques and of a tissue microarray of human pancreatic tumors confirmed the usability of the new scFv for advanced glycation end product detection in tissues. This study demonstrates a promising methodology for high-throughput generation of epitope-mapped monoclonal antibodies against AGE.

A novel monoclonal antibody targeting carboxymethyllysine, an advanced glycation end product in atherosclerosis and pancreatic cancer

PubMed Central

Wendel, Ulrika; Persson, Nina; Risinger, Christian; Bengtsson, Eva; Nodin, Björn; Danielsson, Lena; Welinder, Charlotte; Nordin Fredrikson, Gunilla

2018-01-01

Advanced glycation end products are formed by non-enzymatic reactions between proteins and carbohydrates, causing irreversible lysine and arginine alterations that severely affect protein structure and function. The resulting modifications induce inflammation by binding to scavenger receptors. An increase in advanced glycation end products is observed in a number of diseases e.g. atherosclerosis and cancer. Since advanced glycation end products also are present in healthy individuals, their detection and quantification are of great importance for usage as potential biomarkers. Current methods for advanced glycation end product detection are though limited and solely measure total glycation. This study describes a new epitope-mapped single chain variable fragment, D1-B2, against carboxymethyllysine, produced from a phage library that was constructed from mouse immunizations. The phage library was selected against advanced glycation end product targets using a phage display platform. Characterization of its binding pattern was performed using large synthetic glycated peptide and protein libraries displayed on microarray slides. D1-B2 showed a preference for an aspartic acid, three positions N-terminally from a carboxymethyllysine residue and also bound to a broad collection of glycated proteins. Positive immunohistochemical staining of mouse atherosclerotic plaques and of a tissue microarray of human pancreatic tumors confirmed the usability of the new scFv for advanced glycation end product detection in tissues. This study demonstrates a promising methodology for high-throughput generation of epitope-mapped monoclonal antibodies against AGE. PMID:29420566

Polyadenylation state microarray (PASTA) analysis.

PubMed

Beilharz, Traude H; Preiss, Thomas

2011-01-01

Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

PubMed Central

Sato, Fumiaki; Tsuchiya, Soken; Terasawa, Kazuya; Tsujimoto, Gozoh

2009-01-01

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems. PMID:19436744

Living Cell Microarrays: An Overview of Concepts

PubMed Central

Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

2016-01-01

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

PubMed

Zhang, Zhe; Fenstermacher, David

2005-01-01

Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

Faucher, Sebastien P; Shuman, Howard A

2013-01-01

The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.

Evaluation of the testicular toxicity of prenatal exposure to bisphenol A based on microarray analysis combined with MeSH annotation.

PubMed

Tainaka, Hitoshi; Takahashi, Hikari; Umezawa, Masakazu; Tanaka, Hiromitsu; Nishimune, Yoshitake; Oshio, Shigeru; Takeda, Ken

2012-01-01

Bisphenol A (BPA) is known to be an endocrine disruptor that affects the development of reproductive system. The aim of the present study was to investigate a group of testicular genes dysregulated by prenatal exposure to BPA. Pregnant ICR mice were treated with BPA by subcutaneous administration on days 7 and 14 of pregnancy. Tissue and blood samples were collected from 6-week-old male offspring. Testes were subjected to gene expression analysis using a testis-specific microarray (Testis2), consisting of 2,482 mouse cDNA clones annotated with Medical Subject Headings (MeSH) terms indicative of testicular components and functions. To interpret the microarray data, we used the MeSH terms significantly associated with the altered genes. As a result, MeSH terms related to androgens and Sertoli cells were extracted in BPA-treated groups. Among the genes related to Sertoli cells, downregulation of Msi1h, Ncoa1, Nid1, Hspb2, and Gata6 were detected in the testis of mice treated with BPA (twice administered 50 mg/kg). The MeSH terms associated with this group of genes may provide useful means to interpret the testicular toxicity of BPA. This article concludes that prenatal BPA exposure downregulates expression of genes associated with Sertoli cell function and affects the reproductive function of male offspring. Additionally, a method using MeSH to extract a group of genes was useful for predicting the testicular and reproductive toxicity of prenatal BPA exposure.

Identification of genes modulated in rheumatoid arthritis using complementary DNA microarray analysis of lymphoblastoid B cell lines from disease-discordant monozygotic twins.

PubMed

Haas, Christian S; Creighton, Chad J; Pi, Xiujun; Maine, Ira; Koch, Alisa E; Haines, G Kenneth; Ling, Song; Chinnaiyan, Arul M; Holoshitz, Joseph

2006-07-01

To identify disease-specific gene expression profiles in patients with rheumatoid arthritis (RA), using complementary DNA (cDNA) microarray analyses on lymphoblastoid B cell lines (LCLs) derived from RA-discordant monozygotic (MZ) twins. The cDNA was prepared from LCLs derived from the peripheral blood of 11 pairs of RA-discordant MZ twins. The RA twin cDNA was labeled with cy5 fluorescent dye, and the cDNA of the healthy co-twin was labeled with cy3. To determine relative expression profiles, cDNA from each twin pair was combined and hybridized on 20,000-element microarray chips. Immunohistochemistry and real-time polymerase chain reaction were used to detect the expression of selected gene products in synovial tissue from patients with RA compared with patients with osteoarthritis and normal healthy controls. In RA twin LCLs compared with healthy co-twin LCLs, 1,163 transcripts were significantly differentially expressed. Of these, 747 were overexpressed and 416 were underexpressed. Gene ontology analysis revealed many genes known to play a role in apoptosis, angiogenesis, proteolysis, and signaling. The 3 most significantly overexpressed genes were laeverin (a novel enzyme with sequence homology to CD13), 11beta-hydroxysteroid dehydrogenase type 2 (a steroid pathway enzyme), and cysteine-rich, angiogenic inducer 61 (a known angiogenic factor). The products of these genes, heretofore uncharacterized in RA, were all abundantly expressed in RA synovial tissues. Microarray cDNA analysis of peripheral blood-derived LCLs from well-controlled patient populations is a useful tool to detect RA-relevant genes and could help in identifying novel therapeutic targets.

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

Gene Profiling in Experimental Models of Eye Growth: Clues to Myopia Pathogenesis

PubMed Central

Stone, Richard A.; Khurana, Tejvir S.

2010-01-01

To understand the complex regulatory pathways that underlie the development of refractive errors, expression profiling has evaluated gene expression in ocular tissues of well-characterized experimental models that alter postnatal eye growth and induce refractive errors. Derived from a variety of platforms (e.g. differential display, spotted microarrays or Affymetrix GeneChips), gene expression patterns are now being identified in species that include chicken, mouse and primate. Reconciling available results is hindered by varied experimental designs and analytical/statistical features. Continued application of these methods offers promise to provide the much-needed mechanistic framework to develop therapies to normalize refractive development in children. PMID:20363242

Expression of truncated Int6/eIF3e in mammary alveolar epithelium leads to persistent hyperplasia and tumorigenesis

PubMed Central

Mack, David L; Boulanger, Corinne A; Callahan, Robert; Smith, Gilbert H

2007-01-01

Introduction Int6 has been shown to be an interactive participant with the protein translation initiation complex eIF3, the COP9 signalosome and the regulatory lid of the 26S proteasome. Insertion of mouse mammary tumor virus into the Int6 locus creates a C-terminally truncated form of the protein. Expression of the truncated form of Int6 (Int6sh) in stably transfected human and mouse mammary epithelial cell lines leads to cellular transformation. In addition, decreased expression of Int6/eIF3e is observed in approximately one third of all human breast carcinomas. Methods To validate that Int6sh has transforming activity in vivo, a transgenic mouse model was designed using the whey acidic protein (Wap) promoter to target expression of truncated Int6 to differentiating alveolar epithelial cells in the mammary gland. Microarray analyses were performed on normal, premalignant and malignant WapInt6sh expressing tissues. Results Mammary tumors developed in 42% of WapInt6sh heterozygous parous females at an average age of 18 months. In WapInt6sh mice, the contralateral mammary glands from both tumorous and non-tumorous tissues contained widespread focal alveolar hyperplasia. Only 4% of WapInt6sh non-breeding females developed tumors by 2 years of age. The Wap promoter is active only during estrus in the mammary tissue of cycling non-pregnant mice. Microarray analyses of mammary tissues demonstrated that Int6sh expression in the alveolar tissue altered the mammary transcriptome in a specific manner that was detectable even in the first pregnancy. This Int6sh-specific transcriptome pattern subsequently persisted in both the Int6sh-expressing alveolar hyperplasia and mammary tumors. These observations are consistent with the conclusion that WapInt6sh-expressing alveolar cells survive involution following the cessation of lactation, and subsequently give rise to the mammary tumors that arise in aging multiparous females. Conclusion These observations provide direct in vivo evidence that mammary-specific expression of the Int6sh truncation leads to persistence of alveolar hyperplasia with the accompanying increased predisposition to mammary tumorigenesis. PMID:17626637

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), ...

Expression profiling of microRNAs in human bone tissue from postmenopausal women.

PubMed

De-Ugarte, Laura; Serra-Vinardell, Jenny; Nonell, Lara; Balcells, Susana; Arnal, Magdalena; Nogues, Xavier; Mellibovsky, Leonardo; Grinberg, Daniel; Diez-Perez, Adolfo; Garcia-Giralt, Natalia

2018-01-01

Bone tissue is composed of several cell types, which express their own microRNAs (miRNAs) that will play a role in cell function. The set of total miRNAs expressed in all cell types configures the specific signature of the bone tissue in one physiological condition. The aim of this study was to explore the miRNA expression profile of bone tissue from postmenopausal women. Tissue was obtained from trabecular bone and was analyzed in fresh conditions (n = 6). Primary osteoblasts were also obtained from trabecular bone (n = 4) and human osteoclasts were obtained from monocyte precursors after in vitro differentiation (n = 5). MicroRNA expression profiling was obtained for each sample by microarray and a global miRNA analysis was performed combining the data acquired in all the microarray experiments. From the 641 miRNAs detected in bone tissue samples, 346 (54%) were present in osteoblasts and/or osteoclasts. The other 46% were not identified in any of the bone cells analyzed. Intersection of osteoblast and osteoclast arrays identified 101 miRNAs shared by both cell types, which accounts for 30-40% of miRNAs detected in these cells. In osteoblasts, 266 miRNAs were detected, of which 243 (91%) were also present in the total bone array, representing 38% of all bone miRNAs. In osteoclasts, 340 miRNAs were detected, of which 196 (58%) were also present in the bone tissue array, representing 31% of all miRNAs detected in total bone. These analyses provide an overview of miRNAs expressed in bone tissue, broadening our knowledge in the microRNA field.

A mixture model-based approach to the clustering of microarray expression data.

PubMed

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

Facile generation of cell microarrays using vacuum degassing and coverslip sweeping.

PubMed

Wang, Min S; Luo, Zhen; Cherukuri, Sundar; Nitin, Nitin

2014-07-15

A simple method to generate cell microarrays with high-percentage well occupancy and well-defined cell confinement is presented. This method uses a synergistic combination of vacuum degassing and coverslip sweeping. The vacuum degassing step dislodges air bubbles from the microwells, which in turn enables the cells to enter the microwells, while the physical sweeping step using a glass coverslip removes the excess cells outside the microwells. This low-cost preparation method provides a simple solution to generating cell microarrays that can be performed in basic research laboratories and point-of-care settings for routine cell-based screening assays. Copyright © 2014 Elsevier Inc. All rights reserved.

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

PubMed

Tong, Dong Ling; Schierz, Amanda C

2011-09-01

Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the unpreprocessed microarray data as well as extracting known biologically significant genes. We also show that assessing the biological significance of genes based on classification accuracy may be misleading and though the GANN's set of extra genes prove to be more statistically significant than those selected by other methods, a biological assessment of these genes is highly recommended to confirm their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

PubMed Central

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-01-01

Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124

High‐throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Daley, Frances; Zabaglo, Lila; McDuffus, Leigh‐Anne; Blows, Fiona; Coulson, Penny; Raza Ali, H; Benitez, Javier; Milne, Roger; Brenner, Herman; Stegmaier, Christa; Mannermaa, Arto; Chang‐Claude, Jenny; Rudolph, Anja; Sinn, Peter; Couch, Fergus J; Tollenaar, Rob A.E.M.; Devilee, Peter; Figueroa, Jonine; Sherman, Mark E; Lissowska, Jolanta; Hewitt, Stephen; Eccles, Diana; Hooning, Maartje J; Hollestelle, Antoinette; WM Martens, John; HM van Deurzen, Carolien; Investigators, kConFab; Bolla, Manjeet K; Wang, Qin; Jones, Michael; Schoemaker, Minouk; Broeks, Annegien; van Leeuwen, Flora E; Van't Veer, Laura; Swerdlow, Anthony J; Orr, Nick; Dowsett, Mitch; Easton, Douglas; Schmidt, Marjanka K; Pharoah, Paul D; Garcia‐Closas, Montserrat

2016-01-01

Abstract Automated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance. PMID:27499923

Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis

EPA Science Inventory

- Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to two widely-used engineered metal oxide nanoparticles, titanium dioxide (nano-titanium) and cerium dioxide (nano-cerium). Microarray analyses confirmed that e...

Met Nuclear Localization and Signaling in Breast Cancer

DTIC Science & Technology

2006-05-01

and in germinal regions of many tissues using 4 unique antibodies . Cell fractionation reveals a 60kDa band recognized by C-terminal Met antibodies ...cascades such as Gab1 , Grb2 and PI3K, leading to proliferation, scattering, increased motility, invasion and branching morphogenesis (reviewed in (2...Identification of Met antibodies for use on tissue microarray of normal and cancerous cells, Months 12-24 Task 2. Definition of the domain

Development and validation of a mixed-tissue oligonucleotide DNA microarray for Atlantic bluefin tuna, Thunnus thynnus (Linnaeus, 1758).

PubMed

Trumbić, Željka; Bekaert, Michaël; Taggart, John B; Bron, James E; Gharbi, Karim; Mladineo, Ivona

2015-11-25

The largest of the tuna species, Atlantic bluefin tuna (Thunnus thynnus), inhabits the North Atlantic Ocean and the Mediterranean Sea and is considered to be an endangered species, largely a consequence of overfishing. T. thynnus aquaculture, referred to as fattening or farming, is a capture based activity dependent on yearly renewal from the wild. Thus, the development of aquaculture practices independent of wild resources can provide an important contribution towards ensuring security and sustainability of this species in the longer-term. The development of such practices is today greatly assisted by large scale transcriptomic studies. We have used pyrosequencing technology to sequence a mixed-tissue normalised cDNA library, derived from adult T. thynnus. A total of 976,904 raw sequence reads were assembled into 33,105 unique transcripts having a mean length of 893 bases and an N50 of 870. Of these, 33.4% showed similarity to known proteins or gene transcripts and 86.6% of them were matched to the congeneric Pacific bluefin tuna (Thunnus orientalis) genome, compared to 70.3% for the more distantly related Nile tilapia (Oreochromis niloticus) genome. Transcript sequences were used to develop a novel 15 K Agilent oligonucleotide DNA microarray for T. thynnus and comparative tissue gene expression profiles were inferred for gill, heart, liver, ovaries and testes. Functional contrasts were strongest between gills and ovaries. Gills were particularly associated with immune system, signal transduction and cell communication, while ovaries displayed signatures of glycan biosynthesis, nucleotide metabolism, transcription, translation, replication and repair. Sequence data generated from a novel mixed-tissue T. thynnus cDNA library provide an important transcriptomic resource that can be further employed for study of various aspects of T. thynnus ecology and genomics, with strong applications in aquaculture. Tissue-specific gene expression profiles inferred through the use of novel oligo-microarray can serve in the design of new and more focused transcriptomic studies for future research of tuna physiology and assessment of the welfare in a production environment.

The tissue microarray data exchange specification: A document type definition to validate and enhance XML data

PubMed Central

Nohle, David G; Ayers, Leona W

2005-01-01

Background The Association for Pathology Informatics (API) Extensible Mark-up Language (XML) TMA Data Exchange Specification (TMA DES) proposed in April 2003 provides a community-based, open source tool for sharing tissue microarray (TMA) data in a common format. Each tissue core within an array has separate data including digital images; therefore an organized, common approach to produce, navigate and publish such data facilitates viewing, sharing and merging TMA data from different laboratories. The AIDS and Cancer Specimen Resource (ACSR) is a HIV/AIDS tissue bank consortium sponsored by the National Cancer Institute (NCI) Division of Cancer Treatment and Diagnosis (DCTD). The ACSR offers HIV-related malignancies and uninfected control tissues in microarrays (TMA) accompanied by de-identified clinical data to approved researchers. Exporting our TMA data into the proposed API specified format offers an opportunity to evaluate the API specification in an applied setting and to explore its usefulness. Results A document type definition (DTD) that governs the allowed common data elements (CDE) in TMA DES export XML files was written, tested and evolved and is in routine use by the ACSR. This DTD defines TMA DES CDEs which are implemented in an external file that can be supplemented by internal DTD extensions for locally defined TMA data elements (LDE). Conclusion ACSR implementation of the TMA DES demonstrated the utility of the specification and allowed application of a DTD to validate the language of the API specified XML elements and to identify possible enhancements within our TMA data management application. Improvements to the specification have additionally been suggested by our experience in importing other institution's exported TMA data. Enhancements to TMA DES to remove ambiguous situations and clarify the data should be considered. Better specified identifiers and hierarchical relationships will make automatic use of the data possible. Our tool can be used to reorder data and add identifiers; upgrading data for changes in the specification can be automatically accomplished. Using a DTD (optionally reflecting our proposed enhancements) can provide stronger validation of exported TMA data. PMID:15871741

High Frequency of Chlamydia trachomatis Mixed Infections Detected by Microarray Assay in South American Samples.

PubMed

Gallo Vaulet, Lucía; Entrocassi, Carolina; Portu, Ana I; Castro, Erica; Di Bartolomeo, Susana; Ruettger, Anke; Sachse, Konrad; Rodriguez Fermepin, Marcelo

2016-01-01

Chlamydia trachomatis is one of the most common sexually transmitted infections worldwide. Based on sequence variation in the ompA gene encoding the major outer membrane protein, the genotyping scheme distinguishes 17 recognized genotypes, i.e. A, B, Ba, C, D, Da, E, F, G, H, I, Ia, J, K, L1, L2, and L3. Genotyping is an important tool for epidemiological tracking of C. trachomatis infections, including the revelation of transmission pathways and association with tissue tropism and pathogenicity. Moreover, genotyping can be useful for clinicians to establish the correct treatment when LGV strains are detected. Recently a microarray assay was described that offers several advantages, such as rapidity, ease of standardization and detection of mixed infections. The aim of this study was to evaluate the performance of the DNA microarray-based assay for C. trachomatis genotyping of clinical samples already typed by PCR-RFLP from South America. The agreement between both typing techniques was 90.05% and the overall genotype distribution obtained with both techniques was similar. Detection of mixed-genotype infections was significantly higher using the microarray assay (8.4% of cases) compared to PCR-RFLP (0.5%). Among 178 samples, the microarray assay identified 10 ompA genotypes, i.e. D, Da, E, F, G, H, I, J, K and L2. The most predominant type was genotype E, followed by D and F.

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

A putative OTU domain-containing protein 1 deubiquitinating enzyme is differentially expressed in thyroid cancer and identifies less-aggressive tumours

PubMed Central

Carneiro, A P; Reis, C F; Morari, E C; Maia, Y C P; Nascimento, R; Bonatto, J M C; de Souza, M A; Goulart, L R; Ward, L S

2014-01-01

Background: This study aimed to identify novel biomarkers for thyroid carcinoma diagnosis and prognosis. Methods: We have constructed a human single-chain variable fragment (scFv) antibody library that was selected against tumour thyroid cells using the BRASIL method (biopanning and rapid analysis of selective interactive ligands) and phage display technology. Results: One highly reactive clone, scFv-C1, with specific binding to papillary thyroid tumour proteins was confirmed by ELISA, which was further tested against a tissue microarray that comprised of 229 thyroid tissues, including: 110 carcinomas (38 papillary thyroid carcinomas (PTCs), 42 follicular carcinomas, 30 follicular variants of PTC), 18 normal thyroid tissues, 49 nodular goitres (NG) and 52 follicular adenomas. The scFv-C1 was able to distinguish carcinomas from benign lesions (P=0.0001) and reacted preferentially against T1 and T2 tumour stages (P=0.0108). We have further identified an OTU domain-containing protein 1, DUBA-7 deubiquitinating enzyme as the scFv-binding antigen using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Conclusions: The strategy of screening and identifying a cell-surface-binding antibody against thyroid tissues was highly effective and resulted in a useful biomarker that recognises malignancy among thyroid nodules and may help identify lower-risk cases that can benefit from less-aggressive management. PMID:24937664

Recommendations for the use of microarrays in prenatal diagnosis.

PubMed

Suela, Javier; López-Expósito, Isabel; Querejeta, María Eugenia; Martorell, Rosa; Cuatrecasas, Esther; Armengol, Lluis; Antolín, Eugenia; Domínguez Garrido, Elena; Trujillo-Tiebas, María José; Rosell, Jordi; García Planells, Javier; Cigudosa, Juan Cruz

2017-04-07

Microarray technology, recently implemented in international prenatal diagnosis systems, has become one of the main techniques in this field in terms of detection rate and objectivity of the results. This guideline attempts to provide background information on this technology, including technical and diagnostic aspects to be considered. Specifically, this guideline defines: the different prenatal sample types to be used, as well as their characteristics (chorionic villi samples, amniotic fluid, fetal cord blood or miscarriage tissue material); variant reporting policies (including variants of uncertain significance) to be considered in informed consents and prenatal microarray reports; microarray limitations inherent to the technique and which must be taken into account when recommending microarray testing for diagnosis; a detailed clinical algorithm recommending the use of microarray testing and its introduction into routine clinical practice within the context of other genetic tests, including pregnancies in families with a genetic history or specific syndrome suspicion, first trimester increased nuchal translucency or second trimester heart malformation and ultrasound findings not related to a known or specific syndrome. This guideline has been coordinated by the Spanish Association for Prenatal Diagnosis (AEDP, «Asociación Española de Diagnóstico Prenatal»), the Spanish Human Genetics Association (AEGH, «Asociación Española de Genética Humana») and the Spanish Society of Clinical Genetics and Dysmorphology (SEGCyD, «Sociedad Española de Genética Clínica y Dismorfología»). Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica

PubMed Central

Guard, Jean; Sanchez-Ingunza, Roxana; Morales, Cesar; Stewart, Tod; Liljebjelke, Karen; Kessel, JoAnn; Ingram, Kim; Jones, Deana; Jackson, Charlene; Fedorka-Cray, Paula; Frye, Jonathan; Gast, Richard; Hinton, Arthur

2012-01-01

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research. PMID:22998607

Pro-oncogene Pokemon promotes breast cancer progression by upregulating survivin expression.

PubMed

Zu, Xuyu; Ma, Jun; Liu, Hongxia; Liu, Feng; Tan, Chunyan; Yu, Lingling; Wang, Jue; Xie, Zhenhua; Cao, Deliang; Jiang, Yuyang

2011-03-10

Pokemon is an oncogenic transcription factor involved in cell growth, differentiation and oncogenesis, but little is known about its role in human breast cancer. In this study, we aimed to reveal the role of Pokemon in breast cancer progression and patient survival and to understand its underlying mechanisms. Tissue microarray analysis of breast cancer tissues from patients with complete clinicopathological data and more than 20 years of follow-up were used to evaluate Pokemon expression and its correlation with the progression and prognosis of the disease. DNA microarray analysis of MCF-7 cells that overexpress Pokemon was used to identify Pokemon target genes. Chromatin immunoprecipitation (ChIP) and site-directed mutagenesis were utilized to determine how Pokemon regulates survivin expression, a target gene. Pokemon was found to be overexpressed in 158 (86.8%) of 182 breast cancer tissues, and its expression was correlated with tumor size (P = 0.0148) and lymph node metastasis (P = 0.0014). Pokemon expression led to worse overall (n = 175, P = 0.01) and disease-related (n = 79, P = 0.0134) patient survival. DNA microarray analyses revealed that in MCF-7 breast cancer cells, Pokemon regulates the expression of at least 121 genes involved in several signaling and metabolic pathways, including anti-apoptotic survivin. In clinical specimens, Pokemon and survivin expression were highly correlated (n = 49, r = 0.6799, P < 0.0001). ChIP and site-directed mutagenesis indicated that Pokemon induces survivin expression by binding to the GT boxes in its promoter. Pokemon promotes breast cancer progression by upregulating survivin expression and thus may be a potential target for the treatment of this malignancy.

In-vitro analysis of Quantum Molecular Resonance effects on human mesenchymal stromal cells

PubMed Central

Sella, Sabrina; Adami, Valentina; Amati, Eliana; Bernardi, Martina; Chieregato, Katia; Gatto, Pamela; Menarin, Martina; Pozzato, Alessandro; Pozzato, Gianantonio; Astori, Giuseppe

2018-01-01

Electromagnetic fields play an essential role in cellular functions interfering with cellular pathways and tissue physiology. In this context, Quantum Molecular Resonance (QMR) produces waves with a specific form at high-frequencies (4–64 MHz) and low intensity through electric fields. We evaluated the effects of QMR stimulation on bone marrow derived mesenchymal stromal cells (MSC). MSC were treated with QMR for 10 minutes for 4 consecutive days for 2 weeks at different nominal powers. Cell morphology, phenotype, multilineage differentiation, viability and proliferation were investigated. QMR effects were further investigated by cDNA microarray validated by real-time PCR. After 1 and 2 weeks of QMR treatment morphology, phenotype and multilineage differentiation were maintained and no alteration of cellular viability and proliferation were observed between treated MSC samples and controls. cDNA microarray analysis evidenced more transcriptional changes on cells treated at 40 nominal power than 80 ones. The main enrichment lists belonged to development processes, regulation of phosphorylation, regulation of cellular pathways including metabolism, kinase activity and cellular organization. Real-time PCR confirmed significant increased expression of MMP1, PLAT and ARHGAP22 genes while A2M gene showed decreased expression in treated cells compared to controls. Interestingly, differentially regulated MMP1, PLAT and A2M genes are involved in the extracellular matrix (ECM) remodelling through the fibrinolytic system that is also implicated in embryogenesis, wound healing and angiogenesis. In our model QMR-treated MSC maintained unaltered cell phenotype, viability, proliferation and the ability to differentiate into bone, cartilage and adipose tissue. Microarray analysis may suggest an involvement of QMR treatment in angiogenesis and in tissue regeneration probably through ECM remodelling. PMID:29293552

Genome Consortium for Active Teaching: Meeting the Goals of BIO2010

PubMed Central

Ledbetter, Mary Lee S.; Hoopes, Laura L.M.; Eckdahl, Todd T.; Heyer, Laurie J.; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students. PMID:17548873

Genome Consortium for Active Teaching: meeting the goals of BIO2010.

PubMed

Campbell, A Malcolm; Ledbetter, Mary Lee S; Hoopes, Laura L M; Eckdahl, Todd T; Heyer, Laurie J; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students.

Support vector machine and principal component analysis for microarray data classification

NASA Astrophysics Data System (ADS)

Astuti, Widi; Adiwijaya

2018-03-01

Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

Psychiatric Brain Banking: Three Perspectives on Current Trends and Future Directions

PubMed Central

Deep-Soboslay, Amy; Benes, Francine M.; Haroutunian, Vahram; Ellis, Justin K.; Kleinman, Joel E.; Hyde, Thomas M.

2011-01-01

Introduction The study of postmortem human brain tissue is central to the advancement of the neurobiological studies of psychiatric illness, particularly for the study of brain-specific isoforms and molecules. Methods The state-of-the-art methods and recommendations for maintaining a successful brain bank for psychiatric disorders are discussed, using the convergence of viewpoints from three brain collections, the National Institute of Mental Health Brain Collection (NIMH), the Harvard Brain Tissue Resource Center (HBTRC), and the Mt. Sinai School of Medicine Brain Bank (MSSM-BB), with diverse research interests and divergent approaches to tissue acquisition. Results While the NIMH obtains donations from medical examiners for its collection, and places particular emphasis on clinical diagnosis, toxicology, and building lifespan control cohorts, the HBTRC is uniquely designed as a repository whose sole purpose is to collect large-volume, high quality brain tissue from community-based donors based on relationships across an expansive nationwide network, and places emphasis on the accessibility of its bank in disseminating tissue and related data to research groups worldwide. The MSSM-BB collection has shown that, with dedication, prospective recruitment is a successful approach to tissue donation, and places particular emphasis on rigorous clinical diagnosis through antemortem contact with donors. The MSSM-BB places great importance on stereological tissue sampling methods for neuroanatomical studies, and frozen tissue sampling approaches that enable multiple assessments (RNA, DNA, protein, enzyme activity, binding, etc.) of the same tissue block. Promising scientific approaches for elucidating the molecular and cellular pathways in brain that may contribute to schizophrenia and/or bipolar disorder, such as cell culture techniques and microarray-based gene expression and genotyping studies are briefly discussed. Conclusions Despite unique perspectives from three established brain collections, there is a consensus that (1) diverse strategies for tissue acquisition, (2) rigor in tissue and diagnostic characterization, (3) the importance of sample accessibility, and (4) continual application of innovative scientific approaches to the study of brain tissue are all integral to the success and future of psychiatric brain banking. The future of neuropsychiatric research depends upon in the availability of high quality brain specimens from large numbers of subjects, including non-psychiatric controls. PMID:20673875

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method.

PubMed

Bengtsson, Henrik; Hössjer, Ola

2006-03-01

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method. We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions.

PubMed

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions

PubMed Central

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity. PMID:25191551

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

PubMed

Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

2014-01-01

Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed heat shock protein (Hsp) and cardiomyopathy genes (Bag3, Cryab, Kras, Emd, Plec), which was significantly replicated using separate failing heart and liver gene expression datasets in humans, thus revealing a conserved functional role for Hsp genes in cardiovascular disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

PubMed

Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

2010-10-07

Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

PubMed Central

2010-01-01

Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet-sensitive changes in constituent genes, as well as strong correlations between gene expression and plasma markers of metabolic syndrome independent of the dietary effect. Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of analysis has the potential to generate novel transcriptome-based biomarkers of disease. PMID:20929581

Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans

PubMed Central

Gong, Ai-Xiu; Zhang, Jing-Han; Li, Jing; Wu, Jun; Wang, Lin; Miao, Deng-Shun

2017-01-01

There are anatomical and functional differences between human dental pulp (DP) and periodontal ligament (PDL). However, the molecular biological differences and function of these tissues are poorly understood. In the present study, we employed a cDNA microarray array to screen for differentially expressed genes (DEGs) between human DP and PDL tissues, and used the online software WebGestalt to perform the functional analysis of the DEGs. In addition, the STRING database and KEGG pathway analysis were applied for interaction network and pathway analysis of the DEGs. DP and PDL samples were obtained from permanent premolars (n=16) extracted for orthodontic purposes. The results of the microarray assay were confirmed by RT-qPCR. The DEGs were found to be significantly associated with the extracellular matrix and focal adhesion. A total of 10 genes were selected to confirm the results. The mRNA levels of integrin alpha 4 (ITGA4), integrin alpha 8 (ITGA8), neurexin 1 (NRXN1) and contactin 1 (CNTN1) were significantly higher in the DP than in the PDL tissues. However, the levels of collagen type XI alpha 1 (COL11A1), aggrecan (ACAN), collagen type VI alpha 1 (COL6A1), chondroadherin (CHAD), laminin gamma 2 (LAMC2) and laminin alpha 3 (LAMA3) were higher in the PDL than in the DP samples. The gene expression profiles provide novel insight into the characterization of DP and PDL tissues, and contribute to our understanding of the potential molecular mechanisms of dental tissue mineralization and regeneration. PMID:28713908

An alternative method to amplify RNA without loss of signal conservation for expression analysis with a proteinase DNA microarray in the ArrayTube format.

PubMed

Schüler, Susann; Wenz, Ingrid; Wiederanders, B; Slickers, P; Ehricht, R

2006-06-12

Recent developments in DNA microarray technology led to a variety of open and closed devices and systems including high and low density microarrays for high-throughput screening applications as well as microarrays of lower density for specific diagnostic purposes. Beside predefined microarrays for specific applications manufacturers offer the production of custom-designed microarrays adapted to customers' wishes. Array based assays demand complex procedures including several steps for sample preparation (RNA extraction, amplification and sample labelling), hybridization and detection, thus leading to a high variability between several approaches and resulting in the necessity of extensive standardization and normalization procedures. In the present work a custom designed human proteinase DNA microarray of lower density in ArrayTube format was established. This highly economic open platform only requires standard laboratory equipment and allows the study of the molecular regulation of cell behaviour by proteinases. We established a procedure for sample preparation and hybridization and verified the array based gene expression profile by quantitative real-time PCR (QRT-PCR). Moreover, we compared the results with the well established Affymetrix microarray. By application of standard labelling procedures with e.g. Klenow fragment exo-, single primer amplification (SPA) or In Vitro Transcription (IVT) we noticed a loss of signal conservation for some genes. To overcome this problem we developed a protocol in accordance with the SPA protocol, in which we included target specific primers designed individually for each spotted oligomer. Here we present a complete array based assay in which only the specific transcripts of interest are amplified in parallel and in a linear manner. The array represents a proof of principle which can be adapted to other species as well. As the designed protocol for amplifying mRNA starts from as little as 100 ng total RNA, it presents an alternative method for detecting even low expressed genes by microarray experiments in a highly reproducible and sensitive manner. Preservation of signal integrity is demonstrated out by QRT-PCR measurements. The little amounts of total RNA necessary for the analyses make this method applicable for investigations with limited material as in clinical samples from, for example, organ or tumour biopsies. Those are arguments in favour of the high potential of our assay compared to established procedures for amplification within the field of diagnostic expression profiling. Nevertheless, the screening character of microarray data must be mentioned, and independent methods should verify the results.

Increasing consistency of disease biomarker prediction across datasets.

PubMed

Chikina, Maria D; Sealfon, Stuart C

2014-01-01

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern.

Strategies for cell manipulation and skeletal tissue engineering using high-throughput polymer blend formulation and microarray techniques.

PubMed

Khan, Ferdous; Tare, Rahul S; Kanczler, Janos M; Oreffo, Richard O C; Bradley, Mark

2010-03-01

A combination of high-throughput material formulation and microarray techniques were synergistically applied for the efficient analysis of the biological functionality of 135 binary polymer blends. This allowed the identification of cell-compatible biopolymers permissive for human skeletal stem cell growth in both in vitro and in vivo applications. The blended polymeric materials were developed from commercially available, inexpensive and well characterised biodegradable polymers, which on their own lacked both the structural requirements of a scaffold material and, critically, the ability to facilitate cell growth. Blends identified here proved excellent templates for cell attachment, and in addition, a number of blends displayed remarkable bone-like architecture and facilitated bone regeneration by providing 3D biomimetic scaffolds for skeletal cell growth and osteogenic differentiation. This study demonstrates a unique strategy to generate and identify innovative materials with widespread application in cell biology as well as offering a new reparative platform strategy applicable to skeletal tissues. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

EPConDB: a web resource for gene expression related to pancreatic development, beta-cell function and diabetes.

PubMed

Mazzarelli, Joan M; Brestelli, John; Gorski, Regina K; Liu, Junmin; Manduchi, Elisabetta; Pinney, Deborah F; Schug, Jonathan; White, Peter; Kaestner, Klaus H; Stoeckert, Christian J

2007-01-01

EPConDB (http://www.cbil.upenn.edu/EPConDB) is a public web site that supports research in diabetes, pancreatic development and beta-cell function by providing information about genes expressed in cells of the pancreas. EPConDB displays expression profiles for individual genes and information about transcripts, promoter elements and transcription factor binding sites. Gene expression results are obtained from studies examining tissue expression, pancreatic development and growth, differentiation of insulin-producing cells, islet or beta-cell injury, and genetic models of impaired beta-cell function. The expression datasets are derived using different microarray platforms, including the BCBC PancChips and Affymetrix gene expression arrays. Other datasets include semi-quantitative RT-PCR and MPSS expression studies. For selected microarray studies, lists of differentially expressed genes, derived from PaGE analysis, are displayed on the site. EPConDB provides database queries and tools to examine the relationship between a gene, its transcriptional regulation, protein function and expression in pancreatic tissues.

Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis.

PubMed

Fagone, Paolo; Nicoletti, Ferdinando; Salvatorelli, Lucia; Musumeci, Giuseppe; Magro, Gaetano

2015-10-01

Recent immunohistochemical analyses have showed that cyclin D1 is expressed in soft tissue Ewing's sarcoma/peripheral neuroectodermal tumor (PNET) of childhood and adolescents, while it is undetectable in both embryonal and alveolar rhabdomyosarcoma. In the present paper, microarray analysis provided evidence of a significant upregulation of cyclin D1 in Ewing's sarcoma as compared to normal tissues. In addition, we confirmed our previous findings of a significant over-expression of cyclin D1 in Ewing sarcoma as compared to rhabdomyosarcoma. Bioinformatic analysis also allowed to identify some other genes, strongly correlated to cyclin D1, which, although not previously studied in pediatric tumors, could represent novel markers for the diagnosis and prognosis of Ewing's sarcoma/PNET. The data herein provided support not only the use of cyclin D1 as a diagnostic marker of Ewing sarcoma/PNET but also the possibility of using drugs targeting cyclin D1 as potential therapeutic strategies. Copyright © 2015 Elsevier GmbH. All rights reserved.

Meta-review of protein network regulating obesity between validated obesity candidate genes in the white adipose tissue of high-fat diet-induced obese C57BL/6J mice.

PubMed

Kim, Eunjung; Kim, Eun Jung; Seo, Seung-Won; Hur, Cheol-Goo; McGregor, Robin A; Choi, Myung-Sook

2014-01-01

Worldwide obesity and related comorbidities are increasing, but identifying new therapeutic targets remains a challenge. A plethora of microarray studies in diet-induced obesity models has provided large datasets of obesity associated genes. In this review, we describe an approach to examine the underlying molecular network regulating obesity, and we discuss interactions between obesity candidate genes. We conducted network analysis on functional protein-protein interactions associated with 25 obesity candidate genes identified in a literature-driven approach based on published microarray studies of diet-induced obesity. The obesity candidate genes were closely associated with lipid metabolism and inflammation. Peroxisome proliferator activated receptor gamma (Pparg) appeared to be a core obesity gene, and obesity candidate genes were highly interconnected, suggesting a coordinately regulated molecular network in adipose tissue. In conclusion, the current network analysis approach may help elucidate the underlying molecular network regulating obesity and identify anti-obesity targets for therapeutic intervention.

Low-Cost Peptide Microarrays for Mapping Continuous Antibody Epitopes.

PubMed

McBride, Ryan; Head, Steven R; Ordoukhanian, Phillip; Law, Mansun

2016-01-01

With the increasing need for understanding antibody specificity in antibody and vaccine research, pepscan assays provide a rapid method for mapping and profiling antibody responses to continuous epitopes. We have developed a relatively low-cost method to generate peptide microarray slides for studying antibody binding. Using a setup of an IntavisAG MultiPep RS peptide synthesizer, a Digilab MicroGrid II 600 microarray printer robot, and an InnoScan 1100 AL scanner, the method allows the interrogation of up to 1536 overlapping, alanine-scanning, and mutant peptides derived from the target antigens. Each peptide is tagged with a polyethylene glycol aminooxy terminus to improve peptide solubility, orientation, and conjugation efficiency to the slide surface.

Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.

PubMed

Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong

2017-03-01

The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC in the future. ii) Differentially expressed genes may be involved in the occurrence of GC via a variety of mechanisms. iii) CD44, CXXC5, MYH9, MALAT1 and other genes may have important implications for the occurrence and development of GC through the regulation, interaction, and mutual influence of circRNA-miRNA-mRNA via different mechanisms.

Adipose tissue transcriptome changes during obesity development in female dogs.

PubMed

Grant, Ryan W; Vester Boler, Brittany M; Ridge, Tonya K; Graves, Thomas K; Swanson, Kelly S

2011-03-29

During the development of obesity, adipose tissue undergoes major expansion and remodeling, but the biological processes involved in this transition are not well understood. The objective of this study was to analyze global gene expression profiles of adipose tissue in dogs, fed a high-fat diet, during the transition from a lean to obese phenotype. Nine female beagles (4.09 ± 0.64 yr; 8.48 ± 0.35 kg) were randomized to ad libitum feeding or body weight maintenance. Subcutaneous adipose tissue biopsy, blood, and dual x-ray absorptiometry measurements were collected at 0, 4, 8, 12, and 24 wk of feeding. Serum was analyzed for glucose, insulin, fructosamine, triglycerides, free fatty acids, adiponectin, and leptin. Formalin-fixed adipose tissue was used for determination of adipocyte size. Adipose RNA samples were hybridized to Affymetrix Canine 2.0 microarrays. Statistical analysis, using repeated-measures ANOVA, showed ad libitum feeding increased (P < 0.05) body weight (0 wk, 8.36 ± 0.34 kg; 24 wk, 14.64 ± 0.34 kg), body fat mass (0 wk, 1.36 ± 0.24 kg; 24 wk, 6.52 ± 0.24 kg), adipocyte size (0 wk, 114.66 ± 17.38 μm(2); 24 wk, 320.97 ± 0.18.17 μm(2)), and leptin (0 wk, 0.8 ± 1.0 ng/ml; 24 wk, 12.9 ± 1.0 ng/ml). Microarrays displayed 1,665 differentially expressed genes in adipose tissue as weight increased. Alterations were seen in adipose tissue homeostatic processes including metabolism, oxidative stress, mitochondrial homeostasis, and extracellular matrix. Adipose transcriptome changes highlight the dynamic and adaptive response to ad libitum feeding and obesity development.

Recovery of high-quality RNA from laser capture microdissected human and rodent pancreas.

PubMed

Butler, Alexandra E; Matveyenko, Aleksey V; Kirakossian, David; Park, Johanna; Gurlo, Tatyana; Butler, Peter C

Laser capture microdissection (LCM) is a powerful method to isolate specific populations of cells for subsequent analysis such as gene expression profiling, for example, microarrays or ribonucleic (RNA)-Seq. This technique has been applied to frozen as well as formalin-fixed, paraffin-embedded (FFPE) specimens with variable outcomes regarding quality and quantity of extracted RNA. The goal of the study was to develop the methods to isolate high-quality RNA from islets of Langerhans and pancreatic duct glands (PDG) isolated by LCM. We report an optimized protocol for frozen sections to minimize RNA degradation and maximize recovery of expected transcripts from the samples using quantitative real-time polymerase chain reaction (RT-PCR) by adding RNase inhibitors at multiple steps during the experiment. This technique reproducibly delivered intact RNA (RIN values 6-7). Using quantitative RT-PCR, the expected profiles of insulin, glucagon, mucin6 (Muc6), and cytokeratin-19 (CK-19) mRNA in PDGs and pancreatic islets were detected. The described experimental protocol for frozen pancreas tissue might also be useful for other tissues with moderate to high levels of intrinsic ribonuclease (RNase) activity.

Microarray Meta-Analysis Focused on the Response of Genes Involved in Redox Homeostasis to Diverse Abiotic Stresses in Rice

PubMed Central

de Abreu Neto, Joao B.; Frei, Michael

2016-01-01

Plants are exposed to a wide range of abiotic stresses (AS), which often occur in combination. Because physiological investigations typically focus on one stress, our understanding of unspecific stress responses remains limited. The plant redox homeostasis, i.e., the production and removal of reactive oxygen species (ROS), may be involved in many environmental stress conditions. Therefore, this study intended to identify genes, which are activated in diverse AS, focusing on ROS-related pathways. We conducted a meta-analysis (MA) of microarray experiments, focusing on rice. Transcriptome data were mined from public databases and fellow researchers, which represented 36 different experiments and investigated diverse AS, including ozone stress, drought, heat, cold, salinity, and mineral deficiencies/toxicities. To overcome the inherent artifacts of different MA methods, data were processed using Fisher, rOP, REM, and product of rank (GeneSelector), and genes identified by most approaches were considered as shared differentially expressed genes (DEGs). Two MA strategies were adopted: first, datasets were separated into shoot, root, and seedling experiments, and these tissues were analyzed separately to identify shared DEGs. Second, shoot and seedling experiments were classed into oxidative stress (OS), i.e., ozone and hydrogen peroxide treatments directly producing ROS in plant tissue, and other AS, in which ROS production is indirect. In all tissues and stress conditions, genes a priori considered as ROS-related were overrepresented among the DEGs, as they represented 4% of all expressed genes but 7–10% of the DEGs. The combined MA approach was substantially more conservative than individual MA methods and identified 1001 shared DEGs in shoots, 837 shared DEGs in root, and 1172 shared DEGs in seedlings. Within the OS and AS groups, 990 and 1727 shared DEGs were identified, respectively. In total, 311 genes were shared between OS and AS, including many regulatory genes. Combined co-expression analysis identified among those a cluster of 42 genes, many involved in the photosynthetic apparatus and responsive to drought, iron deficiency, arsenic toxicity, and ozone. Our data demonstrate the importance of redox homeostasis in plant stress responses and the power of MA to identify candidate genes underlying unspecific signaling pathways. PMID:26793229

Expression of spermidine/spermine N(1) -acetyl transferase (SSAT) in human prostate tissues is related to prostate cancer progression and metastasis.

PubMed

Huang, Wei; Eickhoff, Jens C; Mehraein-Ghomi, Farideh; Church, Dawn R; Wilding, George; Basu, Hirak S

2015-08-01

Prostate cancer (PCa) in many patients remains indolent for the rest of their lives, but in some patients, it progresses to lethal metastatic disease. Gleason score is the current clinical method for PCa prognosis. It cannot reliably identify aggressive PCa, when GS is ≤ 7. It is shown that oxidative stress plays a key role in PCa progression. We have shown that in cultured human PCa cells, an activation of spermidine/spermine N(1) -acetyl transferase (SSAT; EC 2.3.1.57) enzyme initiates a polyamine oxidation pathway and generates copious amounts of reactive oxygen species in polyamine-rich PCa cells. We used RNA in situ hybridization and immunohistochemistry methods to detect SSAT mRNA and protein expression in two tissue microarrays (TMA) created from patient's prostate tissues. We analyzed 423 patient's prostate tissues in the two TMAs. Our data show that there is a significant increase in both SSAT mRNA and the enzyme protein in the PCa cells as compared to their benign counterpart. This increase is even more pronounced in metastatic PCa tissues as compared to the PCa localized in the prostate. In the prostatectomy tissues from early-stage patients, the SSAT protein level is also high in the tissues obtained from the patients who ultimately progress to advanced metastatic disease. Based on these results combined with published data from our and other laboratories, we propose an activation of an autocrine feed-forward loop of PCa cell proliferation in the absence of androgen as a possible mechanism of castrate-resistant prostate cancer growth. © 2015 Wiley Periodicals, Inc.

mRNA-Based Parallel Detection of Active Methanotroph Populations by Use of a Diagnostic Microarray

PubMed Central

Bodrossy, Levente; Stralis-Pavese, Nancy; Konrad-Köszler, Marianne; Weilharter, Alexandra; Reichenauer, Thomas G.; Schöfer, David; Sessitsch, Angela

2006-01-01

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities. PMID:16461725

Quantitative proteomic analysis of cultured skin fibroblast cells derived from patients with triglyceride deposit cardiomyovasculopathy

PubMed Central

2013-01-01

Background Triglyceride deposit cardiomyovasculopathy (TGCV) is a rare disease, characterized by the massive accumulation of triglyceride (TG) in multiple tissues, especially skeletal muscle, heart muscle and the coronary artery. TGCV is caused by mutation of adipose triglyceride lipase, which is an essential molecule for the hydrolysis of TG. TGCV is at high risk for skeletal myopathy and heart dysfunction, and therefore premature death. Development of therapeutic methods for TGCV is highly desirable. This study aims to discover specific molecules responsible for TGCV pathogenesis. Methods To identify differentially expressed proteins in TGCV patient cells, the stable isotope labeling with amino acids in cell culture (SILAC) method coupled with LC-MS/MS was performed using skin fibroblast cells derived from two TGCV patients and three healthy volunteers. Altered protein expression in TGCV cells was confirmed using the selected reaction monitoring (SRM) method. Microarray-based transcriptome analysis was simultaneously performed to identify changes in gene expression in TGCV cells. Results Using SILAC proteomics, 4033 proteins were quantified, 53 of which showed significantly altered expression in both TGCV patient cells. Twenty altered proteins were chosen and confirmed using SRM. SRM analysis successfully quantified 14 proteins, 13 of which showed the same trend as SILAC proteomics. The altered protein expression data set was used in Ingenuity Pathway Analysis (IPA), and significant networks were identified. Several of these proteins have been previously implicated in lipid metabolism, while others represent new therapeutic targets or markers for TGCV. Microarray analysis quantified 20743 transcripts, and 252 genes showed significantly altered expression in both TGCV patient cells. Ten altered genes were chosen, 9 of which were successfully confirmed using quantitative RT-PCR. Biological networks of altered genes were analyzed using an IPA search. Conclusions We performed the SILAC- and SRM-based identification-through-confirmation study using skin fibroblast cells derived from TGCV patients, and first identified altered proteins specific for TGCV. Microarray analysis also identified changes in gene expression. The functional networks of the altered proteins and genes are discussed. Our findings will be exploited to elucidate the pathogenesis of TGCV and discover clinically relevant molecules for TGCV in the near future. PMID:24360150

Expansion of Multipotent Stem Cells from the Adult Human Brain

PubMed Central

Murrell, Wayne; Palmero, Emily; Bianco, John; Stangeland, Biljana; Joel, Mrinal; Paulson, Linda; Thiede, Bernd; Grieg, Zanina; Ramsnes, Ingunn; Skjellegrind, Håvard K.; Nygård, Ståle; Brandal, Petter; Sandberg, Cecilie; Vik-Mo, Einar; Palmero, Sheryl; Langmoen, Iver A.

2013-01-01

The discovery of stem cells in the adult human brain has revealed new possible scenarios for treatment of the sick or injured brain. Both clinical use of and preclinical research on human adult neural stem cells have, however, been seriously hampered by the fact that it has been impossible to passage these cells more than a very few times and with little expansion of cell numbers. Having explored a number of alternative culturing conditions we here present an efficient method for the establishment and propagation of human brain stem cells from whatever brain tissue samples we have tried. We describe virtually unlimited expansion of an authentic stem cell phenotype. Pluripotency proteins Sox2 and Oct4 are expressed without artificial induction. For the first time multipotency of adult human brain-derived stem cells is demonstrated beyond tissue boundaries. We characterize these cells in detail in vitro including microarray and proteomic approaches. Whilst clarification of these cells’ behavior is ongoing, results so far portend well for the future repair of tissues by transplantation of an adult patient’s own-derived stem cells. PMID:23967194

Expression of SET Protein in the Ovaries of Patients with Polycystic Ovary Syndrome

PubMed Central

Boqun, Xu; Xiaonan, Dai; YuGui, Cui; Lingling, Gao; Xue, Dai; Gao, Chao; Feiyang, Diao; Jiayin, Liu; Gao, Li; Li, Mei; Zhang, Yuan; Ma, Xiang

2013-01-01

Background. We previously found that expression of SET gene was up-regulated in polycystic ovaries by using microarray. It suggested that SET may be an attractive candidate regulator involved in the pathophysiology of polycystic ovary syndrome (PCOS). In this study, expression and cellular localization of SET protein were investigated in human polycystic and normal ovaries. Method. Ovarian tissues, six normal ovaries and six polycystic ovaries, were collected during transsexual operation and surgical treatment with the signed consent form. The cellular localization of SET protein was observed by immunohistochemistry. The expression levels of SET protein were analyzed by Western Blot. Result. SET protein was expressed predominantly in the theca cells and oocytes of human ovarian follicles in both PCOS ovarian tissues and normal ovarian tissues. The level of SET protein expression in polycystic ovaries was triple higher than that in normal ovaries (P < 0.05). Conclusion. SET was overexpressed in polycystic ovaries more than that in normal ovaries. Combined with its localization in theca cells, SET may participate in regulating ovarian androgen biosynthesis and the pathophysiology of hyperandrogenism in PCOS. PMID:23861679

Expression of SET Protein in the Ovaries of Patients with Polycystic Ovary Syndrome.

PubMed

Boqun, Xu; Xiaonan, Dai; Yugui, Cui; Lingling, Gao; Xue, Dai; Gao, Chao; Feiyang, Diao; Jiayin, Liu; Gao, Li; Li, Mei; Zhang, Yuan; Ma, Xiang

2013-01-01

Background. We previously found that expression of SET gene was up-regulated in polycystic ovaries by using microarray. It suggested that SET may be an attractive candidate regulator involved in the pathophysiology of polycystic ovary syndrome (PCOS). In this study, expression and cellular localization of SET protein were investigated in human polycystic and normal ovaries. Method. Ovarian tissues, six normal ovaries and six polycystic ovaries, were collected during transsexual operation and surgical treatment with the signed consent form. The cellular localization of SET protein was observed by immunohistochemistry. The expression levels of SET protein were analyzed by Western Blot. Result. SET protein was expressed predominantly in the theca cells and oocytes of human ovarian follicles in both PCOS ovarian tissues and normal ovarian tissues. The level of SET protein expression in polycystic ovaries was triple higher than that in normal ovaries (P < 0.05). Conclusion. SET was overexpressed in polycystic ovaries more than that in normal ovaries. Combined with its localization in theca cells, SET may participate in regulating ovarian androgen biosynthesis and the pathophysiology of hyperandrogenism in PCOS.

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

PubMed

Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian

2012-10-24

Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.

Study of hepatitis B virus gene mutations with enzymatic colorimetry-based DNA microarray.

PubMed

Mao, Hailei; Wang, Huimin; Zhang, Donglei; Mao, Hongju; Zhao, Jianlong; Shi, Jian; Cui, Zhichu

2006-01-01

To establish a modified microarray method for detecting HBV gene mutations in the clinic. Site-specific oligonucleotide probes were immobilized to microarray slides and hybridized to biotin-labeled HBV gene fragments amplified from two-step PCR. Hybridized targets were transferred to nitrocellulose membranes, followed by intensity measurement using BCIP/NBT colorimetry. HBV genes from 99 Hepatitis B patients and 40 healthy blood donors were analyzed. Mutation frequencies of HBV pre-core/core and basic core promoter (BCP) regions were found to be significantly higher in the patient group (42%, 40% versus 2.5%, 5%, P < 0.01). Compared with a traditional fluorescence method, the colorimetry method exhibited the same level of sensitivity and reproducibility. An enzymatic colorimetry-based DNA microarray assay was successfully established to monitor HBV mutations. Pre-core/core and BCP mutations of HBV genes could be major causes of HBV infection in HBeAg-negative patients and could also be relevant to chronicity and aggravation of hepatitis B.

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation

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

Daly, Don S.; Anderson, Kevin K.; White, Amanda M.

Background: A microarray of enzyme-linked immunosorbent assays, or ELISA microarray, predicts simultaneously the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Making sound biological inferences as well as improving the ELISA microarray process require require both concentration predictions and creditable estimates of their errors. Methods: We present a statistical method based on monotonic spline statistical models, penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict concentrations and estimate prediction errors in ELISA microarray. PCLS restrains the flexible spline to a fit of assay intensitymore » that is a monotone function of protein concentration. With MC, both modeling and measurement errors are combined to estimate prediction error. The spline/PCLS/MC method is compared to a common method using simulated and real ELISA microarray data sets. Results: In contrast to the rigid logistic model, the flexible spline model gave credible fits in almost all test cases including troublesome cases with left and/or right censoring, or other asymmetries. For the real data sets, 61% of the spline predictions were more accurate than their comparable logistic predictions; especially the spline predictions at the extremes of the prediction curve. The relative errors of 50% of comparable spline and logistic predictions differed by less than 20%. Monte Carlo simulation rendered acceptable asymmetric prediction intervals for both spline and logistic models while propagation of error produced symmetric intervals that diverged unrealistically as the standard curves approached horizontal asymptotes. Conclusions: The spline/PCLS/MC method is a flexible, robust alternative to a logistic/NLS/propagation-of-error method to reliably predict protein concentrations and estimate their errors. The spline method simplifies model selection and fitting, and reliably estimates believable prediction errors. For the 50% of the real data sets fit well by both methods, spline and logistic predictions are practically indistinguishable, varying in accuracy by less than 15%. The spline method may be useful when automated prediction across simultaneous assays of numerous proteins must be applied routinely with minimal user intervention.« less

Whole transcriptome RNA-Seq analysis of breast cancer recurrence risk using formalin-fixed paraffin-embedded tumor tissue.

PubMed

Sinicropi, Dominick; Qu, Kunbin; Collin, Francois; Crager, Michael; Liu, Mei-Lan; Pelham, Robert J; Pho, Mylan; Dei Rossi, Andrew; Jeong, Jennie; Scott, Aaron; Ambannavar, Ranjana; Zheng, Christina; Mena, Raul; Esteban, Jose; Stephans, James; Morlan, John; Baker, Joffre

2012-01-01

RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.

Whole Transcriptome RNA-Seq Analysis of Breast Cancer Recurrence Risk Using Formalin-Fixed Paraffin-Embedded Tumor Tissue

PubMed Central

Sinicropi, Dominick; Qu, Kunbin; Collin, Francois; Crager, Michael; Liu, Mei-Lan; Pelham, Robert J.; Pho, Mylan; Rossi, Andrew Dei; Jeong, Jennie; Scott, Aaron; Ambannavar, Ranjana; Zheng, Christina; Mena, Raul; Esteban, Jose; Stephans, James; Morlan, John; Baker, Joffre

2012-01-01

RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts. PMID:22808097

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Implementation of spectral clustering on microarray data of carcinoma using k-means algorithm

NASA Astrophysics Data System (ADS)

Frisca, Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluation of gene expression classification studies: factors associated with classification performance.

PubMed

Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-01-01

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

Clearance of a persistent Picornavirus infection is associated with enhanced pro-apoptotic and cellular immune responses

USDA-ARS?s Scientific Manuscript database

Immunomodulatory mechanisms associated with clearance versus persistence of foot-and-mouth disease virus (FMDV) in distinct microanatomic compartments of the bovine nasopharynx were investigated using quantitative RT-PCR and whole transcriptome microarray. Analysis of tissue samples obtained during ...

Identification of Gender-specific Transcripts by Microarray in Gonad Tissue of Larval and Juvenile Xenopus tropicalis

EPA Science Inventory

Amphibian model species Xenopus tropicalis is currently being utilized by EPA in the development of a standardized in vivo reproductive toxicity assay. Perturbations to the hypothalamic-pituitary-gonadal axis from exposure to endocrine disrupting compounds during larval develop...

Transcriptome response to elevated CO2, water deficit, and thermal stress in peanut

USDA-ARS?s Scientific Manuscript database

Previously, our laboratories have performed gene expression studies using EST sequencing and spotted microarrays to investigate tissue-specific gene expression and response to abiotic stress. While these studies have provided valuable insight into these processes, they are constrained by sequencer t...

Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis

PubMed Central

Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng

2016-01-01

Background. Long noncoding RNAs (lncRNAs) play key roles in a wide range of biological processes and their deregulation results in human disease, including keloids. Earlobe keloid is a type of pathological skin scar, and the molecular pathogenesis of this disease remains largely unknown. Methods. In this study, microarray analysis was used to determine the expression profiles of lncRNAs and mRNAs between 3 pairs of earlobe keloid and normal specimens. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify the main functions of the differentially expressed genes and earlobe keloid-related pathways. Results. A total of 2068 lncRNAs and 1511 mRNAs were differentially expressed between earlobe keloid and normal tissues. Among them, 1290 lncRNAs and 1092 mRNAs were upregulated, and 778 lncRNAs and 419 mRNAs were downregulated. Pathway analysis revealed that 24 pathways were correlated to the upregulated transcripts, while 11 pathways were associated with the downregulated transcripts. Conclusion. We characterized the expression profiles of lncRNA and mRNA in earlobe keloids and suggest that lncRNAs may serve as diagnostic biomarkers for the therapy of earlobe keloid. PMID:28101509

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

NASA Technical Reports Server (NTRS)

Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

2005-01-01

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Viral Disease Networks?

NASA Astrophysics Data System (ADS)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.

Long non-coding RNA expression profile in cervical cancer tissues

PubMed Central

Zhu, Hua; Chen, Xiangjian; Hu, Yan; Shi, Zhengzheng; Zhou, Qing; Zheng, Jingjie; Wang, Yifeng

2017-01-01

Cervical cancer (CC), one of the most common types of cancer of the female population, presents an enormous challenge in diagnosis and treatment. Long non-coding (lnc)RNAs, non-coding (nc)RNAs with length >200 nucleotides, have been identified to be associated with multiple types of cancer, including CC. This class of nc transcripts serves an important role in tumor suppression and oncogenic signaling pathways. In the present study, the microarray method was used to obtain the expression profile of lncRNAs and protein-coding mRNAs and to compare the expression of lncRNAs between CC tissues and corresponding adjacent non-cancerous tissues in order to screen potential lncRNAs for associations with CC. Overall, 3356 lncRNAs with significantly different expression pattern in CC tissues compared with adjacent non-cancerous tissues were identified, while 1,857 of them were upregulated. These differentially expressed lncRNAs were additionally classified into 5 subgroups. Reverse transcription quantitative polymerase chain reactions were performed to validate the expression pattern of 5 random selected lncRNAs, and 2lncRNAs were identified to have significantly different expression in CC samples compared with adjacent non-cancerous tissues. This finding suggests that those lncRNAs with different expression may serve important roles in the development of CC, and the expression data may provide information for additional study on the involvement of lncRNAs in CC. PMID:28789353

Molecular differential diagnosis of follicular thyroid carcinoma and adenoma based on gene expression profiling by using formalin-fixed paraffin-embedded tissues

PubMed Central

2013-01-01

Background Differential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples. Methods A molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples). The performance of the classifier was assessed using an independent dataset comprising 71 formalin-fixed paraffin-embedded (FFPE) samples (31 FTC and 40 FTA), which were analysed by quantitative real-time PCR (qPCR). In addition, three other microarray datasets (62 samples) were used to confirm the utility of the classifier. Results Five of 8 genes selected from training datasets (ELMO1, EMCN, ITIH5, KCNAB1, SLCO2A1) were amplified by qPCR in FFPE material from an independent sample set. Three other genes did not amplify in FFPE material, probably due to low abundance. All 5 analysed genes were downregulated in FTC compared to FTA. The sensitivity and specificity of the 5-gene classifier tested on the FFPE dataset were 71% and 72%, respectively. Conclusions The proposed approach could support histopathological examination: 5-gene classifier may aid in molecular discrimination between FTC and FTA in FFPE material. PMID:24099521

Protective effect of bicyclol against bile duct ligation-induced hepatic fibrosis in rats

PubMed Central

Zhen, Yong-Zhan; Li, Na-Ren; He, Hong-Wei; Zhao, Shuang-Shuang; Zhang, Guang-Ling; Hao, Xiao-Fang; Shao, Rong-Guang

2015-01-01

AIM: To evaluate the protective effect of bicyclol against bile duct ligation (BDL)-induced hepatic fibrosis in rats. METHODS: Sprague-Dawley male rats underwent BDL and sham-operated animals were used as healthy controls. The BDL rats were divided into two groups which received sterilized PBS or bicyclol (100 mg/kg per day) orally for two consecutive weeks. Serum, urine and bile were collected for biochemical determinations. Liver tissues were collected for histological analysis and a whole genome oligonucleotide microarray assay. Reverse transcription-polymerase chain reaction and Western blotting were used to verify the expression of liver fibrosis-related genes. RESULTS: Treatment with bicyclol significantly reduced liver fibrosis and bile duct proliferation after BDL. The levels of alanine aminotransferase (127.7 ± 72.3 vs 230.4 ± 69.6, P < 0.05) and aspartate aminotransferase (696.8 ± 232.6 vs 1032.6 ± 165.8, P < 0.05) were also decreased by treatment with bicyclol in comparison to PBS. The expression changes of 45 fibrogenic genes and several fibrogenesis-related pathways were reversed by bicyclol in the microarray assay. Bicyclol significantly reduced liver mRNA and/or protein expression levels of collagen 1a1, matrix metalloproteinase 2, tumor necrosis factor, tissue inhibitors of metalloproteinases 2, transforming growth factor-β1 and α-smooth muscle actin. CONCLUSION: Bicyclol significantly attenuates BDL-induced liver fibrosis by reversing fibrogenic gene expression. These findings suggest that bicyclol might be an effective anti-fibrotic drug for the treatment of cholestatic liver disease. PMID:26109801

Detection of Multiple Waterborne Pathogens Using Microsequencing Arrays

EPA Science Inventory

Aims: A microarray was developed to simultaneously detect Cryptosporidium parvum, Cryptosporidium hominis, Enterococcus faecium, Bacillus anthracis and Francisella tularensis in water. Methods and Results: A DNA microarray was designed to contain probes that specifically dete...

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Nanotechnology: moving from microarrays toward nanoarrays.

PubMed

Chen, Hua; Li, Jun

2007-01-01

Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

On-Chip Synthesis of Protein Microarrays from DNA Microarrays Via Coupled In Vitro Transcription and Translation for Surface Plasmon Resonance Imaging Biosensor Applications

PubMed Central

Seefeld, Ting H.; Halpern, Aaron R.; Corn, Robert M.

2012-01-01

Protein microarrays are fabricated from double-stranded DNA (dsDNA) microarrays by a one-step, multiplexed enzymatic synthesis in an on-chip microfluidic format and then employed for antibody biosensing measurements with surface plasmon resonance imaging (SPRI). A microarray of dsDNA elements (denoted as generator elements) that encode either a His-tagged green fluorescent protein (GFP) or a His-tagged luciferase protein is utilized to create multiple copies of messenger RNA (mRNA) in a surface RNA polymerase reaction; the mRNA transcripts are then translated into proteins by cell-free protein synthesis in a microfluidic format. The His-tagged proteins diffuse to adjacent Cu(II)-NTA microarray elements (denoted as detector elements) and are specifically adsorbed. The net result is the on-chip, cell-free synthesis of a protein microarray that can be used immediately for SPRI protein biosensing. The dual element format greatly reduces any interference from the nonspecific adsorption of enzyme or proteins. SPRI measurements for the detection of the antibodies anti-GFP and anti-luciferase were used to verify the formation of the protein microarray. This convenient on-chip protein microarray fabrication method can be implemented for multiplexed SPRI biosensing measurements in both clinical and research applications. PMID:22793370

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

2015-01-01

DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

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

Gardner, Shea N.; McLoughlin, Kevin; Be, Nicholas A.

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broadmore » panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Lastly, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.« less

Predicting chemical bioavailability using microarray gene expression data and regression modeling: A tale of three explosive compounds.

PubMed

Gong, Ping; Nan, Xiaofei; Barker, Natalie D; Boyd, Robert E; Chen, Yixin; Wilkins, Dawn E; Johnson, David R; Suedel, Burton C; Perkins, Edward J

2016-03-08

Chemical bioavailability is an important dose metric in environmental risk assessment. Although many approaches have been used to evaluate bioavailability, not a single approach is free from limitations. Previously, we developed a new genomics-based approach that integrated microarray technology and regression modeling for predicting bioavailability (tissue residue) of explosives compounds in exposed earthworms. In the present study, we further compared 18 different regression models and performed variable selection simultaneously with parameter estimation. This refined approach was applied to both previously collected and newly acquired earthworm microarray gene expression datasets for three explosive compounds. Our results demonstrate that a prediction accuracy of R(2) = 0.71-0.82 was achievable at a relatively low model complexity with as few as 3-10 predictor genes per model. These results are much more encouraging than our previous ones. This study has demonstrated that our approach is promising for bioavailability measurement, which warrants further studies of mixed contamination scenarios in field settings.

Customizing chemotherapy for colon cancer: the potential of gene expression profiling.

PubMed

Mariadason, John M; Arango, Diego; Augenlicht, Leonard H

2004-06-01

The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.

Carbohydrate Microarrays Identify Blood Group Precursor Cryptic Epitopes as Potential Immunological Targets of Breast Cancer

PubMed Central

Wang, Denong; Tang, Jin; Liu, Shaoyi

2015-01-01

Using carbohydrate microarrays, we explored potential natural ligands of antitumor monoclonal antibody HAE3. This antibody was raised against a murine mammary tumor antigen but was found to cross-react with a number of human epithelial tumors in tissues. Our carbohydrate microarray analysis reveals that HAE3 is specific for an O-glycan cryptic epitope that is normally hidden in the cores of blood group substances. Using HAE3 to screen tumor cell surface markers by flow cytometry, we found that the HAE3 glycoepitope, gpHAE3, was highly expressed by a number of human breast cancer cell lines, including some triple-negative cancers that lack the estrogen, progesterone, and Her2/neu receptors. Taken together, we demonstrate that HAE3 recognizes a conserved cryptic glycoepitope of blood group precursors, which is nevertheless selectively expressed and surface-exposed in certain breast tumor cells. The potential of this class of O-glycan cryptic antigens in breast cancer subtyping and targeted immunotherapy warrants further investigation. PMID:26539555

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Detection of pathogenic Vibrio spp. in shellfish by using multiplex PCR and DNA microarrays.

PubMed

Panicker, Gitika; Call, Douglas R; Krug, Melissa J; Bej, Asim K

2004-12-01

This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50 degrees C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 10(2) to 10(3) CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers.

Detection of Pathogenic Vibrio spp. in Shellfish by Using Multiplex PCR and DNA Microarrays

PubMed Central

Panicker, Gitika; Call, Douglas R.; Krug, Melissa J.; Bej, Asim K.

2004-01-01

This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50°C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 102 to 103 CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers. PMID:15574946

Development and experimental validation of a 20K Atlantic cod (Gadus morhua) oligonucleotide microarray based on a collection of over 150,000 ESTs.

PubMed

Booman, Marije; Borza, Tudor; Feng, Charles Y; Hori, Tiago S; Higgins, Brent; Culf, Adrian; Léger, Daniel; Chute, Ian C; Belkaid, Anissa; Rise, Marlies; Gamperl, A Kurt; Hubert, Sophie; Kimball, Jennifer; Ouellette, Rodney J; Johnson, Stewart C; Bowman, Sharen; Rise, Matthew L

2011-08-01

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.

PubMed

Yang, Yunfeng; Zhu, Mengxia; Wu, Liyou; Zhou, Jizhong

2008-09-16

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality. Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses. These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

PubMed

Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

2005-05-18

To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

Oncogene GAEC1 regulates CAPN10 expression which predicts survival in esophageal squamous cell carcinoma

PubMed Central

Chan, Dessy; Tsoi, Miriam Yuen-Tung; Liu, Christina Di; Chan, Sau-Hing; Law, Simon Ying-Kit; Chan, Kwok-Wah; Chan, Yuen-Piu; Gopalan, Vinod; Lam, Alfred King-Yin; Tang, Johnny Cheuk-On

2013-01-01

AIM: To identify the downstream regulated genes of GAEC1 oncogene in esophageal squamous cell carcinoma and their clinicopathological significance. METHODS: The anti-proliferative effect of knocking down the expression of GAEC1 oncogene was studied by using the RNA interference (RNAi) approach through transfecting the GAEC1-overexpressed esophageal carcinoma cell line KYSE150 with the pSilencer vector cloned with a GAEC1-targeted sequence, followed by MTS cell proliferation assay and cell cycle analysis using flow cytometry. RNA was then extracted from the parental, pSilencer-GAEC1-targeted sequence transfected and pSilencer negative control vector transfected KYSE150 cells for further analysis of different patterns in gene expression. Genes differentially expressed with suppressed GAEC1 expression were then determined using Human Genome U133 Plus 2.0 cDNA microarray analysis by comparing with the parental cells and normalized with the pSilencer negative control vector transfected cells. The most prominently regulated genes were then studied by immunohistochemical staining using tissue microarrays to determine their clinicopathological correlations in esophageal squamous cell carcinoma by statistical analyses. RESULTS: The RNAi approach of knocking down gene expression showed the effective suppression of GAEC1 expression in esophageal squamous cell carcinoma cell line KYSE150 that resulted in the inhibition of cell proliferation and increase of apoptotic population. cDNA microarray analysis for identifying differentially expressed genes detected the greatest levels of downregulation of calpain 10 (CAPN10) and upregulation of trinucleotide repeat containing 6C (TNRC6C) transcripts when GAEC1 expression was suppressed. At the tissue level, the high level expression of calpain 10 protein was significantly associated with longer patient survival (month) of esophageal squamous cell carcinoma compared to the patients with low level of calpain 10 expression (37.73 ± 16.33 vs 12.62 ± 12.44, P = 0.032). No significant correction was observed among the TNRC6C protein expression level and the clinocopathologcial features of esophageal squamous cell carcinoma. CONCLUSION: GAEC1 regulates the expression of CAPN10 and TNRC6C downstream. Calpain 10 expression is a potential prognostic marker in patients with esophageal squamous cell carcinoma. PMID:23687414

Long non-coding RNA ENST00462717 suppresses the proliferation, survival, and migration by inhibiting MDM2/MAPK pathway in glioma

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

Wang, Aiqin; Meng, Mingzhu; Zhao, Xiuhe

Gliomas are the most common and aggressive primary malignant tumor in the central nervous system, and requires new biomarkers and therapeutic methods. Long noncoding RNAs (lncRNAs) are important factors in numerous human diseases, including cancer. But studies on lncRNAs and gliomas are limited. In this study, we investigated the expression patterns of lncRNAs in 3 pairs of glioma samples and adjacent non-tumor tissues via microarray and selected the most down-regulated lnc00462717 to further verify its roles in glioma. We observed that decreased lnc00462717 expression was associated with the malignant status in glioma. In vitro experiment demonstrated that lnc00462717 overexpression suppressed gliomamore » cell proliferation, survival and migration while knockdown of lnc00462717 had an opposite result. Moreover, we identified MDM2 as a direct target of lnc00462717 and lnc00462717 played a role by partially regulating the MDM2/MAPK pathway. In conclusion, lnc00462717 may function in suppressing glioma cell proliferation, survival, migration and may potentially serve as a novel biomarker and therapeutic target for glioma. - Highlights: • Using microarray to investigate the expression patterns of lncRNAs in glioma. • Selecting the most down-regulated lnc00462717 via microarray to verify its roles. • Identifying MDM2 as a direct target of lnc00462717. • The mechanism of lnc00462717 regulating the MDM2/MAPK pathway. • lnc00462717 serve as a novel biomarker and therapeutic target for treating glioma.« less

Form-Deprivation Myopia in Chick Induces Limited Changes in Retinal Gene Expression

PubMed Central

McGlinn, Alice M.; Baldwin, Donald A.; Tobias, John W.; Budak, Murat T.; Khurana, Tejvir S.; Stone, Richard A.

2007-01-01

Purpose Evidence has implicated the retina as a principal controller of refractive development. In the present study, the retinal transcriptome was analyzed to identify alterations in gene expression and potential signaling pathways involved in form-deprivation myopia of the chick. Methods One-week-old white Leghorn chicks wore a unilateral image-degrading goggle for 6 hours or 3 days (n = 6 at each time). Total RNA from the retina/(retinal pigment epithelium) was used for expression profiling with chicken gene microarrays (Chicken GeneChips; Affymetrix, Santa Clara, CA). To identify gene expression level differences between goggled and contralateral nongoggled eyes, normalized microarray signal intensities were analyzed by the significance analysis of microarrays (SAM) approach. Differentially expressed genes were validated by real-time quantitative reverse transcription–polymerase chain reaction (qPCR) in independent biological replicates. Results Small changes were detected in differentially expressed genes in form-deprived eyes. In chickens that had 6 hours of goggle wear, downregulation of bone morphogenetic protein 2 and connective tissue growth factor was validated. In those with 3 days of goggle wear, downregulation of bone morphogenetic protein 2, vasoactive intestinal peptide, preopro-urotensin II–related peptide and mitogen-activated protein kinase phosphatase 2 was validated, and upregulation of endothelin receptor type B and interleukin-18 was validated. Conclusions Form-deprivation myopia, in its early stages, is associated with only minimal changes in retinal gene expression at the level of the transcriptome. While the list of validated genes is short, each merits further study for potential involvement in the signaling cascade mediating myopia development. PMID:17652709

[Oligonucleotide microarray for subtyping avian influenza virus].

PubMed

Xueqing, Han; Xiangmei, Lin; Yihong, Hou; Shaoqiang, Wu; Jian, Liu; Lin, Mei; Guangle, Jia; Zexiao, Yang

2008-09-01

Avian influenza viruses are important human and animal respiratory pathogens and rapid diagnosis of novel emerging avian influenza viruses is vital for effective global influenza surveillance. We developed an oligonucleotide microarray-based method for subtyping all avian influenza virus (16 HA and 9 NA subtypes). In total 25 pairs of primers specific for different subtypes and 1 pair of universal primers were carefully designed based on the genomic sequences of influenza A viruses retrieved from GenBank database. Several multiplex RT-PCR methods were then developed, and the target cDNAs of 25 subtype viruses were amplified by RT-PCR or overlapping PCR for evaluating the microarray. Further 52 oligonucleotide probes specific for all 25 subtype viruses were designed according to published gene sequences of avian influenza viruses in amplified target cDNAs domains, and a microarray for subtyping influenza A virus was developed. Then its specificity and sensitivity were validated by using different subtype strains and 2653 samples from 49 different areas. The results showed that all the subtypes of influenza virus could be identified simultaneously on this microarray with high sensitivity, which could reach to 2.47 pfu/mL virus or 2.5 ng target DNA. Furthermore, there was no cross reaction with other avian respiratory virus. An oligonucleotide microarray-based strategy for detection of avian influenza viruses has been developed. Such a diagnostic microarray will be useful in discovering and identifying all subtypes of avian influenza virus.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

The importance of prenatal 3-dimensional sonography in a case of a segmental overgrowth syndrome with unclear chromosomal microarray results.

PubMed

Asoglu, Mehmet Resit; Higgs, Amanda; Esin, Sertac; Kaplan, Julie; Turan, Sifa

2018-06-01

PIK3CA-related overgrowth spectrum, caused by mosaic mutations in the PIK3CA gene, is associated with regional or generalized asymmetric overgrowth of the body or a body part in addition to other clinical findings. Three-dimensional ultrasonography (3-D US) has the capability to display structural abnormalities in soft tissues or other organs, thereby facilitating identification of segmental overgrowth lesions. We present a case suspected of having a segmental overgrowth disorder based on 3-D US, whose chromosomal microarray result was abnormal, but apparently was not the cause of the majority of the fetus's clinical features. © 2017 Wiley Periodicals, Inc.

Lack of concordance in microarray gene expression responses to Phenobarbital in companion aged FFPE and Frozen liver samples

EPA Science Inventory

Despite the immense potential value of public and private biorepositories, direct utilization of archival tissues for molecular profiling has been limited. A major reason for this limited use is the difficulty in obtaining reliable transcriptomic profiles from formalin-fixed par...

A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

PubMed

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

A robust two-way semi-linear model for normalization of cDNA microarray data

PubMed Central

Wang, Deli; Huang, Jian; Xie, Hehuang; Manzella, Liliana; Soares, Marcelo Bento

2005-01-01

Background Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. Conclusions Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods. PMID:15663789

High Quality Genomic Copy Number Data from Archival Formalin-Fixed Paraffin-Embedded Leiomyosarcoma: Optimisation of Universal Linkage System Labelling

PubMed Central

Salawu, Abdulazeez; Ul-Hassan, Aliya; Hammond, David; Fernando, Malee; Reed, Malcolm; Sisley, Karen

2012-01-01

Most soft tissue sarcomas are characterized by genetic instability and frequent genomic copy number aberrations that are not subtype-specific. Oligonucleotide microarray-based Comparative Genomic Hybridisation (array CGH) is an important technique used to map genome-wide copy number aberrations, but the traditional requirement for high-quality DNA typically obtained from fresh tissue has limited its use in sarcomas. Although large archives of Formalin-fixed Paraffin-embedded (FFPE) tumour samples are available for research, the degradative effects of formalin on DNA from these tissues has made labelling and analysis by array CGH technically challenging. The Universal Linkage System (ULS) may be used for a one-step chemical labelling of such degraded DNA. We have optimised the ULS labelling protocol to perform aCGH on archived FFPE leiomyosarcoma tissues using the 180k Agilent platform. Preservation age of samples ranged from a few months to seventeen years and the DNA showed a wide range of degradation (when visualised on agarose gels). Consistently high DNA labelling efficiency and low microarray probe-to-probe variation (as measured by the derivative log ratio spread) was seen. Comparison of paired fresh and FFPE samples from identical tumours showed good correlation of CNAs detected. Furthermore, the ability to macro-dissect FFPE samples permitted the detection of CNAs that were masked in fresh tissue. Aberrations were visually confirmed using Fluorescence in situ Hybridisation. These results suggest that archival FFPE tissue, with its relative abundance and attendant clinical data may be used for effective mapping for genomic copy number aberrations in such rare tumours as leiomyosarcoma and potentially unravel clues to tumour origins, progression and ultimately, targeted treatment. PMID:23209738

Genes that characterize T3-predominant Graves' thyroid tissues.

PubMed

Matsumoto, Chisa; Ito, Mitsuru; Yamada, Hiroya; Yamakawa, Noriko; Yoshida, Hiroshi; Date, Arisa; Watanabe, Mikio; Hidaka, Yoh; Iwatani, Yoshinori; Miyauchi, Akira; Takano, Toru

2013-02-01

3,5,3'-Triiodothyronine (T(3))-predominant Graves' disease is characterized by the increasing volume of thyroid goiter resulting in poor prognosis. Although type 1 and type 2 iodothyronine deiodinases (DIO1 and DIO2 respectively) are known to be overexpressed in the thyroid tissues of T(3)-predominant Graves' disease, the pathogenesis of this disease is still unclear. The aim of our study is to identify genes that characterize T(3)-predominant Graves' disease tissue in order to clarify the molecular mechanism of this disease. mRNAs from two thyroid tissues of both typical T(3)-predominant and common-type Graves' disease were analyzed with DNA microarrays with probes for 28 869 genes. Genes identified to be differentially expressed between the two groups were further analyzed in the second and third screenings using 70 Graves' thyroid tissues by real-time quantitative RT-PCR. Twenty-three candidate genes were selected as being differentially expressed in the first screening with microarrays. Among these, seven genes, leucine-rich repeat neuronal 1 (LRRN1), bone morphogenetic protein 8a (BMP8A), N-cadherin (CDH2), phosphodiesterase 1A (PDE1A), creatine kinase mitochondrial 2 (CKMT2), integrin beta-3 (ITGB3), and protein tyrosine phosphatase non-receptor type 4 (PTPN4), were confirmed to be differentially expressed in DIO1 or DIO2 over- and underexpressing Graves' tissues. These genes are related to the characteristics of T(3)-predominant Graves' disease, such as high titer level of serum anti-TSH receptor antibody, high free T(3) to free thyroxine ratio, and a large goiter size. They might play a role in the pathogenesis of T(3)-predominant Graves' disease.

The 'PUCE CAFE' Project: the First 15K Coffee Microarray, a New Tool for Discovering Candidate Genes correlated to Agronomic and Quality Traits

PubMed Central

2011-01-01

Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research. PMID:21208403

The 'PUCE CAFE' Project: the first 15K coffee microarray, a new tool for discovering candidate genes correlated to agronomic and quality traits.

PubMed

Privat, Isabelle; Bardil, Amélie; Gomez, Aureliano Bombarely; Severac, Dany; Dantec, Christelle; Fuentes, Ivanna; Mueller, Lukas; Joët, Thierry; Pot, David; Foucrier, Séverine; Dussert, Stéphane; Leroy, Thierry; Journot, Laurent; de Kochko, Alexandre; Campa, Claudine; Combes, Marie-Christine; Lashermes, Philippe; Bertrand, Benoit

2011-01-05

Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research.

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

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

Zhu, Yuerong; Zhu, Yuelin; Xu, Wei

2008-01-01

Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103

Upregulated epidermal growth factor receptor expression following near-infrared irradiation simulating solar radiation in a three-dimensional reconstructed human corneal epithelial tissue culture model

PubMed Central

Tanaka, Yohei; Nakayama, Jun

2016-01-01

Background and objective Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. Materials and methods DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000–1,800 nm wavelengths and excluded 1,400–1,500 nm wavelengths. Results A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm2 irradiation (P<0.05). Conclusion We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage. PMID:27536083

High-throughput quantum cascade laser (QCL) spectral histopathology: a practical approach towards clinical translation.

PubMed

Pilling, Michael J; Henderson, Alex; Bird, Benjamin; Brown, Mick D; Clarke, Noel W; Gardner, Peter

2016-06-23

Infrared microscopy has become one of the key techniques in the biomedical research field for interrogating tissue. In partnership with multivariate analysis and machine learning techniques, it has become widely accepted as a method that can distinguish between normal and cancerous tissue with both high sensitivity and high specificity. While spectral histopathology (SHP) is highly promising for improved clinical diagnosis, several practical barriers currently exist, which need to be addressed before successful implementation in the clinic. Sample throughput and speed of acquisition are key barriers and have been driven by the high volume of samples awaiting histopathological examination. FTIR chemical imaging utilising FPA technology is currently state-of-the-art for infrared chemical imaging, and recent advances in its technology have dramatically reduced acquisition times. Despite this, infrared microscopy measurements on a tissue microarray (TMA), often encompassing several million spectra, takes several hours to acquire. The problem lies with the vast quantities of data that FTIR collects; each pixel in a chemical image is derived from a full infrared spectrum, itself composed of thousands of individual data points. Furthermore, data management is quickly becoming a barrier to clinical translation and poses the question of how to store these incessantly growing data sets. Recently, doubts have been raised as to whether the full spectral range is actually required for accurate disease diagnosis using SHP. These studies suggest that once spectral biomarkers have been predetermined it may be possible to diagnose disease based on a limited number of discrete spectral features. In this current study, we explore the possibility of utilising discrete frequency chemical imaging for acquiring high-throughput, high-resolution chemical images. Utilising a quantum cascade laser imaging microscope with discrete frequency collection at key diagnostic wavelengths, we demonstrate that we can diagnose prostate cancer with high sensitivity and specificity. Finally we extend the study to a large patient dataset utilising tissue microarrays, and show that high sensitivity and specificity can be achieved using high-throughput, rapid data collection, thereby paving the way for practical implementation in the clinic.

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

Comprehensive adipocytic and neurogenic tissue microarray analysis of NY-ESO-1 expression - a promising immunotherapy target in malignant peripheral nerve sheath tumor and liposarcoma

PubMed Central

Shurell, Elizabeth; Vergara-Lluri, Maria E.; Li, Yunfeng; Crompton, Joseph G.; Singh, Arun; Bernthal, Nicholas; Wu, Hong; Eilber, Fritz C.; Dry, Sarah M.

2016-01-01

Background Immunotherapy targeting cancer-testis antigen NY-ESO-1 shows promise for tumors with poor response to chemoradiation. Malignant peripheral nerve sheath tumors (MPNSTs) and liposarcomas (LPS) are chemoresistant and have few effective treatment options. Materials Methods Using a comprehensive tissue microarray (TMA) of both benign and malignant tumors in primary, recurrent, and metastatic samples, we examined NY-ESO-1 expression in peripheral nerve sheath tumor (PNST) and adipocytic tumors. The PNST TMA included 42 MPNSTs (spontaneous n = 26, NF1-associated n = 16), 35 neurofibromas (spontaneous n = 22, NF-1 associated n = 13), 11 schwannomas, and 18 normal nerves. The LPS TMA included 48 well-differentiated/dedifferentiated (WD/DD) LPS, 13 myxoid/round cell LPS, 3 pleomorphic LPS, 8 lipomas, 1 myelolipoma, and 3 normal adipocytic tissue samples. Stained in triplicate, NY-ESO-1 intensity and density were scored. Results NY-ESO-1 expression was exclusive to malignant tumors. 100% of myxoid/round cell LPS demonstrated NY-ESO-1 expression, while only 6% of WD/DD LPS showed protein expression, one of which was WD LPS. Of MPNST, 4/26 (15%) spontaneous and 2/16 (12%) NF1-associated MPNSTs demonstrated NY-ESO-1 expression. Strong NY-ESO-1 expression was observed in myxoid/round cell and dedifferentiated LPS, and MPNST in primary, neoadjuvant, and metastatic settings. Conclusions We found higher prevalence of NY-ESO-1 expression in MPNSTs than previously reported, highlighting a subset of MPNST patients who may benefit from immunotherapy. This study expands our understanding of NY-ESO-1 in WD/DD LPS and is the first demonstration of staining in a WD LPS and metastatic/recurrent myxoid/round cell LPS. These results suggest immunotherapy targeting NY-ESO-1 may benefit patients with aggressive tumors resistant to conventional therapy. PMID:27655679

Screening differential circular RNA expression profiles reveal that hsa_circ_0128298 is a biomarker in the diagnosis and prognosis of hepatocellular carcinoma.

PubMed

Chen, Dawei; Zhang, Chenyue; Lin, Jiamao; Song, Xinyu; Wang, Haiyong

2018-01-01

The aim of this study was to analyze the diagnostic and prognostic values of the circular RNA (circRNA) hsa_circ_0128298 in hepatocellular carcinoma (HCC). The global circRNA expression was measured using circRNA microarray using three pairs of cancer and noncancerous tissues from HCC patients. The microarray analysis revealed that two circRNAs were differentially expressed in the three pairs of cancerous and noncancerous tissues. The higher levels of two representative circRNAs, such as hsa_circ_0128298 and hsa_circ_0091582, were further confirmed by real-time polymerase chain reaction. In addition, the association between the expression level of hsa_circ_0128298 and the clinicopathological features of patients with HCC was further analyzed. The clinical diagnosis value was confirmed by receiver operating characteristic (ROC) curve analysis. Independent prognostic factors of patient outcome were identified using the Cox regression model. The survival data were analyzed by the Kaplan-Meier method, and the differences were evaluated using log-rank tests. Two-sided P -values <0.05 were considered statistically significant. The expression levels of hsa_circ_0128298 in HCC were significantly higher than those of paratumorous tissues ( P <0.001). Additionally, hsa_circ_0128298 was a diagnostic factor, with the area under the ROC curve of 0.668 (95% CI =0.503-0.794, P <0.001). The sensitivity and specificity values were 0.716 and 0.815, respectively. The AFP and hsa_circ_0128298 expression levels were independent prognostic factors. The overall survival of patients with low hsa_circ_0128298 expression was significantly higher than that of patients with high hsa_circ_0128298 expression. hsa_circ_0128298 may promote proliferation and metastasis and potentially represents a novel diagnostic and prognostic biomarker for HCC patients. However, studies with larger sample size are needed to confirm our conclusion.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums.

PubMed

Shakoor, Nadia; Nair, Ramesh; Crasta, Oswald; Morris, Geoffrey; Feltus, Alex; Kresovich, Stephen

2014-01-23

Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

PubMed Central

2014-01-01

Background Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. Results This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Conclusions Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community. PMID:24456189

Identification of candidate biomarkers with cancer-specific glycosylation in the tissue and serum of endometrioid ovarian cancer patients by glycoproteomic analysis

PubMed Central

Abbott, Karen L.; Lim, Jae-Min; Wells, Lance; Benigno, Benedict B.; McDonald, John F.; Pierce, Michael

2016-01-01

Epithelial ovarian cancer is diagnosed less than 25% of the time when the cancer is confined to the ovary, leading to 5-year survival rates of less than 30%. Therefore, there is an urgent need for early diagnostics for ovarian cancer. Our study using glycotranscriptome comparative analysis of endometrioid ovarian cancer tissue and normal ovarian tissue led to the identification of distinct differences in the transcripts of a restricted set of glycosyltransferases involved in N-linked glycosylation. Utilizing lectins that bind to glycan structures predicted to show changes, we observed differences in lectin-bound glycoproteins consistent with some of the transcript differences. In this study, we have extended our observations by the use of selected lectins to perform a targeted glycoproteomic analysis of ovarian cancer and normal ovarian tissues. Our results have identified several glycoproteins that display tumor-specific glycosylation changes. We have verified these glycosylation changes on glycoproteins from tissue using immunoprecipitation followed by lectin blot detection. The glycoproteins that were verified were then analyzed further using existing microarray data obtained from benign ovarian adenomas, borderline ovarian adenocarcinomas, and malignant ovarian adenocarcinomas. The verified glycoproteins found to be expressed above control levels in the microarray data sets were then screened for tumor-specific glycan modifications in serum from ovarian cancer patients. Results obtained from two of these glycoprotein markers, periostin and thrombospondin, have confirmed that tumor-specific glycan changes can be used to distinguish ovarian cancer patient serum from normal serum. PMID:19953551

Programmed cell death-ligand 1 (PD-L1) expression is associated with RAS/TP53 mutations in lung adenocarcinoma.

PubMed

Serra, Pierre; Petat, Arthur; Maury, Jean-Michel; Thivolet-Bejui, Françoise; Chalabreysse, Lara; Barritault, Marc; Ebran, Nathalie; Milano, Gérard; Girard, Nicolas; Brevet, Marie

2018-04-01

The systematic assessment of anti-programmed cell death ligand 1 (PD-L1) expression by immunohistochemistry (IHC) in lung adenocarcinomas is becoming standard practice. However, the assessment of PD-L1 expression on small tissue specimens needs to be evaluated and the association with other features more thoroughly analyzed. This retrospective single center study evaluated the immunohistochemical expression of the SP263 anti-PD-L1 antibody on tissue microarrays (TMA) of 152 surgically resected lung adenocarcinomas, using a 25% positivity threshold. The positive cases and 50 randomly chosen negative cases in tissue microarray (TMA) were reassessed on whole tissue sections. The results were correlated to clinical, histopathological and to molecular data obtained through the screening of 214 mutations in 26 genes (LungCarta panel, Agena Biosciences). Among 152 primary lung adenocarcinomas, 19 cases (13%) showed PD-L1 expression. The agreement between TMA and whole tissue sections was 89%, specificity was 97%. PD-L1 expression was correlated to RAS mutations (p = .04), RAS/TP53 co-mutations (p = .01) and to the solid or acinar subtype (p = .048). With the SP263 PD-L1 antibody, small samples appear as a reliable means to evaluate the PD-L1 status in lung adenocarcinoma. The association between PD-L1 expression and RAS/TP53 mutations may have clinical relevance to predict the efficacy of PD-1/PD-L1 immune checkpoints inhibitors. Copyright © 2018 Elsevier B.V. All rights reserved.

Gene expression profiles help identify the Tissue of Origin for metastatic brain cancers

PubMed Central

2010-01-01

Background Metastatic brain cancers are the most common intracranial tumor and occur in about 15% of all cancer patients. In up to 10% of these patients, the primary tumor tissue remains unknown, even after a time consuming and costly workup. The Pathwork® Tissue of Origin Test (Pathwork Diagnostics, Redwood City, CA, USA) is a gene expression test to aid in the diagnosis of metastatic, poorly differentiated and undifferentiated tumors. It measures the expression pattern of 1,550 genes in these tumors and compares it to the expression pattern of a panel of 15 known tumor types. The purpose of this study was to evaluate the performance of the Tissue of Origin Test in the diagnosis of primary sites for metastatic brain cancer patients. Methods Fifteen fresh-frozen metastatic brain tumor specimens of known origins met specimen requirements. These specimens were entered into the study and processed using the Tissue of Origin Test. Results were compared to the known primary site and the agreement between the two results was assessed. Results Fourteen of the fifteen specimens produced microarray data files that passed all quality metrics. One originated from a tissue type that was off-panel. Among the remaining 13 cases, the Tissue of Origin Test accurately predicted the available diagnosis in 12/13 (92.3%) cases. Discussion This study demonstrates the accuracy of the Tissue of Origin Test when applied to predict the tissue of origin of metastatic brain tumors. This test could be a very useful tool for pathologists as they classify metastatic brain cancers. PMID:20420692

MMASS: an optimized array-based method for assessing CpG island methylation.

PubMed

Ibrahim, Ashraf E K; Thorne, Natalie P; Baird, Katie; Barbosa-Morais, Nuno L; Tavaré, Simon; Collins, V Peter; Wyllie, Andrew H; Arends, Mark J; Brenton, James D

2006-01-01

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.

Deregulation of energetic metabolism in the clear cell renal cell carcinoma: A multiple pathway analysis based on microarray profiling.

PubMed

Soltysova, Andrea; Breza, Jan; Takacova, Martina; Feruszova, Jana; Hudecova, Sona; Novotna, Barbora; Rozborilova, Eva; Pastorekova, Silvia; Kadasi, Ludevit; Krizanova, Olga

2015-07-01

Clear cell renal cell carcinoma (ccRCC) is the most frequent type of kidney cancer. In order to better understand the biology of ccRCC, we accomplished the gene profiling of fresh tissue specimens from 11 patients with the renal tumors (9 ccRCCs, 1 oncocytoma and 1 renal B-lymphoma), in which the tumor-related data were compared to the paired healthy kidney tissues from the same patients. All ccRCCs exhibited a considerably elevated transcription of the gene coding for carbonic anhydrase IX (CAIX). Moreover, the ccRCC tumors consistently displayed increased expression of genes encoding the glycolytic pathway enzymes, e.g. hexokinase II (HK2) and lactate dehydrogenase A (LDHA) and a decreased expression of genes for the mitochondrial electron transport chain components, indicating an overall reprogramming of the energetic metabolism in this tumor type. This appears to be accompanied by altered expression of the genes of the pH regulating machinery, including ion and lactate transporters. Immunohistochemical staining of tumor tissue sections confirmed the increased expression of CAIX, HK2 and LDHA in ccRCC, validating the microarray data and supporting their potential as the energetic metabolism-related biomarkers of the ccRCC.

Long noncoding RNA OR3A4 promotes metastasis and tumorigenicity in gastric cancer

PubMed Central

Guo, Xiaobo; Yang, Ziguo; Zhi, Qiaoming; Wang, Dan; Guo, Lei; Li, Guimei; Miao, Ruizhen; Shi, Yulong; Kuang, Yuting

2016-01-01

The contribution of long noncoding RNAs (lncRNAs) to metastasis of gastric cancer remains largely unknown. We used microarray analysis to identify lncRNAs differentially expressed between normal gastric tissues and gastric cancer tissues and validated these differences in quantitative real-time (qRT)-PCR experiments. The expression levels of lncRNA olfactory receptor, family 3, subfamily A, member 4 (OR3A4) were significantly associated with lymphatic metastasis, the depth of cancer invasion, and distal metastasis in 130 paired gastric cancer tissues. The effects of OR3A4 were assessed by overexpressing and silencing OR3A4 in gastric cancer cells. OR3A4 promoted cancer cell growth, angiogenesis, metastasis, and tumorigenesis in vitro and in vivo. Global microarray analysis combined with RT-PCR, RNA immunoprecipitation, and RNA pull-down analyses after OR3A4 transfection demonstrated that OR3A4 influenced biologic functions in gastric cancer cells via regulating the activation of PDLIM2, MACC1, NTN4, and GNB2L1. Our results reveal OR3A4 as an oncogenic lncRNA that promotes tumor progression, Therefore, lncRNAs might function as key regulatory hubs in gastric cancer progression. PMID:26863570

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Strand-specific transcriptome profiling with directly labeled RNA on genomic tiling microarrays

PubMed Central

2011-01-01

Background With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles. Results RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts. Conclusions An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment. PMID:21235785

A bioinformatics approach to identify patients with symptomatic peanut allergy using peptide microarray immunoassay

PubMed Central

Lin, Jing; Bruni, Francesca M.; Fu, Zhiyan; Maloney, Jennifer; Bardina, Ludmilla; Boner, Attilio L.; Gimenez, Gustavo; Sampson, Hugh A.

2013-01-01

Background Peanut allergy is relatively common, typically permanent, and often severe. Double-blind, placebo-controlled food challenge is considered the gold standard for the diagnosis of food allergy–related disorders. However, the complexity and potential of double-blind, placebo-controlled food challenge to cause life-threatening allergic reactions affects its clinical application. A laboratory test that could accurately diagnose symptomatic peanut allergy would greatly facilitate clinical practice. Objective We sought to develop an allergy diagnostic method that could correctly predict symptomatic peanut allergy by using peptide microarray immunoassays and bioinformatic methods. Methods Microarray immunoassays were performed by using the sera from 62 patients (31 with symptomatic peanut allergy and 31 who had outgrown their peanut allergy or were sensitized but were clinically tolerant to peanut). Specific IgE and IgG4 binding to 419 overlapping peptides (15 mers, 3 offset) covering the amino acid sequences of Ara h 1, Ara h 2, and Ara h 3 were measured by using a peptide microarray immunoassay. Bioinformatic methods were applied for data analysis. Results Individuals with peanut allergy showed significantly greater IgE binding and broader epitope diversity than did peanut-tolerant individuals. No significant difference in IgG4 binding was found between groups. By using machine learning methods, 4 peptide biomarkers were identified and prediction models that can predict the outcome of double-blind, placebo-controlled food challenges with high accuracy were developed by using a combination of the biomarkers. Conclusions In this study, we developed a novel diagnostic approach that can predict peanut allergy with high accuracy by combining the results of a peptide microarray immunoassay and bioinformatic methods. Further studies are needed to validate the efficacy of this assay in clinical practice. PMID:22444503

Adaptable gene-specific dye bias correction for two-channel DNA microarrays.

PubMed

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank C P

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays

PubMed Central

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank CP

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available. PMID:19401678

RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.

PubMed

Hou, Qi; Bing, Zhi-Tong; Hu, Cheng; Li, Mao-Yin; Yang, Ke-Hu; Mo, Zu; Xie, Xiang-Wei; Liao, Ji-Lin; Lu, Yan; Horie, Shigeo; Lou, Ming-Wu

2018-06-01

Prostate cancer (PCa) is the most commonly diagnosed cancer in males in the Western world. Although prostate-specific antigen (PSA) has been widely used as a biomarker for PCa diagnosis, its results can be controversial. Therefore, new biomarkers are needed to enhance the clinical management of PCa. From publicly available microarray data, differentially expressed genes (DEGs) were identified by meta-analysis with RankProd. Genetic algorithm optimized artificial neural network (GA-ANN) was introduced to establish a diagnostic prediction model and to filter candidate genes. The diagnostic and prognostic capability of the prediction model and candidate genes were investigated in both GEO and TCGA datasets. Candidate genes were further validated by qPCR, Western Blot and Tissue microarray. By RankProd meta-analyses, 2306 significantly up- and 1311 down-regulated probes were found in 133 cases and 30 controls microarray data. The overall accuracy rate of the PCa diagnostic prediction model, consisting of a 15-gene signature, reached up to 100% in both the training and test dataset. The prediction model also showed good results for the diagnosis (AUC = 0.953) and prognosis (AUC of 5 years overall survival time = 0.808) of PCa in the TCGA database. The expression levels of three genes, FABP5, C1QTNF3 and LPHN3, were validated by qPCR. C1QTNF3 high expression was further validated in PCa tissue by Western Blot and Tissue microarray. In the GEO datasets, C1QTNF3 was a good predictor for the diagnosis of PCa (GSE6956: AUC = 0.791; GSE8218: AUC = 0.868; GSE26910: AUC = 0.972). In the TCGA database, C1QTNF3 was significantly associated with PCa patient recurrence free survival (P < .001, AUC = 0.57). In this study, we have developed a diagnostic and prognostic prediction model for PCa. C1QTNF3 was revealed as a promising biomarker for PCa. This approach can be applied to other high-throughput data from different platforms for the discovery of oncogenes or biomarkers in different kinds of diseases. Copyright © 2018. Published by Elsevier B.V.

Relevance of TNBS-Colitis in Rats: A Methodological Study with Endoscopic, Histologic and Transcriptomic Characterization and Correlation to IBD

PubMed Central

Brenna, Øystein; Furnes, Marianne W.; Drozdov, Ignat; van Beelen Granlund, Atle; Flatberg, Arnar; Sandvik, Arne K.; Zwiggelaar, Rosalie T. M.; Mårvik, Ronald; Nordrum, Ivar S.; Kidd, Mark; Gustafsson, Björn I.

2013-01-01

Background Rectal instillation of trinitrobenzene sulphonic acid (TNBS) in ethanol is an established model for inflammatory bowel disease (IBD). We aimed to 1) set up a TNBS-colitis protocol resulting in an endoscopic and histologic picture resembling IBD, 2) study the correlation between endoscopic, histologic and gene expression alterations at different time points after colitis induction, and 3) compare rat and human IBD mucosal transcriptomic data to evaluate whether TNBS-colitis is an appropriate model of IBD. Methodology/Principal Findings Five female Sprague Daley rats received TNBS diluted in 50% ethanol (18 mg/0.6 ml) rectally. The rats underwent colonoscopy with biopsy at different time points. RNA was extracted from rat biopsies and microarray was performed. PCR and in situ hybridization (ISH) were done for validation of microarray results. Rat microarray profiles were compared to human IBD expression profiles (25 ulcerative colitis Endoscopic score demonstrated mild to moderate colitis after three and seven days, but declined after twelve days. Histologic changes corresponded with the endoscopic appearance. Over-represented Gene Ontology Biological Processes included: Cell Adhesion, Immune Response, Lipid Metabolic Process, and Tissue Regeneration. IL-1α, IL-1β, TLR2, TLR4, PRNP were all significantly up-regulated, while PPARγ was significantly down-regulated. Among genes with highest fold change (FC) were SPINK4, LBP, ADA, RETNLB and IL-1α. The highest concordance in differential expression between TNBS and IBD transcriptomes was three days after colitis induction. ISH and PCR results corresponded with the microarray data. The most concordantly expressed biologically relevant pathways included TNF signaling, Cell junction organization, and Interleukin-1 processing. Conclusions/Significance Endoscopy with biopsies in TNBS-colitis is useful to follow temporal changes of inflammation visually and histologically, and to acquire tissue for gene expression analyses. TNBS-colitis is an appropriate model to study specific biological processes in IBD. PMID:23382912

The Porcelain Crab Transcriptome and PCAD, the Porcelain Crab Microarray and Sequence Database

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

Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika

2010-01-27

Background: With the emergence of a completed genome sequence of the freshwater crustacean Daphnia pulex, construction of genomic-scale sequence databases for additional crustacean sequences are important for comparative genomics and annotation. Porcelain crabs, genus Petrolisthes, have been powerful crustacean models for environmental and evolutionary physiology with respect to thermal adaptation and understanding responses of marine organisms to climate change. Here, we present a large-scale EST sequencing and cDNA microarray database project for the porcelain crab Petrolisthes cinctipes. Methodology/Principal Findings: A set of ~;;30K unique sequences (UniSeqs) representing ~;;19K clusters were generated from ~;;98K high quality ESTs from a set ofmore » tissue specific non-normalized and mixed-tissue normalized cDNA libraries from the porcelain crab Petrolisthes cinctipes. Homology for each UniSeq was assessed using BLAST, InterProScan, GO and KEGG database searches. Approximately 66percent of the UniSeqs had homology in at least one of the databases. All EST and UniSeq sequences along with annotation results and coordinated cDNA microarray datasets have been made publicly accessible at the Porcelain Crab Array Database (PCAD), a feature-enriched version of the Stanford and Longhorn Array Databases.Conclusions/Significance: The EST project presented here represents the third largest sequencing effort for any crustacean, and the largest effort for any crab species. Our assembly and clustering results suggest that our porcelain crab EST data set is equally diverse to the much larger EST set generated in the Daphnia pulex genome sequencing project, and thus will be an important resource to the Daphnia research community. Our homology results support the pancrustacea hypothesis and suggest that Malacostraca may be ancestral to Branchiopoda and Hexapoda. Our results also suggest that our cDNA microarrays cover as much of the transcriptome as can reasonably be captured in EST library sequencing approaches, and thus represent a rich resource for studies of environmental genomics.« less

The Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) Screening Trial Pathology Tissue Resource.

PubMed

Zhu, Claire S; Huang, Wen-Yi; Pinsky, Paul F; Berg, Christine D; Sherman, Mark; Yu, Kelly J; Carrick, Danielle M; Black, Amanda; Hoover, Robert; Lenz, Petra; Williams, Craig; Hawkins, Laura; Chaloux, Matthew; Yurgalevitch, Susan; Mathew, Sunitha; Miller, Amy; Olivo, Vanessa; Khan, Asia; Pretzel, Shannon M; Multerer, Deborah; Beckmann, Patricia; Broski, Karen G; Freedman, Neal D

2016-12-01

Pathology tissue specimens with associated epidemiologic and clinical data are valuable for cancer research. The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial undertook a large-scale effort to create a public resource of pathology tissues from PLCO participants who developed a cancer during the trial. Formalin-fixed paraffin-embedded tissue blocks were obtained from pathology laboratories on a loan basis for central processing of tissue microarrays, with additional free-standing tissue cores collected for nucleic acid extraction. Pathology tissue specimens were obtained for prostate cancer (n = 1,052), lung cancer (n = 434), colorectal cancer (n = 675) and adenoma (n = 658), ovarian cancer and borderline tumors (n = 212), breast cancer (n = 870), and bladder cancer (n = 204). The process of creating this resource was complex, involving multidisciplinary teams with expertise in pathology, epidemiology, information technology, project management, and specialized laboratories. Creating the PLCO tissue resource required a multistep process, including obtaining medical records and contacting pathology departments where pathology materials were stored after obtaining necessary patient consent and authorization. The potential to link tissue biomarkers to prospectively collected epidemiologic information, screening and clinical data, and matched blood or buccal samples offers valuable opportunities to study etiologic heterogeneity, mechanisms of carcinogenesis, and biomarkers for early detection and prognosis. The methods and protocols developed for this effort, and the detailed description of this resource provided here, will be useful for those seeking to use PLCO pathology tissue specimens for their research and may also inform future tissue collection efforts in other settings. Cancer Epidemiol Biomarkers Prev; 25(12); 1635-42. ©2016 AACR. ©2016 American Association for Cancer Research.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Downregulation of TES by hypermethylation in glioblastoma reduces cell apoptosis and predicts poor clinical outcome.

PubMed

Bai, Yu; Zhang, Quan-Geng; Wang, Xin-Hua

2014-12-11

Gliomas are the most common human brain tumors. Glioblastoma, also known as glioblastoma multiform (GBM), is the most aggressive, malignant, and lethal glioma. The investigation of prognostic and diagnostic molecular biomarkers in glioma patients to provide direction on clinical practice is urgent. Recent studies demonstrated that abnormal DNA methylation states play a key role in the pathogenesis of this kind of tumor. In this study, we want to identify a novel biomarker related to glioma initiation and find the role of the glioma-related gene. We performed a methylation-specific microarray on the promoter region to identify methylation gene(s) that may affect outcome of GBM patients. Normal and GBM tissues were collected from Tiantan Hospital. Genomic DNA was extracted from these tissues and analyzed with a DNA promoter methylation microarray. Testis derived transcript (TES) protein expression was analyzed by immunohistochemistry in paraffin-embedded patient tissues. Western blotting was used to detect TES protein expression in the GBM cell line U251 with or without 5-aza-dC treatment. Cell apoptosis was evaluated by flow cytometry analysis using Annexin V/PI staining. We found that the TES promoter was hypermethylated in GBM compared to normal brain tissues under DNA promoter methylation microarray analysis. The GBM patients with TES hypermethylation had a short overall survival (P <0.05, log-rank test). Among GBM samples, reduced TES protein level was detected in 33 (89.2%) of 37 tumor tissues by immunohistochemical staining. Down regulation of TES was also correlated with worse patient outcome (P <0.05, log-rank test). Treatment on the GBM cell line U251 with 5-aza-dC can greatly increase TES expression, confirming the hypermethylation of TES promoter in GBM. Up-regulation of TES prompts U251 apoptosis significantly. This study demonstrated that both TES promoter hypermethylation and down-regulated protein expression significantly correlated with worse patient outcome. Treatment on the GBM cell line (U251) with 5-aza-dC can highly release TES expression resulting in significant apoptosis in these cells. Our findings suggest that the TES gene is a novel tumor suppressor gene and might represent a valuable prognostic marker for glioblastoma, indicating a potential target for future GBM therapy.

Addressable droplet microarrays for single cell protein analysis.

PubMed

Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

2014-11-07

Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Temperature-controlled microintaglio printing for high-resolution micropatterning of RNA molecules.

PubMed

Kobayashi, Ryo; Biyani, Manish; Ueno, Shingo; Kumal, Subhashini Raj; Kuramochi, Hiromi; Ichiki, Takanori

2015-05-15

We have developed an advanced microintaglio printing method for fabricating fine and high-density micropatterns and applied it to the microarraying of RNA molecules. The microintaglio printing of RNA reported here is based on the hybridization of RNA with immobilized complementary DNA probes. The hybridization was controlled by switching the RNA conformation via the temperature, and an RNA microarray with a diameter of 1.5 µm and a density of 40,000 spots/mm(2) with high contrast was successfully fabricated. Specifically, no size effects were observed in the uniformity of patterned signals over a range of microarray feature sizes spanning one order of magnitude. Additionally, we have developed a microintaglio printing method for transcribed RNA microarrays on demand using DNA-immobilized magnetic beads. The beads were arrayed on wells fabricated on a printing mold and the wells were filled with in vitro transcription reagent and sealed with a DNA-immobilized glass substrate. Subsequently, RNA was in situ synthesized using the bead-immobilized DNA as a template and printed onto the substrate via hybridization. Since the microintaglio printing of RNA using DNA-immobilized beads enables the fabrication of a microarray of spots composed of multiple RNA sequences, it will be possible to screen or analyze RNA functions using an RNA microarray fabricated by temperature-controlled microintaglio printing (TC-µIP). Copyright © 2014 Elsevier B.V. All rights reserved.

Integrative missing value estimation for microarray data.

PubMed

Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine

2006-10-12

Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

Internal controls for quantitative polymerase chain reaction of swine mammary glands during pregnancy and lactation.

PubMed

Tramontana, S; Bionaz, M; Sharma, A; Graugnard, D E; Cutler, E A; Ajmone-Marsan, P; Hurley, W L; Loor, J J

2008-08-01

High-throughput microarray analysis is an efficient means of obtaining a genome-wide view of transcript profiles across physiological states. However, quantitative PCR (qPCR) remains the chosen method for high-precision mRNA abundance analysis. Essential for reliability of qPCR data is normalization using appropriate internal control genes (ICG), which is now, more than ever before, a fundamental step for accurate gene expression profiling. We mined mammary tissue microarray data on >13,000 genes at -34, -14, 0, 7, 14, 21, and 28 d relative to parturition in 27 crossbred primiparous gilts to identify suitable ICG. Initial analysis revealed TBK1, PCSK2, PTBP1, API5, VAPB, QTRT1, TRIM41, TMEM24, PPP2R5B, and AP1S1 as the most stable genes (sample/reference = 1 +/- 0.2). We also included 9 genes previously identified as ICG in bovine mammary tissue. Gene network analysis of the 19 genes identified AP1S1, API5, MTG1, VAPB, TRIM41, MRPL39, and RPS15A as having no known co-regulation. In addition, UXT and ACTB were added to this list, and mRNA abundance of these 9 genes was measured by qPCR. Expression of all 9 of these genes was decreased markedly during lactation. In a previous study with bovine mammary tissue, mRNA of stably expressed genes decreased during lactation due to a dilution effect brought about by large increases in expression of highly abundant genes. To verify this effect, highly abundant mammary genes such as CSN1S2, SCD, FABP3, and LTF were evaluated by qPCR. The tested ICG had a negative correlation with these genes, demonstrating a dilution effect in the porcine mammary tissue. Gene stability analysis identified API5, VABP, and MRPL39 as the most stable ICG in porcine mammary tissue and indicated that the use of those 3 genes was most appropriate for calculating a normalization factor. Overall, results underscore the importance of proper validation of internal controls for qPCR and highlight the limitations of using absence of time effects as the criteria for selection of appropriate ICG. Further, we showed that use of the same ICG from one organism might not be suitable for qPCR normalization in other species.

Immunohistochemical characterization of neoplastic cells of breast origin.

PubMed

Noriega, Mariadelasmercedes; Paesani, Fernando; Perazzo, Florencia; Lago, Néstor; Krupitzki, Hugo; Nieto, Silvana; Garcia, Alejandro; Avagnina, Alejandra; Elsner, Boris; Denninghoff, Valeria Cecilia

2012-06-22

After skin cancer, breast cancer is the most common malignancy in women. Tumors of unknown origin account for 5-15% of malignant neoplasms, with 1.5% being breast cancer. An immunohistochemical panel with conventional and newer markers, such as mammaglobin, was selected for the detection of neoplastic cells of breast origin. The specific objectives are: 1) to determine the sensitivity and specificity of the panel, with a special emphasis on the inclusion of the mammaglobin marker, and 2) to compare immunohistochemistry performed on whole tissue sections and on tissue micro-array. Twenty-nine metastatic breast tumors were included and assumed as tumors of unknown origin. Other 48 biopsies of diverse tissues were selected and assumed as negative controls. Tissue Micro-Array was performed. Immunohistochemistry for mammaglobin, gross cystic disease fluid protein-15, estrogen receptor, progesterone receptor and cytokeratin 7 was done. Mammaglobin positive staining was observed in 10/29 cases, in 13/29 cases for gross cystic disease fluid protein-15, in 20/29 cases for estrogen receptor, in 9/29 cases for progesterone receptor, and in 25/29 cases for cytokeratin 7. Among the negative controls, mammaglobin was positive in 2/48, and gross cystic disease fluid protein-15 in 4/48. The inclusion of MAG antibody in the immunohistochemical panel for the detection of tumors of unknown origin contributed to the detection of metastasis of breast cancer. The diagnostic strategy with the highest positive predictive value (88%) included hormone receptors and mammaglobin in serial manner.

Doxycycline affects gene expression profiles in aortic tissues in a rat model of vascular calcification.

PubMed

Lu, Hailin; Jiang, Wenhong; Yang, Han; Qin, Zhong; Guo, Si-En; Hu, Ming; Qin, Xiao

2017-11-01

Vitamin D 3 -induced vascular calcification (VC) in rats shares many phenotypical similarities with calcification occurring in human atherosclerosis, diabetes mellitus and chronic kidney disease, thereby it is a reliable model for identifying chemopreventive agents. Doxycycline has been shown to effectively attenuated VC. This study aimed to explore the effects of doxycycline on gene expression profiles in VC rats. The model of VC in rats was established by subcutaneous injection of vitamin D3 for 3days. Doxycycline at 120mgkg -1 day -1 was given via subcutaneous injection for 14days. Rat pathological changes, calcium deposition and calcium content in aortic tissues were measured by Hematoxylin-eosin, von Kossa staining and colorimetry, respectively. The gene change profile of aortic tissues after doxycycline treatment was assessed by Gene Microarray analysis using the Agilent Whole Rat Genome Oligo Microarray. The results showed that doxycycline significantly decreased the deposition of calcium, reduced the relative calcification area and alleviated pathological injury in aortic tissues. In addition, doxycycline treatment altered 88 gene expressions compared with untreated VD group. Of these, 61 genes were down-regulated and 27 genes were up-regulated. The functions of differentially expressed (DE) genes were involved in neutrophil chemotaxis, chronic inflammatory response, negative regulation of apoptotic process, cellular response to mechanical stimulus and immune response, etc. In conclusions, this study might provide the potential novel insights into the molecular mechanisms of doxycycline on VC. Copyright © 2017. Published by Elsevier Inc.

The impact of luteal phase support on endometrial estrogen and progesterone receptor expression: a randomized control trial

PubMed Central

2012-01-01

Background To assess the impact of luteal phase support on the expression of estrogen receptor (ER) alpha and progesterone receptors B (PR-B) on the endometrium of oocyte donors undergoing controlled ovarian hyperstimulation (COH). Methods A prospective, randomized study was conducted in women undergoing controlled ovarian hyperstimulation for oocyte donation. Participants were randomized to receive no luteal support, vaginal progesterone alone, or vaginal progesterone plus orally administered 17 Beta estradiol. Endometrial biopsies were obtained at 4 time points in the luteal phase and evaluated by tissue microarray for expression of ER alpha and PR-B. Results One-hundred and eight endometrial tissue samples were obtained from 12 patients. No differences were found in expression of ER alpha and PR-B among all the specimens with the exception of one sample value. Conclusions The administration of progesterone during the luteal phase of COH for oocyte donor cycles, either with or without estrogen, does not significantly affect the endometrial expression of ER alpha and PR. PMID:22360924

Signal amplification by rolling circle amplification on DNA microarrays

PubMed Central

Nallur, Girish; Luo, Chenghua; Fang, Linhua; Cooley, Stephanie; Dave, Varshal; Lambert, Jeremy; Kukanskis, Kari; Kingsmore, Stephen; Lasken, Roger; Schweitzer, Barry

2001-01-01

While microarrays hold considerable promise in large-scale biology on account of their massively parallel analytical nature, there is a need for compatible signal amplification procedures to increase sensitivity without loss of multiplexing. Rolling circle amplification (RCA) is a molecular amplification method with the unique property of product localization. This report describes the application of RCA signal amplification for multiplexed, direct detection and quantitation of nucleic acid targets on planar glass and gel-coated microarrays. As few as 150 molecules bound to the surface of microarrays can be detected using RCA. Because of the linear kinetics of RCA, nucleic acid target molecules may be measured with a dynamic range of four orders of magnitude. Consequently, RCA is a promising technology for the direct measurement of nucleic acids on microarrays without the need for a potentially biasing preamplification step. PMID:11726701

A perspective on microarrays: current applications, pitfalls, and potential uses

PubMed Central

Jaluria, Pratik; Konstantopoulos, Konstantinos; Betenbaugh, Michael; Shiloach, Joseph

2007-01-01

With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold. PMID:17254338

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

Network-based de-noising improves prediction from microarray data.

PubMed

Kato, Tsuyoshi; Murata, Yukio; Miura, Koh; Asai, Kiyoshi; Horton, Paul B; Koji, Tsuda; Fujibuchi, Wataru

2006-03-20

Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as the high variance of living cell responses to drugs. Hence there is a strong need for more practical and robust methods than standard methods for real-value prediction. We devised an extended version of the off-subspace noise-reduction (de-noising) method to incorporate heterogeneous network data such as sequence similarity or protein-protein interactions into a single framework. Using that method, we first de-noise the gene expression data for training and test data and also the drug-response data for training data. Then we predict the unknown responses of each drug from the de-noised input data. For ascertaining whether de-noising improves prediction or not, we carry out 12-fold cross-validation for assessment of the prediction performance. We use the Pearson's correlation coefficient between the true and predicted response values as the prediction performance. De-noising improves the prediction performance for 65% of drugs. Furthermore, we found that this noise reduction method is robust and effective even when a large amount of artificial noise is added to the input data. We found that our extended off-subspace noise-reduction method combining heterogeneous biological data is successful and quite useful to improve prediction of human cell cancer drug responses from microarray data.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data

PubMed Central

Watson, Christopher M.; Crinnion, Laura A.; Gurgel‐Gianetti, Juliana; Harrison, Sally M.; Daly, Catherine; Antanavicuite, Agne; Lascelles, Carolina; Markham, Alexander F.; Pena, Sergio D. J.; Bonthron, David T.

2015-01-01

ABSTRACT Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease‐causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome‐wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. PMID:26037133

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

2009-01-01

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

Head and Neck Squamous Cell Carcinomas Do Not Express EGFRvIII

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

Melchers, Lieuwe J., E-mail: l.j.melchers@umcg.nl; Department of Pathology, University Medical Center Groningen, University of Groningen, Groningen; Clausen, Martijn J.A.M.

2014-10-01

Purpose: To assess the prevalence of EGFRvIII, a specific variant of EGFR (epidermal growth factor receptor), in 3 well-defined cohorts of head and neck squamous cell carcinoma (HNSCC). Methods and Materials: Immunohistochemistry for the specific detection of EGFRvIII using the L8A4 antibody was optimized on formalin-fixed, paraffin-embedded tissue using glioblastoma tissue. It was compared with EGFR and EGFRvIII RNA expression using a specific reverse transcription–polymerase chain reaction also optimized for formalin-fixed, paraffin-embedded tissue. Tissue microarrays including 531 HNSCCs of various stages with complete clinicopathologic and follow-up data were tested for the presence of EGFRvIII. Results: None of the 531 casesmore » showed EGFRvIII protein expression. Using an immunohistochemistry protocol reported by others revealed cytoplasmic staining in 8% of cases. Reverse transcription–polymerase chain reaction for the EGFRvIII transcript of the 28 highest cytoplasmic staining cases, as well as 69 negative cases, did not show expression in any of the tested cases, suggesting aspecific staining by a nonoptimal protocol. Conclusions: The EGFRvIII mutation is not present in HNSCC. Therefore, EGFRvIII does not influence treatment response in HNSCC and is not a usable clinical prognostic marker.« less

West Nile virus infection in killer whale, Texas, USA, 2007.

PubMed

St Leger, Judy; Wu, Guang; Anderson, Mark; Dalton, Les; Nilson, Erika; Wang, David

2011-08-01

In 2007, nonsuppurative encephalitis was identified in a killer whale at a Texas, USA, marine park. Panviral DNA microarray of brain tissue suggested West Nile virus (WNV); WNV was confirmed by reverse transcription PCR and sequencing. Immunohistochemistry demonstrated WNV antigen within neurons. WNV should be considered in cases of encephalitis in cetaceans.

Differences in X-chromosome transcriptional activity and cholesterol metabolism between placentae from swine breeds from asian and western origins

USDA-ARS?s Scientific Manuscript database

To gain insight into placental physiology differences between the Chinese Meishan and white composite (WC) swine breeds, short-oligonucleotide microarray gene expression profiles of gestational Day 25, 45, 65, 85, and 105 placental tissues were compared. Differential expression was determined by a ...

Endoglin (CD105) expression on microvessel endothelial cells in juvenile nasopharyngeal angiofibroma: tissue microarray analysis and association with prognostic significance.

PubMed

Wang, Jing-Jing; Sun, Xi-Cai; Hu, Li; Liu, Zhuo-Fu; Yu, Hua-Peng; Li, Han; Wang, Shu-Yi; Wang, De-Hui

2013-12-01

The purpose of this study was to examine endoglin (CD105) expression on microvessel endothelial cells (ECs) in juvenile nasopharyngeal angiofibroma (JNA) and its relationship with recurrence. Immunohistochemistry was performed to detect CD105 expression in a tissue microarray from 70 patients with JNA. Correlation between CD105 expression on microvessel ECs and clinicopathological features, as well as tumor recurrence, were analyzed. Immunohistochemistry revealed CD105 expression on ECs but not in stroma of patients with JNA. Chi-square analysis indicated CD105-based microvessel density (MVD) was correlated with JNA recurrence (p = .013). Univariate and multivariate analyses determined that MVD was a significant predictor of time to recurrence (p = .009). The CD105-based MVD was better for predicting disease recurrence (AUROC: 0.673; p = .036) than other clinicopathological features. MVD is a useful predictor for poor prognosis of patients with JNA after curative resection. Angiogenesis, which may play an important role in the occurrence and development of JNA, is therefore a potential therapeutic target for JNA. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

Circular RNA hsa_circ_0008344 regulates glioblastoma cell proliferation, migration, invasion, and apoptosis.

PubMed

Zhou, Jinxu; Wang, Hongxiang; Chu, Junsheng; Huang, Qilin; Li, Guangxu; Yan, Yong; Xu, Tao; Chen, Juxiang; Wang, Yuhai

2018-04-24

Recent studies have found circular RNAs (circRNAs) involved in the biological process of cancers. However, little is known about their functional roles in glioblastoma. Human circRNA microarray analysis was performed to screen the expression profile of circRNAs in IDH1 wild-type glioblastoma tissue. The expression of hsa_circ_0008344 in glioblastoma and normal brain samples was quantified by qRT-PCR. Functional experiments were performed to investigate the biological functions of hsa_circ_0008344, including MTT assay, colony formation assay, transwell assay, and cell apoptosis assay. CircRNA microarray revealed a total of 417 abnormally expressed circRNAs (>1.5-fold, P < .05) in glioblastoma tissue compared with the adjacent normal brain. Hsa_circ_0008344, among the top differentially expressed circRNAs, was significantly upregulated in IDH1 wild-type glioblastoma. Further in vitro studies showed that knockdown of hsa_circ_0008344 suppressed glioblastoma cell proliferation, colony formation, migration, and invasion, but increased cell apoptotic rate. Hsa_circ_0008344 is upregulated in glioblastoma and may contribute to the progression of this malignancy. © 2018 Wiley Periodicals, Inc.

Automatic tissue segmentation of breast biopsies imaged by QPI

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Nguyen, Tan; Kandel, Mikhail; Marcias, Virgilia; Do, Minh; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2016-03-01

The current tissue evaluation method for breast cancer would greatly benefit from higher throughput and less inter-observer variation. Since quantitative phase imaging (QPI) measures physical parameters of tissue, it can be used to find quantitative markers, eliminating observer subjectivity. Furthermore, since the pixel values in QPI remain the same regardless of the instrument used, classifiers can be built to segment various tissue components without need for color calibration. In this work we use a texton-based approach to segment QPI images of breast tissue into various tissue components (epithelium, stroma or lumen). A tissue microarray comprising of 900 unstained cores from 400 different patients was imaged using Spatial Light Interference Microscopy. The training data were generated by manually segmenting the images for 36 cores and labelling each pixel (epithelium, stroma or lumen.). For each pixel in the data, a response vector was generated by the Leung-Malik (LM) filter bank and these responses were clustered using the k-means algorithm to find the centers (called textons). A random forest classifier was then trained to find the relationship between a pixel's label and the histogram of these textons in that pixel's neighborhood. The segmentation was carried out on the validation set by calculating the texton histogram in a pixel's neighborhood and generating a label based on the model learnt during training. Segmentation of the tissue into various components is an important step toward efficiently computing parameters that are markers of disease. Automated segmentation, followed by diagnosis, can improve the accuracy and speed of analysis leading to better health outcomes.

Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.

PubMed

Ooi, Chia Huey; Chetty, Madhu; Teng, Shyh Wei

2006-06-23

Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gene expression-based tissue classification while improving accuracy at the same time. Surprisingly, this does not appear to be the case for all multiclass microarray datasets. The reason is that many feature selection techniques applied on microarray datasets are either rank-based and hence do not take into account correlations between genes, or are wrapper-based, which require high computational cost, and often yield difficult-to-reproduce results. In studies where correlations between genes are considered, attempts to establish the merit of the proposed techniques are hampered by evaluation procedures which are less than meticulous, resulting in overly optimistic estimates of accuracy. We present two realistically evaluated correlation-based feature selection techniques which incorporate, in addition to the two existing criteria involved in forming a predictor set (relevance and redundancy), a third criterion called the degree of differential prioritization (DDP). DDP functions as a parameter to strike the balance between relevance and redundancy, providing our techniques with the novel ability to differentially prioritize the optimization of relevance against redundancy (and vice versa). This ability proves useful in producing optimal classification accuracy while using reasonably small predictor set sizes for nine well-known multiclass microarray datasets. For multiclass microarray datasets, especially the GCM and NCI60 datasets, DDP enables our filter-based techniques to produce accuracies better than those reported in previous studies which employed similarly realistic evaluation procedures.

ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

PubMed Central

2014-01-01

Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361

DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

PubMed

Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh

2017-01-01

A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.

Normal uniform mixture differential gene expression detection for cDNA microarrays

PubMed Central

Dean, Nema; Raftery, Adrian E

2005-01-01

Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE) detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002) [1]. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM), and Empirical Bayes for microarrays (EBarrays) with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at . PMID:16011807

Universal ligation-detection-reaction microarray applied for compost microbes

PubMed Central

Hultman, Jenni; Ritari, Jarmo; Romantschuk, Martin; Paulin, Lars; Auvinen, Petri

2008-01-01

Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities. PMID:19116002

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

The clinicopathologic association of c-MET overexpression in Iranian gastric carcinomas; an immunohistochemical study of tissue microarrays.

PubMed

Sotoudeh, Kambiz; Hashemi, Forough; Madjd, Zahra; Sadeghipour, Alireza; Molanaei, Saadat; Kalantary, Elham

2012-05-28

c-MET is an oncogene protein that plays important role in gastric carcinogenesis and has been introduced as a prognostic marker and potential therapeutic target. The aim of this study was to evaluate the frequency of c-MET overexpression and its relationship with clinicopathological variables in gastric cancer of Iranian population using tissue microarray. In a cross sectional study, representative paraffin blocks of 130 patients with gastric carcinoma treated by curative gastrectomy during a 2 years period of 2008-2009 in two university hospitals in Tehran-Iran were collected in tissue microarray and c-MET expression was studied by immunohistochemical staining. Finally 124 cases were evaluated, constituted of 99 male and 25 female with the average age of 61.5 years. In 71% (88/124) of tumors, c-MET high expression was found. c-MET high expression was more associated with intestinal than diffuse tumor type (P = 0.04), deeper tumor invasion, pT3 and pT4 versus pT1 and pT2 (P = 0.014), neural invasion (P = 0.002) and advanced TNM staging, stage 3 and 4 versus stage 1 and2 (P = 0.044). The c-MET high expression was not associated with age, sex, tumor location, differentiation grade and distant metastasis, but relative associations with lymph node metastasis (P = 0.065) and vascular invasion (P = 0.078) were observed. c-MET oncogene protein was frequently overexpressed in Iranian gastric carcinomas and it was related to clinicopathological characteristics such as tumor type, depth of invasion, neural invasion and TNM staging. It can also support the idea that c-MET is a potential marker for target therapy in Iranian gastric cancer. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9744598757151429.

High-Density Droplet Microarray of Individually Addressable Electrochemical Cells.

PubMed

Zhang, Huijie; Oellers, Tobias; Feng, Wenqian; Abdulazim, Tarik; Saw, En Ning; Ludwig, Alfred; Levkin, Pavel A; Plumeré, Nicolas

2017-06-06

Microarray technology has shown great potential for various types of high-throughput screening applications. The main read-out methods of most microarray platforms, however, are based on optical techniques, limiting the scope of potential applications of such powerful screening technology. Electrochemical methods possess numerous complementary advantages over optical detection methods, including its label-free nature, capability of quantitative monitoring of various reporter molecules, and the ability to not only detect but also address compositions of individual compartments. However, application of electrochemical methods for the purpose of high-throughput screening remains very limited. In this work, we develop a high-density individually addressable electrochemical droplet microarray (eDMA). The eDMA allows for the detection of redox-active reporter molecules irrespective of their electrochemical reversibility in individual nanoliter-sized droplets. Orthogonal band microelectrodes are arranged to form at their intersections an array of three-electrode systems for precise control of the applied potential, which enables direct read-out of the current related to analyte detection. The band microelectrode array is covered with a layer of permeable porous polymethacrylate functionalized with a highly hydrophobic-hydrophilic pattern, forming spatially separated nanoliter-sized droplets on top of each electrochemical cell. Electrochemical characterization of single droplets demonstrates that the underlying electrode system is accessible to redox-active molecules through the hydrophilic polymeric pattern and that the nonwettable hydrophobic boundaries can spatially separate neighboring cells effectively. The eDMA technology opens the possibility to combine the high-throughput biochemical or living cell screenings using the droplet microarray platform with the sequential electrochemical read-out of individual droplets.

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

Quantification of viable and non-viable Legionella spp. by heterogeneous asymmetric recombinase polymerase amplification (haRPA) on a flow-based chemiluminescence microarray.

PubMed

Kober, Catharina; Niessner, Reinhard; Seidel, Michael

2018-02-15

Increasing numbers of legionellosis outbreaks within the last years have shown that Legionella are a growing challenge for public health. Molecular biological detection methods capable of rapidly identifying viable Legionella are important for the control of engineered water systems. The current gold standard based on culture methods takes up to 10 days to show positive results. For this reason, a flow-based chemiluminescence (CL) DNA microarray was developed that is able to quantify viable and non-viable Legionella spp. as well as Legionella pneumophila in one hour. An isothermal heterogeneous asymmetric recombinase polymerase amplification (haRPA) was carried out on flow-based CL DNA microarrays. Detection limits of 87 genomic units (GU) µL -1 and 26GUµL -1 for Legionella spp. and Legionella pneumophila, respectively, were achieved. In this work, it was shown for the first time that the combination of a propidium monoazide (PMA) treatment with haRPA, the so-called viability haRPA, is able to identify viable Legionella on DNA microarrays. Different proportions of viable and non-viable Legionella, shown with the example of L. pneumophila, ranging in a total concentration between 10 1 to 10 5 GUµL -1 were analyzed on the microarray analysis platform MCR 3. Recovery values for viable Legionella spp. were found between 81% and 133%. With the combination of these two methods, there is a chance to replace culture-based methods in the future for the monitoring of engineered water systems like condensation recooling plants. Copyright © 2017 Elsevier B.V. All rights reserved.

Connective tissue growth factor immunohistochemical expression is associated with gallbladder cancer progression.

PubMed

Garcia, Patricia; Leal, Pamela; Alvarez, Hector; Brebi, Priscilla; Ili, Carmen; Tapia, Oscar; Roa, Juan C

2013-02-01

Gallbladder cancer (GBC) is an aggressive neoplasia associated with late diagnosis, unsatisfactory treatment, and poor prognosis. Molecular mechanisms involved in GBC pathogenesis remain poorly understood. Connective tissue growth factor (CTGF) is thought to play a role in the pathologic processes and is overexpressed in several human cancers, including GBC. No information is available about CTGF expression in early stages of gallbladder carcinogenesis. Objective.- To evaluate the expression level of CTGF in benign and malignant lesions of gallbladder and its correlation with clinicopathologic features and GBC prognosis. Connective tissue growth factor protein was examined by immunohistochemistry on tissue microarrays containing tissue samples of chronic cholecystitis (n = 51), dysplasia (n = 15), and GBC (n = 169). The samples were scored according to intensity of staining as low/absent and high CTGF expressers. Statistical analysis was performed using the χ(2) test or Fisher exact probability test with a significance level of P < .05. Survival analysis was assessed by the Kaplan-Meier method and the log-rank test. Connective tissue growth factor expression showed a progressive increase from chronic cholecystitis to dysplasia and then to early and advanced carcinoma. Immunohistochemical expression (score ≥2) was significantly higher in advanced tumors, in comparison with chronic cholecystitis (P < .001) and dysplasia (P = .03). High levels of CTGF expression correlated with better survival (P = .04). Our results suggest a role for CTGF in GBC progression and a positive association with better prognosis. In addition, they underscore the importance of considering the involvement of inflammation on GBC development.

The role of extracellular matrix components in pin bone attachments during storage-a comparison between farmed Atlantic salmon (Salmo salar) and cod (Gadus morhua L.).

PubMed

Rønning, Sissel B; Østbye, Tone-Kari; Krasnov, Aleksei; Vuong, Tram T; Veiseth-Kent, Eva; Kolset, Svein O; Pedersen, Mona E

2017-04-01

Pin bones represent a major problem for processing and quality of fish products. Development of methods of removal requires better knowledge of the pin bones' attachment to the muscle and structures involved in the breakdown during loosening. In this study, pin bones from cod and salmon were dissected from fish fillets after slaughter or storage on ice for 5 days, and thereafter analysed with molecular methods, which revealed major differences between these species before and after storage. The connective tissue (CT) attaches the pin bone to the muscle in cod, while the pin bones in salmon are embedded in adipose tissue. Collagens, elastin, lectin-binding proteins and glycosaminoglycans (GAGs) are all components of the attachment site, and this differ between salmon and cod, resulting in a CT in cod that is more resistant to enzymatic degradation compared to the CT in salmon. Structural differences are reflected in the composition of transcriptome. Microarray analysis comparing the attachment sites of the pin bones with a reference muscle sample showed limited differences in salmon. In cod, on the other hand, the variances were substantial, and the gene expression profiles suggested difference in myofibre structure, metabolism and cell processes between the pin bone attachment site and the reference muscle. Degradation of the connective tissue occurs closest to the pin bones and not in the neighbouring tissue, which was shown using light microscopy. This study shows that the attachment of the pin bones in cod and salmon is different; therefore, the development of methods for removal should be tailored to each individual species.

Method for analyzing microbial communities

DOEpatents

Zhou, Jizhong [Oak Ridge, TN; Wu, Liyou [Oak Ridge, TN

2010-07-20

The present invention provides a method for quantitatively analyzing microbial genes, species, or strains in a sample that contains at least two species or strains of microorganisms. The method involves using an isothermal DNA polymerase to randomly and representatively amplify genomic DNA of the microorganisms in the sample, hybridizing the resultant polynucleotide amplification product to a polynucleotide microarray that can differentiate different genes, species, or strains of microorganisms of interest, and measuring hybridization signals on the microarray to quantify the genes, species, or strains of interest.

Analysis of mutations in oral poliovirus vaccine by hybridization with generic oligonucleotide microchips.

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

Proudnikov, D.; Kirillov, E.; Chumakov, K.

2000-01-01

This paper describes use of a new technology of hybridization with a micro-array of immobilized oligonucleotides for detection and quantification of neurovirulent mutants in Oral Poliovirus Vaccine (OPV). We used a micro-array consisting of three-dimensional gel-elements containing all possible hexamers (total of 4096 probes). Hybridization of fluorescently labelled viral cDNA samples with such microchips resulted in a pattern of spots that was registered and quantified by a computer-linked CCD camera, so that the sequence of the original cDNA could be deduced. The method could reliably identify single point mutations, since each of them affected fluorescence intensity of 12 micro-array elements.more » Micro-array hybridization of DNA mixtures with varying contents of point mutants demonstrated that the method can detect as little as 10% of revertants in a population of vaccine virus. This new technology should be useful for quality control of live viral vaccines, as well as for other applications requiring identification and quantification of point mutations.« less

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

Astronomical algorithms for automated analysis of tissue protein expression in breast cancer

PubMed Central

Ali, H R; Irwin, M; Morris, L; Dawson, S-J; Blows, F M; Provenzano, E; Mahler-Araujo, B; Pharoah, P D; Walton, N A; Brenton, J D; Caldas, C

2013-01-01

Background: High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress. Methods: We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists. Results: All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to ‘positive' or ‘negative' categories with agreement rates of up to 96%. Conclusion: The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology. PMID:23329232

The Use of P63 Immunohistochemistry for the Identification of Squamous Cell Carcinoma of the Lung

PubMed Central

Conde, Esther; Angulo, Bárbara; Redondo, Pilar; Toldos, Oscar; García-García, Elena; Suárez-Gauthier, Ana; Rubio-Viqueira, Belén; Marrón, Carmen; García-Luján, Ricardo; Sánchez-Céspedes, Montse; López-Encuentra, Angel; Paz-Ares, Luis; López-Ríos, Fernando

2010-01-01

Introduction While some targeted agents should not be used in squamous cell carcinomas (SCCs), other agents might preferably target SCCs. In a previous microarray study, one of the top differentially expressed genes between adenocarcinomas (ACs) and SCCs is P63. It is a well-known marker of squamous differentiation, but surprisingly, its expression is not widely used for this purpose. Our goals in this study were (1) to further confirm our microarray data, (2) to analize the value of P63 immunohistochemistry (IHC) in reducing the number of large cell carcinoma (LCC) diagnoses in surgical specimens, and (3) to investigate the potential of P63 IHC to minimize the proportion of “carcinoma NOS (not otherwise specified)” in a prospective series of small tumor samples. Methods With these goals in mind, we studied (1) a tissue-microarray comprising 33 ACs and 99 SCCs on which we performed P63 IHC, (2) a series of 20 surgically resected LCCs studied for P63 and TTF-1 IHC, and (3) a prospective cohort of 66 small thoracic samples, including 32 carcinoma NOS, that were further classified by the result of P63 and TTF-1 IHC. Results The results in the three independent cohorts were as follows: (1) P63 IHC was differentially expressed in SCCs when compared to ACs (p<0.0001); (2) half of the 20 (50%) LCCs were positive for P63 and were reclassified as SCCs; and (3) all P63 positive cases (34%) were diagnosed as SCCs. Conclusions P63 IHC is useful for the identification of lung SCCs. PMID:20808915

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.

TAM: a method for enrichment and depletion analysis of a microRNA category in a list of microRNAs.

PubMed

Lu, Ming; Shi, Bing; Wang, Juan; Cao, Qun; Cui, Qinghua

2010-08-09

MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing). For the above purpose, this study presents a method and develops a tool (TAM) for annotations of meaningful human miRNAs categories. We first integrated miRNAs into various meaningful categories according to prior knowledge, such as miRNA family, miRNA cluster, miRNA function, miRNA associated diseases, and tissue specificity. Using TAM, given lists of miRNAs can be rapidly annotated and summarized according to the integrated miRNA categorical data. Moreover, given a list of miRNAs, TAM can be used to predict novel related miRNAs. Finally, we confirmed the usefulness and reliability of TAM by applying it to deregulated miRNAs in acute myocardial infarction (AMI) from two independent experiments. TAM can efficiently identify meaningful categories for given miRNAs. In addition, TAM can be used to identify novel miRNA biomarkers. TAM tool, source codes, and miRNA category data are freely available at http://cmbi.bjmu.edu.cn/tam.