Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

PubMed

Mundt, Filip; Johansson, Henrik J; Forshed, Jenny; Arslan, Sertaç; Metintas, Muzaffer; Dobra, Katalin; Lehtiö, Janne; Hjerpe, Anders

2014-03-01

Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

PubMed

Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

2017-02-01

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

PubMed

Metz, Thomas O; Qian, Wei-Jun; Jacobs, Jon M; Gritsenko, Marina A; Moore, Ronald J; Polpitiya, Ashoka D; Monroe, Matthew E; Camp, David G; Mueller, Patricia W; Smith, Richard D

2008-02-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

Integrating multiple ‘omics’ analyses identifies serological protein biomarkers for preeclampsia

PubMed Central

2013-01-01

Background Preeclampsia (PE) is a pregnancy-related vascular disorder which is the leading cause of maternal morbidity and mortality. We sought to identify novel serological protein markers to diagnose PE with a multi-’omics’ based discovery approach. Methods Seven previous placental expression studies were combined for a multiplex analysis, and in parallel, two-dimensional gel electrophoresis was performed to compare serum proteomes in PE and control subjects. The combined biomarker candidates were validated with available ELISA assays using gestational age-matched PE (n=32) and control (n=32) samples. With the validated biomarkers, a genetic algorithm was then used to construct and optimize biomarker panels in PE assessment. Results In addition to the previously identified biomarkers, the angiogenic and antiangiogenic factors (soluble fms-like tyrosine kinase (sFlt-1) and placental growth factor (PIGF)), we found 3 up-regulated and 6 down-regulated biomakers in PE sera. Two optimal biomarker panels were developed for early and late onset PE assessment, respectively. Conclusions Both early and late onset PE diagnostic panels, constructed with our PE biomarkers, were superior over sFlt-1/PIGF ratio in PE discrimination. The functional significance of these PE biomarkers and their associated pathways were analyzed which may provide new insights into the pathogenesis of PE. PMID:24195779

Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program (DASP) sample subset

PubMed Central

Metz, Thomas O.; Qian, Wei-Jun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; Mueller, Patricia W.; Smith, Richard D.

2009-01-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted “-omics” approaches are under-utilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. Alpha-2-glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples. PMID:18092746

Identification of novel biomarker and therapeutic target candidates for acute intracerebral hemorrhage by quantitative plasma proteomics.

PubMed

Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling

2017-01-01

The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P  < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Meta-Analysis and Experimental Validation Identified FREM2 and SPRY1 as New Glioblastoma Marker Candidates.

PubMed

Vidak, Marko; Jovcevska, Ivana; Samec, Neja; Zottel, Alja; Liovic, Mirjana; Rozman, Damjana; Dzeroski, Saso; Juvan, Peter; Komel, Radovan

2018-05-04

Glioblastoma (GB) is the most aggressive brain malignancy. Although some potential glioblastoma biomarkers have already been identified, there is a lack of cell membrane-bound biomarkers capable of distinguishing brain tissue from glioblastoma and/or glioblastoma stem cells (GSC), which are responsible for the rapid post-operative tumor reoccurrence. In order to find new GB/GSC marker candidates that would be cell surface proteins (CSP), we have performed meta-analysis of genome-scale mRNA expression data from three data repositories (GEO, ArrayExpress and GLIOMASdb). The search yielded ten appropriate datasets, and three (GSE4290/GDS1962, GSE23806/GDS3885, and GLIOMASdb) were used for selection of new GB/GSC marker candidates, while the other seven (GSE4412/GDS1975, GSE4412/GDS1976, E-GEOD-52009, E-GEOD-68848, E-GEOD-16011, E-GEOD-4536, and E-GEOD-74571) were used for bioinformatic validation. The selection identified four new CSP-encoding candidate genes— CD276 , FREM2 , SPRY1 , and SLC47A1 —and the bioinformatic validation confirmed these findings. A review of the literature revealed that CD276 is not a novel candidate, while SLC47A1 had lower validation test scores than the other new candidates and was therefore not considered for experimental validation. This validation revealed that the expression of FREM2—but not SPRY1—is higher in glioblastoma cell lines when compared to non-malignant astrocytes. In addition, FREM2 gene and protein expression levels are higher in GB stem-like cell lines than in conventional glioblastoma cell lines. FREM2 is thus proposed as a novel GB biomarker and a putative biomarker of glioblastoma stem cells. Both FREM2 and SPRY1 are expressed on the surface of the GB cells, while SPRY1 alone was found overexpressed in the cytosol of non-malignant astrocytes.

Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

PubMed

Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-10-01

The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

Identifying Candidate Chemical-Disease Linkages ...

EPA Pesticide Factsheets

Presentation at meeting on Environmental and Epigenetic Determinants of IBD in New York, NY on identifying candidate chemical-disease linkages by using AOPs to identify molecular initiating events and using relevant high throughput assays to screen for candidate chemicals. This hazard information is combined with exposure models to inform risk assessment. Presentation at meeting on Environmental and Epigenetic Determinants of IBD in New York, NY on identifying candidate chemical-disease linkages by using AOPs to identify molecular initiating events and using relevant high throughput assays to screen for candidate chemicals. This hazard information is combined with exposure models to inform risk assessment.

Exosomal Fetuin-A identified by proteomics: a novel urinary biomarker for detecting acute kidney injury

PubMed Central

Zhou, Hua; Pisitkun, Trairak; Aponte, Angel; Yuen, Peter S.T.; Hoffert, Jason D.; Yasuda, Hideo; Hu, Xuzhen; Chawla, Lakhmir; Shen, Rong-Fong; Knepper, Mark A.; Star., Robert A.

2008-01-01

Urinary exosomes containing apical membrane and intracellular fluid are normally secreted into the urine from all nephron segments, and may carry protein markers of renal dysfunction and structural injury. We aimed to discover biomarkers in urinary exosomes to detect acute kidney injury (AKI) which has a high mortality and morbidity. Animals were injected intravenously with cisplatin. Urinary exosomes were isolated by differential centrifugation. Protein changes were evaluated by two-dimensional difference in gel electrophoresis and changed proteins were identified by MALDI-TOF-TOF or LC-MS/MS. The identified candidate biomarkers were validated by western blotting in individual urine samples from rats subjected to cisplatin injection; bilateral ischemia and reperfusion (I/R); volume depletion (VD); and ICU patients with and without AKI. We identified 18 proteins that were increased and 9 proteins that were decreased 8 hr after cisplatin. Most of the candidates could not be validated by western blotting. However, exosomal Fetuin-A increased 52.5-fold at day 2 (1 day before serum creatinine increase and tubule damage) and remained elevated 51.5-fold at day 5 (peak renal injury) after cisplatin injection. By immuno-electron microscopy and elution studies, Fetuin-A was located inside urinary exosomes. Urinary Fetuin-A was increased 31.6-fold in the early phase (2~8hr) of ischemia/reperfusion, but not in prerenal azotemia. Urinary exosomal Fetuin-A also increased in three ICU patients with AKI compared to the patients without AKI. We conclude that 1) Proteomic analysis of urinary exosomes can provide biomarker candidates for the diagnosis of AKI; 2) Urinary Fetuin-A might be a predictive biomarker of structural renal injury. PMID:17021608

Cerebrospinal Fluid Biomarker Candidates for Parkinsonian Disorders

PubMed Central

Constantinescu, Radu; Mondello, Stefania

2013-01-01

The Parkinsonian disorders are a large group of neurodegenerative diseases including idiopathic Parkinson’s disease (PD) and atypical Parkinsonian disorders (APD), such as multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, and dementia with Lewy bodies. The etiology of these disorders is not known although it is considered to be a combination of genetic and environmental factors. One of the greatest obstacles for developing efficacious disease-modifying treatment strategies is the lack of biomarkers. Reliable biomarkers are needed for early and accurate diagnosis, to measure disease progression, and response to therapy. In this review several of the most promising cerebrospinal biomarker candidates are discussed. Alpha-synuclein seems to be intimately involved in the pathogenesis of synucleinopathies and its levels can be measured in the cerebrospinal fluid and in plasma. In a similar way, tau protein accumulation seems to be involved in the pathogenesis of tauopathies. Urate, a potent antioxidant, seems to be associated to the risk of developing PD and with its progression. Neurofilament light chain levels are increased in APD compared with PD and healthy controls. The new “omics” techniques are potent tools offering new insights in the patho-etiology of these disorders. Some of the difficulties encountered in developing biomarkers are discussed together with future perspectives. PMID:23346074

Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.

PubMed

Moon, Myungjin; Nakai, Kenta

2018-04-01

Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.

Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Barnhart, Kurt T.; Speicher, David W.

2011-01-01

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers. PMID:21726088

Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Barnhart, Kurt T; Speicher, David W

2011-09-02

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

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

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

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

Novel Biomarker Candidates for Colorectal Cancer Metastasis: A Meta-analysis of In Vitro Studies

PubMed Central

Long, Nguyen Phuoc; Lee, Wun Jun; Huy, Nguyen Truong; Lee, Seul Ji; Park, Jeong Hill; Kwon, Sung Won

2016-01-01

Colorectal cancer (CRC) is one of the most common and lethal cancers. Although numerous studies have evaluated potential biomarkers for early diagnosis, current biomarkers have failed to reach an acceptable level of accuracy for distant metastasis. In this paper, we performed a gene set meta-analysis of in vitro microarray studies and combined the results from this study with previously published proteomic data to validate and suggest prognostic candidates for CRC metastasis. Two microarray data sets included found 21 significant genes. Of these significant genes, ALDOA, IL8 (CXCL8), and PARP4 had strong potential as prognostic candidates. LAMB2, MCM7, CXCL23A, SERPINA3, ABCA3, ALDH3A2, and POLR2I also have potential. Other candidates were more controversial, possibly because of the biologic heterogeneity of tumor cells, which is a major obstacle to predicting metastasis. In conclusion, we demonstrated a meta-analysis approach and successfully suggested ten biomarker candidates for future investigation. PMID:27688707

Novel Biomarker Candidates for Colorectal Cancer Metastasis: A Meta-analysis of In Vitro Studies.

PubMed

Long, Nguyen Phuoc; Lee, Wun Jun; Huy, Nguyen Truong; Lee, Seul Ji; Park, Jeong Hill; Kwon, Sung Won

2016-01-01

Colorectal cancer (CRC) is one of the most common and lethal cancers. Although numerous studies have evaluated potential biomarkers for early diagnosis, current biomarkers have failed to reach an acceptable level of accuracy for distant metastasis. In this paper, we performed a gene set meta-analysis of in vitro microarray studies and combined the results from this study with previously published proteomic data to validate and suggest prognostic candidates for CRC metastasis. Two microarray data sets included found 21 significant genes. Of these significant genes, ALDOA, IL8 (CXCL8), and PARP4 had strong potential as prognostic candidates. LAMB2, MCM7, CXCL23A, SERPINA3, ABCA3, ALDH3A2, and POLR2I also have potential. Other candidates were more controversial, possibly because of the biologic heterogeneity of tumor cells, which is a major obstacle to predicting metastasis. In conclusion, we demonstrated a meta-analysis approach and successfully suggested ten biomarker candidates for future investigation.

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

PubMed Central

Craciun, Florin L.; Bijol, Vanesa; Ajay, Amrendra K.; Rao, Poornima; Kumar, Ramya K.; Hutchinson, John; Hofmann, Oliver; Joshi, Nikita; Luyendyk, James P.; Kusebauch, Ulrike; Moss, Christopher L.; Srivastava, Anand; Himmelfarb, Jonathan; Waikar, Sushrut S.; Moritz, Robert L.

2016-01-01

CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acid-induced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten- to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two- to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P<0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD. PMID:26449608

Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds.

PubMed

Nagaraja, Sridevi; Chen, Lin; DiPietro, Luisa A; Reifman, Jaques; Mitrophanov, Alexander Y

2018-02-20

Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.

International Team Identifies Biomarker for Scleroderma

MedlinePlus

... Identifies Biomarker for Scleroderma Spotlight on Research International Team Identifies Biomarker for Scleroderma By Kirstie Saltsman, Ph. ... suggests it stems from immune system malfunction. The team chose to focus on immune cells called plasmacytoid ...

New Candidate Biomarkers in the Female Genital Tract to Evaluate Microbicide Toxicity

PubMed Central

Rasoul, Bareza; Fong, Julie; Works, Melissa G.; Shew, Kenneth; Yiu, Ying; Mirsalis, Jon; D'Andrea, Annalisa

2014-01-01

Vaginal microbicides hold great promise for the prevention of viral diseases like HIV, but the failure of several microbicide candidates in clinical trials has raised important questions regarding the parameters to be evaluated to determine in vivo efficacy in humans. Clinical trials of the candidate microbicides nonoxynol-9 (N9) and cellulose sulfate revealed an increase in HIV infection, vaginal inflammation, and recruitment of HIV susceptible lymphocytes, highlighting the need to identify biomarkers that can accurately predict microbicide toxicity early in preclinical development and in human trials. We used quantitative proteomics and RT-PCR approaches in mice and rabbits to identify protein changes in vaginal fluid and tissue in response to treatment with N9 or benzalkonium chloride (BZK). We compared changes generated with N9 and BZK treatment to the changes generated in response to tenofovir gel, a candidate microbicide that holds promise as a safe and effective microbicide. Both compounds down regulated mucin 5 subtype B, and peptidoglycan recognition protein 1 in vaginal tissue; however, mucosal brush samples also showed upregulation of plasma proteins fibrinogen, plasminogen, apolipoprotein A-1, and apolipoprotein C-1, which may be a response to the erosive nature of N9 and BZK. Additional proteins down-regulated in vaginal tissue by N9 or BZK treatment include CD166 antigen, olfactomedin-4, and anterior gradient protein 2 homolog. We also observed increases in the expression of C-C chemokines CCL3, CCL5, and CCL7 in response to treatment. There was concordance in expression level changes for several of these proteins using both the mouse and rabbit models. Using a human vaginal epithelial cell line, the expression of mucin 5 subtype B and olfactomedin-4 were down-regulated in response to N9, suggesting these markers could apply to humans. These data identifies new proteins that after further validation could become part of a panel of biomarkers to

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

PubMed Central

Kawahara, Rebeca; Bollinger, James G.; Rivera, César; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Paes Leme, Adriana F.; MacCoss, Michael J.

2015-01-01

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850

Large-Scale SRM Screen of Urothelial Bladder Cancer Candidate Biomarkers in Urine.

PubMed

Duriez, Elodie; Masselon, Christophe D; Mesmin, Cédric; Court, Magali; Demeure, Kevin; Allory, Yves; Malats, Núria; Matondo, Mariette; Radvanyi, François; Garin, Jérôme; Domon, Bruno

2017-04-07

Urothelial bladder cancer is a condition associated with high recurrence and substantial morbidity and mortality. Noninvasive urinary tests that would detect bladder cancer and tumor recurrence are required to significantly improve patient care. Over the past decade, numerous bladder cancer candidate biomarkers have been identified in the context of extensive proteomics or transcriptomics studies. To translate these findings in clinically useful biomarkers, the systematic evaluation of these candidates remains the bottleneck. Such evaluation involves large-scale quantitative LC-SRM (liquid chromatography-selected reaction monitoring) measurements, targeting hundreds of signature peptides by monitoring thousands of transitions in a single analysis. The design of highly multiplexed SRM analyses is driven by several factors: throughput, robustness, selectivity and sensitivity. Because of the complexity of the samples to be analyzed, some measurements (transitions) can be interfered by coeluting isobaric species resulting in biased or inconsistent estimated peptide/protein levels. Thus the assessment of the quality of SRM data is critical to allow flagging these inconsistent data. We describe an efficient and robust method to process large SRM data sets, including the processing of the raw data, the detection of low-quality measurements, the normalization of the signals for each protein, and the estimation of protein levels. Using this methodology, a variety of proteins previously associated with bladder cancer have been assessed through the analysis of urine samples from a large cohort of cancer patients and corresponding controls in an effort to establish a priority list of most promising candidates to guide subsequent clinical validation studies.

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

2016-01-01

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

PubMed Central

Craig-Schapiro, Rebecca; Kuhn, Max; Xiong, Chengjie; Pickering, Eve H.; Liu, Jingxia; Misko, Thomas P.; Perrin, Richard J.; Bales, Kelly R.; Soares, Holly; Fagan, Anne M.; Holtzman, David M.

2011-01-01

Background Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181). Methods and Findings Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age. Conclusions/Significance Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best

Candidate-based proteomics in the search for biomarkers of cardiovascular disease

PubMed Central

Anderson, Leigh

2005-01-01

The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

Putting the Oxylipidome to Work: A Novel Lipidomics Pipeline Reveals Candidate Biomarkers for Photooxidative Stress in Phytoplankton

NASA Astrophysics Data System (ADS)

Collins, J.; Edwards, B. R.; Fredricks, H. F.; Van Mooy, B. A.

2016-02-01

The lipids of marine plankton encompass a diversity of biochemical functions and chemotaxonomic specificities that make them ideal molecular biomarkers in living biomass. While core, nonpolar lipids such as free fatty acids (FFA) have formed the basis for many biomarker studies in fresh biomass, methods that enable the simultaneous profiling of core lipids and intact polar lipids (IPL) have opened new avenues for characterization of environmental stressors. We demonstrate the application of a novel, rules-based lipidomics data analysis pipeline to putatively identify a broad range of intact polar lipids, intact oxidized lipids (ox-lipids) and oxylipins in accurate-mass HPLC-ESI-MS data. Using mass spectra from a lipid peroxidation experiment conducted under the natural, ultraviolet-enriched light field in West Antarctica, we use the pipeline to identify ox-lipid and oxylipin biomarkers that might serve as indicators of photooxidative stress in phytoplankton. The lipidomics pipeline derives much of its functionality from two boutique lipid-oxylipin databases, which together contain entries for more than 60,000 candidate lipid biomarkers. These databases and all scripts required by the pipeline will be publicly available online to other users.

Identifying cut points for biomarker defined subset effects in clinical trials with survival endpoints.

PubMed

He, Pei

2014-07-01

The advancements in biotechnology and genetics lead to an increasing research interest in personalized medicine, where a patient's genetic profile or biological traits contribute to choosing the most effective treatment for the patient. The process starts with finding a specific biomarker among all possible candidates that can best predict the treatment effect. After a biomarker is chosen, identifying a cut point of the biomarker value that splits the patients into treatment effective and non-effective subgroups becomes an important scientific problem. Numerous methods have been proposed to validate the predictive marker and select the appropriate cut points either prospectively or retrospectively using clinical trial data. In trials with survival outcomes, the current practice applies an interaction testing procedure and chooses the cut point that minimizes the p-values for the tests. Such method assumes independence between the baseline hazard and biomarker value. In reality, however, this assumption is often violated, as the chosen biomarker might also be prognostic in addition to its predictive nature for treatment effect. In this paper we propose a block-wise estimation and a sequential testing approach to identify the cut point in biomarkers that can group the patients into subsets based on their distinct treatment outcomes without assuming independence between the biomarker and baseline hazard. Numerical results based on simulated survival data show that the proposed method could pinpoint accurately the cut points in biomarker values that separate the patient subpopulations into subgroups with distinctive treatment outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Transcriptional profiling in facioscapulohumeral muscular dystrophy to identify candidate biomarkers

PubMed Central

Rahimov, Fedik; King, Oliver D.; Leung, Doris G.; Bibat, Genila M.; Emerson, Charles P.; Kunkel, Louis M.; Wagner, Kathryn R.

2012-01-01

Facioscapulohumeral muscular dystrophy (FSHD) is a progressive neuromuscular disorder caused by contractions of repetitive elements within the macrosatellite D4Z4 on chromosome 4q35. The pathophysiology of FSHD is unknown and, as a result, there is currently no effective treatment available for this disease. To better understand the pathophysiology of FSHD and develop mRNA-based biomarkers of affected muscles, we compared global analysis of gene expression in two distinct muscles obtained from a large number of FSHD subjects and their unaffected first-degree relatives. Gene expression in two muscle types was analyzed using GeneChip Gene 1.0 ST arrays: biceps, which typically shows an early and severe disease involvement; and deltoid, which is relatively uninvolved. For both muscle types, the expression differences were mild: using relaxed cutoffs for differential expression (fold change ≥1.2; nominal P value <0.01), we identified 191 and 110 genes differentially expressed between affected and control samples of biceps and deltoid muscle tissues, respectively, with 29 genes in common. Controlling for a false-discovery rate of <0.25 reduced the number of differentially expressed genes in biceps to 188 and in deltoid to 7. Expression levels of 15 genes altered in this study were used as a “molecular signature” in a validation study of an additional 26 subjects and predicted them as FSHD or control with 90% accuracy based on biceps and 80% accuracy based on deltoids. PMID:22988124

Pharmacokinetic optimization of class-selective histone deacetylase inhibitors and identification of associated candidate predictive biomarkers of hepatocellular carcinoma tumor response.

PubMed

Wong, Jason C; Tang, Guozhi; Wu, Xihan; Liang, Chungen; Zhang, Zhenshan; Guo, Lei; Peng, Zhenghong; Zhang, Weixing; Lin, Xianfeng; Wang, Zhanguo; Mei, Jianghua; Chen, Junli; Pan, Song; Zhang, Nan; Liu, Yongfu; Zhou, Mingwei; Feng, Lichun; Zhao, Weili; Li, Shijie; Zhang, Chao; Zhang, Meifang; Rong, Yiping; Jin, Tai-Guang; Zhang, Xiongwen; Ren, Shuang; Ji, Ying; Zhao, Rong; She, Jin; Ren, Yi; Xu, Chunping; Chen, Dawei; Cai, Jie; Shan, Song; Pan, Desi; Ning, Zhiqiang; Lu, Xianping; Chen, Taiping; He, Yun; Chen, Li

2012-10-25

Herein, we describe the pharmacokinetic optimization of a series of class-selective histone deacetylase (HDAC) inhibitors and the subsequent identification of candidate predictive biomarkers of hepatocellular carcinoma (HCC) tumor response for our clinical lead using patient-derived HCC tumor xenograft models. Through a combination of conformational constraint and scaffold hopping, we lowered the in vivo clearance (CL) and significantly improved the bioavailability (F) and exposure (AUC) of our HDAC inhibitors while maintaining selectivity toward the class I HDAC family with particular potency against HDAC1, resulting in clinical lead 5 (HDAC1 IC₅₀ = 60 nM, mouse CL = 39 mL/min/kg, mouse F = 100%, mouse AUC after single oral dose at 10 mg/kg = 6316 h·ng/mL). We then evaluated 5 in a biomarker discovery pilot study using patient-derived tumor xenograft models, wherein two out of the three models responded to treatment. By comparing tumor response status to compound tumor exposure, induction of acetylated histone H3, candidate gene expression changes, and promoter DNA methylation status from all three models at various time points, we identified preliminary candidate response prediction biomarkers that warrant further validation in a larger cohort of patient-derived tumor models and through confirmatory functional studies.

Candidate immune biomarkers for radioimmunotherapy.

PubMed

Levy, Antonin; Nigro, Giulia; Sansonetti, Philippe J; Deutsch, Eric

2017-08-01

Newly available immune checkpoint blockers (ICBs), capable to revert tumor immune tolerance, are revolutionizing the anticancer armamentarium. Recent evidence also established that ionizing radiation (IR) could produce antitumor immune responses, and may as well synergize with ICBs. Multiple radioimmunotherapy combinations are thenceforth currently assessed in early clinical trials. Past examples have highlighted the need for treatment personalization, and there is an unmet need to decipher immunological biomarkers that could allow selecting patients who could benefit from these promising but expensive associations. Recent studies have identified potential predictive and prognostic immune assays at the cellular (tumor microenvironment composition), genomic (mutational/neoantigen load), and peripheral blood levels. Within this review, we collected the available evidence regarding potential personalized immune biomarker-directed radiation therapy strategies that might be used for patient selection in the era of radioimmunotherapy. Copyright © 2017. Published by Elsevier B.V.

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers

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

Matheis, Katja A., E-mail: katja.matheis@boehringer-ingelheim.com; Com, Emmanuelle; High-Throughput Proteomics Core Facility OUEST-genopole

2011-04-15

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with 'omics' data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinicalmore » chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.« less

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

Identifying candidate driver genes by integrative ovarian cancer genomics data

NASA Astrophysics Data System (ADS)

Lu, Xinguo; Lu, Jibo

2017-08-01

Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

Comparing human pancreatic cell secretomes by in vitro aptamer selection identifies cyclophilin B as a candidate pancreatic cancer biomarker

PubMed Central

Ray, Partha; Rialon-Guevara, Kristy L.; Veras, Emanuela; Sullenger, Bruce A.; White, Rebekah R.

2012-01-01

Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition–based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer. PMID:22484812

Comparing human pancreatic cell secretomes by in vitro aptamer selection identifies cyclophilin B as a candidate pancreatic cancer biomarker.

PubMed

Ray, Partha; Rialon-Guevara, Kristy L; Veras, Emanuela; Sullenger, Bruce A; White, Rebekah R

2012-05-01

Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition-based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer.

Candidate biomarker discovery and selection for ‘Granny Smith' superficial scald risk management and diagnosis, poster board

USDA-ARS?s Scientific Manuscript database

Discovery of candidate biomarkers for superficial scald, a peel disorder that develops during storage of susceptible apple cultivars, is part of a larger project aimed at developing biomarker-based risk-management and diagnostic tools for multiple apple postharvest disorders (http://www.tfrec.wsu.ed...

Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2018-04-30

Spontaneous preterm birth (sPTB) remains a major clinical dilemma; current diagnostics and interventions have not reduced the rate of this serious healthcare burden. This study characterizes differential protein profiles and post-translational modifications (PTMs) in first trimester maternal serum using a refined top-down approach coupling two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) to directly compare subsequent term and preterm labour events and identify marked protein differences. 30 proteoforms were found to be significantly increased or decreased in the sPTB group including 9 phosphoproteins and 11 glycoproteins. Changes occurred in proteins associated with immune and defence responses. We identified protein species that are associated with several clinically relevant biological processes, including interrelated biological networks linked to regulation of the complement cascade and coagulation pathways, immune modulation, metabolic processes and cell signalling. The finding of altered proteoforms in maternal serum from pregnancies that delivered preterm suggests these as potential early biomarkers of sPTB and also possible mediators of the disorder. Identifying changes in protein profiles is critical in the study of cell biology, and disease treatment and prevention. Identifying consistent changes in the maternal serum proteome during early pregnancy, including specific protein PTMs (e.g. phosphorylation, glycosylation), is likely to provide better opportunities for prediction, intervention and prevention of preterm birth. This is the first study to examine first trimester maternal serum using a highly refined top-down proteomic analytical approach based on high resolution 2DE coupled with mass spectrometry to directly compare preterm (<37 weeks) and preterm (≥37 weeks) events and identify select protein differences between these conditions. As such, the data present a promising avenue for translation of biomarker discovery to a

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

PubMed Central

2014-01-01

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic–based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research. PMID:24679154

Identifying novel biomarkers in sarcoidosis using genome-based approaches

PubMed Central

Knox, Kenneth S.; Garcia, Joe G.N.

2015-01-01

Synopsis We briefly review conventional biomarkers used clinically to 1) support a diagnosis and 2) monitor disease progression in patients with sarcoidosis. We describe potential new biomarkers identified by genome-wide screening and the approaches to discover these biomarkers. PMID:26593137

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Proteomic profiling identifies the inorganic pyrophosphatase (PPA1) protein as a potential biomarker of metastasis in laryngeal squamous cell carcinoma.

PubMed

Bodnar, Magdalena; Luczak, Magdalena; Bednarek, Kinga; Szylberg, Lukasz; Marszalek, Andrzej; Grenman, Reidar; Szyfter, Krzysztof; Jarmuz-Szymczak, Malgorzata; Giefing, Maciej

2016-06-01

Relapse and metastasis are the main causes of unfavorable outcome in head and neck cancers. Whereas, understanding of the molecular background of these processes is far from being complete. Therefore, in this study we aimed to identify potential biomarker candidates of relapse and metastasis in laryngeal squamous cell carcinoma (LSCC) by combining the 2D electrophoresis based protein screen and immunohistochemical analysis of candidate proteins. We screened three groups of LSCC cell lines derived from primary tumors, recurrent tumors and metastases and identified seven proteins that differed significantly in relative abundance between the analyzed groups. Among the identified proteins were the heat shock proteins HSP60 and HSP70 that were significantly downregulated both in recurrences- and metastases-derived cell lines but not in primary tumor-derived cell lines. Moreover, we identified significant upregulation of the annexin V, calreticulin and the inorganic pyrophosphatase (PPA1) exclusively in the metastases-derived cell lines. As these upregulated proteins could potentially become novel biomarkers of metastasis, we have compared their abundance in primary tumor LSCC N(0) cases, primary tumor LSCC N(+) cases as well as in LSCC metastases N(+). Our results show an intense increase of cytoplasmic PPA1 abundance in the N(+) (p = 0.000042) compared to the N(0) group. In summary, we show a group of proteins deregulated in recurrences and metastases of LSCC. Moreover, we suggest the PPA1 protein as a potential new biomarker for metastasis in this cancer.

Sarcoidosis Related Novel Candidate Genes Identified by Multi-Omics Integrative Analyses.

PubMed

Hočevar, Keli; Maver, Aleš; Kunej, Tanja; Peterlin, Borut

2018-05-01

Sarcoidosis is a multifactorial systemic disease characterized by granulomatous inflammation and greatly impacting on global public health. The etiology and mechanisms of sarcoidosis are not fully understood. Recent high-throughput biological research has generated vast amounts of multi-omics big data on sarcoidosis, but their significance remains to be determined. We sought to identify novel candidate regions, and genes consistently altered in heterogeneous omics studies so as to reveal the underlying molecular mechanisms. We conducted a comprehensive integrative literature analysis on global data on sarcoidosis, including genomic, transcriptomic, proteomic, and phenomic studies. We performed positional integration analysis of 38 eligible datasets originating from 17 different biological layers. Using the integration interval length of 50 kb, we identified 54 regions reaching significance value p ≤ 0.0001 and 15 regions with significance value p ≤ 0.00001, when applying more stringent criteria. Secondary literature analysis of the top 20 regions, with the most significant accumulation of signals, revealed several novel candidate genes for which associations with sarcoidosis have not yet been established, but have considerable support for their involvement based on omic data. These new plausible candidate genes include NELFE, CFB, EGFL7, AGPAT2, FKBPL, NRC3, and NEU1. Furthermore, annotated data were prepared to enable custom visualization and browsing of these sarcoidosis related omics evidence in the University of California Santa Cruz (UCSC) Genome Browser. Further multi-omics approaches are called for sarcoidosis biomarkers and diagnostic and therapeutic innovation. Our approach for harnessing multi-omics data and the findings presented herein reflect important steps toward understanding the etiology and underlying pathological mechanisms of sarcoidosis.

Biomarker Candidate Identification in Yersinia Pestis Using Organism-Wide Semiquantitative Proteomics

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

Hixson, Kim K.; Adkins, Joshua N.; Baker, Scott E.

2006-11-03

Yersinia pestis, the causative agent of plague, is listed by the CDC as a level A select pathogen. To better enable detection, intervention and treatment of Y. pestis infections, it is necessary to understand its protein expression under conditions that promote or inhibit virulence. To this end, we have utilized a novel combination of the accurate mass and time tag methodology of mass spectrometry and clustering analysis using OmniViz™ to compare the protein abundance changes of 992 identified proteins under four growth conditions. Temperature and Ca2+ concentration were used to trigger virulence associated protein expression fundamental to the low calciummore » response. High-resolution liquid chromatography and electrospray ionization mass spectrometry were utilized to determine protein identity and abundance on the genome-wide level. The cluster analyses revealed, in a rapid visual platform, the reproducibility of the current method as well as relevant protein abundance changes of expected and novel proteins relating to a specific growth condition and sub-cellular location. Using this method, 89 proteins were identified as having a similar abundance change profile to 29 known virulence associated proteins, providing additional biomarker candidates for future detection and vaccine development strategies.« less

Biomarker Candidates of Chlamydophila pneumoniae Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

NASA Astrophysics Data System (ADS)

Susnea, Iuliana; Bunk, Sebastian; Wendel, Albrecht; Hermann, Corinna; Przybylski, Michael

2011-04-01

We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.

Clinical Neuropathology practice news 2-2014: ATRX, a new candidate biomarker in gliomas.

PubMed

Haberler, Christine; Wöhrer, Adelheid

2014-01-01

Genome-wide molecular approaches have substantially elucidated molecular alterations and pathways involved in the oncogenesis of brain tumors. In gliomas, several molecular biomarkers including IDH mutation, 1p/19q co-deletion, and MGMT promotor methylation status have been introduced into neuropathological practice. Recently, mutations of the ATRX gene have been found in various subtypes and grades of gliomas and were shown to refine the prognosis of malignant gliomas in combination with IDH and 1p/19q status. Mutations of ATRX are associated with loss of nuclear ATRX protein expression, detectable by a commercially available antibody, thus turning ATRX into a promising prognostic candidate biomarker in the routine neuropathological setting.

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

PubMed Central

2012-01-01

Background Alzheimer’s Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders. PMID:23113945

A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

PubMed

Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

2015-12-01

An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

CSF CXCL10, CXCL9, and Neopterin as Candidate Prognostic Biomarkers for HTLV-1-Associated Myelopathy/Tropical Spastic Paraparesis

PubMed Central

Sato, Tomoo; Coler-Reilly, Ariella; Utsunomiya, Atae; Araya, Natsumi; Yagishita, Naoko; Ando, Hitoshi; Yamauchi, Junji; Inoue, Eisuke; Ueno, Takahiko; Hasegawa, Yasuhiro; Nishioka, Kusuki; Nakajima, Toshihiro; Jacobson, Steven; Izumo, Shuji; Yamano, Yoshihisa

2013-01-01

Background Human T-lymphotropic virus type 1 (HTLV-1) -associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a rare chronic neuroinflammatory disease. Since the disease course of HAM/TSP varies among patients, there is a dire need for biomarkers capable of predicting the rate of disease progression. However, there have been no studies to date that have compared the prognostic values of multiple potential biomarkers for HAM/TSP. Methodology/Principal Findings Peripheral blood and cerebrospinal fluid (CSF) samples from HAM/TSP patients and HTLV-1-infected control subjects were obtained and tested retrospectively for several potential biomarkers, including chemokines and other cytokines, and nine optimal candidates were selected based on receiver operating characteristic (ROC) analysis. Next, we evaluated the relationship between these candidates and the rate of disease progression in HAM/TSP patients, beginning with a first cohort of 30 patients (Training Set) and proceeding to a second cohort of 23 patients (Test Set). We defined “deteriorating HAM/TSP” as distinctly worsening function (≥3 grades on Osame's Motor Disability Score (OMDS)) over four years and “stable HAM/TSP” as unchanged or only slightly worsened function (1 grade on OMDS) over four years, and we compared the levels of the candidate biomarkers in patients divided into these two groups. The CSF levels of chemokine (C-X-C motif) ligand 10 (CXCL10), CXCL9, and neopterin were well-correlated with disease progression, better even than HTLV-1 proviral load in PBMCs. Importantly, these results were validated using the Test Set. Conclusions/Significance As the CSF levels of CXCL10, CXCL9, and neopterin were the most strongly correlated with rate of disease progression, they represent the most viable candidates for HAM/TSP prognostic biomarkers. The identification of effective prognostic biomarkers could lead to earlier detection of high-risk patients, more patient-specific treatment

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

PubMed Central

Cohen Freue, Gabriela V.; Meredith, Anna; Smith, Derek; Bergman, Axel; Sasaki, Mayu; Lam, Karen K. Y.; Hollander, Zsuzsanna; Opushneva, Nina; Takhar, Mandeep; Lin, David; Wilson-McManus, Janet; Balshaw, Robert; Keown, Paul A.; Borchers, Christoph H.; McManus, Bruce; Ng, Raymond T.; McMaster, W. Robert

2013-01-01

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

PubMed

Iyappan, Anandhi; Kawalia, Shweta Bagewadi; Raschka, Tamara; Hofmann-Apitius, Martin; Senger, Philipp

2016-07-08

Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framework to help decipher the complex interactions that occur at molecular and cellular levels. This motivates the need for the development of an approach integrating highly curated and heterogeneous data into a disease model of different regulatory data layers. Although several disease models exist, they often do not consider the quality of underlying data. Moreover, even with the current advancements in semantic web technology, we still do not have cure for complex diseases like Alzheimer's disease. One of the key reasons accountable for this could be the increasing gap between generated data and the derived knowledge. In this paper, we describe an approach, called as NeuroRDF, to develop an integrative framework for modeling curated knowledge in the area of complex neurodegenerative diseases. The core of this strategy lies in the usage of well curated and context specific data for integration into one single semantic web-based framework, RDF. This increases the probability of the derived knowledge to be novel and reliable in a specific disease context. This infrastructure integrates highly curated data from databases (Bind, IntAct, etc.), literature (PubMed), and gene expression resources (such as GEO and ArrayExpress). We illustrate the effectiveness of our approach by asking real-world biomedical questions that link these resources to prioritize the plausible biomarker candidates. Among the 13 prioritized candidate genes, we identified MIF to be a potential emerging candidate due to its role as a pro-inflammatory cytokine. We additionally report on the effort and challenges faced during generation of such an indication-specific knowledge base comprising of curated and quality-controlled data. Although many alternative approaches

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

PubMed Central

2010-01-01

Background To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Methods Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Results Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Conclusions Coronin-1C could be a candidate biomarker to predict HCC invasive behavior. PMID:20181269

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation.

PubMed

Wu, Long; Peng, Chun-Wei; Hou, Jin-Xuan; Zhang, Yan-Hua; Chen, Chuang; Chen, Liang-Dong; Li, Yan

2010-02-24

To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.

A protocol for identifying suitable biomarkers to assess fish health: A systematic review

PubMed Central

2017-01-01

Background Biomarkers have been used extensively to provide the connection between external levels of contaminant exposure, internal levels of tissue contamination, and early adverse effects in organisms. Objectives To present a three-step protocol for identifying suitable biomarkers to assess fish health in coastal and marine ecosystems, using Gladstone Harbour (Australia) as a case study. Methods Prior to applying our protocol, clear working definitions for biomarkers were developed to ensure consistency with the global literature on fish health assessment. First, contaminants of concern were identified based on the presence of point and diffuse sources of pollution and available monitoring data for the ecosystem of interest. Second, suitable fish species were identified using fisheries dependent and independent data, and prioritised based on potential pathways of exposure to the contaminants of concern. Finally, a systematic and critical literature review was conducted on the use of biomarkers to assess the health of fish exposed to the contaminants of concern. Results/Discussion We present clear working definitions for bioaccumulation markers, biomarkers of exposure, biomarkers of effect and biomarkers of susceptibility. Based on emission and concentration information, seven metals were identified as contaminants of concern for Gladstone Harbour. Twenty out of 232 fish species were abundant enough to be potentially suitable for biomarker studies; five of these were prioritised based on potential pathways of exposure and susceptibility to metals. The literature search on biomarkers yielded 5,035 articles, of which 151met the inclusion criteria. Based on our review, the most suitable biomarkers include bioaccumulation markers, biomarkers of exposure (CYP1A, EROD, SOD, LPOX, HSP, MT, DNA strand breaks, micronuclei, apoptosis), and biomarkers of effect (histopathology, TAG:ST). Conclusion Our protocol outlines a clear pathway to identify suitable biomarkers to

Fluid Biomarkers in Alzheimer Disease

PubMed Central

Blennow, Kaj; Zetterberg, Henrik; Fagan, Anne M.

2012-01-01

Research progress has provided detailed understanding of the molecular pathogenesis of Alzheimer disease (AD). This knowledge has been translated into new drug candidates with putative disease-modifying effects, which are now being tested in clinical trials. The promise of effective therapy has created a great need for biomarkers able to detect AD in the predementia phase, because drugs will probably be effective only if neurodegeneration is not too advanced. In this chapter, cerebrospinal fluid (CSF) and plasma biomarkers are reviewed. The core CSF biomarkers total tau (T-tau), phosphorylated tau (P-tau) and the 42 amino acid form of β-amyloid (Aβ42) reflect AD pathology, and have high diagnostic accuracy to diagnose AD with dementia and prodromal AD in mild cognitive impairment cases. The rationale for the use of CSF biomarkers to identify and monitor the mechanism of action of new drug candidates is also outlined in this chapter. PMID:22951438

Identification of Candidate Biomarkers Associated with Response to Vedolizumab in Inflammatory Bowel Disease.

PubMed

Boden, Elisa K; Shows, Donna M; Chiorean, Michael V; Lord, James D

2018-01-25

Vedolizumab is an anti-α4β7 monoclonal antibody approved for the treatment of inflammatory bowel disease (IBD). This exploratory study aimed to identify biomarkers associated with vedolizumab response. Twenty-six IBD patients (15 with Crohn's, 11 with ulcerative or indeterminate colitis) initiating vedolizumab at a single center between 2014 and 2016 underwent sampling of serum and peripheral blood mononuclear cells (PBMCs) before and during vedolizumab therapy. Response was defined as steroid-free improvement in endoscopic score or Harvey-Bradshaw index/simple clinical colitis activity index (reduction greater than 3 or total less than 3). PBMCs were evaluated for immunophenotype and expression of α4β7 integrin on lymphocytes before and during vedolizumab therapy. Serum vedolizumab levels and α4β7 saturation were measured serially after induction. Fourteen out of 26 (54%) patients treated with vedolizumab responded to therapy. Pretreatment α4β7 expression was higher in responders on multiple subsets of T, B, and NK cells, with terminal effector memory (p = .0009 for CD4 and .0043 for CD8) and NK cells (p = .0047) best discriminating between responders and nonresponders. During therapy, log 10 serum vedolizumab levels at trough were higher in responders than nonresponders (p = .0007). Conversely, the percentage of effector memory T cells with free α4β7 at trough was lower in responders than nonresponders (p < .0001). However, loss of α4β7 saturation with vedolizumab was more sensitive to low serum vedolizumab in nonresponders. Pretreatment α4β7 expression and α4β7 receptor saturation during maintenance therapy were identified as candidate biomarkers for vedolizumab response.

ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism

PubMed Central

Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry

2012-01-01

Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility. PMID:22258617

Gene expression profiles of putative biomarker candidates in Mycobacterium avium subsp. paratuberculosis-infected cattle.

PubMed

Park, Hyun-Eui; Shin, Min-Kyoung; Park, Hong-Tae; Jung, Myunghwan; Cho, Yong Il; Yoo, Han Sang

2016-06-01

This study was conducted to analyze the gene expression of prognostic potential biomarker candidates using the whole blood of cattle naturally infected with ITALIC! Mycobacterium aviumsubsp. ITALIC! paratuberculosis(MAP). We conducted real-time PCR to evaluate 23 potential biomarker candidates. Experimental animals were divided into four groups based on fecal MAP PCR and serum ELISA. Seven ( ITALIC! KLRB1, ITALIC! HGF, ITALIC! MPO, ITALIC! LTF, ITALIC! SERPINE1, ITALIC! S100A8and ITALIC! S100A9) genes were up-regulated in fecal MAP-positive cattle and three ( ITALIC! KLRB1, ITALIC! MPOand ITALIC! S100A9) were up-regulated in MAP-seropositive cattle relative to uninfected cattle. In subclinically infected animals, 17 genes ( ITALIC! TFRC, ITALIC! S100A8, ITALIC! S100A9, ITALIC! MPO, ITALIC! GBP6, ITALIC! LTF, ITALIC! KLRB1, ITALIC! SERPINE1, ITALIC! PIGR, ITALIC! IL-10, ITALIC! CXCR3, ITALIC! CD14, ITALIC! MMP9, ITALIC! ELANE, ITALIC! CHI3L1, ITALIC! HPand ITALIC! HGF) were up-regulated compared with the control group. Moreover, six genes ( ITALIC! CXCR3, ITALIC! HP, ITALIC! HGF, ITALIC! LTF, ITALIC! TFRCand ITALIC! GBP6) showed significant differences between experimental groups. Taken together, our data suggest that six genes ( ITALIC! LTF, ITALIC! HGF, ITALIC! HP, ITALIC! CXCR3, ITALIC! GBP6and ITALIC! TFRC) played essential roles in the immune response to MAP during the subclinical stage and therefore might be useful as prognostic biomarkers. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identifying Thoracic Malignancies Through Pleural Fluid Biomarkers: A Predictive Multivariate Model.

PubMed

Porcel, José M; Esquerda, Aureli; Martínez-Alonso, Montserrat; Bielsa, Silvia; Salud, Antonieta

2016-03-01

The diagnosis of malignant pleural effusions may be challenging when cytological examination of aspirated pleural fluid is equivocal or noncontributory. The purpose of this study was to identify protein candidate biomarkers differentially expressed in the pleural fluid of patients with mesothelioma, lung adenocarcinoma, lymphoma, and tuberculosis (TB).A multiplex protein biochip comprising 120 biomarkers was used to determine the pleural fluid protein profile of 29 mesotheliomas, 29 lung adenocarcinomas, 12 lymphomas, and 35 tuberculosis. The relative abundance of these predetermined biomarkers among groups served to establish the differential diagnosis of: malignant versus benign (TB) effusions, lung adenocarcinoma versus mesothelioma, and lymphoma versus TB. The selected putative markers were validated using widely available commercial techniques in an independent sample of 102 patients.Significant differences were found in the protein expressions of metalloproteinase-9 (MMP-9), cathepsin-B, C-reactive protein, and chondroitin sulfate between malignant and TB effusions. When integrated into a scoring model, these proteins yielded 85% sensitivity, 100% specificity, and an area under the curve (AUC) of 0.98 for labeling malignancy in the verification sample. For lung adenocarcinoma-mesothelioma discrimination, combining CA19-9, CA15-3, and kallikrein-12 had maximal discriminatory capacity (65% sensitivity, 100% specificity, AUC 0.94); figures which also refer to the validation set. Last, cathepsin-B in isolation was only moderately useful (sensitivity 89%, specificity 62%, AUC 0.75) in separating lymphomatous and TB effusions. However, this last differentiation improved significantly when cathepsin-B was used with respect to the patient's age (sensitivity 72%, specificity 100%, AUC 0.94).In conclusion, panels of 4 (i.e., MMP-9, cathepsin-B, C-reactive protein, chondroitin sulfate), or 3 (i.e., CA19-9, CA15-3, kallikrein-12) different protein biomarkers on pleural

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

Practical analytical approach for the identification of biomarker candidates in prediabetic state based upon metabonomic study by ultraperformance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry.

PubMed

Tsutsui, Haruhito; Maeda, Toshio; Toyo'oka, Toshimasa; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki

2010-08-06

The number of diabetic patients has recently been increasing worldwide. Thus, the discovery of potential diabetic biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, is strongly required. The diagnosis of the prediabetic state in humans is a very difficult issue because of the lifestyle differences in each person and ethical consideration. Upon the basis of these considerations, animal experiments using ddY strain mice (ddY-H), which undergo naturally occurring diabetes along with age, were carried out in this study. Biomarker discovery based upon a metabonome study is now quite common, the same as that in the proteome analysis. Reversed-phase liquid chromatography-mass spectrometry (LC-MS) has mainly been used for the extensive analysis of low-molecular mass compounds including metabolites. The metabolites in the plasma of diabetic mice (ddY-H) and normal mice (ddY-L) were exhaustively separated and detected by ultraperformance liquid chromatography along with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS) using T3-C18 and HS-F5 columns. The biomarker candidates related to diabetes mellitus were extracted from the metabolite profiling of ddY-H and ddY-L at 5, 9 13, and 20 weeks old using a multivariate statistical analysis such as orthogonal partial least-squares-discriminant analysis (OPLS-DA). Various metabolites and unknown compounds were detected as biomarker candidates related to diabetic mellitus. Furthermore, the concentration of several metabolites on Lysine biosynthesis and Lysine degradation pathways were remarkably changed between the 9-week old ddY-H and ddY-L mice. Because a couple of biomarker candidates related to the prediabetic state were identified using the present approach, the metabolite profiling study could be helpful for understanding the abnormal state of various diseases.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

PubMed

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Serum Immunoproteomics Combined With Pathological Reassessment of Surgical Specimens Identifies TCP-1ζ Autoantibody as a Potential Biomarker in Thyroid Neoplasia.

PubMed

Belousov, Pavel V; Bogolyubova, Apollinariya V; Kim, Yan S; Abrosimov, Alexander Y; Kopylov, Arthur T; Tvardovskiy, Andrey A; Lanshchakov, Kirill V; Sazykin, Alexei Y; Dvinskikh, Nina Y; Bobrovskaya, Yana I; Selivanova, Lilia S; Shilov, Evgeniy S; Schwartz, Anton M; Shebzukhov, Yuriy V; Severskaia, Natalya V; Vanushko, Vladimir E; Moshkovskii, Sergei A; Nedospasov, Sergei A; Kuprash, Dmitry V

2015-09-01

Current methods of preoperative diagnostics frequently fail to discriminate between benign and malignant thyroid neoplasms. In encapsulated follicular-patterned tumors (EnFPT), this discrimination is challenging even using histopathological analysis. Autoantibody response against tumor-associated antigens is a well-documented phenomenon with prominent diagnostic potential; however, autoantigenicity of thyroid tumors remains poorly explored. Objectives were exploration of tumor-associated antigen repertoire of thyroid tumors and identification of candidate autoantibody biomarkers capable of discrimination between benign and malignant thyroid neoplasms. Proteins isolated from FTC-133 cells were subjected to two-dimensional Western blotting using pooled serum samples of patients originally diagnosed with either papillary thyroid carcinoma (PTC) or EnFPT represented by apparently benign follicular thyroid adenomas, as well as healthy individuals. Immunoreactive proteins were identified using liquid chromatography-tandem mass-spectrometry. Pathological reassessment of EnFPT was performed applying nonconservative criteria for capsular invasion and significance of focal PTC nuclear changes (PTC-NCs). Recombinant T-complex protein 1 subunitζ (TCP-1ζ) was used to examine an expanded serum sample set of patients with various thyroid neoplasms (n = 89) for TCP-1ζ autoantibodies. All patients were included in tertiary referral centers. A protein demonstrating a distinct pattern of EnFPT-specific seroreactivity was identified as TCP-1ζ protein. A subsequent search for clinicopathological correlates of TCP-1ζ seroreactivity revealed nonclassical capsular invasion or focal PTC-NC in all TCP-1ζ antibody-positive cases. Further studies in an expanded sample set confirmed the specificity of TCP-1ζ autoantibodies to malignant EnFPT. We identified TCP-1ζ autoantibodies as a potential biomarker for presurgical discrimination between benign and malignant encapsulated follicular

Improving the quality of biomarker discovery research: the right samples and enough of them.

PubMed

Pepe, Margaret S; Li, Christopher I; Feng, Ziding

2015-06-01

Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

Biomarkers of tolerance: searching for the hidden phenotype.

PubMed

Perucha, Esperanza; Rebollo-Mesa, Irene; Sagoo, Pervinder; Hernandez-Fuentes, Maria P

2011-08-01

Induction of transplantation tolerance remains the ideal long-term clinical and logistic solution to the current challenges facing the management of renal allograft recipients. In this review, we describe the recent studies and advances made in identifying biomarkers of renal transplant tolerance, from study inceptions, to the lessons learned and their implications for current and future studies with the same goal. With the age of biomarker discovery entering a new dimension of high-throughput technologies, here we also review the current approaches, developments, and pitfalls faced in the subsequent statistical analysis required to identify valid biomarker candidates.

Identification of low-abundance cancer biomarker candidate TIMP1 from serum with lectin fractionation and peptide affinity enrichment by ultrahigh-resolution mass spectrometry.

PubMed

Ahn, Yeong Hee; Kim, Kwang Hoe; Shin, Park Min; Ji, Eun Sun; Kim, Hoguen; Yoo, Jong Shin

2012-02-07

As investigating a proteolytic target peptide originating from the tissue inhibitor of metalloproteinase 1 (TIMP1) known to be aberrantly glycosylated in patients with colorectal cancer (CRC), we first confirmed that TIMP1 is to be a CRC biomarker candidate in human serum. For this, we utilized matrix-assisted laser desorption/ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) showing ultrahigh-resolution and high mass accuracy. This investigation used phytohemagglutinin-L(4) (L-PHA) lectin, which shows binding affinity to the β-1,6-N-acetylglucosamine moiety of N-linked glycan on a protein, to compare fractionated aberrant protein glycoforms from both noncancerous control and CRC serum. Each lectin-captured fraction containing aberrant glycoforms of TIMP1 was digested by trypsin, resulting in the tryptic target peptide, representative of the serum glycoprotein TIMP1. The resulting target peptide was enriched using a stable isotope standard and capture by the antipeptide antibody (SISCAPA) technique and analyzed by a 15 T MALDI FTICR mass spectrometer with high mass accuracy (Δ < 0.5 ppm to the theoretical mass value of the target peptide). Since exact measurement of multiplex isotopic peaks of the target peptide could be accomplished by virtue of high mass resolution (Rs > 400,000), robust identification of the target peptide is only achievable with 15 T FTICR MS. Also, MALDI data obtained in this study showed that the L-PHA-captured glycoforms of TIMP1 were measured in the pooled CRC serum with about 5 times higher abundance than that in the noncancerous serum, and were further proved by MRM mass analysis. These results confirm that TIMP1 in human serum is a potent CRC biomarker candidate, demonstrating that ultrahigh-resolution MS can be a powerful tool toward identifying and verifying potential protein biomarker candidates. © 2011 American Chemical Society

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

MFAP4: a candidate biomarker for hepatic and pulmonary fibrosis?

PubMed

Mölleken, Christian; Poschmann, Gereon; Bonella, Francesco; Costabel, Ulrich; Sitek, Barbara; Stühler, Kai; Meyer, Helmut E; Schmiegel, Wolff H; Marcussen, Niels; Helmer, Michael; Nielsen, Ole; Hansen, Søren; Schlosser, Anders; Holmskov, Uffe; Sorensen, Grith Lykke

2016-03-29

Several comparable mechanisms have been identified for hepatic and pulmonary fibrosis. The human microfibrillar associated glycoprotein 4 (MFAP4), produced by activated myofibroblasts, is a ubiquitous protein playing a potential role in extracellular matrix (ECM) turnover and was recently identified as biomarker for hepatic fibrosis in hepatitis C patients. The current study aimed to evaluate serum levels of MFAP4 in patients with pulmonary fibrosis in order to test its potential as biomarker in clinical practice. A further aim was to determine whether MFAP4 deficiency in mice affects the formation of pulmonary fibrosis in the bleomycin model of lung fibrosis. 91 patients with idiopathic pulmonary fibrosis (IPF), 23 with hypersensitivity pneumonitis (HP) and 31 healthy subjects were studied. In the mouse model, C57BL/6 Mfap4+/+ and Mfap4-/- mice between 6-8 weeks of age were studied. Serum levels of MFAP4 were measured by ELISA in patients and in mice. Surfactant protein D (SP-D) and LDH were measured as comparison biomarkers in patients with pulmonary fibrosis. Morphometric assessment and the Sircol kit were used to determine the amount of collagen in the lung tissue in the mouse model. Serum levels of MFAP4 were not elevated in lung fibrosis - neither in the patients with IPF or HP nor in the animal model. Furthermore no significant correlations with pulmonary function tests of IPF patients could be found for MFAP4. MFAP4 levels were increased in BAL of bleomycin treated mice with pulmonary fibrosis. MFAP4 is not elevated in sera of patients with pulmonary fibrosis or bleomycin treated mice with pulmonary fibrosis. This may be due to different pathogenic mechanisms of liver and lung fibrogenesis. MFAP4 seems to be useful as serum biomarker for hepatic but not for lung fibrosis.

Identifying Candidate Chemical-Disease Linkages (Environmental and Epigenetic Determinants of IBD)

EPA Science Inventory

Presentation at meeting on Environmental and Epigenetic Determinants of IBD in New York, NY on identifying candidate chemical-disease linkages by using AOPs to identify molecular initiating events and using relevant high throughput assays to screen for candidate chemicals. This h...

Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics

PubMed Central

Min, Hophil; Kim, Sang Jin; Oh, Sohee; Kim, Kyunggon; Yu, Hyeong Gon; Park, Taesung; Kim, Youngsoo

2016-01-01

Diabetic retinopathy (DR) is a common microvascular complication caused by diabetes mellitus (DM) and is a leading cause of vision impairment and loss among adults. Here, we performed a comprehensive proteomic analysis to discover biomarkers for DR. First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. To confirm and validate the selected biomarker candidates, candidates were selected, confirmed, and validated using plasma from diabetic patients without DR (No DR) and diabetics with mild or moderate nonproliferative diabetic retinopathy (Mi or Mo NPDR) using semiquantitative multiple reaction monitoring (SQ-MRM) and stable-isotope dilution multiple reaction monitoring (SID-MRM). Additionally, we performed a multiplex assay using 15 biomarker candidates identified in the SID-MRM analysis, which resulted in merged AUC values of 0.99 (No DR versus Mo NPDR) and 0.93 (No DR versus Mi and Mo NPDR). Although further validation with a larger sample size is needed, the 4-protein marker panel (APO4, C7, CLU, and ITIH2) could represent a useful multibiomarker model for detecting the early stages of DR. PMID:26665153

Multiplexed MRM-based quantitation of candidate cancer biomarker proteins in undepleted and non-enriched human plasma.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Borchers, Christoph H

2013-07-01

An emerging approach for multiplexed targeted proteomics involves bottom-up LC-MRM-MS, with stable isotope-labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer-biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM-based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom-up workflow) for the 27 biomarker proteins (represented by 57 interference-free peptides). The linear dynamic range for the MRM assays spanned four orders-of-magnitude, with 25 assays covering a 10(3) -10(4) range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin-like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer-associated protein biomarker panels in human plasma, prior to clinical use. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

PubMed

Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

2012-09-18

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. Copyright © 2012 Elsevier B.V. All rights reserved.

Pilot study on the use of data mining to identify cochlear implant candidates.

PubMed

Grisel, Jedidiah J; Schafer, Erin; Lam, Anne; Griffin, Terry

2018-05-01

The goal of this pilot study was to determine the clinical utility of data-mining software that screens for cochlear implant (CI) candidacy. The Auditory Implant Initiative developed a software module that screens for CI candidates via integration with a software system (Noah 4) that serves as a depository for hearing test data. To identify candidates, patient audiograms from one practice were exported into the screening module. Candidates were tracked to determine if any eventually underwent implantation. After loading 4836 audiograms from the Noah 4 system, the screening module identified 558 potential CI candidates. After reviewing the data for the potential candidates, 117 were targeted and invited to an educational event. Following the event, a total of six candidates were evaluated, and two were implanted. This objective approach to identifying candidates has the potential to address the gross underutilization of CIs by removing any bias or lack of knowledge regarding the management of severe to profound sensorineural hearing loss with CIs. The screening module was an effective tool for identifying potential CI candidates at one ENT practice. On a larger scale, the screening module has the potential to impact thousands of CI candidates worldwide.

Use of biomarkers for assessing radiation injury and efficacy of countermeasures

PubMed Central

Singh, Vijay K; Newman, Victoria L; Romaine, Patricia LP; Hauer-Jensen, Martin; Pollard, Harvey B

2016-01-01

Several candidate drugs for acute radiation syndrome (ARS) have been identified that have low toxicity and significant radioprotective and radiomitigative efficacy. Inasmuch as exposing healthy human volunteers to injurious levels of radiation is unethical, development and approval of new radiation countermeasures for ARS are therefore presently based on animal studies and Phase I safety study in healthy volunteers. The Animal Efficacy Rule, which underlies the Food and Drug Administration approval pathway, requires a sound understanding of the mechanisms of injury, drug efficacy, and efficacy biomarkers. In this context, it is important to identify biomarkers for radiation injury and drug efficacy that can extrapolate animal efficacy results, and can be used to convert drug doses deduced from animal studies to those that can be efficacious when used in humans. Here, we summarize the progress of studies to identify candidate biomarkers for the extent of radiation injury and for evaluation of countermeasure efficacy. PMID:26568096

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer.

PubMed

Chang, Hae Ryung; Nam, Seungyoon; Lee, Jinhyuk; Kim, Jin-Hee; Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-12-06

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of "hit" compounds.

Prioritization of biomarker targets in human umbilical cord blood: identification of proteins in infant blood serving as validated biomarkers in adults.

PubMed

Hansmeier, Nicole; Chao, Tzu-Chiao; Goldman, Lynn R; Witter, Frank R; Halden, Rolf U

2012-05-01

Early diagnosis represents one of the best lines of defense in the fight against a wide array of human diseases. Umbilical cord blood (UCB) is one of the first easily available diagnostic biofluids and can inform about the health status of newborns. However, compared with adult blood, its diagnostic potential remains largely untapped. Our goal was to accelerate biomarker research on UCB by exploring its detectable protein content and providing a priority list of potential biomarkers based on known proteins involved in disease pathways. We explored cord blood serum proteins by profiling a UCB pool of 12 neonates with different backgrounds using a combination of isoelectric focusing and liquid chromatography coupled with matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) and by comparing results with information contained in metabolic and disease databases available for adult blood. A total of 1,210 UCB proteins were identified with a protein-level false discovery rate of ~ 5% as estimated by naïve target-decoy and MAYU approaches, signifying a 6-fold increase in the number of UCB proteins described to date. Identified proteins correspond to 138 different metabolic and disease pathways and provide a platform of mechanistically linked biomarker candidates for tracking disruptions in cellular processes. Moreover, among the identified proteins, 38 were found to be approved biomarkers for adult blood. The results of this study advance current knowledge of the human cord blood serum proteome. They showcase the potential of UCB as a diagnostic medium for assessing infant health by detection and identification of candidate biomarkers for known disease pathways using a global, nontargeted approach. These biomarkers may inform about mechanisms of exposure-disease relationships. Furthermore, biomarkers approved by the U.S. Food and Drug Administration for screening in adult blood were detected in UCB and represent high-priority targets for

Cerebrospinal Fluid Biomarkers for Huntington's Disease.

PubMed

Byrne, Lauren M; Wild, Edward J

2016-01-01

Cerebrospinal fluid (CSF) is enriched in brain-derived components and represents an accessible and appealing means of interrogating the CNS milieu to study neurodegenerative diseases and identify biomarkers to facilitate the development of novel therapeutics. Many such CSF biomarkers have been proposed for Huntington's disease (HD) but none has been validated for clinical trial use. Across many studies proposing dozens of biomarker candidates, there is a notable lack of statistical power, consistency, rigor and validation. Here we review proposed CSF biomarkers including neurotransmitters, transglutaminase activity, kynurenine pathway metabolites, oxidative stress markers, inflammatory markers, neuroendocrine markers, protein markers of neuronal death, proteomic approaches and mutant huntingtin protein itself. We reflect on the need for large-scale, standardized CSF collections with detailed phenotypic data to validate and qualify much-needed CSF biomarkers for clinical trial use in HD.

A CONCISE PANEL OF BIOMARKERS IDENTIFIES NEUROCOGNITIVE FUNCTIONING CHANGES IN HIV-INFECTED INDIVIDUALS

PubMed Central

Marcotte, Thomas D.; Deutsch, Reena; Michael, Benedict Daniel; Franklin, Donald; Cookson, Debra Rosario; Bharti, Ajay R.; Grant, Igor; Letendre, Scott L.

2013-01-01

Background Neurocognitive (NC) impairment (NCI) occurs commonly in people living with HIV. Despite substantial effort, no biomarkers have been sufficiently validated for diagnosis and prognosis of NCI in the clinic. The goal of this project was to identify diagnostic or prognostic biomarkers for NCI in a comprehensively characterized HIV cohort. Methods Multidisciplinary case review selected 98 HIV-infected individuals and categorized them into four NC groups using normative data: stably normal (SN), stably impaired (SI), worsening (Wo), or improving (Im). All subjects underwent comprehensive NC testing, phlebotomy, and lumbar puncture at two timepoints separated by a median of 6.2 months. Eight biomarkers were measured in CSF and blood by immunoassay. Results were analyzed using mixed model linear regression and staged recursive partitioning. Results At the first visit, subjects were mostly middle-aged (median 45) white (58%) men (84%) who had AIDS (70%). Of the 73% who took antiretroviral therapy (ART), 54% had HIV RNA levels below 50 c/mL in plasma. Mixed model linear regression identified that only MCP-1 in CSF was associated with neurocognitive change group. Recursive partitioning models aimed at diagnosis (i.e., correctly classifying neurocognitive status at the first visit) were complex and required most biomarkers to achieve misclassification limits. In contrast, prognostic models were more efficient. A combination of three biomarkers (sCD14, MCP-1, SDF-1α) correctly classified 82% of Wo and SN subjects, including 88% of SN subjects. A combination of two biomarkers (MCP-1, TNF-α) correctly classified 81% of Im and SI subjects, including 100% of SI subjects. Conclusions This analysis of well-characterized individuals identified concise panels of biomarkers associated with NC change. Across all analyses, the two most frequently identified biomarkers were sCD14 and MCP-1, indicators of monocyte/macrophage activation. While the panels differed depending on

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma

PubMed Central

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

Background There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Methods Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. Results The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. Conclusions TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC. PMID:27798689

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma.

PubMed

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC.

Epigenetic Biomarkers of Preterm Birth and Its Risk Factors

PubMed Central

Knight, Anna K.; Smith, Alicia K.

2016-01-01

A biomarker is a biological measure predictive of a normal or pathogenic process or response. Biomarkers are often useful for making clinical decisions and determining treatment course. One area where such biomarkers would be particularly useful is in identifying women at risk for preterm delivery and related pregnancy complications. Neonates born preterm have significant morbidity and mortality, both in the perinatal period and throughout the life course, and identifying women at risk of delivering preterm may allow for targeted interventions to prevent or delay preterm birth (PTB). In addition to identifying those at increased risk for preterm birth, biomarkers may be able to distinguish neonates at particular risk for future complications due to modifiable environmental factors, such as maternal smoking or alcohol use during pregnancy. Currently, there are no such biomarkers available, though candidate gene and epigenome-wide association studies have identified DNA methylation differences associated with PTB, its risk factors and its long-term outcomes. Further biomarker development is crucial to reducing the health burden associated with adverse intrauterine conditions and preterm birth, and the results of recent DNA methylation studies may advance that goal. PMID:27089367

A novel gammaretroviral shuttle vector insertional mutagenesis screen identifies SHARPIN as a breast cancer metastasis gene and prognostic biomarker.

PubMed

Bii, Victor M; Rae, Dustin T; Trobridge, Grant D

2015-11-24

Breast cancer (BC) is the second leading cause of malignancy among U.S. women. Metastasis results in a poor prognosis and increased mortality, but the molecular mechanisms by which metastatic tumors occur are not well understood. Identifying the genes that drive the metastatic process could provide targets for improved therapy and biomarkers to improve BC patient outcomes. Using a forward mutagenesis screen, BC cells mutagenized with a replication-incompetent gammaretroviral vector (γRV) were xenotransplanted into the mammary fat pad of immunodeficient mice. In this approach the vector provirus dysregulates nearby genes, providing a selective advantage to transduced cells to form metastases. Metastatic tumors were analyzed for proviral integration sites to identify nearby candidate metastasis genes. The γRV has a transgene cassette that allows for rescue in bacteria and rapid identification of vector integration sites. Using this approach, we identified the previously described metastasis gene WWTR1 (TAZ), and three other novel candidate metastasis genes including SHARPIN. SHARPIN was independently validated in vivo as a BC metastasis gene. Analysis of patient data showed that SHARPIN expression predicts metastasis-free survival after adjuvant therapy. Our approach has broad potential to identify genes involved in oncogenic processes for BC and other cancers. We show here it can identify both known (WWTR1) and novel (SHARPIN) BC metastasis genes.

Identification of candidate diagnostic serum biomarkers for Kawasaki disease using proteomic analysis

PubMed Central

Kimura, Yayoi; Yanagimachi, Masakatsu; Ino, Yoko; Aketagawa, Mao; Matsuo, Michie; Okayama, Akiko; Shimizu, Hiroyuki; Oba, Kunihiro; Morioka, Ichiro; Imagawa, Tomoyuki; Kaneko, Tetsuji; Yokota, Shumpei; Hirano, Hisashi; Mori, Masaaki

2017-01-01

Kawasaki disease (KD) is a systemic vasculitis and childhood febrile disease that can lead to cardiovascular complications. The diagnosis of KD depends on its clinical features, and thus it is sometimes difficult to make a definitive diagnosis. In order to identify diagnostic serum biomarkers for KD, we explored serum KD-related proteins, which differentially expressed during the acute and recovery phases of two patients by mass spectrometry (MS). We identified a total of 1,879 proteins by MS-based proteomic analysis. The levels of three of these proteins, namely lipopolysaccharide-binding protein (LBP), leucine-rich alpha-2-glycoprotein (LRG1), and angiotensinogen (AGT), were higher in acute phase patients. In contrast, the level of retinol-binding protein 4 (RBP4) was decreased. To confirm the usefulness of these proteins as biomarkers, we analyzed a total of 270 samples, including those collected from 55 patients with acute phase KD, by using western blot analysis and microarray enzyme-linked immunosorbent assays (ELISAs). Over the course of this experiment, we determined that the expression level of these proteins changes specifically in the acute phase of KD, rather than the recovery phase of KD or other febrile illness. Thus, LRG1 could be used as biomarkers to facilitate KD diagnosis based on clinical features. PMID:28262744

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer

PubMed Central

Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-01-01

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer “Big Data” has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of “hit” compounds. PMID:27806312

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates.

PubMed

Alanazi, Ibrahim O; AlYahya, Sami A; Ebrahimie, Esmaeil; Mohammadi-Dehcheshmeh, Manijeh

2018-06-15

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer. Particular attention was paid to non-coding biomarkers. In total, 60 MicroRNA biomarkers were reported for lung cancer, including some prognostic biomarkers. MIR21, MIR155, MALAT1, and MIR31 were the top non-coding RNA biomarkers of lung cancer. Text mining identified 447 proteins which have been studied as biomarkers in lung cancer. EGFR (receptor), TP53 (transcription factor), KRAS, CDKN2A, ENO2, KRT19, RASSF1, GRP (ligand), SHOX2 (transcription factor), and ERBB2 (receptor) were the most studied proteins. Within small molecules, thymosin-a1, oestrogen, and 8-OHdG have received more attention. We found some chromosomal bands, such as 7q32.2, 18q12.1, 6p12, 11p15.5, and 3p21.3 that are highly involved in deriving lung cancer biomarkers. Copyright © 2018 Elsevier B.V. All rights reserved.

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

Target biomarker profile for the clinical management of paracetamol overdose

PubMed Central

Vliegenthart, A D Bastiaan; Antoine, Daniel J; Dear, James W

2015-01-01

Paracetamol (acetaminophen) overdose is one of the most common causes of acute liver injury in the Western world. To improve patient care and reduce pressure on already stretched health care providers new biomarkers are needed that identify or exclude liver injury soon after an overdose of paracetamol is ingested. This review highlights the current state of paracetamol poisoning management and how novel biomarkers could improve patient care and save healthcare providers money. Based on the widely used concept of defining a target product profile, a target biomarker profile is proposed that identifies desirable and acceptable key properties for a biomarker in development to enable the improved treatment of this patient population. The current biomarker candidates, with improved hepatic specificity and based on the fundamental mechanistic basis of paracetamol-induced liver injury, are reviewed and their performance compared with our target profile. PMID:26076366

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

PubMed

Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

2013-01-01

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to

Utilization of metabonomics to identify serum biomarkers in murine H22 hepatocarcinoma and deduce antitumor mechanism of Rhizoma Paridis saponins.

PubMed

Qiu, Peiyu; Man, Shuli; Yang, He; Fan, Wei; Yu, Peng; Gao, Wenyuan

2016-08-25

Murine H22 hepatocarcinoma model is so popular to be used for the preclinical anticancer candidate's evaluation. However, the metabolic biomarkers of this model were not identified. Meanwhile, Rhizoma Paridis saponins (RPS) as natural products have been found to show strong antitumor activity, while its anti-cancer mechanism is not clear. To search for potential metabolite biomarkers of this model, serum metabonomics approach was applied to detect the variation of metabolite biomarkers and the related metabolism genes and signaling pathway were used to deduce the antitumor mechanisms of RPS. As a result, ten serum metabolites were identified in twenty-four mice including healthy mice, non-treated cancer mice, RPS-treated cancer mice and RPS-treated healthy mice. RPS significantly decreased tumor weight correlates to down-regulating lactate, acetate, N-acetyl amino acid and glutamine signals (p < 0.05), which were marked metabolites screened according to the very important person (VIP), loading plot and receiver operating characteristic curve (ROC) tests. For the analysis of metabolic enzyme related genes, RPS reversed the aerobic glycolysis through activating tumor suppressor p53 and PTEN, and suppressed FASN to inhibit lipogenesis. What's more, RPS repressed Myc and GLS expression and decreased glutamine level. The regulating PI3K/Akt/mTOR and HIF-1α/Myc/Ras networks also participated in these metabolic changes. Taken together, RPS suppressed ATP product made the tumor growth slow, which indicated a good anti-cancer effect and new angle for understanding the mechanism of RPS. In conclusion, this study demonstrated that the utility of (1)H NMR metabolic profiles taken together with tumor weight and viscera index was a promising screening tool for evaluating the antitumor effect of candidates. In addition, RPS was a potent anticancer agent through inhibiting cancer cellular metabolism to suppress proliferation in hepatoma H22 tumor murine, which promoted the

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease

PubMed Central

Choi1, Yong Seok; Lee, Kelvin H.

2016-01-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (> 90%) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R2 = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78%), and inter-day reproducibility (average CV = 9.85%). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard. PMID:26404792

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease.

PubMed

Choi, Yong Seok; Lee, Kelvin H

2016-03-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (>90 %) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems in laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R(2) = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78 %), and inter-day reproducibility (average CV = 9.85 %). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard.

Prioritization of Biomarker Targets in Human Umbilical Cord Blood: Identification of Proteins in Infant Blood Serving as Validated Biomarkers in Adults

PubMed Central

Hansmeier, Nicole; Chao, Tzu-Chiao; Goldman, Lynn R.; Witter, Frank R.

2012-01-01

Background: Early diagnosis represents one of the best lines of defense in the fight against a wide array of human diseases. Umbilical cord blood (UCB) is one of the first easily available diagnostic biofluids and can inform about the health status of newborns. However, compared with adult blood, its diagnostic potential remains largely untapped. Objectives: Our goal was to accelerate biomarker research on UCB by exploring its detectable protein content and providing a priority list of potential biomarkers based on known proteins involved in disease pathways. Methods: We explored cord blood serum proteins by profiling a UCB pool of 12 neonates with different backgrounds using a combination of isoelectric focusing and liquid chromatography coupled with matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) and by comparing results with information contained in metabolic and disease databases available for adult blood. Results: A total of 1,210 UCB proteins were identified with a protein-level false discovery rate of ~ 5% as estimated by naïve target-decoy and MAYU approaches, signifying a 6-fold increase in the number of UCB proteins described to date. Identified proteins correspond to 138 different metabolic and disease pathways and provide a platform of mechanistically linked biomarker candidates for tracking disruptions in cellular processes. Moreover, among the identified proteins, 38 were found to be approved biomarkers for adult blood. Conclusions: The results of this study advance current knowledge of the human cord blood serum proteome. They showcase the potential of UCB as a diagnostic medium for assessing infant health by detection and identification of candidate biomarkers for known disease pathways using a global, nontargeted approach. These biomarkers may inform about mechanisms of exposure–disease relationships. Furthermore, biomarkers approved by the U.S. Food and Drug Administration for screening in adult blood were

A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

PubMed

Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-06-01

Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Imaging Biomarkers for Adult Medulloblastomas: Genetic Entities May Be Identified by Their MR Imaging Radiophenotype.

PubMed

Keil, V C; Warmuth-Metz, M; Reh, C; Enkirch, S J; Reinert, C; Beier, D; Jones, D T W; Pietsch, T; Schild, H H; Hattingen, E; Hau, P

2017-10-01

The occurrence of medulloblastomas in adults is rare; nevertheless, these tumors can be subdivided into genetic and histologic entities each having distinct prognoses. This study aimed to identify MR imaging biomarkers to classify these entities and to uncover differences in MR imaging biomarkers identified in pediatric medulloblastomas. Eligible preoperative MRIs from 28 patients (11 women; 22-53 years of age) of the Multicenter Pilot-study for the Therapy of Medulloblastoma of Adults (NOA-7) cohort were assessed by 3 experienced neuroradiologists. Lesions and perifocal edema were volumetrized and multiparametrically evaluated for classic morphologic characteristics, location, hydrocephalus, and Chang criteria. To identify MR imaging biomarkers, we correlated genetic entities sonic hedgehog ( SHH ) TP53 wild type, wingless ( WNT ), and non -WNT/ non -SHH medulloblastomas (in adults, Group 4), and histologic entities were correlated with the imaging criteria. These MR imaging biomarkers were compared with corresponding data from a pediatric study. There were 19 SHH TP53 wild type (69%), 4 WNT -activated (14%), and 5 Group 4 (17%) medulloblastomas. Six potential MR imaging biomarkers were identified, 3 of which, hydrocephalus ( P = .03), intraventricular macrometastases ( P = .02), and hemorrhage ( P = .04), when combined, could identify WNT medulloblastoma with 100% sensitivity and 88.3% specificity (95% CI, 39.8%-100.0% and 62.6%-95.3%). WNT -activated nuclear β-catenin accumulating medulloblastomas were smaller than the other entities (95% CI, 5.2-22.3 cm 3 versus 35.1-47.6 cm 3 ; P = .03). Hemorrhage was exclusively present in non -WNT/ non -SHH medulloblastomas ( P = .04; n = 2/5). MR imaging biomarkers were all discordant from those identified in the pediatric cohort. Desmoplastic/nodular medulloblastomas were more rarely in contact with the fourth ventricle (4/15 versus 7/13; P = .04). MR imaging biomarkers can help distinguish histologic and genetic

Improving low-level plasma protein mass spectrometry-based detection for candidate biomarker discovery and validation

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

Page, Jason S.; Kelly, Ryan T.; Camp, David G.

2008-09-01

Methods. To improve the detection of low abundance protein candidate biomarker discovery and validation, particularly in complex biological fluids such as blood plasma, increased sensitivity is desired using mass spectrometry (MS)-based instrumentation. A key current limitation on the sensitivity of electrospray ionization (ESI) MS is due to the fact that many sample molecules in solution are never ionized, and the vast majority of the ions that are created are lost during transmission from atmospheric pressure to the low pressure region of the mass analyzer. Two key technologies, multi-nanoelectrospray emitters and the electrodynamic ion funnel have recently been developed and refinedmore » at Pacific Northwest National Laboratory (PNNL) to greatly improve the ionization and transmission efficiency of ESI MS based analyses. Multi-emitter based ESI enables the flow from a single source (typically a liquid chromatography [LC] column) to be divided among an array of emitters (Figure 1). The flow rate delivered to each emitter is thus reduced, allowing the well-documented benefits of nanoelectrospray 1 for both sensitivity and quantitation to be realized for higher flow rate separations. To complement the increased ionization efficiency afforded by multi-ESI, tandem electrodynamic ion funnels have also been developed at PNNL, and shown to greatly improve ion transmission efficiency in the ion source interface.2, 3 These technologies have been integrated into a triple quadrupole mass spectrometer for multiple reaction monitoring (MRM) of probable biomarker candidates in blood plasma and show promise for the identification of new species even at low level concentrations.« less

A Proteomics View of the Molecular Mechanisms and Biomarkers of Glaucomatous Neurodegeneration

PubMed Central

Tezel, Gülgün

2013-01-01

Despite improving understanding of glaucoma, key molecular players of neurodegeneration that can be targeted for treatment of glaucoma, or molecular biomarkers that can be useful for clinical testing, remain unclear. Proteomics technology offers a powerful toolbox to accomplish these important goals of the glaucoma research and is increasingly being applied to identify molecular mechanisms and biomarkers of glaucoma. Recent studies of glaucoma using proteomics analysis techniques have resulted in the lists of differentially expressed proteins in human glaucoma and animal models. The global analysis of protein expression in glaucoma has been followed by cell-specific proteome analysis of retinal ganglion cells and astrocytes. The proteomics data have also guided targeted studies to identify post-translational modifications and protein-protein interactions during glaucomatous neurodegeneration. In addition, recent applications of proteomics have provided a number of potential biomarker candidates. Proteomics technology holds great promise to move glaucoma research forward toward new treatment strategies and biomarker discovery. By reviewing the major proteomics approaches and their applications in the field of glaucoma, this article highlights the power of proteomics in translational and clinical research related to glaucoma and also provides a framework for future research to functionally test the importance of specific molecular pathways and validate candidate biomarkers. PMID:23396249

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

PubMed Central

Zetterberg, Henrik; Mattsson, Niklas; Johansson, Per; Minthon, Lennart; Blennow, Kaj; Olsson, Mattias

2015-01-01

Objective: To compare the diagnostic accuracy of CSF biomarkers and amyloid PET for diagnosing early-stage Alzheimer disease (AD). Methods: From the prospective, longitudinal BioFINDER study, we included 122 healthy elderly and 34 patients with mild cognitive impairment who developed AD dementia within 3 years (MCI-AD). β-Amyloid (Aβ) deposition in 9 brain regions was examined with [18F]-flutemetamol PET. CSF was analyzed with INNOTEST and EUROIMMUN ELISAs. The results were replicated in 146 controls and 64 patients with MCI-AD from the Alzheimer's Disease Neuroimaging Initiative study. Results: The best CSF measures for identifying MCI-AD were Aβ42/total tau (t-tau) and Aβ42/hyperphosphorylated tau (p-tau) (area under the curve [AUC] 0.93–0.94). The best PET measures performed similarly (AUC 0.92–0.93; anterior cingulate, posterior cingulate/precuneus, and global neocortical uptake). CSF Aβ42/t-tau and Aβ42/p-tau performed better than CSF Aβ42 and Aβ42/40 (AUC difference 0.03–0.12, p < 0.05). Using nonoptimized cutoffs, CSF Aβ42/t-tau had the highest accuracy of all CSF/PET biomarkers (sensitivity 97%, specificity 83%). The combination of CSF and PET was not better than using either biomarker separately. Conclusions: Amyloid PET and CSF biomarkers can identify early AD with high accuracy. There were no differences between the best CSF and PET measures and no improvement when combining them. Regional PET measures were not better than assessing the global Aβ deposition. The results were replicated in an independent cohort using another CSF assay and PET tracer. The choice between CSF and amyloid PET biomarkers for identifying early AD can be based on availability, costs, and doctor/patient preferences since both have equally high diagnostic accuracy. Classification of evidence: This study provides Class III evidence that amyloid PET and CSF biomarkers identify early-stage AD equally accurately. PMID:26354982

Circulating microRNAs in Pancreatic Juice as Candidate Biomarkers of Pancreatic Cancer

PubMed Central

Wang, Jin; Raimondo, Massimo; Guha, Sushovan; Chen, Jinyun; Diao, Lixia; Dong, Xiaoqun; Wallace, Michael B.; Killary, Ann M.; Frazier, Marsha L.; Woodward, Timothy A.; Wang, Jing; Sen, Subrata

2014-01-01

Development of sensitive and specific biomarkers, preferably those circulating in body fluids is critical for early diagnosis of cancer. This study performed profiling of microRNAs (miRNAs) in exocrine pancreatic secretions (pancreatic juice) by microarray analysis utilizing pancreatic juice from 6 pancreatic ductal adenocarcinoma (PDAC) patients and two pooled samples from 6 non-pancreatic, non-healthy (NPNH) as controls. Differentially circulating miRNAs were subsequently validated in 88 pancreatic juice samples from 50 PDAC, 19 chronic pancreatitis (CP) patients and 19 NPNH controls. A marked difference in the profiles of four circulating miRNAs (miR-205, miR-210, miR-492, and miR-1427) was observed in pancreatic juice collected from patients with PDAC and those without pancreatic disease. Elevated levels of the four miRNAs together predicted PDAC with a specificity of 88% and sensitivity of 87%. Inclusion of serum CA19-9 level increased the sensitivity to 91% and the specificity to 100%. Enrichment of the four miRNAs in pancreatic juice was associated with decreased OS, as was the combination of miR-205 and miR-210. Higher contents of miR-205 and miR-210 were also associated with lymph node metastasis. Elevated levels of circulating miR-205, miR-210, miR-492, and miR-1247 in pancreatic juice are, therefore, promising candidate biomarkers of disease and poor prognosis in patients with PDAC. PMID:25258651

An exploration into study design for biomarker identification: issues and recommendations.

PubMed

Hall, Jacqueline A; Brown, Robert; Paul, Jim

2007-01-01

Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

PubMed Central

Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

2013-01-01

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities

Identifying protein biomarkers in predicting disease severity of dengue virus infection using immune-related protein microarray.

PubMed

Soe, Hui Jen; Yong, Yean K; Al-Obaidi, Mazen M Jamil; Raju, Chandramathi Samudi; Gudimella, Ranganath; Manikam, Rishya; Sekaran, Shamala Devi

2018-02-01

Dengue virus is one of the most widespread flaviviruses that re-emerged throughout recent decades. The progression from mild dengue to severe dengue (SD) with the complications such as vascular leakage and hemorrhage increases the fatality rate of dengue. The pathophysiology of SD is not entirely clear. To investigate potential biomarkers that are suggestive of pathogenesis of SD, a small panel of serum samples selected from 1 healthy individual, 2 dengue patients without warning signs (DWS-), 2 dengue patients with warning signs (DWS+), and 5 patients with SD were subjected to a pilot analysis using Sengenics Immunome protein array. The overall fold changes of protein expressions and clustering heat map revealed that PFKFB4, TPM1, PDCL3, and PTPN20A were elevated among patients with SD. Differential expression analysis identified that 29 proteins were differentially elevated greater than 2-fold in SD groups than DWS- and DWS+. From the 29 candidate proteins, pathways enrichment analysis also identified insulin signaling and cytoskeleton pathways were involved in SD, suggesting that the insulin pathway may play a pivotal role in the pathogenesis of SD.

Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action.

PubMed

Xuan, Jiekun; Pan, Guihua; Qiu, Yunping; Yang, Lun; Su, Mingming; Liu, Yumin; Chen, Jian; Feng, Guoyin; Fang, Yiru; Jia, Wei; Xing, Qinghe; He, Lin

2011-12-02

Despite recent advances in understanding the pathophysiology of schizophrenia and the mechanisms of antipsychotic drug action, the development of biomarkers for diagnosis and therapeutic monitoring in schizophrenia remains challenging. Metabolomics provides a powerful approach to discover diagnostic and therapeutic biomarkers by analyzing global changes in an individual's metabolic profile in response to pathophysiological stimuli or drug intervention. In this study, we performed gas chromatography-mass spectrometry based metabolomic profiling in serum of unmedicated schizophrenic patients before and after an 8-week risperidone monotherapy, to detect potential biomarkers associated with schizophrenia and risperidone treatment. Twenty-two marker metabolites contributing to the complete separation of schizophrenic patients from matched healthy controls were identified, with citrate, palmitic acid, myo-inositol, and allantoin exhibiting the best combined classification performance. Twenty marker metabolites contributing to the complete separation between posttreatment and pretreatment patients were identified, with myo-inositol, uric acid, and tryptophan showing the maximum combined classification performance. Metabolic pathways including energy metabolism, antioxidant defense systems, neurotransmitter metabolism, fatty acid biosynthesis, and phospholipid metabolism were found to be disturbed in schizophrenic patients and partially normalized following risperidone therapy. Further study of these metabolites may facilitate the development of noninvasive biomarkers and more efficient therapeutic strategies for schizophrenia.

A tuberculosis biomarker database: the key to novel TB diagnostics.

PubMed

Yerlikaya, Seda; Broger, Tobias; MacLean, Emily; Pai, Madhukar; Denkinger, Claudia M

2017-03-01

New diagnostic innovations for tuberculosis (TB), including point-of-care solutions, are critical to reach the goals of the End TB Strategy. However, despite decades of research, numerous reports on new biomarker candidates, and significant investment, no well-performing, simple and rapid TB diagnostic test is yet available on the market, and the search for accurate, non-DNA biomarkers remains a priority. To help overcome this 'biomarker pipeline problem', FIND and partners are working on the development of a well-curated and user-friendly TB biomarker database. The web-based database will enable the dynamic tracking of evidence surrounding biomarker candidates in relation to target product profiles (TPPs) for needed TB diagnostics. It will be able to accommodate raw datasets and facilitate the verification of promising biomarker candidates and the identification of novel biomarker combinations. As such, the database will simplify data and knowledge sharing, empower collaboration, help in the coordination of efforts and allocation of resources, streamline the verification and validation of biomarker candidates, and ultimately lead to an accelerated translation into clinically useful tools. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis 5b...Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children.

PubMed

Wong, Hector R; Cvijanovich, Natalie Z; Hall, Mark; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Lin, Richard; Bigham, Michael T; Sen, Anita; Nowak, Jeffrey; Quasney, Michael; Henricksen, Jared W; Chopra, Arun; Banschbach, Sharon; Beckman, Eileen; Harmon, Kelli; Lahni, Patrick; Shanley, Thomas P

2012-10-29

Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. Genome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children

PubMed Central

2012-01-01

Introduction Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. Methods Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. Results Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. Conclusions Genome-wide expression analysis has provided the foundation

Fibrinogen gamma-A chain precursor in CSF: a candidate biomarker for Alzheimer's disease

PubMed Central

Lee, Joung Wook; Namkoong, Hong; Kim, Hyun Kee; Kim, Sanghee; Hwang, Dong Whi; Na, Hae Ri; Ha, Seon-Ah; Kim, Jae-Ryong; Kim, Jin Woo

2007-01-01

Background Cerebrospinal fluid (CSF) may be valuable for exploring protein markers for the diagnosis of Alzheimer's disease (AD). The prospect of early detection and treatment, to slow progression, holds hope for aging populations with increased average lifespan. The aim of the present study was to investigate candidate CSF biological markers in patients with mild cognitive impairment (MCI) and AD and compare them with age-matched normal control subjects. Methods We applied proteomics approaches to analyze CSF samples derived from 27 patients with AD, 3 subjects with MCI and 30 controls. The AD group was subdivided into three groups by clinical severity according to clinical dementia rating (CDR), a well known clinical scale for dementia. Results We demonstrated an elevated level of fibrinogen gamma-A chain precursor protein in CSF from patients with mild cognitive impairment and AD compared to the age-matched normal subjects. Moreover, its expression was more prominent in the AD group than in the MCI and correlated with disease severity and progression. In contrast, fibrinogen gamma-A chain precursor protein was detected very low in the age-matched normal group. Conclusion These findings suggest that the CSF level of fibrinogen gamma-A chain precursor may be a candidate biomarker for AD. PMID:17565664

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

PubMed

Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

2014-09-01

Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

Discovery and characterization of potential prognostic biomarkers for dengue hemorrhagic fever.

PubMed

Poole-Smith, B Katherine; Gilbert, Alexa; Gonzalez, Andrea L; Beltran, Manuela; Tomashek, Kay M; Ward, Brian J; Hunsperger, Elizabeth A; Ndao, Momar

2014-12-01

Half a million patients are hospitalized with severe dengue every year, many of whom would die without timely, appropriate clinical intervention. The majority of dengue cases are uncomplicated; however, 2-5% progress to severe dengue. Severe dengue cases have been reported with increasing frequency over the last 30 years. To discover biomarkers for severe dengue, we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to analyze dengue virus positive serum samples from the acute phase of infection. Using this method, 16 proteins were identified as candidate biomarkers for severe dengue. From these 16 biomarkers, three candidates were selected for confirmation by enzyme-linked immunosorbent assay and Western blot: vitronectin (Vtn, 55.1 kDa), hemopexin (Hx, 52.4 kDa), and serotransferrin (Tf, 79.2 kDa). Vitronectin, Hx, and Tf best differentiated between dengue and severe dengue. © The American Society of Tropical Medicine and Hygiene.

Discovery and Characterization of Potential Prognostic Biomarkers for Dengue Hemorrhagic Fever

PubMed Central

Poole-Smith, B. Katherine; Gilbert, Alexa; Gonzalez, Andrea L.; Beltran, Manuela; Tomashek, Kay M.; Ward, Brian J.; Hunsperger, Elizabeth A.; Ndao, Momar

2014-01-01

Half a million patients are hospitalized with severe dengue every year, many of whom would die without timely, appropriate clinical intervention. The majority of dengue cases are uncomplicated; however, 2–5% progress to severe dengue. Severe dengue cases have been reported with increasing frequency over the last 30 years. To discover biomarkers for severe dengue, we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to analyze dengue virus positive serum samples from the acute phase of infection. Using this method, 16 proteins were identified as candidate biomarkers for severe dengue. From these 16 biomarkers, three candidates were selected for confirmation by enzyme-linked immunosorbent assay and Western blot: vitronectin (Vtn, 55.1 kDa), hemopexin (Hx, 52.4 kDa), and serotransferrin (Tf, 79.2 kDa). Vitronectin, Hx, and Tf best differentiated between dengue and severe dengue. PMID:25349378

Biomarkers to guide clinical therapeutics in rheumatology?

PubMed

Robinson, William H; Mao, Rong

2016-03-01

The use of biomarkers in rheumatology can help identify disease risk, improve diagnosis and prognosis, target therapy, assess response to treatment, and further our understanding of the underlying pathogenesis of disease. Here, we discuss the recent advances in biomarkers for rheumatic disorders, existing impediments to progress in this field, and the potential of biomarkers to enable precision medicine and thereby transform rheumatology. Although significant challenges remain, progress continues to be made in biomarker discovery and development for rheumatic diseases. The use of next-generation technologies, including large-scale sequencing, proteomic technologies, metabolomic technologies, mass cytometry, and other single-cell analysis and multianalyte analysis technologies, has yielded a slew of new candidate biomarkers. Nevertheless, these biomarkers still require rigorous validation and have yet to make their way into clinical practice and therapeutic development. This review focuses on advances in the biomarker field in the last 12 months as well as the challenges that remain. Better biomarkers, ideally mechanistic ones, are needed to guide clinical decision making in rheumatology. Although the use of next-generation techniques for biomarker discovery is making headway, it is imperative that the roadblocks in our search for new biomarkers are overcome to enable identification of biomarkers with greater diagnostic and predictive utility. Identification of biomarkers with robust diagnostic and predictive utility would enable precision medicine in rheumatology.

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges.

PubMed

Root, Alex; Allen, Peter; Tempst, Paul; Yu, Kenneth

2018-03-07

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread.

PubMed

Spreafico, Filippo; Bongarzone, Italia; Pizzamiglio, Sara; Magni, Ruben; Taverna, Elena; De Bortoli, Maida; Ciniselli, Chiara M; Barzanò, Elena; Biassoni, Veronica; Luchini, Alessandra; Liotta, Lance A; Zhou, Weidong; Signore, Michele; Verderio, Paolo; Massimino, Maura

2017-07-11

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

The MCP-4/MCP-1 ratio in plasma is a candidate circadian biomarker for chronic post-traumatic stress disorder

PubMed Central

Dalgard, C; Eidelman, O; Jozwik, C; Olsen, C H; Srivastava, M; Biswas, R; Eudy, Y; Rothwell, S W; Mueller, G P; Yuan, P; Drevets, W C; Manji, H K; Vythlingam, M; Charney, D S; Neumeister, A; Ursano, R J; Jacobowitz, D M; Pollard, H B; Bonne, O

2017-01-01

Post-traumatic stress disorder (PTSD) is psychiatric disease, which can occur following exposure to traumatic events. PTSD may be acute or chronic, and can have a waxing and waning course of symptoms. It has been hypothesized that proinflammatory cytokines and chemokines in the cerebrospinal fluid (CSF) or plasma might be mediators of the psychophysiological mechanisms relating a history of trauma exposure to changes in behavior and mental health disorders, and medical morbidity. Here we test the cytokine/chemokine hypothesis for PTSD by examining levels of 17 classical cytokines and chemokines in CSF, sampled at 0900 hours, and in plasma sampled hourly for 24 h. The PTSD and healthy control patients are from the NIMH Chronic PTSD and healthy control cohort, initially described by Bonne et al. (2011), in which the PTSD patients have relatively low comorbidity for major depressive disorder (MDD), drug or alcohol use. We find that in plasma, but not CSF, the bivariate MCP4 (CCL13)/ MCP1(CCL2) ratio is ca. twofold elevated in PTSD patients compared with healthy controls. The MCP-4/MCP-1 ratio is invariant over circadian time, and is independent of gender, body mass index or the age at which the trauma was suffered. By contrast, MIP-1β is a candidate biomarker for PTSD only in females, whereas TARC is a candidate biomarker for PTSD only in males. It remains to be discovered whether these disease-specific differences in circadian expression for these specific immune signaling molecules are biomarkers, surrogates, or drivers for PTSD, or whether any of these analytes could contribute to therapy. PMID:28170001

Whole exome sequencing identifies novel candidate genes that modify chronic obstructive pulmonary disease susceptibility.

PubMed

Bruse, Shannon; Moreau, Michael; Bromberg, Yana; Jang, Jun-Ho; Wang, Nan; Ha, Hongseok; Picchi, Maria; Lin, Yong; Langley, Raymond J; Qualls, Clifford; Klensney-Tait, Julia; Zabner, Joseph; Leng, Shuguang; Mao, Jenny; Belinsky, Steven A; Xing, Jinchuan; Nyunoya, Toru

2016-01-07

Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible airflow limitation in response to inhalation of noxious stimuli, such as cigarette smoke. However, only 15-20 % smokers manifest COPD, suggesting a role for genetic predisposition. Although genome-wide association studies have identified common genetic variants that are associated with susceptibility to COPD, effect sizes of the identified variants are modest, as is the total heritability accounted for by these variants. In this study, an extreme phenotype exome sequencing study was combined with in vitro modeling to identify COPD candidate genes. We performed whole exome sequencing of 62 highly susceptible smokers and 30 exceptionally resistant smokers to identify rare variants that may contribute to disease risk or resistance to COPD. This was a cross-sectional case-control study without therapeutic intervention or longitudinal follow-up information. We identified candidate genes based on rare variant analyses and evaluated exonic variants to pinpoint individual genes whose function was computationally established to be significantly different between susceptible and resistant smokers. Top scoring candidate genes from these analyses were further filtered by requiring that each gene be expressed in human bronchial epithelial cells (HBECs). A total of 81 candidate genes were thus selected for in vitro functional testing in cigarette smoke extract (CSE)-exposed HBECs. Using small interfering RNA (siRNA)-mediated gene silencing experiments, we showed that silencing of several candidate genes augmented CSE-induced cytotoxicity in vitro. Our integrative analysis through both genetic and functional approaches identified two candidate genes (TACC2 and MYO1E) that augment cigarette smoke (CS)-induced cytotoxicity and, potentially, COPD susceptibility.

Urinary and Blood MicroRNA-126 and -770 are Potential Noninvasive Biomarker Candidates for Diabetic Nephropathy: a Meta-Analysis.

PubMed

Park, Sungjin; Moon, SeongRyeol; Lee, Kiyoung; Park, Ie Byung; Lee, Dae Ho; Nam, Seungyoon

2018-01-01

Diabetic nephropathy (DN), a major diabetic microvascular complication, has a long and growing list of biomarkers, including microRNA biomarkers, which have not been consistent across preclinical and clinical studies. This meta-analysis aims to identify significant blood- and urine-incident microRNAs as diagnostic/prognostic biomarker candidates for DN. PubMed, Web of Science, and Cochrane Library were searched from their earliest records through 12th Dec 2016. Relevant publications for the meta-analysis included (1) human participants; (2) microRNAs in blood and urine; (3) DN studies; and (4) English language. Four reviewers, including two physicians, independently and blindly extracted published data regarding microRNA profiles in blood and/or urine from subjects with diabetic nephropathy. A random-effect model was used to pool the data. Statistical associations between diabetic nephropathy and urinary or blood microRNA expression levels were assessed. Fourteen out of 327 studies (n=2,747 patients) were selected. Blood or urinary microRNA expression data of diabetic nephropathy were pooled for this analysis. The hsa-miR-126 family was significantly (OR: 0.57; 95% CI: 0.44-0.74; p-value < 0.0001) downregulated in blood from patients with diabetic kidney disease, while its urinary level was upregulated (OR: 2931.12; 95% CI: 9.96-862623.21; p-value = 0.0059). The hsa-miR-770 family microRNA were significantly (OR: 10.24; 95% CI: 2.37-44.25; p-value = 0.0018) upregulated in both blood and urine from patients with diabetic nephropathy. Our meta-analysis suggests that hsa-miR-126 and hsa-miR-770 family microRNA may have important diagnostic and pathogenetic implications for DN, which warrants further systematic clinical studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury.

PubMed

Jones, Jace W; Jackson, Isabel L; Vujaskovic, Zeljko; Kaytor, Michael D; Kane, Maureen A

2017-12-01

Biomarkers serve a number of purposes during drug development including defining the natural history of injury/disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.

Development of Biomarkers for Screening Hepatocellular Carcinoma Using Global Data Mining and Multiple Reaction Monitoring

PubMed Central

Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases. PMID:23717429

Development of biomarkers for screening hepatocellular carcinoma using global data mining and multiple reaction monitoring.

PubMed

Kim, Hyunsoo; Kim, Kyunggon; Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.

Biomarkers for Severity of Spinal Cord Injury in the Cerebrospinal Fluid of Rats

PubMed Central

Lubieniecka, Joanna M.; Streijger, Femke; Lee, Jae H. T.; Stoynov, Nikolay; Liu, Jie; Mottus, Randy; Pfeifer, Tom; Kwon, Brian K.; Coorssen, Jens R.; Foster, Leonard J.; Grigliatti, Thomas A.; Tetzlaff, Wolfram

2011-01-01

One of the major challenges in management of spinal cord injury (SCI) is that the assessment of injury severity is often imprecise. Identification of reliable, easily quantifiable biomarkers that delineate the severity of the initial injury and that have prognostic value for the degree of functional recovery would significantly aid the clinician in the choice of potential treatments. To find such biomarkers we performed quantitative liquid chromatography-mass spectrometry (LC-MS/MS) analyses of cerebrospinal fluid (CSF) collected from rats 24 h after either a moderate or severe SCI. We identified a panel of 42 putative biomarkers of SCI, 10 of which represent potential biomarkers of SCI severity. Three of the candidate biomarkers, Ywhaz, Itih4, and Gpx3 were also validated by Western blot in a biological replicate of the injury. The putative biomarkers identified in this study may potentially be a valuable tool in the assessment of the extent of spinal cord damage. PMID:21559420

Proteomics of gliomas: Initial biomarker discovery and evolution of technology

PubMed Central

Kalinina, Juliya; Peng, Junmin; Ritchie, James C.; Van Meir, Erwin G.

2011-01-01

Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers. PMID:21852429

Global microRNA expression profiling of microdissected tissues identifies miR-135b as a novel biomarker for pancreatic ductal adenocarcinoma.

PubMed

Munding, Johanna B; Adai, Alex T; Maghnouj, Abdelouahid; Urbanik, Aleksandra; Zöllner, Hannah; Liffers, Sven T; Chromik, Ansgar M; Uhl, Waldemar; Szafranska-Schwarzbach, Anna E; Tannapfel, Andrea; Hahn, Stephan A

2012-07-15

Pancreatic ductal adenocarcinoma (PDAC) is known for its poor prognosis resulting from being diagnosed at an advanced stage. Accurate early diagnosis and new therapeutic modalities are therefore urgently needed. MicroRNAs (miRNAs), considered a new class of biomarkers and therapeutic targets, may be able to fulfill those needs. Combining tissue microdissection with global miRNA array analyses, cell type-specific miRNA expression profiles were generated for normal pancreatic ductal cells, acinar cells, PDAC cells derived from xenografts and also from macrodissected chronic pancreatitis (CP) tissues. We identified 78 miRNAs differentially expressed between ND and PDAC cells providing new insights into the miRNA-driven pathophysiological mechanisms involved in PDAC development. Having filtered miRNAs which are upregulated in the three pairwise comparisons of PDAC vs. ND, PDAC vs. AZ and PDAC vs. CP, we identified 15 miRNA biomarker candidates including miR-135b. Using relative qRT-PCR to measure miR-135b normalized to miR-24 in 75 FFPE specimens (42 PDAC and 33 CP) covering a broad range of tumor content, we discriminated CP from PDAC with a sensitivity and specificity of 92.9% [95% CI=(80.5, 98.5)] and 93.4% [95% CI=(79.8, 99.3)], respectively. Furthermore, the area under the curve (AUC) value reached of 0.97 was accompanied by positive and negative predictive values of 95% and 91%, respectively. In conclusion, we report pancreatic cell-specific global miRNA profiles, which offer new candidate miRNAs to be exploited for functional studies in PDAC. Furthermore, we provide evidence that miRNAs are well-suited analytes for development of sensitive and specific aid-in-diagnosis tests for PDAC. Copyright © 2011 UICC.

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics

PubMed Central

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients’ saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects (p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity. PMID:28326926

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

PubMed

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Discriminant biomarkers of acute respiratory distress syndrome associated to H1N1 influenza identified by metabolomics HPLC-QTOF-MS/MS platform.

PubMed

Ferrarini, Alessia; Righetti, Laura; Martínez, Ma Paz; Fernández-López, Mariano; Mastrangelo, Annalaura; Horcajada, Juan P; Betbesé, Antoni; Esteban, Andrés; Ordóñez, Jordi; Gea, Joaquín; Cabello, Jesús Ruiz; Pellati, Federica; Lorente, José A; Nin, Nicolás; Rupérez, Francisco J

2017-09-01

Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC-MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC-MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty-three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications.

PubMed

de Graaf, Gimon; Postmus, Douwe; Westerink, Jan; Buskens, Erik

2018-01-01

Translating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study. We defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers. The most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more. It is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.

MicroRNA-206: A Potential Circulating Biomarker Candidate for Amyotrophic Lateral Sclerosis

PubMed Central

Toivonen, Janne M.; Manzano, Raquel; Oliván, Sara; Zaragoza, Pilar; García-Redondo, Alberto; Osta, Rosario

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a lethal motor neuron disease that progressively debilitates neuronal cells that control voluntary muscle activity. Biomarkers are urgently needed to facilitate ALS diagnosis and prognosis, and as indicators of therapeutic response in clinical trials. microRNAs (miRNAs), small posttranscriptional modifiers of gene expression, are frequently altered in disease conditions. Besides their important regulatory role in variety of biological processes, miRNAs can also be released into the circulation by pathologically affected tissues and display remarkable stability in body fluids. In a mouse model of ALS that expresses mutated human superoxide dismutase 1 (SOD1-G93A) skeletal muscle is one of the tissues affected early by mutant SOD1 toxicity. To find biomarkers for ALS, we studied miRNA alterations from skeletal muscle and plasma of SOD1-G93A mice, and subsequently tested the levels of the affected miRNAs in the serum from human ALS patients. Fast-twitch and slow-twitch muscles from symptomatic SOD1-G93A mice (age 90 days) and their control littermates were first studied using miRNA microarrays and then evaluated with quantitative PCR from five age groups from neonatal to the terminal disease stage (10–120 days). Among those miRNA changed in various age/gender/muscle groups (miR-206, -1, -133a, -133b, -145, -21, -24), miR-206 was the only one consistently altered during the course of the disease pathology. In both sexes, mature miR-206 was increased in fast-twitch muscles preferably affected in the SOD1-G93A model, with highest expression towards the most severely affected animals. Importantly, miR-206 was also increased in the circulation of symptomatic animals and in a group of 12 definite ALS patients tested. We conclude that miR-206 is elevated in the circulation of symptomatic SOD1-G93A mice and possibly in human ALS patients. Although larger scale studies on ALS patients are warranted, miR-206 is a promising candidate

Human alpha defensin 5 is a candidate biomarker to delineate inflammatory bowel disease

PubMed Central

Williams, Amanda D.; Korolkova, Olga Y.; Sakwe, Amos M.; Geiger, Timothy M.; James, Samuel D.; Muldoon, Roberta L.; Herline, Alan J.; Goodwin, J. Shawn; Izban, Michael G.; Washington, Mary K.; Smoot, Duane T.; Ballard, Billy R.; Gazouli, Maria

2017-01-01

�-Defensin-5 is a potential candidate biomarker to molecularly differentiate Crohn's colitis from ulcerative colitis, to our knowledge. These data give us both a potential diagnostic marker in Human α-Defensin-5 and insight to develop future mechanistic studies to better understand crypt biology in Crohn's colitis. PMID:28817680

Evaluation of the biomarker candidate MFAP4 for non-invasive assessment of hepatic fibrosis in hepatitis C patients.

PubMed

Bracht, Thilo; Mölleken, Christian; Ahrens, Maike; Poschmann, Gereon; Schlosser, Anders; Eisenacher, Martin; Stühler, Kai; Meyer, Helmut E; Schmiegel, Wolff H; Holmskov, Uffe; Sorensen, Grith L; Sitek, Barbara

2016-07-04

The human microfibrillar-associated protein 4 (MFAP4) is located to extracellular matrix fibers and plays a role in disease-related tissue remodeling. Previously, we identified MFAP4 as a serum biomarker candidate for hepatic fibrosis and cirrhosis in hepatitis C patients. The aim of the present study was to elucidate the potential of MFAP4 as biomarker for hepatic fibrosis with a focus on the differentiation of no to moderate (F0-F2) and severe fibrosis stages and cirrhosis (F3 and F4, Desmet-Scheuer scoring system). MFAP4 levels were measured using an AlphaLISA immunoassay in a retrospective study including n = 542 hepatitis C patients. We applied a univariate logistic regression model based on MFAP4 serum levels and furthermore derived a multivariate model including also age and gender. Youden-optimal cutoffs for binary classification were determined for both models without restrictions and considering a lower limit of 80 % sensitivity (correct classification of F3 and F4), respectively. To assess the generalization error, leave-one-out cross validation (LOOCV) was performed. MFAP4 levels were shown to differ between no to moderate fibrosis stages F0-F2 and severe stages (F3 and F4) with high statistical significance (t test on log scale, p value <2.2·10(-16)). In the LOOCV, the univariate classification resulted in 85.8 % sensitivity and 54.9 % specificity while the multivariate model yielded 81.3 % sensitivity and 61.5 % specificity (restricted approaches). We confirmed the applicability of MFAP4 as a novel serum biomarker for assessment of hepatic fibrosis and identification of high-risk patients with severe fibrosis stages in hepatitis C. The combination of MFAP4 with existing tests might lead to a more accurate non-invasive diagnosis of hepatic fibrosis and allow a cost-effective disease management in the era of new direct acting antivirals.

Identification of candidate biomarkers of the exposure to PCBs in contaminated cattle: A gene expression- and proteomic-based approach.

PubMed

Girolami, F; Badino, P; Spalenza, V; Manzini, L; Renzone, G; Salzano, A M; Dal Piaz, F; Scaloni, A; Rychen, G; Nebbia, C

2018-05-28

Dioxins and polychlorinated biphenyls (PCBs) are widespread and persistent contaminants. Through a combined gene expression/proteomic-based approach, candidate biomarkers of the exposure to such environmental pollutants in cattle subjected to a real eco-contamination event were identified. Animals were removed from the polluted area and fed a standard ration for 6 months. The decontamination was monitored by evaluating dioxin and PCB levels in pericaudal fat two weeks after the removal from the contaminated area (day 0) and then bimonthly for six months (days 59, 125 and 188). Gene expression measurements demonstrated that CYP1B1 expression was significantly higher in blood lymphocytes collected in contaminated animals (day 0), and decreased over time during decontamination. mRNA levels of interleukin 2 showed an opposite quantitative trend. MALDI-TOF-MS polypeptide profiling of serum samples ascertained a progressive decrease (from day 0 to 188) of serum levels of fibrinogen β-chain and serpin A3-7-like fragments, apolipoprotein (APO) C-II and serum amyloid A-4 protein, along with an augmented representation of transthyretin isoforms, as well as APOC-III and APOA-II proteins during decontamination. When differentially represented species were combined with serum antioxidant, acute phase and proinflammatory protein levels already ascertained in the same animals (Cigliano et al., 2016), bioinformatics unveiled an interaction network linking together almost all components. This suggests the occurrence of a complex PCB-responsive mechanism associated with animal contamination/decontamination, including a cohort of protein/polypeptide species involved in blood redox homeostasis, inflammation and lipid transport. All together, these results suggest the use in combination of such biomarkers for identifying PCB-contaminated animals, and for monitoring the restoring of their healthy condition following a decontamination process. Copyright © 2018 Elsevier B.V. All

Biomarkers in DILI: One More Step Forward

PubMed Central

Robles-Díaz, Mercedes; Medina-Caliz, Inmaculada; Stephens, Camilla; Andrade, Raúl J.; Lucena, M. Isabel

2016-01-01

Despite being relatively rare, drug-induced liver injury (DILI) is a serious condition, both for the individual patient due to the risk of acute liver failure, and for the drug development industry and regulatory agencies due to associations with drug development attritions, black box warnings, and postmarketing withdrawals. A major limitation in DILI diagnosis and prediction is the current lack of specific biomarkers. Despite refined usage of traditional liver biomarkers in DILI, reliable disease outcome predictions are still difficult to make. These limitations have driven the growing interest in developing new more sensitive and specific DILI biomarkers, which can improve early DILI prediction, diagnosis, and course of action. Several promising DILI biomarker candidates have been discovered to date, including mechanistic-based biomarker candidates such as glutamate dehydrogenase, high-mobility group box 1 protein and keratin-18, which can also provide information on the injury mechanism of different causative agents. Furthermore, microRNAs have received much attention lately as potential non-invasive DILI biomarker candidates, in particular miR-122. Advances in “omics” technologies offer a new approach for biomarker exploration studies. The ability to screen a large number of molecules (e.g., metabolites, proteins, or DNA) simultaneously enables the identification of ‘toxicity signatures,’ which may be used to enhance preclinical safety assessments and disease diagnostics. Omics-based studies can also provide information on the underlying mechanisms of distinct forms of DILI that may further facilitate the identification of early diagnostic biomarkers and safer implementation of personalized medicine. In this review, we summarize recent advances in the area of DILI biomarker studies. PMID:27597831

Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

PubMed Central

Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

2009-01-01

Background Acute lymphoblastic leukemia (ALL) is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls) and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML) patients). Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS). A classification model was established by Biomarker Pattern Software (BPS). Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z) were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z) were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4) and pro-platelet basic protein precursor (PBP). Two other candidate protein peaks (8137 and 8937 m/z) were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a). Conclusion Platelet factor (PF4), connective tissue activating peptide III (CTAP-III) and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with additional

Urinary metabolomics analysis identifies key biomarkers of different stages of nonalcoholic fatty liver disease

PubMed Central

Dong, Shu; Zhan, Zong-Ying; Cao, Hong-Yan; Wu, Chao; Bian, Yan-Qin; Li, Jian-Yuan; Cheng, Gen-Hong; Liu, Ping; Sun, Ming-Yu

2017-01-01

AIM To identify a panel of biomarkers that can distinguish between non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), and explore molecular mechanism involved in the process of developing NASH from NAFLD. METHODS Biomarkers may differ during stages of NAFLD. Urine and blood were obtained from non-diabetic subjects with NAFLD and steatosis, with normal liver function (n = 33), from patients with NASH, with abnormal liver function (n = 45), and from healthy age and sex-matched controls (n = 30). Samples were subjected to metabolomic analysis to identify potential non-invasive biomarkers. Differences in urinary metabolic profiles were analyzed using liquid chromatography tandem mass spectrometry with principal component analysis and partial least squares-discriminate analysis. RESULTS Compared with NAFLD patients, patients with NASH had abnormal liver function and high serum lipid concentrations. Urinary metabonomics found differences in 31 metabolites between these two groups, including differences in nucleic acids and amino acids. Pathway analysis based on overlapping metabolites showed that pathways of energy and amino acid metabolism, as well as the pentose phosphate pathway, were closely associated with pathological processes in NAFLD and NASH. CONCLUSION These findings suggested that a panel of biomarkers could distinguish between NAFLD and NASH, and could help to determine the molecular mechanism involved in the process of developing NASH from NAFLD. Urinary biomarkers may be diagnostic in these patients and could be used to assess responses to therapeutic interventions. PMID:28487615

Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence.

PubMed

Long, Qi; Xu, Jianpeng; Osunkoya, Adeboye O; Sannigrahi, Soma; Johnson, Brent A; Zhou, Wei; Gillespie, Theresa; Park, Jong Y; Nam, Robert K; Sugar, Linda; Stanimirovic, Aleksandra; Seth, Arun K; Petros, John A; Moreno, Carlos S

2014-06-15

Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer. ©2014 American Association for Cancer Research.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Biomarkers for wound healing and their evaluation.

PubMed

Patel, S; Maheshwari, A; Chandra, A

2016-01-01

A biological marker (biomarker) is a substance used as an indicator of biological state. Advances in genomics, proteomics and molecular pathology have generated many candidate biomarkers with potential clinical value. Research has identified several cellular events and mediators associated with wound healing that can serve as biomarkers. Macrophages, neutrophils, fibroblasts and platelets release cytokines molecules including TNF-α, interleukins (ILs) and growth factors, of which platelet-derived growth factor (PDGF) holds the greatest importance. As a result, various white cells and connective tissue cells release both matrix metalloproteinases (MMPs) and the tissue inhibitors of metalloproteinases (TIMPs). Studies have demonstrated that IL-1, IL-6, and MMPs, levels above normal, and an abnormally high MMP/TIMP ratio are often present in non-healing wounds. Clinical examination of wounds for these mediators could predict which wounds will heal and which will not, suggesting use of these chemicals as biomarkers of wound healing. There is also evidence that the application of growth factors like PDGF will alleviate the recuperating process of chronic, non-healing wounds. Finding a specific biomarker for wound healing status would be a breakthrough in this field and helping treat impaired wound healing.

BluePen Biomarkers LLC: integrated biomarker solutions

PubMed Central

Blair, Ian A; Mesaros, Clementina; Lilley, Patrick; Nunez, Matthew

2016-01-01

BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests. PMID:28031971

Using bacterial biomarkers to identify early indicators of cystic fibrosis pulmonary exacerbation onset

PubMed Central

Rogers, Geraint B; Hoffman, Lucas R; Johnson, Matt W; Mayer-Hamblett, Nicole; Schwarze, Jürgen; Carroll, Mary P; Bruce, Kenneth D

2011-01-01

Acute periods of pulmonary exacerbation are the single most important cause of morbidity in cystic fibrosis patients, and may be associated with a loss of lung function. Intervening prior to the onset of a substantially increased inflammatory response may limit the associated damage to the airways. While a number of biomarker assays based on inflammatory markers have been developed, providing useful and important measures of disease during these periods, such factors are typically only elevated once the process of exacerbation has been initiated. Identifying biomarkers that can predict the onset of pulmonary exacerbation at an early stage would provide an opportunity to intervene before the establishment of a substantial immune response, with major implications for the advancement of cystic fibrosis care. The precise triggers of pulmonary exacerbation remain to be determined; however, the majority of models relate to the activity of microbes present in the patient's lower airways of cystic fibrosis. Advances in diagnostic microbiology now allow for the examination of these complex systems at a level likely to identify factors on which biomarker assays can be based. In this article, we discuss key considerations in the design and testing of assays that could predict pulmonary exacerbations. PMID:21405970

Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study.

PubMed

Rastegar-Mojarad, Majid; Liu, Hongfang; Nambisan, Priya

2016-06-16

Drug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates. Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications. Our aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing. We retrieved patient reviews of 180 medications from an online forum, WebMD. Using dictionary-based and machine learning approaches, we identified disease names in the reviews. Several publicly available resources were used to exclude comments containing known indications and adverse drug effects. After manually reviewing some of the remaining comments, we implemented a rule-based system to identify beneficial effects. The dictionary-based system and machine learning system identified 2178 and 6171 disease names respectively in 64,616 patient comments. We provided a list of 10 common patterns that patients used to report any beneficial effects or uses of medication. After manually reviewing the comments tagged by our rule-based system, we identified five potential drug repurposing candidates. To our knowledge, this is the first study to consider using social media data to identify drug-repurposing candidates. We found that even a rule-based system, with a limited number of rules, could identify beneficial effect mentions in patient comments. Our preliminary study shows that social media has the potential to be used in drug repurposing.

Electrophysiological biomarkers of epileptogenicity after traumatic brain injury.

PubMed

Perucca, Piero; Smith, Gregory; Santana-Gomez, Cesar; Bragin, Anatol; Staba, Richard

2018-06-05

Post-traumatic epilepsy is the architype of acquired epilepsies, wherein a brain insult initiates an epileptogenic process culminating in an unprovoked seizure after weeks, months or years. Identifying biomarkers of such process is a prerequisite for developing and implementing targeted therapies aimed at preventing the development of epilepsy. Currently, there are no validated electrophysiological biomarkers of post-traumatic epileptogenesis. Experimental EEG studies using the lateral fluid percussion injury model have identified three candidate biomarkers of post-traumatic epileptogenesis: pathological high-frequency oscillations (HFOs, 80-300 Hz); repetitive HFOs and spikes (rHFOSs); and reduction in sleep spindle duration and dominant frequency at the transition from stage III to rapid eye movement sleep. EEG studies in humans have yielded conflicting data; recent evidence suggests that epileptiform abnormalities detected acutely after traumatic brain injury carry a significantly increased risk of subsequent epilepsy. Well-designed studies are required to validate these promising findings, and ultimately establish whether there are post-traumatic electrophysiological features which can guide the development of 'antiepileptogenic' therapies. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying Canadian Teacher Candidates' Needs for Training in the Use of Inclusive Classroom Assessment

ERIC Educational Resources Information Center

Lin, Pei-Ying; Lin, Yu-Cheng

2015-01-01

To identify teacher candidates' needs for training in inclusive classroom assessment, the present study investigated teacher candidates' beliefs about inclusive classroom assessments for all students educated in regular classrooms, including those with special needs and English language learners. An innovative theoretical assessment model,…

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

PubMed

Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan; Chen, Emily I

2016-11-01

Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

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

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially

Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

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

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. PMID:23792823

Urine protein profiling identified alpha-1-microglobulin and haptoglobin as biomarkers for early diagnosis of acute allograft rejection following kidney transplantation.

PubMed

Stubendorff, Beatrice; Finke, Stephanie; Walter, Martina; Kniemeyer, Olaf; von Eggeling, Ferdinand; Gruschwitz, Torsten; Steiner, Thomas; Ott, Undine; Wolf, Gunter; Wunderlich, Heiko; Junker, Kerstin

2014-12-01

Early diagnosis of acute rejection and effective immunosuppressive therapy lead to improvement in graft survival following kidney transplantation. In this study, we aimed to establish a urinary protein profile suitable to distinguish between patients with rejection and stable graft function and to predict acute rejection based on postoperatively collected urine samples. A further objective was to identify candidate proteins for the use as biomarkers in clinical practice. Urine samples of 116 kidney recipients were included. Rejection was proven by biopsy (n = 58), and stable transplant function was monitored for at least 2 years (n = 58). Postoperative urine samples were collected between 3rd and 10th day following transplantation. Urinary protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein identification and validation were performed using multiplex fluorescence 2DE, peptide mass fingerprinting and enzyme-linked immunosorbent assay. A protein profile including four mass peaks differentiated acute rejection from stable transplants at the time point of rejection and at the postoperative state with 73 % sensitivity and 88 % specificity. Alpha-1-microglobulin (A1MG) and Haptoglobin (Hp) were identified as putative rejection biomarkers. Protein levels were significantly higher in postoperative urine from patients with rejection (A1MG 29.13 vs. 22.06 μg/ml, p = 0.001; Hp 628.34 vs. 248.57 ng/ml, p = 0.003). The combination of both proteins enabled the diagnosis of early rejection with 85 % sensitivity and 80 % specificity. Protein profiling using mass spectrometry is suitable for noninvasive detection of rejection-specific changes following kidney transplantation. A specific protein profile enables the prediction of early acute allograft rejection in the immediate postoperative period. A1MG and Hp appear to be reliable rejection biomarkers.

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

PubMed Central

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

The quest for fragile X biomarkers.

PubMed

Westmark, Cara J

2014-12-01

Fragile X is the most common form of inherited intellectual disability and the leading known genetic cause of autism. There is currently no cure or approved medication for fragile X although various drugs target specific disease symptoms and a large number of therapeutics are in various stages of clinical development. Multiple recent clinical trials have failed on their primary endpoints indicating that there is a compelling need for validated biomarkers and outcome measures in fragile X. There are currently no validated blood-based biomarkers to assess disease severity or to monitor drug efficacy in fragile X syndrome. Herein, we review candidate blood protein biomarkers including extracellular-regulated kinase, phosphoinositide 3-kinase, matrix metalloproteinase 9, amyloid-beta and amyloid-beta protein precursor. Bench-to-bedside plans for fragile X syndrome are severely limited by the lack of validated outcome measures. The reviewed candidate biomarkers are at early stages of validation and deserve further investigation.

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids

PubMed Central

2014-01-01

Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cancer’ in conjunction with 14 separate ‘biofluids’ (bile, blood, breastmilk, cerebrospinal fluid, mucus, plasma, saliva, semen, serum, synovial fluid, stool, sweat, tears, and urine), while a negative set of abstracts was defined by the terms ‘(biofluid) NOT breast cancer’ or ‘(biofluid) NOT lung cancer.’ More than 5.3 million total abstracts were obtained from PubMed and examined for biomarker-disease-biofluid associations (34,296 positive and 2,653,396 negative for breast cancer; 28,355 positive and 2,595,034 negative for lung cancer). Biological entities such as genes and proteins were tagged using ABNER, and processed using Python scripts to produce a list of putative biomarkers. Z-scores were calculated, ranked, and used to determine significance of putative biomarkers found. Manual verification of relevant abstracts was performed to assess our method’s performance. Results Biofluid-specific markers were identified from the literature, assigned relevance scores based on frequency of occurrence, and validated using known biomarker lists and/or databases for lung and breast cancer [NCBI’s On-line Mendelian Inheritance in Man (OMIM), Cancer Gene annotation server for cancer genomics (CAGE), NCBI’s Genes & Disease, NCI’s Early Detection Research Network (EDRN), and others]. The specificity of each marker for a given biofluid was calculated, and the performance of our semi-automated literature mining method assessed for breast and lung cancer

Microbiome Networks: A Systems Framework for Identifying Candidate Microbial Assemblages for Disease Management.

PubMed

Poudel, R; Jumpponen, A; Schlatter, D C; Paulitz, T C; Gardener, B B McSpadden; Kinkel, L L; Garrett, K A

2016-10-01

Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. "General network analysis" identifies candidate taxa for maintaining an existing microbial community. "Host-focused analysis" includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. "Pathogen-focused analysis" identifies taxa with direct or indirect associations with taxa known a priori as pathogens. "Disease-focused analysis" identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

Identifying positive selection candidate loci for high-altitude adaptation in Andean populations

PubMed Central

2009-01-01

High-altitude environments (>2,500 m) provide scientists with a natural laboratory to study the physiological and genetic effects of low ambient oxygen tension on human populations. One approach to understanding how life at high altitude has affected human metabolism is to survey genome-wide datasets for signatures of natural selection. In this work, we report on a study to identify selection-nominated candidate genes involved in adaptation to hypoxia in one highland group, Andeans from the South American Altiplano. We analysed dense microarray genotype data using four test statistics that detect departures from neutrality. Using a candidate gene, single nucleotide polymorphism-based approach, we identified genes exhibiting preliminary evidence of recent genetic adaptation in this population. These included genes that are part of the hypoxia-inducible transcription factor (HIF) pathway, a biochemical pathway involved in oxygen homeostasis, as well as three other genomic regions previously not known to be associated with high-altitude phenotypes. In addition to identifying selection-nominated candidate genes, we also tested whether the HIF pathway shows evidence of natural selection. Our results indicate that the genes of this biochemical pathway as a group show no evidence of having evolved in response to hypoxia in Andeans. Results from particular HIF-targeted genes, however, suggest that genes in this pathway could play a role in Andean adaptation to high altitude, even if the pathway as a whole does not show higher relative rates of evolution. These data suggest a genetic role in high-altitude adaptation and provide a basis for genotype/phenotype association studies that are necessary to confirm the role of putative natural selection candidate genes and gene regions in adaptation to altitude. PMID:20038496

Potential biomarkers in psychiatry: focus on the cholesterol system

PubMed Central

Woods, Alisa G; Sokolowska, Izabela; Taurines, Regina; Gerlach, Manfred; Dudley, Edward; Thome, Johannes; Darie, Costel C

2012-01-01

Abstract Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders. PMID:22304330

Identification of multiple novel protein biomarkers shed by human serous ovarian tumors into the blood of immunocompromised mice and verified in patient sera.

PubMed

Beer, Lynn A; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples.

Identification of Multiple Novel Protein Biomarkers Shed by Human Serous Ovarian Tumors into the Blood of Immunocompromised Mice and Verified in Patient Sera

PubMed Central

Beer, Lynn A.; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples. PMID:23544127

Use of ProteinChip technology for identifying biomarkers of parasitic diseases: the example of porcine cysticercosis (Taenia solium).

PubMed

Deckers, N; Dorny, P; Kanobana, K; Vercruysse, J; Gonzalez, A E; Ward, B; Ndao, M

2008-12-01

Taenia solium cysticercosis is a significant public health problem in endemic countries. The current serodiagnostic techniques are not able to differentiate between infections with viable cysts and infections with degenerated cysts. The objectives of this study were to identify specific novel biomarkers of these different disease stages in the serum of experimentally infected pigs using ProteinChip technology (Bio-Rad) and to validate these biomarkers by analyzing serum samples from naturally infected pigs. In the experimental sample set 30 discriminating biomarkers (p<0.05) were found, 13 specific for the viable phenotype, 9 specific for the degenerated phenotype and 8 specific for the infected phenotype (either viable or degenerated cysts). Only 3 of these biomarkers were also significant in the field samples; however, the peak profiles were not consistent among the two sample sets. Five biomarkers discovered in the sera from experimentally infected pigs were identified as clusterin, lecithin-cholesterol acyltransferase, vitronectin, haptoglobin and apolipoprotein A-I.

Classification of Genes and Putative Biomarker Identification Using Distribution Metrics on Expression Profiles

PubMed Central

Huang, Hung-Chung; Jupiter, Daniel; VanBuren, Vincent

2010-01-01

Background Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. Methodology/Principal Findings In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. Conclusions/Significance The methodology employed here may be used to facilitate disease-specific biomarker discovery. PMID:20140228

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

PubMed

Marimuthu, Arivusudar; Chavan, Sandip; Sathe, Gajanan; Sahasrabuddhe, Nandini A; Srikanth, Srinivas M; Renuse, Santosh; Ahmad, Sartaj; Radhakrishnan, Aneesha; Barbhuiya, Mustafa A; Kumar, Rekha V; Harsha, H C; Sidransky, David; Califano, Joseph; Pandey, Akhilesh; Chatterjee, Aditi

2013-11-01

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort.

PubMed

Kim, S; Swaminathan, S; Shen, L; Risacher, S L; Nho, K; Foroud, T; Shaw, L M; Trojanowski, J Q; Potkin, S G; Huentelman, M J; Craig, D W; DeChairo, B M; Aisen, P S; Petersen, R C; Weiner, M W; Saykin, A J

2011-01-04

CSF levels of Aβ1-42, t-tau, and p-tau181p are potential early diagnostic markers for probable Alzheimer disease (AD). The influence of genetic variation on these markers has been investigated for candidate genes but not on a genome-wide basis. We report a genome-wide association study (GWAS) of CSF biomarkers (Aβ1-42, t-tau, p-tau181p, p-tau181p/Aβ1-42, and t-tau/Aβ1-42). A total of 374 non-Hispanic Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative cohort with quality-controlled CSF and genotype data were included in this analysis. The main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed on each of 5 CSF biomarkers. The p values of all SNPs for each CSF biomarker were adjusted for multiple comparisons by the Bonferroni method. We focused on SNPs with corrected p<0.01 (uncorrected p<3.10×10(-8)) and secondarily examined SNPs with uncorrected p values less than 10(-5) to identify potential candidates. Four SNPs in the regions of the APOE, LOC100129500, TOMM40, and EPC2 genes reached genome-wide significance for associations with one or more CSF biomarkers. SNPs in CCDC134, ABCG2, SREBF2, and NFATC4, although not reaching genome-wide significance, were identified as potential candidates. In addition to known candidate genes, APOE, TOMM40, and one hypothetical gene LOC100129500 partially overlapping APOE; one novel gene, EPC2, and several other interesting genes were associated with CSF biomarkers that are related to AD. These findings, especially the new EPC2 results, require replication in independent cohorts.

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

Analysis of the ectoenzymes ADA, ALP, ENPP1, and ENPP3, in the contents of ovarian endometriomas as candidate biomarkers of endometriosis.

PubMed

Trapero, Carla; Jover, Lluis; Fernández-Montolí, Maria Eulàlia; García-Tejedor, Amparo; Vidal, August; Gómez de Aranda, Inmaculada; Ponce, Jordi; Matias-Guiu, Xavier; Martín-Satué, Mireia

2018-02-01

The diagnosis of endometriosis, a prevalent chronic disease with a strong inflammatory component, is usually delayed due to the lack of noninvasive diagnostic tests. Purinergic signaling, a key cell pathway, is altered in many inflammatory disorders. The aim of the present work was to evaluate the levels of adenosine deaminase (ADA), alkaline phosphatase (ALP), ecto-nucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), and ENPP3, elements of purinergic signaling, as biomarker candidates for endometriosis. A case-control comparative study was conducted to determine ADA, ALP, ENPP1 and ENPP3 levels in echo-guided aspirated fluids of endometriomas (case group) and simple ovarian cysts (control group) using the ELISA technique. Adenosine deaminase, ALP, ENPP1, and ENPP3 were present and quantifiable in the contents of endometriomas and simple cysts. There were significant differences in ADA and ENPP1 levels in endometriomas in comparison with simple cysts (2787 U/L and 103.9 ng/mL more in endometriomas, for ADA and ENPP1, respectively). Comparisons of ALP and ENPP3 levels between the two groups did not reveal significant differences. The ectoenzymes ADA and ENPP1 are biomarker candidates for endometriosis. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

CHROMOSPHERIC EMISSION OF PLANET CANDIDATE HOST STARS: A WAY TO IDENTIFY FALSE POSITIVES

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

Karoff, Christoffer; Knudsen, Mads Faurschou; Albrecht, Simon

2016-10-10

It has been hypothesized that the presence of closely orbiting giant planets is associated with enhanced chromospheric emission of their host stars. The main cause for such a relation would likely be enhanced dynamo action induced by the planet. We present measurements of chromospheric emission in 234 planet candidate systems from the Kepler mission. This ensemble includes 37 systems with giant-planet candidates, which show a clear emission enhancement. The enhancement, however, disappears when systems that are also identified as eclipsing binary candidates are removed from the ensemble. This suggests that a large fraction of the giant-planet candidate systems with chromosphericmore » emission stronger than the Sun are not giant-planet systems, but false positives. Such false-positive systems could be tidally interacting binaries with strong chromospheric emission. This hypothesis is supported by an analysis of 188 eclipsing binary candidates that show increasing chromospheric emission as function of decreasing orbital period.« less

Single nucleotide polymorphisms in multiple sclerosis: disease susceptibility and treatment response biomarkers.

PubMed

Pravica, Vera; Popadic, Dusan; Savic, Emina; Markovic, Milos; Drulovic, Jelena; Mostarica-Stojkovic, Marija

2012-04-01

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system characterized by unpredictable and variable clinical course. Etiology of MS involves both genetic and environmental factors. New technologies identified genetic polymorphisms associated with MS susceptibility among which immunologically relevant genes are significantly overrepresented. Although individual genes contribute only a small part to MS susceptibility, they might be used as biomarkers, thus helping to identify accurate diagnosis, predict clinical disease course and response to therapy. This review focuses on recent progress in research on MS genetics with special emphasis on the possibility to use single nucleotide polymorphism of candidate genes as biomarkers of susceptibility to disease and response to therapy.

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome—a prospective multicentre biomarker study conducted in the Netherlands

PubMed Central

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-01-01

Purpose Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such ‘vulnerable periods’. Participants BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. Methods and analysis We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate ‘vulnerable periods’ during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case–cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Future plans and dissemination Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and

Experimental Design in Clinical 'Omics Biomarker Discovery.

PubMed

Forshed, Jenny

2017-11-03

This tutorial highlights some issues in the experimental design of clinical 'omics biomarker discovery, how to avoid bias and get as true quantities as possible from biochemical analyses, and how to select samples to improve the chance of answering the clinical question at issue. This includes the importance of defining clinical aim and end point, knowing the variability in the results, randomization of samples, sample size, statistical power, and how to avoid confounding factors by including clinical data in the sample selection, that is, how to avoid unpleasant surprises at the point of statistical analysis. The aim of this Tutorial is to help translational clinical and preclinical biomarker candidate research and to improve the validity and potential of future biomarker candidate findings.

Stool-based biomarkers of interstitial cystitis/bladder pain syndrome.

PubMed

Braundmeier-Fleming, A; Russell, Nathan T; Yang, Wenbin; Nas, Megan Y; Yaggie, Ryan E; Berry, Matthew; Bachrach, Laurie; Flury, Sarah C; Marko, Darlene S; Bushell, Colleen B; Welge, Michael E; White, Bryan A; Schaeffer, Anthony J; Klumpp, David J

2016-05-18

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Operational taxonomic units (OTUs) were identified by16S rDNA sequence analysis. Machine learning by Extended Random Forest (ERF) identified OTUs associated with symptom scores. Quantitative PCR of stool DNA with species-specific primer pairs demonstrated significantly reduced levels of E. sinensis, C. aerofaciens, F. prausnitzii, O. splanchnicus, and L. longoviformis in microbiota of IC patients. These species, deficient in IC pelvic pain (DIPP), were further evaluated by Receiver-operator characteristic (ROC) analyses, and DIPP species emerged as potential IC biomarkers. Stool metabolomic studies identified glyceraldehyde as significantly elevated in IC. Metabolomic pathway analysis identified lipid pathways, consistent with predicted metagenome functionality. Together, these findings suggest that DIPP species and metabolites may serve as candidates for novel IC biomarkers in stool. Functional changes in the IC microbiome may also serve as therapeutic targets for treating chronic pelvic pain.

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review

PubMed Central

Sima, Chao; Amundson, Sally A.; Zenhausern, Frederic

2018-01-01

Purpose To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry. Methods Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability. Results 24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker. Conclusion Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results. PMID:29879226

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

PubMed

Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

2018-05-15

Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

Temporal Patterns of Novel Circulating Biomarkers in IL-2-mediated Vascular Injury in the Rat.

PubMed

Keirstead, Natalie D; Bertinetti-Lapatki, Cristina; Knapp, Denise; Albassam, Mudher; Hughes, Valerie; Hong, Feng; Roth, Adrian B; Mikaelian, Igor

2015-10-01

Recombinant interleukin-2 (rIL-2) administration in oncology indications is hampered by vascular toxicity, which presents as a vascular leak syndrome. We used this aspect of the toxicity of rIL-2 to evaluate candidate biomarkers of drug-induced vascular injury (DIVI) in rats given 0.36 mg/kg rIL-2 daily. Groups of rats were given either 2 or 5 doses of rIL-2 or 5 doses of rIL-2 followed by a 7-day recovery. The histomorphologic lexicon and grading scheme developed by the Vascular Injury Working Group of the Predictive Safety Testing Consortium of the Critical Path Institute were utilized to enable semiquantitative integration with circulating biomarker levels. The administration of rIL-2 was associated with time-dependent endothelial cell hyperplasia and hypertrophy and perivascular inflammation that correlated with increases in circulating angiopoietin-2, lipocalin-2, monocyte chemotactic protein-1, tissue inhibitor of metalloproteinase-1, vascular endothelial growth factor A, E-selectin, and chemokine (C-X-C motif) ligand-1, and the microRNAs miR-21, miR-132, and miR-155. The dose groups were differentially identified by panels comprising novel candidate biomarkers and traditional hematologic parameters. These results identify biomarkers of the early stages of DIVI prior to the onset of vascular smooth muscle necrosis. © 2015 by The Author(s).

Non-invasive detection of candidate pregnancy protein biomarkers in the feces of captive polar bears (Ursus maritimus).

PubMed

Curry, E; Stoops, M A; Roth, T L

2012-07-15

Currently, there is no method of accurately and non-invasively diagnosing pregnancy in polar bears. Specific proteins may exhibit altered profiles in the feces of pregnant bears, but predicting appropriate candidate proteins to investigate is speculative at best. The objective of this study was to identify potential pregnancy biomarker proteins based on their increased abundance in the feces of pregnant polar bears compared to pseudopregnant females (controls) using two-dimensional in-gel electrophoresis (2D-DIGE) and mass spectrometry (MS). Three 2D-DIGE gels were performed to evaluate fecal protein profiles from controls (n=3) and pregnant polar bears (n=3). There were 2224.67±52.39 (mean±SEM) spots resolved per gel. Of these, only five proteins were elevated in the pregnant group (P<0.05), and seven additional spots tended to be higher (0.0599.9% confidence interval. The 11 spots represented seven distinct proteins, five of which were significantly more abundant in the pregnant group: IgGFc-binding protein, filamin-C, carboxypeptidase B, transthyretin, and immunoglobulin heavy chain variable region. To our knowledge, this was the first study that employed 2D-DIGE to identify differentially expressed proteins in fecal samples to characterize a physiological condition other than those related to gastrointestinal disorders. These promising results provided a strong foundation for ensuing efforts to develop a non-invasive pregnancy assay for use in both captive and wild polar bears. Copyright © 2012 Elsevier Inc. All rights reserved.

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Current advances in biomarkers for targeted therapy in triple-negative breast cancer

PubMed Central

Fleisher, Brett; Clarke, Charlotte; Ait-Oudhia, Sihem

2016-01-01

Triple-negative breast cancer (TNBC) is a complex heterogeneous disease characterized by the absence of three hallmark receptors: human epidermal growth factor receptor 2, estrogen receptor, and progesterone receptor. Compared to other breast cancer subtypes, TNBC is more aggressive, has a higher prevalence in African-Americans, and more frequently affects younger patients. Currently, TNBC lacks clinically accepted targets for tailored therapy, warranting the need for candidate biomarkers. BiomarkerBase, an online platform used to find biomarkers reported in clinical trials, was utilized to screen all potential biomarkers for TNBC and select only the ones registered in completed TNBC trials through clinicaltrials.gov. The selected candidate biomarkers were classified as surrogate, prognostic, predictive, or pharmacodynamic (PD) and organized by location in the blood, on the cell surface, in the cytoplasm, or in the nucleus. Blood biomarkers include vascular endothelial growth factor/vascular endothelial growth factor receptor and interleukin-8 (IL-8); cell surface biomarkers include EGFR, insulin-like growth factor binding protein, c-Kit, c-Met, and PD-L1; cytoplasm biomarkers include PIK3CA, pAKT/S6/p4E-BP1, PTEN, ALDH1, and the PIK3CA/AKT/mTOR-related metabolites; and nucleus biomarkers include BRCA1, the gluco-corticoid receptor, TP53, and Ki67. Candidate biomarkers were further organized into a “cellular protein network” that demonstrates potential connectivity. This review provides an inventory and reference point for promising biomarkers for breakthrough targeted therapies in TNBC. PMID:27785100

Comparison of Protein Immunoprecipitation-Multiple Reaction Monitoring with ELISA for Assay of Biomarker Candidates in Plasma

PubMed Central

2013-01-01

Quantitative analysis of protein biomarkers in plasma is typically done by ELISA, but this method is limited by the availability of high-quality antibodies. An alternative approach is protein immunoprecipitation combined with multiple reaction monitoring mass spectrometry (IP-MRM). We compared IP-MRM to ELISA for the analysis of six colon cancer biomarker candidates (metalloproteinase inhibitor 1 (TIMP1), cartilage oligomeric matrix protein (COMP), thrombospondin-2 (THBS2), endoglin (ENG), mesothelin (MSLN) and matrix metalloproteinase-9 (MMP9)) in plasma from colon cancer patients and noncancer controls. Proteins were analyzed by multiplex immunoprecipitation from plasma with the ELISA capture antibodies, further purified by SDS-PAGE, digested and analyzed by stable isotope dilution MRM. IP-MRM provided linear responses (r = 0.978–0.995) between 10 and 640 ng/mL for the target proteins spiked into a “mock plasma” matrix consisting of 60 mg/mL bovine serum albumin. Measurement variation (coefficient of variation at the limit of detection) for IP-MRM assays ranged from 2.3 to 19%, which was similar to variation for ELISAs of the same samples. IP-MRM and ELISA measurements for all target proteins except ENG were highly correlated (r = 0.67–0.97). IP-MRM with high-quality capture antibodies thus provides an effective alternative method to ELISA for protein quantitation in biological fluids. PMID:24224610

Emerging biomarkers for cancer immunotherapy in melanoma.

PubMed

Axelrod, Margaret L; Johnson, Douglas B; Balko, Justin M

2017-09-14

The treatment and prognosis of metastatic melanoma has changed substantially since the advent of novel immune checkpoint inhibitors (ICI), agents that enhance the anti-tumor immune response. Despite the success of these agents, clinically actionable biomarkers to aid patient and regimen selection are lacking. Herein, we summarize and review the evidence for candidate biomarkers of response to ICIs in melanoma. Many of these candidates can be examined as parts of a known molecular pathway of immune response, while others are clinical in nature. Due to the ability of ICIs to illicit dramatic and durable responses, well-validated biomarkers that can be effectively implemented in the clinic will require strong negative predictive values that do not limit patients with who may benefit from ICI therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

PubMed

Li, Jun; Roebuck, Paul; Grünewald, Stefan; Liang, Han

2012-07-01

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.

Wound outcome in combat injuries is associated with a unique set of protein biomarkers

PubMed Central

2013-01-01

Background The ability to forecast whether a wound will heal after closure without further debridement(s), would provide substantial benefits to patients with severe extremity trauma. Methods Wound effluent is a readily available material which can be collected without disturbing healthy tissue. For analysis of potential host response biomarkers, forty four serial combat wound effluent samples from 19 patients with either healing or failing traumatic- and other combat-related wounds were examined by 2-D DIGE. Spot map patterns were correlated to eventual wound outcome (healed or wound failure) and analyzed using DeCyder 7.0 and differential proteins identified via LC-MS/MS. Results This approach identified 52 protein spots that were differentially expressed and thus represent candidate biomarkers for this clinical application. Many of these proteins are intimately involved in inflammatory and immune responses. Furthermore, discriminate analysis further refined the 52 differential protein spots to a smaller subset of which successfully differentiate between wounds that will heal and those that will fail and require further surgical intervention with greater than 83% accuracy. Conclusion These results suggest candidates for a panel of protein biomarkers that may aid traumatic wound care prognosis and treatment. We recommend that this strategy be refined, and then externally validated, in future studies of traumatic wounds. PMID:24192341

Biomarkers of delirium as a clue to diagnosis and pathogenesis of Wernicke-Korsakoff syndrome.

PubMed

Wijnia, J W; Oudman, E

2013-12-01

Wernicke's encephalopathy (WE) and Korsakoff's syndrome are considered to be different stages of the same disorder due to thiamine deficiency, which is called Wernicke-Korsakoff syndrome (WKS). The earliest biochemical change is the decrease of α-ketoglutarate-dehydrogenase activity in astrocytes. According to autopsy-based series, mental status changes are present in 82% of WE cases. The objective of the present review is to identify possible underlying mechanisms relating the occurrence of delirium to WKS. Studies involving delirium in WKS, however, are rare. Therefore, first, a search was done for candidate biomarkers of delirium irrespective of the clinical setting. Secondly, the results were focused on identification of these biomarkers in reports on WKS. In various settings, 10 biochemical and/or genetic biomarkers showed strong associations with the occurrence of delirium. For WKS three of these candidate biomarkers were identified, namely brain tissue cell counts of CD68 positive cells as a marker of microglial activation, high cerebrospinal fluid lactate levels, and MHPG, a metabolite of norepinephrine. Based on current literature, markers of microglial activation may present an interesting patho-etiological relationship between thiamine deficiency and delirium in WKS. In WKS cases, changes in astroglia and microglial proliferation were reported. The possible loss-of-function mechanisms following thiamine deficiency in WKS are proposed to come from microglial activation, resulting in a delirium in the initial phase of WKS. © 2013 The Author(s) European Journal of Neurology © 2013 EFNS.

Identification of Unique Blood and Urine Biomarkers in Influenza Virus and Staphylococcus aureus Co-infection: A Preliminary Study.

PubMed

Prescott, Meagan A; Pastey, Manoj K

2010-12-05

Each year, there are estimated to be approximately 200,000 hospitalizations and 36,000 deaths due to influenza in the United States. Reports have indicated that most deaths are not directly due to influenza virus, but to secondary bacterial pneumonia, predominantly staphylococcal in origin. Here we identify the presence of candidate blood and urine biomarkers in mice with Staphyococcus aureus and influenza virus co-infection. In this pilot study, mice were grouped into four treatments: co-infected with influenza virus and S. aureus, singly infected with influenza virus or S. aureus, and a control group of uninfected mice (PBS treated). Gene expression changes were identified by DNA-microarrays from blood samples taken at day five post infection. Proteomic changes were obtained from urine samples collected at three and five days post infection using 2-D DIGE followed by protein ID by mass spectrometry. Differentially expressed genes and/or proteins were identified as candidate biomarkers for future validation in larger studies.

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome-a prospective multicentre biomarker study conducted in the Netherlands.

PubMed

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-12-23

Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such 'vulnerable periods'. BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate 'vulnerable periods' during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case-cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and conference presentations is expected from the third quarter of 2016. Should

Normalization of Patient-Identified Plasma Biomarkers in SMNΔ7 Mice following Postnatal SMN Restoration

PubMed Central

Arnold, W. David; Duque, Sandra; Iyer, Chitra C.; Zaworski, Phillip; McGovern, Vicki L.; Taylor, Shannon J.; von Herrmann, Katharine M.; Kobayashi, Dione T.; Chen, Karen S.; Kolb, Stephen J.; Paushkin, Sergey V.; Burghes, Arthur H. M.

2016-01-01

Introduction and Objective Spinal muscular atrophy (SMA) is an autosomal recessive motor neuron disorder. SMA is caused by homozygous loss of the SMN1 gene and retention of the SMN2 gene resulting in reduced levels of full length SMN protein that are insufficient for motor neuron function. Various treatments that restore levels of SMN are currently in clinical trials and biomarkers are needed to determine the response to treatment. Here, we sought to investigate in SMA mice a set of plasma analytes, previously identified in patients with SMA to correlate with motor function. The goal was to determine whether levels of plasma markers were altered in the SMNΔ7 mouse model of SMA and whether postnatal SMN restoration resulted in normalization of the biomarkers. Methods SMNΔ7 and control mice were treated with antisense oligonucleotides (ASO) targeting ISS-N1 to increase SMN protein from SMN2 or scramble ASO (sham treatment) via intracerebroventricular injection on postnatal day 1 (P1). Brain, spinal cord, quadriceps muscle, and liver were analyzed for SMN protein levels at P12 and P90. Ten plasma biomarkers (a subset of biomarkers in the SMA-MAP panel available for analysis in mice) were analyzed in plasma obtained at P12, P30, and P90. Results Of the eight plasma biomarkers assessed, 5 were significantly changed in sham treated SMNΔ7 mice compared to control mice and were normalized in SMNΔ7 mice treated with ASO. Conclusion This study defines a subset of the SMA-MAP plasma biomarker panel that is abnormal in the most commonly used mouse model of SMA. Furthermore, some of these markers are responsive to postnatal SMN restoration. These findings support continued clinical development of these potential prognostic and pharmacodynamic biomarkers. PMID:27907033

Derivation and Validation of a Serum Biomarker Panel to Identify Infants With Acute Intracranial Hemorrhage.

PubMed

Berger, Rachel Pardes; Pak, Brian J; Kolesnikova, Mariya D; Fromkin, Janet; Saladino, Richard; Herman, Bruce E; Pierce, Mary Clyde; Englert, David; Smith, Paul T; Kochanek, Patrick M

2017-06-05

Abusive head trauma is the leading cause of death from physical abuse. Missing the diagnosis of abusive head trauma, particularly in its mild form, is common and contributes to increased morbidity and mortality. Serum biomarkers may have potential as quantitative point-of-care screening tools to alert physicians to the possibility of intracranial hemorrhage. To identify and validate a set of biomarkers that could be the basis of a multivariable model to identify intracranial hemorrhage in well-appearing infants using the Ziplex System. Binary logistic regression was used to develop a multivariable model incorporating 3 serum biomarkers (matrix metallopeptidase-9, neuron-specific enolase, and vascular cellular adhesion molecule-1) and 1 clinical variable (total hemoglobin). The model was then prospectively validated. Multiplex biomarker measurements were performed using Flow-Thru microarray technology on the Ziplex System, which has potential as a point-of-care system. The model was tested at 3 pediatric emergency departments in level I pediatric trauma centers (Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Primary Children's Hospital, Salt Lake City, Utah; and Lurie Children's Hospital, Chicago, Illinois) among well-appearing infants who presented for care owing to symptoms that placed them at increased risk of abusive head trauma. The study took place from November 2006 to April 2014 at Children's Hospital of Pittsburgh, June 2010 to August 2013 at Primary Children's Hospital, and January 2011 to August 2013 at Lurie Children's Hospital. A mathematical model that can predict acute intracranial hemorrhage in infants at increased risk of abusive head trauma. The multivariable model, Biomarkers for Infant Brain Injury Score, was applied prospectively to 599 patients. The mean (SD) age was 4.7 (3.1) months. Fifty-two percent were boys, 78% were white, and 8% were Hispanic. At a cutoff of 0.182, the model was 89

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed Central

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-01-01

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-09-28

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

Combined semi-empirical screening and design of experiments (DOE) approach to identify candidate formulations of a lyophilized live attenuated tetravalent viral vaccine candidate.

PubMed

Patel, Ashaben; Erb, Steven M; Strange, Linda; Shukla, Ravi S; Kumru, Ozan S; Smith, Lee; Nelson, Paul; Joshi, Sangeeta B; Livengood, Jill A; Volkin, David B

2018-05-24

A combination experimental approach, utilizing semi-empirical excipient screening followed by statistical modeling using design of experiments (DOE), was undertaken to identify stabilizing candidate formulations for a lyophilized live attenuated Flavivirus vaccine candidate. Various potential pharmaceutical compounds used in either marketed or investigative live attenuated viral vaccine formulations were first identified. The ability of additives from different categories of excipients, either alone or in combination, were then evaluated for their ability to stabilize virus against freeze-thaw, freeze-drying, and accelerated storage (25°C) stresses by measuring infectious virus titer. An exploratory data analysis and predictive DOE modeling approach was subsequently undertaken to gain a better understanding of the interplay between the key excipients and stability of virus as well as to determine which combinations were interacting to improve virus stability. The lead excipient combinations were identified and tested for stabilizing effects using a tetravalent mixture of viruses in accelerated and real time (2-8°C) stability studies. This work demonstrates the utility of combining semi-empirical excipient screening and DOE experimental design strategies in the formulation development of lyophilized live attenuated viral vaccine candidates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Eliciting, Identifying, Interpreting, and Responding to Students' Ideas: Teacher Candidates' Growth in Formative Assessment Practices

NASA Astrophysics Data System (ADS)

Gotwals, Amelia Wenk; Birmingham, Daniel

2016-06-01

With the goal of helping teacher candidates become well-started beginners, it is important that methods courses in teacher education programs focus on high-leverage practices. Using responsive teaching practices, specifically eliciting, identifying, interpreting, and responding to students' science ideas (i.e., formative assessment), can be used to support all students in learning science successfully. This study follows seven secondary science teacher candidates in a yearlong practice-based methods course. Course assignments (i.e., plans for and reflections on teaching) as well as teaching videos were analyzed using a recursive qualitative approach. In this paper, we present themes and patterns in teacher candidates' abilities to elicit, identify, interpret, and respond to students' ideas. Specifically, we found that those teacher candidates who grew in the ways in which they elicited students' ideas from fall to spring were also those who were able to adopt a more balanced reflection approach (considering both teacher and student moves). However, we found that even the teacher candidates who grew in these practices did not move toward seeing students' ideas as nuanced; rather, they saw students' ideas in a dichotomous fashion: right or wrong. We discuss implications for teacher preparation, specifically for how to promote productive reflection and tools for better understanding students' ideas.

Bladder Cancer-associated Protein, a Potential Prognostic Biomarker in Human Bladder Cancer*

PubMed Central

Moreira, José M. A.; Ohlsson, Gita; Gromov, Pavel; Simon, Ronald; Sauter, Guido; Celis, Julio E.; Gromova, Irina

2010-01-01

It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported several candidate biomarker proteins that are deregulated in bladder cancer. Following the conceptual biomarker development phases proposed by the Early Detection Research Network, we have taken some of the most promising candidate proteins into postdiscovery validation studies, and here we report on the characterization of one such biomarker, the bladder cancer-associated protein (BLCAP), formerly termed Bc10. To characterize BLCAP protein expression and cellular localization patterns in benign bladder urothelium and urothelial carcinomas (UCs), we used two independent sets of samples from different patient cohorts: a reference set consisting of 120 bladder specimens (formalin-fixed as well as frozen biopsies) and a validation set consisting of 2,108 retrospectively collected UCs with long term clinical follow-up. We could categorize the UCs examined into four groups based on levels of expression and subcellular localization of BLCAP protein and showed that loss of BLCAP expression is associated with tumor progression. The results indicated that increased expression of this protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Finally, we applied a combinatorial two-marker discriminator using BLCAP and adipocyte-type fatty acid-binding protein, another UC biomarker previously reported by us, and found that the combination of the two markers correlated more closely with grade and/or stage of

Biomarkers for Alzheimer's disease: academic, industry and regulatory perspectives.

PubMed

Hampel, Harald; Frank, Richard; Broich, Karl; Teipel, Stefan J; Katz, Russell G; Hardy, John; Herholz, Karl; Bokde, Arun L W; Jessen, Frank; Hoessler, Yvonne C; Sanhai, Wendy R; Zetterberg, Henrik; Woodcock, Janet; Blennow, Kaj

2010-07-01

Advances in therapeutic strategies for Alzheimer's disease that lead to even small delays in onset and progression of the condition would significantly reduce the global burden of the disease. To effectively test compounds for Alzheimer's disease and bring therapy to individuals as early as possible there is an urgent need for collaboration between academic institutions, industry and regulatory organizations for the establishment of standards and networks for the identification and qualification of biological marker candidates. Biomarkers are needed to monitor drug safety, to identify individuals who are most likely to respond to specific treatments, to stratify presymptomatic patients and to quantify the benefits of treatments. Biomarkers that achieve these characteristics should enable objective business decisions in portfolio management and facilitate regulatory approval of new therapies.

Current status of predictive biomarkers for neoadjuvant therapy in esophageal cancer

PubMed Central

Uemura, Norihisa; Kondo, Tadashi

2014-01-01

Neoadjuvant therapy has been proven to be extremely valuable and is widely used for advanced esophageal cancer. However, a significant proportion of treated patients (60%-70%) does not respond well to neoadjuvant treatments and develop severe adverse effects. Therefore, predictive markers for individualization of multimodality treatments are urgently needed in esophageal cancer. Recently, molecular biomarkers that predict the response to neoadjuvant therapy have been explored in multimodal approaches in esophageal cancer and successful examples of biomarker identification have been reported. In this review, promising candidates for predictive molecular biomarkers developed by using multiple molecular approaches are reviewed. Moreover, treatment strategies based on the status of predicted biomarkers are discussed, while considering the international differences in the clinical background. However, in the absence of adequate treatment options related to the results of the biomarker test, the usefulness of these diagnostic tools is limited and new effective therapies for biomarker-identified nonresponders to cancer treatment should be concurrent with the progress of predictive technologies. Further improvement in the prognosis of esophageal cancer patients can be achieved through the introduction of novel therapeutic approaches in clinical practice. PMID:25133032

Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.

CNS Injury: Posttranslational Modification of the Tau Protein as a Biomarker.

PubMed

Caprelli, Mitchell T; Mothe, Andrea J; Tator, Charles H

2017-11-01

The ideal biomarker for central nervous system (CNS) trauma in patients would be a molecular marker specific for injured nervous tissue that would provide a consistent and reliable assessment of the presence and severity of injury and the prognosis for recovery. One candidate biomarker is the protein tau, a microtubule-associated protein abundant in the axonal compartment of CNS neurons. Following axonal injury, tau becomes modified primarily by hyperphosphorylation of its various amino acid residues and cleavage into smaller fragments. These posttrauma products can leak into the cerebrospinal fluid or bloodstream and become candidate biomarkers of CNS injury. This review examines the primary molecular changes that tau undergoes following traumatic brain injury and spinal cord injury, and reviews the current literature in traumatic CNS biomarker research with a focus on the potential for hyperphosphorylated and cleaved tau as sensitive biomarkers of injury.

Molecular biomarkers for grass pollen immunotherapy

PubMed Central

Popescu, Florin-Dan

2014-01-01

Grass pollen allergy represents a significant cause of allergic morbidity worldwide. Component-resolved diagnosis biomarkers are increasingly used in allergy practice in order to evaluate the sensitization to grass pollen allergens, allowing the clinician to confirm genuine sensitization to the corresponding allergen plant sources and supporting an accurate prescription of allergy immunotherapy (AIT), an important approach in many regions of the world with great plant biodiversity and/or where pollen seasons may overlap. The search for candidate predictive biomarkers for grass pollen immunotherapy (tolerogenic dendritic cells and regulatory T cells biomarkers, serum blocking antibodies biomarkers, especially functional ones, immune activation and immune tolerance soluble biomarkers and apoptosis biomarkers) opens new opportunities for the early detection of clinical responders for AIT, for the follow-up of these patients and for the development of new allergy vaccines. PMID:25237628

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

ALS Biomarkers for Therapy Development: State of the Field & Future Directions

PubMed Central

Benatar, Michael; Boylan, Kevin; Jeromin, Andreas; Rutkove, Seward B.; Berry, James; Atassi, Nazem; Bruijn, Lucie

2015-01-01

Biomarkers have become the focus of intense research in the field of amyotrophic lateral sclerosis (ALS), with the hope that they might aid therapy development efforts. Notwithstanding the discovery of many candidate biomarkers, none have yet emerged as validated tools for drug development. In this review we present a nuanced view of biomarkers based on the perspective of the FDA; highlight the distinction between discovery and validation; describe existing and emerging resources; review leading biological fluid-based, electrophysiological and neuroimaging candidates relevant to therapy development efforts; discuss lessons learned from biomarker initiatives in related neurodegenerative diseases; and outline specific steps that we, as a field, might take in order to hasten the development and validation of biomarkers that will prove useful in enhancing efforts to develop effective treatments for ALS patients. Most important among these perhaps is the proposal to establish a federated ALS Biomarker Consortium (ABC) in which all interested and willing stakeholders may participate with equal opportunity to contribute to the broader mission of biomarker development and validation. PMID:26574709

Identification of Dlk1-Dio3 imprinted gene cluster noncoding RNAs as novel candidate biomarkers for liver tumor promotion.

PubMed

Lempiäinen, Harri; Couttet, Philippe; Bolognani, Federico; Müller, Arne; Dubost, Valérie; Luisier, Raphaëlle; Del Rio Espinola, Alberto; Vitry, Veronique; Unterberger, Elif B; Thomson, John P; Treindl, Fridolin; Metzger, Ute; Wrzodek, Clemens; Hahne, Florian; Zollinger, Tulipan; Brasa, Sarah; Kalteis, Magdalena; Marcellin, Magali; Giudicelli, Fanny; Braeuning, Albert; Morawiec, Laurent; Zamurovic, Natasa; Längle, Ulrich; Scheer, Nico; Schübeler, Dirk; Goodman, Jay; Chibout, Salah-Dine; Marlowe, Jennifer; Theil, Diethilde; Heard, David J; Grenet, Olivier; Zell, Andreas; Templin, Markus F; Meehan, Richard R; Wolf, Roland C; Elcombe, Clifford R; Schwarz, Michael; Moulin, Pierre; Terranova, Rémi; Moggs, Jonathan G

2013-02-01

The molecular events during nongenotoxic carcinogenesis and their temporal order are poorly understood but thought to include long-lasting perturbations of gene expression. Here, we have investigated the temporal sequence of molecular and pathological perturbations at early stages of phenobarbital (PB) mediated liver tumor promotion in vivo. Molecular profiling (mRNA, microRNA [miRNA], DNA methylation, and proteins) of mouse liver during 13 weeks of PB treatment revealed progressive increases in hepatic expression of long noncoding RNAs and miRNAs originating from the Dlk1-Dio3 imprinted gene cluster, a locus that has recently been associated with stem cell pluripotency in mice and various neoplasms in humans. PB induction of the Dlk1-Dio3 cluster noncoding RNA (ncRNA) Meg3 was localized to glutamine synthetase-positive hypertrophic perivenous hepatocytes, suggesting a role for β-catenin signaling in the dysregulation of Dlk1-Dio3 ncRNAs. The carcinogenic relevance of Dlk1-Dio3 locus ncRNA induction was further supported by in vivo genetic dependence on constitutive androstane receptor and β-catenin pathways. Our data identify Dlk1-Dio3 ncRNAs as novel candidate early biomarkers for mouse liver tumor promotion and provide new opportunities for assessing the carcinogenic potential of novel compounds.

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

PubMed

Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

2012-11-02

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated

Identifying DNA Methylation Biomarkers for Non-Endoscopic Detection of Barrett’s Esophagus

PubMed Central

Moinova, Helen R.; LaFramboise, Thomas; Lutterbaugh, James D.; Chandar, Apoorva Krishna; Dumot, John; Faulx, Ashley; Brock, Wendy; De la Cruz Cabrera, Omar; Guda, Kishore; Barnholtz-Sloan, Jill S.; Iyer, Prasad G.; Canto, Marcia I.; Wang, Jean S.; Shaheen, Nicholas J.; Thota, Prashanti N.; Willis, Joseph E.; Chak, Amitabh; Markowitz, Sanford D.

2018-01-01

We report a biomarker-based non-endoscopic method for detecting Barrett’s esophagus (BE), based on detecting methylated DNAs retrieved via a swallowable balloon-based esophageal sampling device. BE is the precursor of, and a major recognized risk factor for, developing esophageal adenocarcinoma (EAC). Endoscopy, the current standard for BE detection, is not cost-effective for population screening. We performed genome-wide screening to ascertain regions targeted for recurrent aberrant cytosine methylation in BE, identifying high-frequency methylation within the CCNA1 locus. We tested CCNA1 DNA methylation as a BE biomarker in cytology brushings of the distal esophagus from 173 individuals with or without BE. CCNA1 DNA methylation demonstrated an area under the curve (AUC)=0.95 for discriminating BE-related metaplasia and neoplasia cases versus normal individuals, performing identically to methylation of VIM DNA, an established BE biomarker. When combined, the resulting two biomarker panel was 95% sensitive and 91% specific. These results were replicated in an independent validation cohort of 149 individuals, who were assayed using the same cutoff values for test positivity established in the training population. To progress toward non-endoscopic esophageal screening, we engineered a well-tolerated, swallowable, encapsulated balloon device able to selectively sample the distal esophagus within 5 minutes. In balloon samples from 86 individuals, tests of CCNA1 plus VIM DNA methylation detected BE metaplasia with 90.3% sensitivity and 91.7% specificity. Combining the balloon sampling device with molecular assays of CCNA1 plus VIM DNA methylation enables an efficient, well-tolerated, sensitive, and specific method of screening at-risk populations for BE. PMID:29343623

Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

PubMed Central

Zhang, Hui; Li, Tangxin; Zheng, Linqing

2017-01-01

Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on their unique regulatory abilities in the network structure of the conditional microRNA-mRNA network and their important functions. These findings were confirmed by literature verification and functional enrichment analysis. Future experimental validation is expected for the further investigation of their molecular mechanisms. PMID:29098014

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Bladder cancer biomarker discovery using global metabolomic profiling of urine.

PubMed

Wittmann, Bryan M; Stirdivant, Steven M; Mitchell, Matthew W; Wulff, Jacob E; McDunn, Jonathan E; Li, Zhen; Dennis-Barrie, Aphrihl; Neri, Bruce P; Milburn, Michael V; Lotan, Yair; Wolfert, Robert L

2014-01-01

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

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

PubMed

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

2010-07-15

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

Urinary vitamin D-binding protein, a novel biomarker for lupus nephritis, predicts the development of proteinuric flare.

PubMed

Go, D J; Lee, J Y; Kang, M J; Lee, E Y; Lee, E B; Yi, E C; Song, Y W

2018-01-01

Lupus nephritis (LN) is a major complication of systemic lupus erythematosus (SLE). Conventional biomarkers for assessing renal disease activity are imperfect in predicting clinical outcomes associated with LN. The aim of this study is to identify urinary protein biomarkers that reliably reflect the disease activity or predict clinical outcomes. A quantitative proteomic analysis was performed to identify protein biomarker candidates that can differentiate between SLE patients with and without LN. Selected biomarker candidates were further verified by enzyme-linked immunosorbent assay using urine samples from a larger cohort of SLE patients ( n = 121) to investigate their predictive values for LN activity measure. Furthermore, the association between urinary levels of a selected panel of potential biomarkers and prognosis of LN was assessed with a four-year follow-up study of renal outcomes. Urinary vitamin D-binding protein (VDBP), transthyretin (TTR), retinol binding protein 4 (RBP4), and prostaglandin D synthase (PTGDS) were significantly elevated in SLE patients with LN, especially in patients with active LN ( n = 21). Among them, VDBP well correlated with severity of proteinuria (rho = 0.661, p < 0.001) and renal SLE Disease Activity Index (renal SLEDAI) (rho = 0.520, p < 0.001). In the four-year follow-up, VDBP was a significant risk factor (hazard ratio 9.627, 95% confidence interval 1.698 to 54.571, p = 0.011) for the development of proteinuric flare in SLE patients without proteinuria ( n = 100) after adjustments for multiple confounders. Urinary VDBP correlated with proteinuria and renal SLEDAI, and predicted the development of proteinuria.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-08-26

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. This manuscript addresses the importance of distinguishing between protein homologs and isoforms when identifying and validating cancer biomarkers in plasma or serum. Specifically, it describes the use of targeted in-depth LC-MS/MS analysis to determine the members of two protein families, chloride intracellular channel (CLIC) and tropomyosin (TPM) proteins that are detectable in sera of ovarian cancer patients. It then establishes a multiplexed isoform- and homology-specific MRM assay to quantify all observed gene products in these two protein

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Identification of Granulocyte Colony-Stimulating Factor and Interleukin-6 as Candidate Biomarkers of CBLB502 Efficacy as a Medical Radiation Countermeasure

PubMed Central

Krivokrysenko, Vadim I.; Shakhov, Alexander N.; Singh, Vijay K.; Bone, Frederick; Kononov, Yevgeniy; Shyshynova, Inna; Cheney, Alec; Maitra, Ratan K.; Purmal, Andrei; Whitnall, Mark H.; Feinstein, Elena

2012-01-01

Given an ever-increasing risk of nuclear and radiological emergencies, there is a critical need for development of medical radiation countermeasures (MRCs) that are safe, easily administered, and effective in preventing and/or mitigating the potentially lethal tissue damage caused by acute high-dose radiation exposure. Because the efficacy of MRCs for this indication cannot be ethically tested in humans, development of such drugs is guided by the Food and Drug Administration's Animal Efficacy Rule. According to this rule, human efficacious doses can be projected from experimentally established animal efficacious doses based on the equivalence of the drug's effects on efficacy biomarkers in the respective species. Therefore, identification of efficacy biomarkers is critically important for drug development under the Animal Efficacy Rule. CBLB502 is a truncated derivative of the Salmonella flagellin protein that acts by triggering Toll-like receptor 5 (TLR5) signaling and is currently under development as a MRC. Here, we report identification of two cytokines, granulocyte colony-stimulating factor (G-CSF) and interleukin-6 (IL-6), as candidate biomarkers of CBLB502's radioprotective/mitigative efficacy. Induction of both G-CSF and IL-6 by CBLB502 1) is strictly TLR5-dependent, 2) occurs in a CBLB502 dose-dependent manner within its efficacious dose range in both nonirradiated and irradiated mammals, including nonhuman primates, and 3) is critically important for the ability of CBLB502 to rescue irradiated animals from death. After evaluation of CBLB502 effects on G-CSF and IL-6 levels in humans, these biomarkers will be useful for accurate prediction of human efficacious CBLB502 doses, a key step in the development of this prospective radiation countermeasure. PMID:22837010

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

PubMed Central

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2018-01-01

Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

PubMed

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

Stable Isotope Ratios as Biomarkers of Diet for Health Research

PubMed Central

O’Brien, Diane M.

2016-01-01

Diet is a leading modifiable risk factor for chronic disease, but it remains difficult to measure accurately due to the error and bias inherent in self-reported methods of diet assessment. Consequently there is a pressing need for more objective biomarkers of diet for use in health research. The stable isotope ratios of light elements are a promising set of candidate biomarkers because they vary naturally and reproducibly among foods, and those variations are captured in molecules and tissues with high fidelity. Recent studies have identified valid isotopic measures of short and long-term sugar intake, meat intake, and fish intake in specific populations. These studies provide a strong foundation for validating stable isotopic biomarkers in the general United States population. Approaches to improve specificity for specific foods are needed, for example, by modeling intake using multiple stable isotope ratios, or by isolating and measuring specific molecules linked to foods of interest. PMID:26048703

ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework.

PubMed

Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing

2011-07-01

Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.

Biomarker Analysis of Samples Visually Identified as Microbial in the Eocene Green River Formation: An Analogue for Mars.

PubMed

Olcott Marshall, Alison; Cestari, Nicholas A

2015-09-01

One of the major exploration targets for current and future Mars missions are lithofacies suggestive of biotic activity. Although such lithofacies are not confirmation of biotic activity, they provide a way to identify samples for further analyses. To test the efficacy of this approach, we identified carbonate samples from the Eocene Green River Formation as "microbial" or "non-microbial" based on the macroscale morphology of their laminations. These samples were then crushed and analyzed by gas chromatography/mass spectroscopy (GC/MS) to determine their lipid biomarker composition. GC/MS analysis revealed that carbonates visually identified as "microbial" contained a higher concentration of more diverse biomarkers than those identified as "non-microbial," suggesting that this could be a viable detection strategy for selecting samples for further analysis or caching on Mars.

A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption.

PubMed

Lee, Regent; Fischer, Roman; Charles, Philip D; Adlam, David; Valli, Alessandro; Di Gleria, Katalin; Kharbanda, Rajesh K; Choudhury, Robin P; Antoniades, Charalambos; Kessler, Benedikt M; Channon, Keith M

2017-01-01

Atherosclerotic plaque rupture is the culprit event which underpins most acute vascular syndromes such as acute myocardial infarction. Novel biomarkers of plaque rupture could improve biological understanding and clinical management of patients presenting with possible acute vascular syndromes but such biomarker(s) remain elusive. Investigation of biomarkers in the context of de novo plaque rupture in humans is confounded by the inability to attribute the plaque rupture as the source of biomarker release, as plaque ruptures are typically associated with prompt down-stream events of myocardial necrosis and systemic inflammation. We developed a novel approach to identify potential biomarkers of plaque rupture by integrating plaque imaging, using optical coherence tomography, with both plaque and plasma proteomic analysis in a human model of angioplasty-induced plaque disruption. We compared two pairs of coronary plaque debris, captured by a FilterWire Device, and their corresponding control samples and found matrix metalloproteinase 9 (MMP9) to be significantly enriched in plaque. Plaque contents, as defined by optical coherence tomography, affect the systemic changes of MMP9. Disruption of lipid-rich plaque led to prompt elevation of plasma MMP9, whereas disruption of non-lipid-rich plaque resulted in delayed elevation of plasma MMP9. Systemic MMP9 elevation is independent of the associated myocardial necrosis and systemic inflammation (measured by Troponin I and C-reactive protein, respectively). This information guided the selection of a subset of subjects of for further label free proteomics analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). We discovered five novel, plaque-enriched proteins (lipopolysaccharide binding protein, Annexin A5, eukaryotic translocation initiation factor, syntaxin 11, cytochrome B5 reductase 3) to be significantly elevated in systemic circulation at 5 min after plaque disruption. This novel approach for biomarker

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

PubMed

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

2017-09-01

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

A cross sectional study of two independent cohorts identifies serum biomarkers for facioscapulohumeral muscular dystrophy (FSHD)

PubMed Central

Petek, Lisa M.; Rickard, Amanda M.; Budech, Christopher; Poliachik, Sandra L.; Shaw, Dennis; Ferguson, Mark R.; Tawil, Rabi; Friedman, Seth D.; Miller, Daniel G.

2016-01-01

Measuring the severity and progression of facioscapulohumeral muscular dystrophy (FSHD) is particularly challenging because muscle weakness progresses over long periods of time and can be sporadic. Biomarkers are essential for measuring disease burden and testing treatment strategies. We utilized the sensitive, specific, high-throughput SomaLogic proteomics platform of 1129 proteins to identify proteins with levels that correlate with FSHD severity in a cross-sectional study of two independent cohorts. We discovered biomarkers that correlate with clinical severity and disease burden measured by magnetic resonance imaging. Sixty-eight proteins in the Rochester cohort (n = 48) and 51 proteins in the Seattle cohort (n = 30) had significantly different levels in FSHD-affected individuals when compared with controls (p-value ≤ .005). A subset of these varied by at least 1.5 fold and four biomarkers were significantly elevated in both cohorts. Levels of creatine kinase MM and MB isoforms, carbonic anhydrase III, and troponin I type 2 reliably predicted the disease state and correlated with disease severity. Other novel biomarkers were also discovered that may reveal mechanisms of disease pathology. Assessing the levels of these biomarkers during clinical trials may add significance to other measures of quantifying disease progression or regression. PMID:27185459

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice[S

PubMed Central

Leduc, Magalie S.; Hageman, Rachael S.; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2011-01-01

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a “toolbox” of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits. PMID:21622629

Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows.

PubMed

Tian, He; Wang, Weiyu; Zheng, Nan; Cheng, Jianbo; Li, Songli; Zhang, Yangdong; Wang, Jiaqi

2015-07-01

Controlling heat stress (HS) is a global challenge for the dairy industry. However, simple and reliable biomarkers that aid the diagnoses of HS-induced metabolic disorders have not yet been identified. In this work, an integrated metabolomic and lipidomic approach using (1)H nuclear magnetic resonance and ultra-fast LC-MS was employed to investigate the discrimination of plasma metabolic profiles between HS-free and HS lactating dairy cows. Targeted detection using LC-MS in multiple reaction monitoring mode was used to verify the reliability of the metabolites as biomarker candidates. Overall, 41 metabolites were identified as candidates for lactating dairy cows exposed to HS, among which 13 metabolites, including trimethylamine, glucose, lactate, betaine, creatine, pyruvate, acetoacetate, acetone, β-hydroxybutyrate, C16 sphinganine, lysophosphatidylcholine (18:0), phosphatidylcholine (16:0/14:0), and arachidonic acid, had high sensitivity and specificity in diagnosing HS status, and are likely to be the potential biomarkers of HS dairy cows. All of these potentially diagnostic biomarkers were involved in carbohydrate, amino acid, lipid, or gut microbiome-derived metabolism, indicating that HS affected the metabolic pathways in lactating dairy cows. Further research is warranted to evaluate these biomarkers in practical applications and to elucidate the physiological mechanisms of HS-induced metabolic disorders. Heat stress (HS) annually causes huge losses to global dairy industry, including animal performance decrease, metabolic disorder and health problem. So far, physiological mechanisms underlying HS of dairy cows still remain elusive. To our best knowledge, this is the first attempt to elucidate the HS-induced metabolic disorders of dairy cows using integrated (1)H NMR and LC-MS-based metabolic study. The results not only provided potential diagnostic biomarkers for HS lactating dairy cows, but also significantly explored the related physiological mechanisms

Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

NASA Astrophysics Data System (ADS)

Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, C.; Jourdain, P.; Magistretti, P. J.

2016-03-01

Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

Biomarkers for immune-related toxicities of checkpoint inhibitors: current progress and the road ahead.

PubMed

Patil, Pradnya D; Burotto, Mauricio; Velcheti, Vamsidhar

2018-03-01

Immune checkpoint pathways are key immune regulatory pathways that play a physiologic role in maintaining immune-homeostasis and are often co-opted by cancer cells to evade the host immune system. Recent developments in cancer immunotherapy, mainly drugs blocking the immune checkpoint pathways, have revolutionized the treatment paradigm for many solid tumors. A wide spectrum of immune-related adverse events (irAEs) have been described with the use of these agents which necessitate treatment with immunosuppression, lead to disruption of therapy and can on occasion be life-threatening. There are currently no clinically validated biomarkers to predict the risk of irAEs. Areas covered: In this review, the authors describe the current progress in identifying biomarkers for irAEs and potential future directions. Literature search was conducted using PubMed-MEDLINE, Embase and Scopus. In addition, abstracts from major conference proceedings were reviewed for relevant content. Expert commentary: The discovery of biomarkers for irAEs is currently in its infancy, however there are a lot of promising candidate biomarkers that are currently being investigated. Biomarkers that can identify patients at a higher risk of developing irAEs or lead to early detection of autoimmune toxicities are crucial to optimize patient selection for immune-oncology agents and to minimize toxicity with their use.

Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

PubMed Central

Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

2015-01-01

The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

Genome-Wide Association Study Identifies Candidate Genes for Starch Content Regulation in Maize Kernels

PubMed Central

Liu, Na; Xue, Yadong; Guo, Zhanyong; Li, Weihua; Tang, Jihua

2016-01-01

Kernel starch content is an important trait in maize (Zea mays L.) as it accounts for 65–75% of the dry kernel weight and positively correlates with seed yield. A number of starch synthesis-related genes have been identified in maize in recent years. However, many loci underlying variation in starch content among maize inbred lines still remain to be identified. The current study is a genome-wide association study that used a set of 263 maize inbred lines. In this panel, the average kernel starch content was 66.99%, ranging from 60.60 to 71.58% over the three study years. These inbred lines were genotyped with the SNP50 BeadChip maize array, which is comprised of 56,110 evenly spaced, random SNPs. Population structure was controlled by a mixed linear model (MLM) as implemented in the software package TASSEL. After the statistical analyses, four SNPs were identified as significantly associated with starch content (P ≤ 0.0001), among which one each are located on chromosomes 1 and 5 and two are on chromosome 2. Furthermore, 77 candidate genes associated with starch synthesis were found within the 100-kb intervals containing these four QTLs, and four highly associated genes were within 20-kb intervals of the associated SNPs. Among the four genes, Glucose-1-phosphate adenylyltransferase (APS1; Gene ID GRMZM2G163437) is known as an important regulator of kernel starch content. The identified SNPs, QTLs, and candidate genes may not only be readily used for germplasm improvement by marker-assisted selection in breeding, but can also elucidate the genetic basis of starch content. Further studies on these identified candidate genes may help determine the molecular mechanisms regulating kernel starch content in maize and other important cereal crops. PMID:27512395

Exome sequencing of a large family identifies potential candidate genes contributing risk to bipolar disorder.

PubMed

Zhang, Tianxiao; Hou, Liping; Chen, David T; McMahon, Francis J; Wang, Jen-Chyong; Rice, John P

2018-03-01

Bipolar disorder is a mental illness with lifetime prevalence of about 1%. Previous genetic studies have identified multiple chromosomal linkage regions and candidate genes that might be associated with bipolar disorder. The present study aimed to identify potential susceptibility variants for bipolar disorder using 6 related case samples from a four-generation family. A combination of exome sequencing and linkage analysis was performed to identify potential susceptibility variants for bipolar disorder. Our study identified a list of five potential candidate genes for bipolar disorder. Among these five genes, GRID1(Glutamate Receptor Delta-1 Subunit), which was previously reported to be associated with several psychiatric disorders and brain related traits, is particularly interesting. Variants with functional significance in this gene were identified from two cousins in our bipolar disorder pedigree. Our findings suggest a potential role for these genes and the related rare variants in the onset and development of bipolar disorder in this one family. Additional research is needed to replicate these findings and evaluate their patho-biological significance. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene-Expression Biomarkers for Application to High-Throughput Radiation Biodosimetry

DTIC Science & Technology

2005-01-01

nuclear disaster . Even with the delayed onset of symptoms, sometimes several days after exposure, gene-expression biomarkers can identify these exposed individuals very early after exposure, allowing for prompt medical intervention. This early assessment of a radiation dose after exposure would enhance the operational commander’s situational awareness of the radiation exposure status of deployed units and increase the prospect of reduced morbidity and mortality through early medical intervention. Candidate gene targets were selected from microarray studies of ex

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

Genome-wide association study to identify potential genetic modifiers in a canine model for Duchenne muscular dystrophy.

PubMed

Brinkmeyer-Langford, Candice; Balog-Alvarez, Cynthia; Cai, James J; Davis, Brian W; Kornegay, Joe N

2016-08-22

Duchenne muscular dystrophy (DMD) causes progressive muscle degeneration, cardiomyopathy and respiratory failure in approximately 1/5,000 boys. Golden Retriever muscular dystrophy (GRMD) resembles DMD both clinically and pathologically. Like DMD, GRMD exhibits remarkable phenotypic variation among affected dogs, suggesting the influence of modifiers. Understanding the role(s) of genetic modifiers of GRMD may identify genes and pathways that also modify phenotypes in DMD and reveal novel therapies. Therefore, our objective in this study was to identify genetic modifiers that affect discrete GRMD phenotypes. We performed a linear mixed-model (LMM) analysis using 16 variably-affected dogs from our GRMD colony (8 dystrophic, 8 non-dystrophic). All of these dogs were either full or half-siblings, and phenotyped for 19 objective, quantitative biomarkers at ages 6 and 12 months. Each biomarker was individually assessed. Gene expression profiles of 59 possible candidate genes were generated for two muscle types: the cranial tibialis and medial head of the gastrocnemius. SNPs significantly associated with GRMD biomarkers were identified on multiple chromosomes (including the X chromosome). Gene expression levels for candidate genes located near these SNPs correlated with biomarker values, suggesting possible roles as GRMD modifiers. The results of this study enhance our understanding of GRMD pathology and represent a first step toward the characterization of GRMD modifiers that may be relevant to DMD pathology. Such modifiers are likely to be useful for DMD treatment development based on their relationships to GRMD phenotypes.

Current status of fluid biomarkers in mild traumatic brain injury

PubMed Central

Kulbe, Jacqueline R.; Geddes, James W.

2015-01-01

Mild traumatic brain injury (mTBI) affects millions of people annually and is difficult to diagnose. Mild injury is insensitive to conventional imaging techniques and diagnoses are often made using subjective criteria such as self-reported symptoms. Many people who sustain a mTBI develop persistent post-concussive symptoms. Athletes and military personnel are at great risk for repeat injury which can result in second impact syndrome or chronic traumatic encephalopathy. An objective and quantifiable measure, such as a serum biomarker, is needed to aid in mTBI diagnosis, prognosis, return to play/duty assessments, and would further elucidate mTBI pathophysiology. The majority of TBI biomarker research focuses on severe TBI with few studies specific to mild injury. Most studies use a hypothesis-driven approach, screening biofluids for markers known to be associated with TBI pathophysiology. This approach has yielded limited success in identifying markers that can be used clinically, additional candidate biomarkers are needed. Innovative and unbiased methods such as proteomics, microRNA arrays, urinary screens, autoantibody identification and phage display would complement more traditional approaches to aid in the discovery of novel mTBI biomarkers. PMID:25981889

Candidates source regions of martian meteorites as identified by OMEGA/MEx

NASA Astrophysics Data System (ADS)

Ody, A.; Poulet, F.; Quantin, C.; Bibring, J.-P.; Bishop, J. L.; Dyar, M. D.

2015-09-01

The objective of this study is to identify and map spectral analogues of some key martian meteorites (basaltic shergottites Los Angeles, Shergotty, QUE 94201, lherzolitic shergottite ALH A77005, Nakhla, Chassigny and the orthopyroxenite ALH 84001) in order to localize terrain candidates for their source regions. We develop a best fit procedure to reproduce the near-infrared (NIR) spectral properties of the martian surface as seen by the hyperspectral imaging spectrometer OMEGA/MEx from the NIR spectra of the martian meteorites. The fitting process is tested and validated, and Root Mean Square (RMS) global maps for each meteorite are obtained. It is found that basaltic shergottites have NIR spectral properties the most representative of the martian surface with the best spectral analogues found in early Hesperian volcanic provinces. Sites with spectral properties similar to those of ALH A77005 are scarce. They are mainly localized in olivine-bearing regions such as Nili Fossae and small Noachian/early Hesperian terrains. The only plausible source region candidate for Chassigny is the Nili Patera caldera dated to 1.6 Ga. Widespread spectral analogues for the ALH 84001 meteorite are found northeast of Syrtis Major and northwest of the Hellas basin. While this distribution is in agreement with the low-calcium-pyroxene-rich composition and old age (4.1 Ga) of this meteorite, the modal mineralogy of these candidates is not consistent with that of this meteorite. No convincing spectral analogue is found for the Amazonian-aged Nakhla meteorite suggesting that its olivine/high-calcium-pyroxene-rich composition could be representative of the Amazonian terrains buried under dust. Finally, some young rayed craters are proposed as possible candidates for source craters of the studied martian meteorites.

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum.

PubMed

Chambers, Andrew G; Percy, Andrew J; Simon, Romain; Borchers, Christoph H

2014-04-01

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

Serum VEGF-C levels as a candidate biomarker of hypervolemia in chronic kidney disease

PubMed Central

Sahutoglu, Tuncay; Sakaci, Tamer; Hasbal, Nuri B.; Ahbap, Elbis; Kara, Ekrem; Sumerkan, Mutlu C.; Sevinc, Mustafa; Akgol, Cuneyt; Koc, Yener; Basturk, Taner; Unsal, Abdulkadir

2017-01-01

Abstract Attaining and maintaining optimal “dry weight” is one of the principal goals during maintenance hemodialysis (MHD). Recent studies have shown a close relationship between Na+ load and serum vascular endothelial growth factor-C (VEGF-C) levels; thus, we aimed to investigate the role of VEGF-C as a candidate biomarker of hypervolemia. Physical examination, basic laboratory tests, N-terminal pro b-type natriuretic peptide (NT-ProBNP), echocardiography, and bioimpedance spectroscopy data of 3 groups of study subjects (euvolemic MHD patients, healthy controls, and hypervolemic chronic kidney disease [CKD] patients) were analyzed. Research data for MHD patients were obtained both before the first and after the last hemodialysis (HD) sessions of the week. Data of 10 subjects from each study groups were included in the analysis. Serum VEGF-C levels were significantly higher in hypervolemic CKD versus in MHD patients both before the first and after the last HD sessions (P = .004 and P = .000, respectively). Healthy controls had serum VEGF-C levels similar to and higher than MHD patients before the first and after the last HD sessions of the week (P = .327 and P = .021, respectively). VEGF-C levels were correlated with bioimpedance spectroscopy results (r2 0.659, P = .000) and edema (r2 0.494, P =0.006), but not with ejection fraction (EF) (r2 −0.251, P = .134), blood pressures (systolic r2 0.037, P = 0.824, diastolic r2 −0.067, P = .691), and NT-ProBNP (r2 −0.047, P = .773). These findings suggest that serum VEGF-C levels could be a potential new biomarker of hypervolemia. The lack of correlation between VEGF-C and EF may hold a promise to eliminate this common confounder. Further studies are needed to define the clinical utility of VEGF-C in volume management. PMID:28471955

Cytokines and MicroRNAs as Candidate Biomarkers for Systemic Lupus Erythematosus

PubMed Central

Stypińska, Barbara; Paradowska-Gorycka, Agnieszka

2015-01-01

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease, with varied course and symptoms. Its etiology is very complex and not clearly understood. There is growing evidence of the important role of cytokines in SLE pathogenesis, as well as their utility as biomarkers and targets in new therapies. Other potential new SLE biomarkers are microRNAs. Recently, over one hundred different microRNAs have been demonstrated to have a significant impact on the immune system. Various alterations in these microRNAs, associated with disease pathogenesis, have been described. They influence the signaling pathways and functions of immune response cells. Here, we aim to review the emerging new data on SLE etiology and pathogenesis. PMID:26473848

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer.

PubMed

Drabik, Anna; Bodzon-Kulakowska, Anna; Suder, Piotr; Silberring, Jerzy; Kulig, Jan; Sierzega, Marek

2017-04-07

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

THE CANDIDATE CLUSTER AND PROTOCLUSTER CATALOG (CCPC). II. SPECTROSCOPICALLY IDENTIFIED STRUCTURES SPANNING 2 <  z  < 6.6

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

Franck, J. R.; McGaugh, S. S.

2016-12-10

The Candidate Cluster and Protocluster Catalog (CCPC) is a list of objects at redshifts z  > 2 composed of galaxies with spectroscopically confirmed redshifts that are coincident on the sky and in redshift. These protoclusters are identified by searching for groups in volumes corresponding to the expected size of the most massive protoclusters at these redshifts. In CCPC1 we identified 43 candidate protoclusters among 14,000 galaxies between 2.74 <  z  < 3.71. Here we expand our search to more than 40,000 galaxies with spectroscopic redshifts z  > 2.00, resulting in an additional 173 candidate structures. The most significant of these are 36 protoclusters withmore » overdensities δ {sub gal} > 7. We also identify three large proto-supercluster candidates containing multiple protoclusters at z  = 2.3, 3.5 and z  = 6.56. Eight candidates with N  ≥ 10 galaxies are found at redshifts z  > 4.0. The last system in the catalog is the most distant spectroscopic protocluster candidate known to date at z  = 6.56.« less

Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross

PubMed Central

Brunner, Joseph I.; Gotter, Anthony L.; Millstein, Joshua; Garson, Susan; Binns, Jacquelyn; Fox, Steven V.; Savitz, Alan T.; Yang, He S.; Fitzpatrick, Karrie; Zhou, Lili; Owens, Joseph R.; Webber, Andrea L.; Vitaterna, Martha H.; Kasarskis, Andrew; Uebele, Victor N.; Turek, Fred; Renger, John J.; Winrow, Christopher J.

2013-01-01

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities. PMID:22091728

An Approach to Identify and Characterize a Subunit Candidate Shigella Vaccine Antigen.

PubMed

Pore, Debasis; Chakrabarti, Manoj K

2016-01-01

Shigellosis remains a serious issue throughout the developing countries, particularly in children under the age of 5. Numerous strategies have been tested to develop vaccines targeting shigellosis; unfortunately despite several years of extensive research, no safe, effective, and inexpensive vaccine against shigellosis is available so far. Here, we illustrate in detail an approach to identify and establish immunogenic outer membrane proteins from Shigella flexneri 2a as subunit vaccine candidates.

Red blood cell populations and membrane levels of peroxiredoxin 2 as candidate biomarkers to reveal blood doping.

PubMed

Marrocco, Cristina; Pallotta, Valeria; D'alessandro, Angelo; Alves, Gilda; Zolla, Lello

2012-05-01

Blood doping represents one main trend in doping strategies. Blood doping refers to the practice of boosting the number of red blood cells (RBCs) in the bloodstream in order to enhance athletic performance, by means of blood transfusions, administration of erythropoiesis-stimulating substances, blood substitutes, natural or artificial altitude facilities, and innovative gene therapies. While detection of recombinant EPO and homologous transfusion is already feasible through electrophoretic, mass spectrometry or flow cytometry-based approaches, no method is currently available to tackle doping strategies relying on autologous transfusions. We exploited an in vitro model of autologous transfusion through a 1:10 dilution of concentrated RBCs after 30 days of storage upon appropriate dilution in freshly withdrawn RBCs from the same donor. Western blot towards membrane Prdx2 and Percoll density gradients were exploited to assess their suitability as biomarkers of transfusion. Membrane Prdx2 was visible in day 30 samples albeit not in day 0, while it was still visible in the 1:10 dilution of day 30 in day 0 RBCs. Cell gradients also highlighted changes in the profile of the RBC subpopulations upon dilution of stored RBCs in the fresh ones. From this preliminary in vitro investigation it emerges that Prdx2 and RBC populations might be further tested as candidate biomarkers of blood doping through autologous transfusion, though it is yet to be assessed whether the kinetics in vivo of Prdx2 exposure in the membrane of transfused RBCs will endow a sufficient time-window to allow reliable anti-doping testing.

Red blood cell populations and membrane levels of peroxiredoxin 2 as candidate biomarkers to reveal blood doping

PubMed Central

Marrocco, Cristina; Pallotta, Valeria; D’Alessandro, Angelo; Alves, Gilda; Zolla, Lello

2012-01-01

Background Blood doping represents one main trend in doping strategies. Blood doping refers to the practice of boosting the number of red blood cells (RBCs) in the bloodstream in order to enhance athletic performance, by means of blood transfusions, administration of erythropoiesis-stimulating substances, blood substitutes, natural or artificial altitude facilities, and innovative gene therapies. While detection of recombinant EPO and homologous transfusion is already feasible through electrophoretic, mass spectrometry or flow cytometry-based approaches, no method is currently available to tackle doping strategies relying on autologous transfusions. Materials and methods. We exploited an in vitro model of autologous transfusion through a 1:10 dilution of concentrated RBCs after 30 days of storage upon appropriate dilution in freshly withdrawn RBCs from the same donor. Western blot towards membrane Prdx2 and Percoll density gradients were exploited to assess their suitability as biomarkers of transfusion. Results Membrane Prdx2 was visible in day 30 samples albeit not in day 0, while it was still visible in the 1:10 dilution of day 30 in day 0 RBCs. Cell gradients also highlighted changes in the profile of the RBC subpopulations upon dilution of stored RBCs in the fresh ones. Discussion. From this preliminary in vitro investigation it emerges that Prdx2 and RBC populations might be further tested as candidate biomarkers of blood doping through autologous transfusion, though it is yet to be assessed whether the kinetics in vivo of Prdx2 exposure in the membrane of transfused RBCs will endow a sufficient time-window to allow reliable anti-doping testing. PMID:22890272

A Roadmap for the Development and Validation of ERP Biomarkers in Schizophrenia Research

PubMed Central

Luck, Steven J.; Mathalon, Daniel H.; O'Donnell, Brian F.; Hämäläinen, Matti S.; Spencer, Kevin M.; Javitt, Daniel C.; Uhlhaas, Peter J.

2010-01-01

New efforts to develop treatments for cognitive dysfunction in mental illnesses would benefit enormously from biomarkers that provide sensitive and reliable measures of the neural events underlying cognition. Here we evaluate the promise of event-related potentials (ERPs) as biomarkers of cognitive dysfunction in schizophrenia. We conclude that ERPs have several desirable properties: (a) they provide a direct measure of electrical activity during neurotransmission; (b) their high temporal resolutions makes it possible to measure neural synchrony and oscillations; (c) they are relatively inexpensive and convenient to record; (d) animal models are readily available for several ERP components; (e) decades of research has established the sensitivity and reliability of ERP measures in psychiatric illnesses; and (f) feasibility of large N (>500) multi-site studies has been demonstrated for key measures. Consequently, ERPs may be useful for identifying endophenotypes and defining treatment targets, for evaluating new compounds in animals and in humans, and for identifying individuals who are good candidates for early interventions or for specific treatments. However, several challenges must be overcome before ERPs gain widespread use as biomarkers in schizophrenia research, and we make several recommendations for the research that is necessary to develop and validate ERP-based biomarkers that can have a real impact on treatment development. PMID:21111401

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

PubMed Central

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging. PMID:28626498

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study.

PubMed

Lehmann, Sylvia G; Bourgoin-Voillard, Sandrine; Seve, Michel; Rachidi, Walid

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

Blood/Brain Biomarkers of Inflammation After Stroke and Their Association With Outcome: From C-Reactive Protein to Damage-Associated Molecular Patterns.

PubMed

Bustamante, Alejandro; Simats, Alba; Vilar-Bergua, Andrea; García-Berrocoso, Teresa; Montaner, Joan

2016-10-01

Stroke represents one of the most important causes of disability and death in developed countries. However, there is a lack of prognostic tools in clinical practice to monitor the neurological condition and predict the final outcome. Blood biomarkers have been proposed and studied in this indication; however, no biomarker is currently used in clinical practice. The stroke-related neuroinflammatory processes have been associated with a poor outcome in stroke, as well as with poststroke complications. In this review, we focus on the most studied blood biomarkers of this inflammatory processes, cytokines, and C-reactive protein, evaluating its association with outcome and complications in stroke through the literature, and performing a systematic review on the association of C-reactive protein and functional outcome after stroke. Globally, we identified uncertainty with regard to the association of the evaluated biomarkers with stroke outcome, with little added value on top of clinical predictors such as age or stroke severity, which makes its implementation unlikely in clinical practice for global outcome prediction. Regarding poststroke complications, despite being more practical scenarios in which to make medical decisions following a biomarker prediction, not many studies have been performed, although there are now some candidates for prediction of poststroke infections. Finally, as potential new candidates, we reviewed the pathophysiological actions of damage-associated molecular patterns as triggers of the neuroinflammatory cascade of stroke, and their possible use as biomarkers.

Transcriptomic Analysis Using Olive Varieties and Breeding Progenies Identifies Candidate Genes Involved in Plant Architecture.

PubMed

González-Plaza, Juan J; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R

2016-01-01

Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species.

Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

PubMed

Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

2015-02-10

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

Biomarkers in Lysosomal Storage Diseases

PubMed Central

Bobillo Lobato, Joaquin; Jiménez Hidalgo, Maria; Jiménez Jiménez, Luis M.

2016-01-01

A biomarker is generally an analyte that indicates the presence and/or extent of a biological process, which is in itself usually directly linked to the clinical manifestations and outcome of a particular disease. The biomarkers in the field of lysosomal storage diseases (LSDs) have particular relevance where spectacular therapeutic initiatives have been achieved, most notably with the introduction of enzyme replacement therapy (ERT). There are two main types of biomarkers. The first group is comprised of those molecules whose accumulation is directly enhanced as a result of defective lysosomal function. These molecules represent the storage of the principal macro-molecular substrate(s) of a specific enzyme or protein, whose function is deficient in the given disease. In the second group of biomarkers, the relationship between the lysosomal defect and the biomarker is indirect. In this group, the biomarker reflects the effects of the primary lysosomal defect on cell, tissue, or organ functions. There is no “gold standard” among biomarkers used to diagnosis and/or monitor LSDs, but there are a number that exist that can be used to reasonably assess and monitor the state of certain organs or functions. A number of biomarkers have been proposed for the analysis of the most important LSDs. In this review, we will summarize the most promising biomarkers in major LSDs and discuss why these are the most promising candidates for screening systems. PMID:28933418

Moesin Is a Biomarker for the Assessment of Genotoxic Carcinogens in Mouse Lymphoma

PubMed Central

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-01-01

1,2-Dibromoethane and glycidol are well known genotoxic carcinogens, which have been widely used in industry. To identify a specific biomarker for these carcinogens in cells, the cellular proteome of L5178Y mouse lymphoma cells treated with these compounds was analyzed by 2-dimensional gel electrophoresis (2-DE) and MALDI-TOF mass spectrometry (MS). Of 50 protein spots showing a greater than 1.5-fold increase or decrease in intensity compared to control cells on a 2-D gel, we focused on the candidate biomarker moesin. Western analysis using monoclonal rabbit anti-moesin confirmed the identity of the protein and its increased level of expression upon exposure to the carcinogenic compounds. Moesin expression also increased in cells treated with six additional genotoxic carcinogens, verifying that moesin could serve as a biomarker to monitor phenotypic change upon exposure to genotoxic carcinogens in L5178Y mouse lymphoma cells. PMID:22358511

Moesin is a biomarker for the assessment of genotoxic carcinogens in mouse lymphoma.

PubMed

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-02-01

1,2-Dibromoethane and glycidol are well known genotoxic carcinogens, which have been widely used in industry. To identify a specific biomarker for these carcinogens in cells, the cellular proteome of L5178Y mouse lymphoma cells treated with these compounds was analyzed by 2-dimensional gel electrophoresis (2-DE) and MALDI-TOF mass spectrometry (MS). Of 50 protein spots showing a greater than 1.5-fold increase or decrease in intensity compared to control cells on a 2-D gel, we focused on the candidate biomarker moesin. Western analysis using monoclonal rabbit anti-moesin confirmed the identity of the protein and its increased level of expression upon exposure to the carcinogenic compounds. Moesin expression also increased in cells treated with six additional genotoxic carcinogens, verifying that moesin could serve as a biomarker to monitor phenotypic change upon exposure to genotoxic carcinogens in L5178Y mouse lymphoma cells.

Sweetening the pot: adding glycosylation to the biomarker discovery equation.

PubMed

Drake, Penelope M; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N Leigh; Regnier, Fred E; Gibson, Bradford W; Fisher, Susan J

2010-02-01

Cancer has profound effects on gene expression, including a cell's glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones. In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies--multiple reaction monitoring and lectin-antibody arrays--as potential tools for biomarker validation studies in pursuit of clinically useful tests. The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.

Potential serum biomarkers from a metabolomics study of autism

PubMed Central

Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

2016-01-01

Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

Serum amyloid A as a prognostic marker in melanoma identified by proteomic profiling.

PubMed

Findeisen, Peter; Zapatka, Marc; Peccerella, Teresa; Matzk, Heike; Neumaier, Michael; Schadendorf, Dirk; Ugurel, Selma

2009-05-01

Currently known prognostic serum biomarkers of melanoma are powerful in metastatic disease, but weak in early-stage patients. This study was aimed to identify new prognostic biomarkers of melanoma by serum mass spectrometry (MS) proteomic profiling, and to validate candidates compared with established markers. Two independent sets of serum samples from 596 melanoma patients were investigated. The first set (stage I = 102; stage IV = 95) was analyzed by matrix assisted laser desorption and ionization time of flight (MALDI TOF) MS for biomarkers differentiating between stage I and IV. In the second set (stage I = 98; stage II = 91; stage III = 87; stage IV = 103), the serum concentrations of the candidate marker serum amyloid A (SAA) and the known biomarkers S100B, lactate dehydrogenase, and C reactive protein (CRP) were measured using immunoassays. MALDI TOF MS revealed a peak at m/z 11.680 differentiating between stage I and IV, which could be identified as SAA. High peak intensities at m/z 11.680 correlated with poor survival. In univariate analysis, SAA was a strong prognostic marker in stage I to III (P = .043) and stage IV (P = .000083) patients. Combination of SAA and CRP increased the prognostic impact to P = .011 in early-stage (I to III) patients. Multivariate analysis revealed sex, stage, tumor load, S100B, SAA, and CRP as independent prognostic factors, with an interaction between SAA and CRP. In stage I to III patients, SAA combined with CRP was superior to S100B in predicting patients' progression-free and overall survival. SAA combined with CRP might be used as prognostic serological biomarkers in early-stage melanoma patients, helping to discriminate low-risk patients from high-risk patients needing adjuvant treatment.

Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

PubMed Central

Ellias, Mohd Faiz; Zainal Ariffin, Shahrul Hisham; Karsani, Saiful Anuar; Abdul Rahman, Mariati; Senafi, Shahidan; Megat Abdul Wahab, Rohaya

2012-01-01

Orthodontic treatment has been shown to induce inflammation, followed by bone remodelling in the periodontium. These processes trigger the secretion of various proteins and enzymes into the saliva. This study aims to identify salivary proteins that change in expression during orthodontic tooth movement. These differentially expressed proteins can potentially serve as protein biomarkers for the monitoring of orthodontic treatment and tooth movement. Whole saliva from three healthy female subjects were collected before force application using fixed appliance and at 14 days after 0.014′′ Niti wire was applied. Salivary proteins were resolved using two-dimensional gel electrophoresis (2DE) over a pH range of 3–10, and the resulting proteome profiles were compared. Differentially expressed protein spots were then identified by MALDI-TOF/TOF tandem mass spectrometry. Nine proteins were found to be differentially expressed; however, only eight were identified by MALDI-TOF/TOF. Four of these proteins—Protein S100-A9, immunoglobulin J chain, Ig alpha-1 chain C region, and CRISP-3—have known roles in inflammation and bone resorption. PMID:22919344

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

Determination of hepatocellular carcinoma grade by needle biopsy is unreliable for liver transplant candidate selection.

PubMed

Court, Colin M; Harlander-Locke, Michael P; Markovic, Daniela; French, Samuel W; Naini, Bita V; Lu, David S; Raman, Steven S; Kaldas, Fady M; Zarrinpar, Ali; Farmer, Douglas G; Finn, Richard S; Sadeghi, Saeed; Tomlinson, James S; Busuttil, Ronald W; Agopian, Vatche G

2017-09-01

The objective of this article is to evaluate the utility of preoperative needle biopsy (PNB) grading of hepatocellular carcinoma (HCC) as a biomarker for liver transplantation (LT) candidate selection. Given the prognostic significance of HCC tumor grade, PNB grading has been proposed as a biomarker for LT candidate selection. Clinicopathologic characteristics of HCC LT recipients (1989-2014) with a PNB were analyzed, and the concordance of PNB grade to explant grade and vascular invasion was assessed to determine whether incorporation of PNB grade to accepted transplant criteria improved candidate selection. Of 965 patients undergoing LT for HCC, 234 (24%) underwent PNB at a median of 280 days prior to transplant. Grade by PNB had poor concordance to final explant pathology (κ = 0.22; P = 0.003), and low sensitivity (29%) and positive predictive value (35%) in identifying poorly differentiated tumors. Vascular invasion was predicted by explant pathologic grade (r s = 0.24; P < 0.001) but not PNB grade (r s = -0.05; P = 0.50). Increasing explant pathology grade (P = 0.02), but not PNB grade (P = 0.65), discriminated post-LT HCC recurrence risk. The incorporation of PNB grade to the established radiologic Milan criteria (MC) did not result in improved prognostication of post-LT recurrence (net reclassification index [NRI] = 0%), whereas grade by explant pathology resulted in significantly improved reclassification of risk (NRI = 19%). Preoperative determination of HCC grade by PNB has low concordance with explant pathologic grade and low sensitivity and positive predictive value in identifying poorly differentiated tumors. PNB grade did not accurately discriminate post-LT HCC recurrence and had no utility in improving prognostication compared with the MC alone. Incorporation of PNB to guide transplant candidate selection appears unjustified. Liver Transplantation 23 1123-1132 2017 AASLD. © 2017 by the American Association for the Study of Liver Diseases.

Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

PubMed

Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

2014-05-01

In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

CXCL14 is a candidate biomarker for Hedgehog signalling in idiopathic pulmonary fibrosis.

PubMed

Jia, Guiquan; Chandriani, Sanjay; Abbas, Alexander R; DePianto, Daryle J; N'Diaye, Elsa N; Yaylaoglu, Murat B; Moore, Heather M; Peng, Ivan; DeVoss, Jason; Collard, Harold R; Wolters, Paul J; Egen, Jackson G; Arron, Joseph R

2017-09-01

Idiopathic pulmonary fibrosis (IPF) is associated with aberrant expression of developmental pathways, including Hedgehog (Hh). As Hh signalling contributes to multiple pro-fibrotic processes, Hh inhibition may represent a therapeutic option for IPF. However, no non-invasive biomarkers are available to monitor lung Hh activity. We assessed gene and protein expression in IPF and control lung biopsies, mouse lung, fibroblasts stimulated in vitro with sonic hedgehog (SHh), and plasma in IPF patients versus controls, and cancer patients before and after treatment with vismodegib, a Hh inhibitor. Lung tissue from IPF patients exhibited significantly greater expression of Hh-related genes versus controls. The gene most significantly upregulated in both IPF lung biopsies and fibroblasts stimulated in vitro with SHh was CXCL14 , which encodes a soluble secreted chemokine whose expression is inhibited in vitro by the addition of vismodegib. CXCL14 expression was induced by SHh overexpression in mouse lung. Circulating CXCL14 protein levels were significantly higher in plasma from IPF patients than controls. In cancer patients, circulating CXCL14 levels were significantly reduced upon vismodegib treatment. CXCL14 is a systemic biomarker that could be used to identify IPF patients with increased Hh pathway activity and monitor the pharmacodynamic effects of Hh antagonist therapy in IPF. Post-results, NCT00968981. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think Tank

PubMed Central

Millan, Mark J.; Bahn, Sabine; Bertolino, Alessandro; Turck, Christoph W.; Kapur, Shitij; Möller, Hans-Jürgen; Dean, Brian

2015-01-01

Background: A think tank sponsored by the Collegium Internationale Neuropsychopharmacologium (CINP) debated the status and prospects of biological markers for psychiatric disorders, focusing on schizophrenia and major depressive disorder. Methods: Discussions covered markers defining and predicting specific disorders or domains of dysfunction, as well as predicting and monitoring medication efficacy. Deliberations included clinically useful and viable biomarkers, why suitable markers are not available, and the need for tightly-controlled sample collection. Results: Different types of biomarkers, appropriate sensitivity, specificity, and broad-based exploitability were discussed. Whilst a number of candidates are in the discovery phases, all will require replication in larger, real-life cohorts. Clinical cost-effectiveness also needs to be established. Conclusions: Since a single measure is unlikely to suffice, multi-modal strategies look more promising, although they bring greater technical and implementation complexities. Identifying reproducible, robust biomarkers will probably require pre-competitive consortia to provide the resources needed to identify, validate, and develop the relevant clinical tests. PMID:25899066

Is there Progress? An Overview of Selecting Biomarker Candidates for Major Depressive Disorder

PubMed Central

Young, Juan Joseph; Silber, Tim; Bruno, Davide; Galatzer-Levy, Isaac Robert; Pomara, Nunzio; Marmar, Charles Raymond

2016-01-01

Major depressive disorder (MDD) contributes to a significant worldwide disease burden, expected to be second only to heart disease by 2050. However, accurate diagnosis has been a historical weakness in clinical psychiatry. As a result, there is a demand for diagnostic modalities with greater objectivity that could improve on current psychiatric practice that relies mainly on self-reporting of symptoms and clinical interviews. Over the past two decades, literature on a growing number of putative biomarkers for MDD increasingly suggests that MDD patients have significantly different biological profiles compared to healthy controls. However, difficulty in elucidating their exact relationships within depression pathology renders individual markers inconsistent diagnostic tools. Consequently, further biomarker research could potentially improve our understanding of MDD pathophysiology as well as aid in interpreting response to treatment, narrow differential diagnoses, and help refine current MDD criteria. Representative of this, multiplex assays using multiple sources of biomarkers are reported to be more accurate options in comparison to individual markers that exhibit lower specificity and sensitivity, and are more prone to confounding factors. In the future, more sophisticated multiplex assays may hold promise for use in screening and diagnosing depression and determining clinical severity as an advance over relying solely on current subjective diagnostic criteria. A pervasive limitation in existing research is heterogeneity inherent in MDD studies, which impacts the validity of biomarker data. Additionally, small sample sizes of most studies limit statistical power. Yet, as the RDoC project evolves to decrease these limitations, and stronger studies with more generalizable data are developed, significant advances in the next decade are expected to yield important information in the development of MDD biomarkers for use in clinical settings. PMID:27199779

Predictive Biomarkers for Asthma Therapy.

PubMed

Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

2017-09-19

Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery

PubMed Central

Wang, Hongyu; Li, Xin; Volk, David E.; Lokesh, Ganesh L.-R.; Elizondo-Riojas, Miguel-Angel; Li, Li; Nick, Alpa M.; Sood, Anil K.; Rosenblatt, Kevin P.; Gorenstein, David G.

2016-01-01

High affinity aptamer-based biomarker discovery has the advantage of simultaneously discovering an aptamer affinity reagent and its target biomarker protein. Here, we demonstrate a morphology-based tissue aptamer selection method that enables us to use tissue sections from individual patients and identify high-affinity aptamers and their associated target proteins in a systematic and accurate way. We created a combinatorial DNA aptamer library that has been modified with thiophosphate substitutions of the phosphate ester backbone at selected 5′dA positions for enhanced nuclease resistance and targeting. Based on morphological assessment, we used image-directed laser microdissection (LMD) to dissect regions of interest bound with the thioaptamer (TA) library and further identified target proteins for the selected TAs. We have successfully identified and characterized the lead candidate TA, V5, as a vimentin-specific sequence that has shown specific binding to tumor vasculature of human ovarian tissue and human microvascular endothelial cells. This new Morph-X-Select method allows us to select high-affinity aptamers and their associated target proteins in a specific and accurate way, and could be used for personalized biomarker discovery to improve medical decision-making and to facilitate the development of targeted therapies to achieve more favorable outcomes. PMID:27839510

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia

2018-06-11

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Biomarkers for pediatric sepsis and septic shock

PubMed Central

Standage, Stephen W; Wong, Hector R

2011-01-01

Sepsis is a clinical syndrome defined by physiologic changes indicative of systemic inflammation, which are likely attributable to documented or suspected infection. Septic shock is the progression of those physiologic changes to the extent that delivery of oxygen and metabolic substrate to tissues is compromised. Biomarkers have the potential to diagnose, monitor, stratify and predict outcome in these syndromes. C-reactive protein is elevated in inflammatory and infectious conditions and has long been used as a biomarker indicating infection. Procalcitonin has more recently been shown to better distinguish infection from inflammation. Newer candidate biomarkers for infection include IL-18 and CD64. Lactate facilitates the diagnosis of septic shock and the monitoring of its progression. Multiple stratification biomarkers based on genome-wide expression profiling are under active investigation and present exciting future possibilities. PMID:21171879

Transcriptomic Analysis Using Olive Varieties and Breeding Progenies Identifies Candidate Genes Involved in Plant Architecture

PubMed Central

González-Plaza, Juan J.; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F.; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R.; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R.

2016-01-01

Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species. PMID:26973682

A Biomarker Bakeoff in Early Stage Pancreatic Cancer — EDRN Public Portal

Cancer.gov

Previous research in EDRN laboratories and elsewhere has produced several candidate biomarker(s) for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC), many of which show promise for significantly improving upon the performance of the current best marker, CA19-9. As yet, the relative performance of the markers in combination is not known because a rigorous comparison using a common sample set has not been performed. A direct comparison of the potential biomarkers in a comparative study (“biomarker bakeoff”) would enable an objective determination of which candidates should move forward for further validation, as well as an assessment of the potential value of using novel combinations of the biomarkers. The gastrointestinal collaborative group within the EDRN is in an optimal position to carry out such a study given its shared resources and interactive structure. In this project, the two pancreatic CVCs in the EDRN will provide samples to be distributed to four laboratories with promising biomarkers. The laboratories will run their own assays and perform initial analyses on the blinded PDAC and control samples. Our biostatistical collaborator, Dr. Huang at FHCRC, will perform the statistical evaluations. Biomarkers meeting the predetermined performance criteria will move forward to further validation using the EDRN reference set. In addition, we will determine whether any novel combinations of biomarkers should be further tested.

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

PubMed Central

Nielson, Jessica L.; Cooper, Shelly R.; Sorani, Marco D.; Inoue, Tomoo; Yuh, Esther L.; Mukherjee, Pratik; Petrossian, Tanya C.; Lum, Pek Y.; Lingsma, Hester F.; Gordon, Wayne A.; Okonkwo, David O.; Manley, Geoffrey T.

2017-01-01

Background Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust

Heptadecanoylcarnitine (C17) a novel candidate biomarker for newborn screening of propionic and methylmalonic acidemias.

PubMed

Malvagia, Sabrina; Haynes, Christopher A; Grisotto, Laura; Ombrone, Daniela; Funghini, Silvia; Moretti, Elisa; McGreevy, Kathleen S; Biggeri, Annibale; Guerrini, Renzo; Yahyaoui, Raquel; Garg, Uttam; Seeterlin, Mary; Chace, Donald; De Jesus, Victor R; la Marca, Giancarlo

2015-10-23

3-Hydroxypalmitoleoyl-carnitine (C16:1-OH) has recently been reported to be elevated in acylcarnitine profiles of patients with propionic acidemia (PA) or methylmalonic acidemia (MMA) during expanded newborn screening (NBS). High levels of C16:1-OH, combined with other hydroxylated long chain acylcarnitines are related to long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) and trifunctional protein (TFP) deficiency. The acylcarnitine profile of two LCHADD patients was evaluated using liquid chromatography-tandem mass spectrometric method. A specific retention time was determined for each hydroxylated long chain acylcarnitine. The same method was applied to some neonatal dried blood spots (DBSs) from PA and MMA patients presenting abnormal C16:1-OH concentrations. The retention time of the peak corresponding to C16:1-OH in LCHADD patients differed from those in MMA and PA patients. Heptadecanoylcarnitine (C17) has been identified as the novel biomarker specific for PA and MMA patients through high resolution mass spectrometry (Orbitrap) experiments. We found that 21 out of 23 neonates (22 MMA, and 1PA) diagnosed through the Tuscany region NBS program exhibited significantly higher levels of C17 compared to controls. Twenty-three maternal deficiency (21 vitamin B12 deficiency, 1 homocystinuria and 1 gastrin deficiency) samples and 82 false positive for elevated propionylcarnitine (C3) were also analyzed. We have characterized a novel biomarker able to detect propionate disorders during expanded newborn screening (NBS). The use of this new biomarker may improve the analytical performances of NBS programs especially in laboratories where second tier tests are not performed. Copyright © 2015 Elsevier B.V. All rights reserved.

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

PubMed Central

Lakhan, Shaheen Emmanuel

2006-01-01

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510

Biology and therapy of fibromyalgia. Evidence-based biomarkers for fibromyalgia syndrome

PubMed Central

Dadabhoy, Dina; Crofford, Leslie J; Spaeth, Michael; Russell, I Jon; Clauw, Daniel J

2008-01-01

Researchers studying fibromyalgia strive to identify objective, measurable biomarkers that may identify susceptible individuals, may facilitate diagnosis, or that parallel activity of the disease. Candidate objective measures range from sophisticated functional neuroimaging to office-ready measures of the pressure pain threshold. A systematic literature review was completed to assess highly investigated, objective measures used in fibromyalgia studies. To date, only experimental pain testing has been shown to coincide with improvements in clinical status in a longitudinal study. Concerted efforts to systematically evaluate additional objective measures in research trials will be vital for ongoing progress in outcome research and translation into clinical practice. PMID:18768089

Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet's Disease by Gas Chromatography/Time-of-Flight-Mass Spectrometry.

PubMed

Ahn, Joong Kyong; Kim, Jungyeon; Hwang, Jiwon; Song, Juhwan; Kim, Kyoung Heon; Cha, Hoon-Suk

2017-11-02

Diagnosing Behcet's disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flight-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R ² X of 0.231, R ² Y of 0.804, and Q ² of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.

Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn

PubMed Central

Maron, Jill L.; Hwang, Jooyeon S.; Pathak, Subash; Ruthazer, Robin; Russell, Ruby L.; Alterovitz, Gil

2014-01-01

Objective To combine mathematical modeling of salivary gene expression microarray data and systems biology annotation with RT-qPCR amplification to identify (phase I) and validate (phase II) salivary biomarker analysis for the prediction of oral feeding readiness in preterm infants. Study design Comparative whole transcriptome microarray analysis from 12 preterm newborns pre- and post-oral feeding success was used for computational modeling and systems biology analysis to identify potential salivary transcripts associated with oral feeding success (phase I). Selected gene expression biomarkers (15 from computational modeling; 6 evidence-based; and 3 reference) were evaluated by RT-qPCR amplification on 400 salivary samples from successful (n=200) and unsuccessful (n=200) oral feeders (phase II). Genes, alone and in combination, were evaluated by a multivariate analysis controlling for sex and post-conceptional age (PCA) to determine the probability that newborns achieved successful oral feeding. Results Advancing post-conceptional age (p < 0.001) and female sex (p = 0.05) positively predicted an infant’s ability to feed orally. A combination of five genes, NPY2R (hunger signaling), AMPK (energy homeostasis), PLXNA1 (olfactory neurogenesis), NPHP4 (visual behavior) and WNT3 (facial development), in addition to PCA and sex, demonstrated good accuracy for determining feeding success (AUROC = 0.78). Conclusions We have identified objective and biologically relevant salivary biomarkers that noninvasively assess a newborn’s developing brain, sensory and facial development as they relate to oral feeding success. Understanding the mechanisms that underlie the development of oral feeding readiness through translational and computational methods may improve clinical decision making while decreasing morbidities and health care costs. PMID:25620512

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

Identification and Quantification of Preterm Birth Biomarkers in Human Cervicovaginal Fluid by Liquid Chromatography/Tandem Mass Spectrometry

PubMed Central

Shah, Sumit J.; Yu, Kenneth H.; Sangar, Vineet; Parry, Samuel I.; Blair, Ian A.

2009-01-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain < 0.5 % of the endogenous unlabeled forms. Identified proteins were screened to provide a set of fifteen candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the fifteen candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger

Identification and quantification of preterm birth biomarkers in human cervicovaginal fluid by liquid chromatography/tandem mass spectrometry.

PubMed

Shah, Sumit J; Yu, Kenneth H; Sangar, Vineet; Parry, Samuel I; Blair, Ian A

2009-05-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). In total, 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain <0.5% of the endogenous unlabeled forms. Identified proteins were screened to provide a set of 15 candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the 15 candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger patient

Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

PubMed

Wostyn, Peter; De Deyn, Peter Paul

2017-11-01

A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

PubMed

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of EBP50 as a Specific Biomarker for Carcinogens Via the Analysis of Mouse Lymphoma Cellular Proteome

PubMed Central

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-01-01

To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens. PMID:22434383

Identification of EBP50 as a specific biomarker for carcinogens via the analysis of mouse lymphoma cellular proteome.

PubMed

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-03-01

To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens.

Validation of Biomarkers for Prostate Cancer Prognosis

DTIC Science & Technology

2013-10-01

prostate cancer research community for testing candidate biomarkers. Groups using the resource include Dr. Jeremy Squire, Dr. Gustavo Ayala, and Dr...Ferrari, Javier Hernandez , Antonio Hurtado-Coll, Kyle Kuchinsky, Janet Liew, Rosario Mendez-Meza, Elizabeth Smith, Imelda Tenggarra, Xiaotun Zhang

Testing of Candidate Icons to Identify Acetaminophen-Containing Medicines

PubMed Central

Shiffman, Saul; Cotton, Helene; Jessurun, Christina; Sembower, Mark A.; Pype, Steve; Phillips, Jerry

2016-01-01

Adding icons on labels of acetaminophen-containing medicines could help users identify the active ingredient and avoid concomitant use of multiple medicines containing acetaminophen. We evaluated five icons for communication effectiveness. Adults (n = 300) were randomized to view a prescription container label or over-the-counter labels with either one or two icons. Participants saw two icon candidates, and reported their interpretation; experts judged whether these reflected critical confusions that might cause harm. Participants rated how effectively each icon communicated key messages. Icons based on abbreviations of “acetaminophen” (“Ac”, “Ace”, “Acm”) were rated less confusing and more effective in communicating the active ingredient than icons based on “APAP” or an abstract symbol. Icons did not result in critical confusion when seen on a readable medicine label. Icon implementation on prescription labels was more effective at communicating the warning against concomitant use than implementation on over-the-counter (OTC) labels. Adding an icon to a second location on OTC labels did not consistently enhance this communication, but reduced rated effectiveness of acetaminophen ingredient communication among participants with limited health literacy. The abbreviation-based icons seem most suitable for labeling acetaminophen-containing medications to enable users to identify acetaminophen-containing products. PMID:28970383

Circulating miR-132-3p as a Candidate Diagnostic Biomarker for Malignant Mesothelioma

PubMed Central

Gawrych, Katarzyna; Casjens, Swaantje; Brik, Alexander; Lehnert, Martin; Taeger, Dirk; Pesch, Beate; Kollmeier, Jens; Bauer, Torsten T.; Johnen, Georg; Brüning, Thomas

2017-01-01

The use of circulating microRNAs as biomarkers has opened new opportunities for diagnosis of cancer because microRNAs exhibit tumor-specific expression profiles. The aim of this study was the identification of circulating microRNAs in human plasma as potential biomarkers for the diagnosis of malignant mesothelioma. For discovery, TaqMan Low Density Array Human MicroRNA Cards were used to analyze 377 microRNAs in plasma samples from 21 mesothelioma patients and 21 asbestos-exposed controls. For verification, individual TaqMan microRNA assays were used for quantitative real-time PCR in plasma samples from 22 mesothelioma patients and 44 asbestos-exposed controls. The circulating miR-132-3p showed different expression levels between mesothelioma patients and asbestos-exposed controls. For discrimination, sensitivity of 86% and specificity of 61% were calculated. Circulating miR-132-3p in plasma was not affected by hemolysis and no impact of age or smoking status on miR-132-3p levels could be observed. For the combination of miR-132-3p with the previously described miR-126, sensitivity of 77% and specificity of 86% were calculated. The results of this study indicate that miR-132-3p might be a new promising diagnostic biomarker for malignant mesothelioma. It is indicated that the combination of miR-132-3p with other individual biomarkers improves the biomarker performance. PMID:28321148

Value of biomarkers in osteoarthritis: current status and perspectives

PubMed Central

Lotz, M; Martel-Pelletier, J; Christiansen, C; Brandi, M-L; Bruyère, O; Chapurlat, R; Collette, J; Cooper, C; Giacovelli, G; Kanis, J A; Karsdal, M A; Kraus, V; Lems, W F; Meulenbelt, I; Pelletier, J-P; Raynauld, J-P; Reiter-Niesert, S; Rizzoli, R; Sandell, L J; Van Spil, W E; Reginster, J-Y

2013-01-01

Osteoarthritis affects the whole joint structure with progressive changes in cartilage, menisci, ligaments and subchondral bone, and synovial inflammation. Biomarkers are being developed to quantify joint remodelling and disease progression. This article was prepared following a working meeting of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis convened to discuss the value of biochemical markers of matrix metabolism in drug development in osteoarthritis. The best candidates are generally molecules or molecular fragments present in cartilage, bone or synovium and may be specific to one type of joint tissue or common to them all. Many currently investigated biomarkers are associated with collagen metabolism in cartilage or bone, or aggrecan metabolism in cartilage. Other biomarkers are related to non-collagenous proteins, inflammation and/or fibrosis. Biomarkers in osteoarthritis can be categorised using the burden of disease, investigative, prognostic, efficacy of intervention, diagnostic and safety classification. There are a number of promising candidates, notably urinary C-terminal telopeptide of collagen type II and serum cartilage oligomeric protein, although none is sufficiently discriminating to differentiate between individual patients and controls (diagnostic) or between patients with different disease severities (burden of disease), predict prognosis in individuals with or without osteoarthritis (prognostic) or perform so consistently that it could function as a surrogate outcome in clinical trials (efficacy of intervention). Future avenues for research include exploration of underlying mechanisms of disease and development of new biomarkers; technological development; the ‘omics’ (genomics, metabolomics, proteomics and lipidomics); design of aggregate scores combining a panel of biomarkers and/or imaging markers into single diagnostic algorithms; and investigation into the relationship between biomarkers and

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

PubMed

Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

2014-09-09

Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes.

PubMed

Morton, Nicholas M; Nelson, Yvonne B; Michailidou, Zoi; Di Rollo, Emma M; Ramage, Lynne; Hadoke, Patrick W F; Seckl, Jonathan R; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J; Dunbar, Donald R

2011-01-01

Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

Blood Biomarkers in Idiopathic Pulmonary Fibrosis.

PubMed

Guiot, Julien; Moermans, Catherine; Henket, Monique; Corhay, Jean-Louis; Louis, Renaud

2017-06-01

Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal lung disease of unknown origin whose incidence has been increasing over the latest decade partly as a consequence of population ageing. New anti-fibrotic therapy including pirfenidone and nintedanib have now proven efficacy in slowing down the disease. Nevertheless, diagnosis and follow-up of IPF remain challenging. This review examines the recent literature on potentially useful blood molecular and cellular biomarkers in IPF. Most of the proposed biomarkers belong to chemokines (IL-8, CCL18), proteases (MMP-1 and MMP-7), and growth factors (IGBPs) families. Circulating T cells and fibrocytes have also gained recent interest in that respect. Up to now, though several interesting candidates are profiling there has not been a single biomarker, which proved to be specific of the disease and predictive of the evolution (decline of pulmonary function test values, risk of acute exacerbation or mortality). Large scale multicentric studies are eagerly needed to confirm the utility of these biomarkers.

Genome-Wide Interaction Study of Omega-3 PUFAs and Other Fatty Acids on Inflammatory Biomarkers of Cardiovascular Health in the Framingham Heart Study.

PubMed

Veenstra, Jenna; Kalsbeek, Anya; Westra, Jason; Disselkoen, Craig; Smith, Caren; Tintle, Nathan

2017-08-18

Numerous genetic loci have been identified as being associated with circulating fatty acid (FA) levels and/or inflammatory biomarkers of cardiovascular health (e.g., C-reactive protein). Recently, using red blood cell (RBC) FA data from the Framingham Offspring Study, we conducted a genome-wide association study of over 2.5 million single nucleotide polymorphisms (SNPs) and 22 RBC FAs (and associated ratios), including the four Omega-3 FAs (ALA, DHA, DPA, and EPA). Our analyses identified numerous causal loci. In this manuscript, we investigate the extent to which polyunsaturated fatty acid (PUFA) levels moderate the relationship of genetics to cardiovascular health biomarkers using a genome-wide interaction study approach. In particular, we test for possible gene-FA interactions on 9 inflammatory biomarkers, with 2.5 million SNPs and 12 FAs, including all Omega-3 PUFAs. We identified eighteen novel loci, including loci which demonstrate strong evidence of modifying the impact of heritable genetics on biomarker levels, and subsequently cardiovascular health. The identified genes provide increased clarity on the biological functioning and role of Omega-3 PUFAs, as well as other common fatty acids, in cardiovascular health, and suggest numerous candidate loci for future replication and biological characterization.

Eliciting, Identifying, Interpreting, and Responding to Students' Ideas: Teacher Candidates' Growth in Formative Assessment Practices

ERIC Educational Resources Information Center

Gotwals, Amelia Wenk; Birmingham, Daniel

2016-01-01

With the goal of helping teacher candidates become well-started beginners, it is important that methods courses in teacher education programs focus on high-leverage practices. Using responsive teaching practices, specifically eliciting, identifying, interpreting, and responding to students' science ideas (i.e., formative assessment), can be used…

Identifying FGA peptides as nasopharyngeal carcinoma-associated biomarkers by magnetic beads.

PubMed

Tao, Ya-Lan; Li, Yan; Gao, Jin; Liu, Zhi-Gang; Tu, Zi-Wei; Li, Guo; Xu, Bing-Qing; Niu, Dao-Li; Jiang, Chang-Bin; Yi, Wei; Li, Zhi-Qiang; Li, Jing; Wang, Yi-Ming; Cheng, Zhi-Bin; Liu, Qiao-Dan; Bai, Li; Zhang, Chun; Zhang, Jing-Yu; Zeng, Mu-Sheng; Xia, Yun-Fei

2012-07-01

Early diagnosis and treatment is known to improve prognosis for nasopharyngeal carcinoma (NPC). The study determined the specific peptide profiles by comparing the serum differences between NPC patients and healthy controls, and provided the basis for the diagnostic model and identification of specific biomarkers of NPC. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) can be used to detect the molecular mass of peptides. Mass spectra of peptides were generated after extracting and purification of 40 NPC samples in the training set, 21 in the single center validation set and 99 in the multicenter validation set using weak cationic-exchanger magnetic beads. The spectra were analyzed statistically using FlexAnalysis™ and ClinProt™ bioinformatics software. The four most significant peaks were selected out to train a genetic algorithm model to diagnose NPC. The diagnostic sensitivity and specificity were 100% and 100% in the training set, 90.5% and 88.9% in the single center validation set, 91.9% and 83.3% in the multicenter validation set, and the false positive rate (FPR) and false negative rate (FNR) were obviously lower in the NPC group (FPR, 16.7%; FNR, 8.1%) than in the other cancer group (FPR, 39%; FNR, 61%), respectively. So, the diagnostic model including four peptides can be suitable for NPC but not for other cancers. FGA peptide fragments identified may serve as tumor-associated biomarkers for NPC. Copyright © 2012 Wiley Periodicals, Inc.

Sweetening the pot: adding glycosylation to the biomarker discovery equation

PubMed Central

Drake, Penelope M.; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N. Leigh; Regnier, Fred E.; Gibson, Bradford W.; Fisher, Susan J.

2010-01-01

Background Cancer has profound effects on gene expression, including a cell’s glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate as compared to their protein backbones. Content We survey clinical tests that target carbohydrate modifications. for diagnosing and treating cancer. Next, we present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling and metastasis, and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies—multiple reaction monitoring and lectin-antibody arrays—as potential tools for biomarker validation studies in pursuit of clinically useful tests. Summary The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses. PMID:19959616

USE OF qRTPCR TO IDENTIFY POTENTIAL BIOMARKERS OF BROMATE EXPOSURE IN F344 MALE RAT KIDNEYS

EPA Science Inventory

Potassium bromate (KBrO3) is a drinking water disinfection by-product that is nephrotoxic and carcinogenic. To identify potential biomarkers of carcinogenicity, male F344 rats were chronically exposed to a carcinogenic dose (400mg/l) of KBrO3 in their drinking water. Kidneys were...

Exosomal microRNA profiling to identify hypoxia-related biomarkers in prostate cancer

PubMed Central

Panigrahi, Gati K.; Ramteke, Anand; Birks, Diane; Abouzeid Ali, Hamdy E.; Venkataraman, Sujatha; Agarwal, Chapla; Vibhakar, Rajeev; Miller, Lance D.; Agarwal, Rajesh; Abd Elmageed, Zakaria Y.; Deep, Gagan

2018-01-01

Hypoxia and expression of hypoxia-related biomarkers are associated with disease progression and treatment failure in prostate cancer (PCa). We have reported that exosomes (nanovesicles of 30-150 nm in diameter) secreted by human PCa cells under hypoxia promote invasiveness and stemness in naïve PCa cells. Here, we identified the unique microRNAs (miRNAs) loaded in exosomes secreted by PCa cells under hypoxia. Using TaqMan® array microRNA cards, we analyzed the miRNA profile in exosomes secreted by human PCa LNCaP cells under hypoxic (ExoHypoxic) and normoxic (ExoNormoxic) conditions. We identified 292 miRNAs loaded in both ExoHypoxic and ExoNormoxic. The top 11 miRNAs with significantly higher level in ExoHypoxic compared to ExoNormoxic were miR-517a, miR-204, miR-885, miR-143, miR-335, miR-127, miR-542, miR-433, miR-451, miR-92a and miR-181a; and top nine miRNA with significantly lower expression level in ExoHypoxic compared to ExoNormoxic were miR-521, miR-27a, miR-324, miR-579, miR-502, miR-222, miR-135b, miR-146a and miR-491. Importantly, the two differentially expressed miRNAs miR-885 (increased expression) and miR-521 (decreased expression) showed similar expression pattern in exosomes isolated from the serum of PCa patients compared to healthy individuals. Additionally, miR-204 and miR-222 displayed correlated expression patterns in prostate tumors (Pearson R = 0.66, p < 0.0001) by The Cancer Genome Atlas (TCGA) prostate adenocarcinoma (PRAD) genomic dataset analysis. Overall, the present study identified unique miRNAs with differential expression in exosomes secreted from hypoxic PCa cells and suggests their potential usefulness as a biomarker of hypoxia in PCa patients. PMID:29568403

Biomarker Development for Intraductal Papillary Mucinous Neoplasms Using Multiple Reaction Monitoring Mass Spectrometry.

PubMed

Kim, Yikwon; Kang, MeeJoo; Han, Dohyun; Kim, Hyunsoo; Lee, KyoungBun; Kim, Sun-Whe; Kim, Yongkang; Park, Taesung; Jang, Jin-Young; Kim, Youngsoo

2016-01-04

Intraductal papillary mucinous neoplasm (IPMN) is a common precursor of pancreatic cancer (PC). Much clinical attention has been directed toward IPMNs due to the increase in the prevalence of PC. The diagnosis of IPMN depends primarily on a radiological examination, but the diagnostic accuracy of this tool is not satisfactory, necessitating the development of accurate diagnostic biomarkers for IPMN to prevent PC. Recently, high-throughput targeted proteomic quantification methods have accelerated the discovery of biomarkers, rendering them powerful platforms for the evolution of IPMN diagnostic biomarkers. In this study, a robust multiple reaction monitoring (MRM) pipeline was applied to discovery and verify IPMN biomarker candidates in a large cohort of plasma samples. Through highly reproducible MRM assays and a stringent statistical analysis, 11 proteins were selected as IPMN marker candidates with high confidence in 184 plasma samples, comprising a training (n = 84) and test set (n = 100). To improve the discriminatory power, we constructed a six-protein panel by combining marker candidates. The multimarker panel had high discriminatory power in distinguishing between IPMN and controls, including other benign diseases. Consequently, the diagnostic accuracy of IPMN can be improved dramatically with this novel plasma-based panel in combination with a radiological examination.

Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

PubMed Central

McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

2016-01-01

Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Promoter Hypermethylation of Tumour Suppressor Genes as Potential Biomarkers in Colorectal Cancer

PubMed Central

Ng, Jennifer Mun-Kar; Yu, Jun

2015-01-01

Colorectal cancer (CRC) is a common malignancy and the fourth leading cause of cancer deaths worldwide. It results from the accumulation of multiple genetic and epigenetic changes leading to the transformation of colon epithelial cells into invasive adenocarcinomas. In CRC, epigenetic changes, in particular promoter CpG island methylation, occur more frequently than genetic mutations. Hypermethylation contributes to carcinogenesis by inducing transcriptional silencing or downregulation of tumour suppressor genes and currently, over 600 candidate hypermethylated genes have been identified. Over the past decade, a deeper understanding of epigenetics coupled with technological advances have hinted at the potential of translating benchtop research into biomarkers for clinical use. DNA methylation represents one of the largest bodies of literature in epigenetics, and hence has the highest potential for minimally invasive biomarker development. Most progress has been made in the development of diagnostic markers and there are currently two, one stool-based and one blood-based, biomarkers that are commercially available for diagnostics. Prognostic and predictive methylation markers are still at their infantile stages. PMID:25622259

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches.

PubMed

Checkley, William; Deza, Maria P; Klawitter, Jost; Romero, Karina M; Klawitter, Jelena; Pollard, Suzanne L; Wise, Robert A; Christians, Uwe; Hansel, Nadia N

2016-12-01

The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that

Biomarkers of PTSD: military applications and considerations.

PubMed

Lehrner, Amy; Yehuda, Rachel

2014-01-01

Although there are no established biomarkers for posttraumatic stress disorder (PTSD) as yet, biological investigations of PTSD have made progress identifying the pathophysiology of PTSD. Given the biological and clinical complexity of PTSD, it is increasingly unlikely that a single biomarker of disease will be identified. Rather, investigations will more likely identify different biomarkers that indicate the presence of clinically significant PTSD symptoms, associate with risk for PTSD following trauma exposure, and predict or identify recovery. While there has been much interest in PTSD biomarkers, there has been less discussion of their potential clinical applications, and of the social, legal, and ethical implications of such biomarkers. This article will discuss possible applications of PTSD biomarkers, including the social, legal, and ethical implications of such biomarkers, with an emphasis on military applications. Literature on applications of PTSD biomarkers and on potential ethical and legal implications will be reviewed. Biologically informed research findings hold promise for prevention, assessment, treatment planning, and the development of prophylactic and treatment interventions. As with any biological indicator of disorder, there are potentially positive and negative clinical, social, legal, and ethical consequences of using such biomarkers. Potential clinical applications of PTSD biomarkers hold promise for clinicians, patients, and employers. The search for biomarkers of PTSD should occur in tandem with an interdisciplinary discussion regarding the potential implications of applying biological findings in clinical and employment settings.

Biomarkers for monitoring intestinal health in poultry: present status and future perspectives.

PubMed

Ducatelle, Richard; Goossens, Evy; De Meyer, Fien; Eeckhaut, Venessa; Antonissen, Gunther; Haesebrouck, Freddy; Van Immerseel, Filip

2018-05-08

Intestinal health is determined by host (immunity, mucosal barrier), nutritional, microbial and environmental factors. Deficiencies in intestinal health are associated with shifts in the composition of the intestinal microbiome (dysbiosis), leakage of the mucosal barrier and/or inflammation. Since the ban on growth promoting antimicrobials in animal feed, these dysbiosis-related problems have become a major issue, especially in intensive animal farming. The economical and animal welfare consequences are considerable. Consequently, there is a need for continuous monitoring of the intestinal health status, particularly in intensively reared animals, where the intestinal function is often pushed to the limit. In the current review, the recent advances in the field of intestinal health biomarkers, both in human and veterinary medicine are discussed, trying to identify present and future markers of intestinal health in poultry. The most promising new biomarkers will be stable molecules ending up in the feces and litter that can be quantified, preferably using rapid and simple pen-side tests. It is unlikely, however, that a single biomarker will be sufficient to follow up all aspects of intestinal health. Combinations of multiple biomarkers and/or metabarcoding, metagenomic, metatranscriptomic, metaproteomic and metabolomic approaches will be the way to go in the future. Candidate biomarkers currently are being investigated by many research groups, but the validation will be a major challenge, due to the complexity of intestinal health in the field.

The serotonin system in autism spectrum disorder: from biomarker to animal models

PubMed Central

Muller, Christopher L.; Anacker, Allison M.J.; Veenstra-VanderWeele, Jeremy

2015-01-01

Elevated whole blood serotonin, or hyperserotonemia, was the first biomarker identified in autism spectrum disorder (ASD) and is present in more than 25% of affected children. The serotonin system is a logical candidate for involvement in ASD due to its pleiotropic role across multiple brain systems both dynamically and across development. Tantalizing clues connect this peripheral biomarker with changes in brain and behavior in ASD, but the contribution of the serotonin system to ASD pathophysiology remains incompletely understood. Studies of whole blood serotonin levels in ASD and in a large founder population indicate greater heritability than for the disorder itself and suggest an association with recurrence risk. Emerging data from both neuroimaging and postmortem samples also indicate changes in the brain serotonin system in ASD. Genetic linkage and association studies of both whole blood serotonin levels and of ASD risk point to the chromosomal region containing the serotonin transporter (SERT) gene in males but not in females. In ASD families with evidence of linkage to this region, multiple rare SERT amino acid variants lead to a convergent increase in serotonin uptake in cell models. A knock-in mouse model of one of these variants, SERT Gly56Ala, recapitulates the hyperserotonemia biomarker and shows increased brain serotonin clearance, increased serotonin receptor sensitivity, and altered social, communication, and repetitive behaviors. Data from other rodent models also suggest an important role for the serotonin system in social behavior, in cognitive flexibility, and in sensory development. Recent work indicates that reciprocal interactions between serotonin and other systems, such as oxytocin, may be particularly important for social behavior. Collectively, these data point to the serotonin system as a prime candidate for treatment development in a subgroup of children defined by a robust, heritable biomarker. PMID:26577932

Identification of novel biomarker candidates for hypertrophic cardiomyopathy and other cardiovascular diseases leading to heart failure.

PubMed

Rehulkova, H; Rehulka, P; Myslivcova Fucikova, A; Stulik, J; Pudil, R

2016-11-23

In-depth proteome discovery analysis represents new strategy in an effort to identify novel reliable specific protein markers for hypertrophic cardiomyopathy and other life threatening cardiovascular diseases. To systematically identify novel protein biomarkers of cardiovascular diseases with high mortality we employed an isobaric tag for relative and absolute quantitation (iTRAQ) proteome technology to make comparative analysis of plasma samples obtained from patients suffering from non-obstructive hypertrophic cardiomyopathy, stable dilated cardiomyopathy, aortic valve stenosis, chronic stable coronary artery disease and stable arterial hypertension. We found 128 plasma proteins whose abundances were uniquely regulated among the analyzed cardiovascular pathologies. 49 of them have not been described yet. Additionally, application of statistical exploratory analyses of the measured protein profiles indicated the relationship in pathophysiology of the examined cardiovascular pathologies.

Overlap of proteomics biomarkers between women with pre-eclampsia and PCOS: a systematic review and biomarker database integration

PubMed Central

Khan, Gulafshana Hafeez; Galazis, Nicolas; Docheva, Nikolina; Layfield, Robert; Atiomo, William

2015-01-01

STUDY QUESTION Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). SUMMARY ANSWER Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. WHAT IS KNOWN ALREADY Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. STUDY DESIGN, SIZE, DURATION A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. MAIN RESULTS AND THE ROLE OF CHANCE Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. LIMITATIONS, REASONS FOR CAUTION The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. WIDER IMPLICATIONS OF THE FINDINGS This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin

Heptadecanoylcarnitine (C17) a novel candidate biomarker for propionic and methylmalonic acidemias during expanded newborn screening

PubMed Central

Malvagia, Sabrina; Haynes, Christopher A.; Grisotto, Laura; Ombrone, Daniela; Funghini, Silvia; Moretti, Elisa; McGreevy, Kathleen; Buggeri, Annibale; Guerrini, Renzo; Yahyaoui, Raquel; Garg, Uttam; Seeterlin, Mary; Chace, Donald; De Jesus, Victor; la Marca, Giancarlo

2017-01-01

Background 3-hydroxypalmitoleoyl-carnitine (C16:1-OH) was recently reported to be elevated in acylcarnitine profile of propionic acidemia (PA) or methylmalonic acidemia (MMA) patients during expanded newborn screening (NBS). High levels of C16:1-OH, combined with other hydroxylated long chain acylcarnitines are related to long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD). Methods The acylcarnitine profile of two LCHADD patients was evaluated using liquid chromatography-tandem mass spectrometric method. A specific retention time was reported for each hydroxylated long chain acylcarnitine. The same method was applied to some neonatal dried blood spots (DBS) from PA and MMA patients presenting abnormal C16:1-OH concentrations. Results The final retention time of the peak corresponding to C16:1-OH in LCHADD patients differed from those in MMA and PA patients. Heptadecanoylcarnitine (C17) has been identified as the novel biomarker specific for PA and MMA patients through high resolution mass spectrometry (Orbitrap) experiments. We found that 21 out of 23 neonates (22 MMA, and 1PA) diagnosed through the Tuscany region NBS program had significantly higher levels of C17 compared to levels detected in controls. Twenty-three maternal deficiencies (21 vitamin B12 deficiency, 1 homocystinuria and 1 gastrin deficiency) and 82 false positive for propionylcarnitine (C3) results were also analyzed. Conclusions This paper reports on the characterization of a novel biomarker able to detect propionate disorders during expanded newborn screening (NBS). The use of this new biomarker may improve the analytical performances of NBS programs especially in laboratories where second tier tests are not performed. PMID:26368264

Detection of urinary biomarkers for early diagnosis of acute renal allograft rejection by proteomic analysis.

PubMed

Jia, Xiongfei; Gan, Chengjun; Xiao, Ke; He, Weifeng; Zhang, Tao; Huang, Cibing; Wu, Xiongfei; Luo, Gaoxing; Wang, Xiaojuan; Hu, Jie; Tan, Jiangling; Zhang, Xiaorong; Larsen, Peter Mose; Wu, Jun

2009-06-01

Acute allograft rejection has been recognized as a major impediment to improved success in renal transplantation. Timely detection and control of rejection are very important for the improvement in long-term renal allograft survival. Thus, biomarkers for early diagnosis of acute rejection are required urgently to clinical medication. This study seeks to search for such biomarker candidates by comparing patients' pre-treatment urinary protein profiling with their post-treatment urinary protein profiling. A total of 15 significantly and consistently down-regulated protein candidates were identified. Among them, alpha-1-antichymotrypsin precursor (AACT), tumor rejection antigen gp96 (GP96) and Zn-Alpha-2-Glycoprotein (ZAG) were selected for further analysis. The results indicated that Western Blot assay of AACT, GP96 and ZAG had advanced the diagnosis time of acute renal rejection by 3 days, compared with current standard clinical observation and laboratory examination. Furthermore, the double-blind detection revealed that the accuracy, sensitivity and specificity of the diagnosis of acute renal rejection of AACT, GP96 and ZAG were 66.67%/100%/60%, 83.33%/100%/80% and 66.67%/100%/60%, respectively, and 100%/100%/100% in combination. In conclusion, urinary protein AACT, GP96 and ZAG could be a set of potential biomarkers for early non-invasive diagnosis of the acute rejection after renal transplantation. Copyright © 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

PubMed

San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean.

PubMed

Zhong, Chao; Sun, Suli; Li, Yinping; Duan, Canxing; Zhu, Zhendong

2018-03-01

A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F 2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.

Rapid Point-Of-Care Breath Test for Biomarkers of Breast Cancer and Abnormal Mammograms

PubMed Central

Phillips, Michael; Beatty, J. David; Cataneo, Renee N.; Huston, Jan; Kaplan, Peter D.; Lalisang, Roy I.; Lambin, Philippe; Lobbes, Marc B. I.; Mundada, Mayur; Pappas, Nadine; Patel, Urvish

2014-01-01

Background Previous studies have reported volatile organic compounds (VOCs) in breath as biomarkers of breast cancer and abnormal mammograms, apparently resulting from increased oxidative stress and cytochrome p450 induction. We evaluated a six-minute point-of-care breath test for VOC biomarkers in women screened for breast cancer at centers in the USA and the Netherlands. Methods 244 women had a screening mammogram (93/37 normal/abnormal) or a breast biopsy (cancer/no cancer 35/79). A mobile point-of-care system collected and concentrated breath and air VOCs for analysis with gas chromatography and surface acoustic wave detection. Chromatograms were segmented into a time series of alveolar gradients (breath minus room air). Segmental alveolar gradients were ranked as candidate biomarkers by C-statistic value (area under curve [AUC] of receiver operating characteristic [ROC] curve). Multivariate predictive algorithms were constructed employing significant biomarkers identified with multiple Monte Carlo simulations and cross validated with a leave-one-out (LOO) procedure. Results Performance of breath biomarker algorithms was determined in three groups: breast cancer on biopsy versus normal screening mammograms (81.8% sensitivity, 70.0% specificity, accuracy 79% (73% on LOO) [C-statistic value], negative predictive value 99.9%); normal versus abnormal screening mammograms (86.5% sensitivity, 66.7% specificity, accuracy 83%, 62% on LOO); and cancer versus no cancer on breast biopsy (75.8% sensitivity, 74.0% specificity, accuracy 78%, 67% on LOO). Conclusions A pilot study of a six-minute point-of-care breath test for volatile biomarkers accurately identified women with breast cancer and with abnormal mammograms. Breath testing could potentially reduce the number of needless mammograms without loss of diagnostic sensitivity. PMID:24599224

Inflammation: an important parameter in the search of prostate cancer biomarkers

PubMed Central

2014-01-01

other 2 were new proteins, not identified in our previous comparisons. Conclusions The present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa. PMID:24944525

Molecular biomarkers in idiopathic pulmonary fibrosis

PubMed Central

Ley, Brett; Brown, Kevin K.

2014-01-01

Molecular biomarkers are highly desired in idiopathic pulmonary fibrosis (IPF), where they hold the potential to elucidate underlying disease mechanisms, accelerated drug development, and advance clinical management. Currently, there are no molecular biomarkers in widespread clinical use for IPF, and the search for potential markers remains in its infancy. Proposed core mechanisms in the pathogenesis of IPF for which candidate markers have been offered include alveolar epithelial cell dysfunction, immune dysregulation, and fibrogenesis. Useful markers reflect important pathological pathways, are practically and accurately measured, have undergone extensive validation, and are an improvement upon the current approach for their intended use. The successful development of useful molecular biomarkers is a central challenge for the future of translational research in IPF and will require collaborative efforts among those parties invested in advancing the care of patients with IPF. PMID:25260757

Prognostic Biomarkers Used for Localised Prostate Cancer Management: A Systematic Review.

PubMed

Lamy, Pierre-Jean; Allory, Yves; Gauchez, Anne-Sophie; Asselain, Bernard; Beuzeboc, Philippe; de Cremoux, Patricia; Fontugne, Jacqueline; Georges, Agnès; Hennequin, Christophe; Lehmann-Che, Jacqueline; Massard, Christophe; Millet, Ingrid; Murez, Thibaut; Schlageter, Marie-Hélène; Rouvière, Olivier; Kassab-Chahmi, Diana; Rozet, François; Descotes, Jean-Luc; Rébillard, Xavier

2017-03-07

Prostate cancer stratification is based on tumour size, pretreatment PSA level, and Gleason score, but it remains imperfect. Current research focuses on the discovery and validation of novel prognostic biomarkers to improve the identification of patients at risk of aggressive cancer or of tumour relapse. This systematic review by the Intergroupe Coopérateur Francophone de Recherche en Onco-urologie (ICFuro) analysed new evidence on the analytical validity and clinical validity and utility of six prognostic biomarkers (PHI, 4Kscore, MiPS, GPS, Prolaris, Decipher). All available data for the six biomarkers published between January 2002 and April 2015 were systematically searched and reviewed. The main endpoints were aggressive prostate cancer prediction, additional value compared to classical prognostic parameters, and clinical benefit for patients with localised prostate cancer. The preanalytical and analytical validations were heterogeneous for all tests and often not adequate for the molecular signatures. Each biomarker was studied for specific indications (candidates for a first or second biopsy, and potential candidates for active surveillance, radical prostatectomy, or adjuvant treatment) for which the level of evidence (LOE) was variable. PHI and 4Kscore were the biomarkers with the highest LOE for discriminating aggressive and indolent tumours in different indications. Blood biomarkers (PHI and 4Kscore) have the highest LOE for the prediction of more aggressive prostate cancer and could help clinicians to manage patients with localised prostate cancer. The other biomarkers show a potential prognostic value; however, they should be evaluated in additional studies to confirm their clinical validity. We reviewed studies assessing the value of six prognostic biomarkers for prostate cancer. On the basis of the available evidence, some biomarkers could help in discriminating between aggressive and non-aggressive tumours with an additional value compared to the

Potential metabolomic biomarkers for reliable diagnosis of Behcet's disease using gas chromatography/ time-of-flight-mass spectrometry.

PubMed

Ahn, Joong Kyong; Kim, Jungyeon; Hwang, Jiwon; Song, Juhwan; Kim, Kyoung Heon; Cha, Hoon-Suk

2018-05-01

Although many diagnostic criteria of Behcet's disease (BD) have been developed and revised by experts, diagnosing BD is still complicated and challenging. No metabolomic studies on serum have been attempted to improve the diagnosis and to identify potential biomarkers of BD. The purposes of this study were to investigate distinctive metabolic changes in serum samples of BD patients and to identify metabolic candidate biomarkers for reliable diagnosis of BD using the metabolomics platform. Metabolomic profiling of 90 serum samples from 45 BD patients and 45 healthy controls (HCs) were performed via gas chromatography with time-of-flight mass spectrometry (GC/TOF-MS) with multivariate statistical analyses. A total of 104 metabolites were identified from samples. The serum metabolite profiles obtained from GC/TOF-MS analysis can distinguish BD patients from HC group in discovery set. The variation values of the partial least squared-discrimination analysis (PLS-DA) model are R 2 X of 0.246, R 2 Y of 0.913 and Q 2 of 0.852, respectively, indicating strong explanation and prediction capabilities of the model. A panel of five metabolic biomarkers, namely, decanoic acid, fructose, tagatose, linoleic acid and oleic acid were selected and adequately validated as putative biomarkers of BD (sensitivity 100%, specificity 97.1%, area under the curve 0.998) in the discovery set and independent set. The PLS_DA model showed clear discrimination of BD and HC groups by the five metabolic biomarkers in independent set. This is the first report on characteristic metabolic profiles and potential metabolite biomarkers in serum for reliable diagnosis of BD using GC/TOF-MS. Copyright © 2017. Published by Elsevier SAS.

Evaluating biomarkers to model cancer risk post cosmic ray exposure

PubMed Central

Sridhara, Deepa M.; Asaithamby, Aroumougame; Blattnig, Steve R.; Costes, Sylvain V.; Doetsch, Paul W.; Dynan, William S.; Hahnfeldt, Philip; Hlatky, Lynn; Kidane, Yared; Kronenberg, Amy; Naidu, Mamta D.; Peterson, Leif E.; Plante, Ianik; Ponomarev, Artem L.; Saha, Janapriya; Snijders, Antoine M.; Srinivasan, Kalayarasan; Tang, Jonathan; Werner, Erica; Pluth, Janice M.

2017-01-01

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing

Evaluating biomarkers to model cancer risk post cosmic ray exposure

NASA Astrophysics Data System (ADS)

Sridharan, Deepa M.; Asaithamby, Aroumougame; Blattnig, Steve R.; Costes, Sylvain V.; Doetsch, Paul W.; Dynan, William S.; Hahnfeldt, Philip; Hlatky, Lynn; Kidane, Yared; Kronenberg, Amy; Naidu, Mamta D.; Peterson, Leif E.; Plante, Ianik; Ponomarev, Artem L.; Saha, Janapriya; Snijders, Antoine M.; Srinivasan, Kalayarasan; Tang, Jonathan; Werner, Erica; Pluth, Janice M.

2016-06-01

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing

Biomarkers for Allergen Immunotherapy: A "Panoromic" View.

PubMed

Moingeon, Philippe

2016-02-01

Biomarkers (BMKs) are biological parameters that can be measured to predict or monitor disease severity or treatment efficacy. The induction of regulatory dendritic cells (DCs) concomitantly with a downregulation of proallergic DC2s (ie, DCs supporting the differentiation of T-helper lymphocyte type 2 cells) in the blood of patients allergic to grass pollen has been correlated with the early onset of allergen immunotherapy efficacy. The combined use of omics technologies to compare biological samples from clinical responders and nonresponders is being implemented in the context of nonhypothesis-driven approaches. Such comprehensive "panoromic" strategies help identify completely novel candidate BMKs, to be subsequently validated as companion diagnostics in large-scale clinical trials. Copyright © 2016 Elsevier Inc. All rights reserved.

Lipid Biomarkers in Acute Myocardial Infarction Before and After Percutaneous Coronary Intervention by Lipidomics Analysis.

PubMed

Feng, Limin; Yang, Jianzhou; Liu, Wennan; Wang, Qing; Wang, Huijie; Shi, Le; Fu, Liyan; Xu, Qiang; Wang, Baohe; Li, Tian

2018-06-18

BACKGROUND Reperfusion injury is one of the leading causes of myocardial cell death and heart failure. This study was performed to identify new candidate lipid biomarkers for the purpose of optimizing the diagnosis of myocardial ischemia reperfusion (I/R) injury, assessing the severity of myocardial I/R injury and trying to find the novel mechanism related to lipids. MATERIAL AND METHODS Forty patients who were diagnosed with ST-segment elevation myocardial infarction (STEMI) were randomly selected for this study. Serum samples from all the patients with STEMI were collected at 3 time periods: after STEMI diagnosis but prior to reperfusion (T0); and then at 2 hours (T2) and 24 hours (T24) after the end of the percutaneous coronary intervention procedure. Plasma lipidomics profiling analysis was performed to identify the lipid metabolic signatures of myocardial I/R injury using lipidomics. RESULTS Sixteen types of potential lipid biomarkers at different time periods (T0, T2, T24) were identified by using lipidomics technology. The T0 time periods exhibited 16 differentially metabolized lipid peaks in the patients after STEMI diagnosis but prior to reperfusion. With the increase of reperfusion times, the contents of these 16 lipid biomarkers decreased gradually, but there was a 1.5- to 2-fold increase of those 16 lipid biomarkers contents at T2 compared with T24. CONCLUSIONS Lipidomics analysis demonstrated differential change before and after reperfusion, suggesting a potential role of some of these lipids as biomarkers for optimizing the diagnosis of myocardial I/R, as well as for therapeutic targets against myocardial I/R injury.

A new biomarker panel in bronchoalveolar lavage for an improved lung cancer diagnosis.

PubMed

Uribarri, María; Hormaeche, Itsaso; Zalacain, Rafael; Lopez-Vivanco, Guillermo; Martinez, Antonio; Nagore, Daniel; Ruiz-Argüello, M Begoña

2014-10-01

The enormous biological complexity and high mortality rate of lung cancer highlights the need for new global approaches for the discovery of reliable early diagnostic biomarkers. The study of bronchoalveolar lavage samples by proteomic techniques could identify new lung cancer biomarkers and may provide promising noninvasive diagnostic tools able to enhance the sensitivity of current methods. First, an observational prospective study was designed to assess protein expression differences in bronchoalveolar lavages from patients with (n = 139) and without (n = 49) lung cancer, using two-dimensional gel electrophoresis and subsequent protein identification by mass spectrometry. Second, validation of candidate biomarkers was performed by bead-based immunoassays with a different patient cohort (204 patients, 48 controls). Thirty-two differentially expressed proteins were identified in bronchoalveolar lavages, 10 of which were confirmed by immunoassays. The expression levels of APOA1, CO4A, CRP, GSTP1, and SAMP led to a lung cancer diagnostic panel that reached 95% sensitivity and 81% specificity, and the quantification of STMN1 and GSTP1 proteins allowed the two main lung cancer subtypes to be discriminated with 90% sensitivity and 57% specificity. Bronchoalveolar lavage represents a promising noninvasive source of lung cancer specific protein biomarkers with high diagnostic accuracy. Measurement of APOA1, CO4A, CRP, GSTP1, SAMP, and STMN1 in this fluid may be a useful tool for lung cancer diagnosis, although a further validation in a larger clinical set is required for early stages.

Endocannabinoids as biomarkers of human reproduction.

PubMed

Rapino, Cinzia; Battista, Natalia; Bari, Monica; Maccarrone, Mauro

2014-01-01

Infertility is a condition of the reproductive system that affects ∼10-15% of couples attempting to conceive a baby. More than half of all cases of infertility are a result of female conditions, while the remaining cases can be attributed to male factors, or to a combination of both. The search for suitable biomarkers of pregnancy outcome is a challenging issue in human reproduction, aimed at identifying molecules with predictive significance of the reproductive potential of male and female gametes. Among the various candidates, endocannabinoids (eCBs), and in particular anandamide (AEA), represent potential biomarkers of human fertility disturbances. Any perturbation of the balance between synthesis and degradation of eCBs will result in local changes of their tone in human female and male reproductive tracts, which in turn regulates various pathophysiological processes, oocyte and sperm maturation included. PubMed and Web of Science databases were searched for papers using relevant keywords like 'biomarker', 'endocannabinoid', 'infertility', 'pregnancy' and 'reproduction'. In this review, we discuss different studies on the measurements of AEA and related eCBs in human reproductive cells, tissues and fluids, where the local contribution of these bioactive lipids could be critical in ensuring normal sperm fertilizing ability and pregnancy. Based on the available data, we suggest that the AEA tone has the potential to be exploited as a novel diagnostic biomarker of infertility, to be used in association with assays of conventional hormones (e.g. progesterone, β-chorionic gonadotrophin) and semen analysis. However further quantitative research of its predictive capacity is required. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identifying Individual Differences among Doctoral Candidates: A Framework for Understanding Problematic Candidature

ERIC Educational Resources Information Center

Cantwell, Robert H.; Scevak, Jill J.; Bourke, Sid; Holbrook, Allyson

2012-01-01

Understanding how candidates cope with the demands of PhD candidature is important for institutions, supervisors and candidates. Individual differences in affective and metacognitive disposition were explored in 263 PhD candidates from two Australian universities. Several questionnaires relating to affective and metacognitive beliefs were…

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

PubMed Central

Morton, Nicholas M.; Nelson, Yvonne B.; Michailidou, Zoi; Di Rollo, Emma M.; Ramage, Lynne; Hadoke, Patrick W. F.; Seckl, Jonathan R.; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J.; Dunbar, Donald R.

2011-01-01

Background Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. Results To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. Conclusions A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes

Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

PubMed

Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

2012-12-01

To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Evaluating Candidate Principal Surrogate Endpoints

PubMed Central

Gilbert, Peter B.; Hudgens, Michael G.

2009-01-01

Summary Frangakis and Rubin (2002, Biometrics 58, 21–29) proposed a new definition of a surrogate endpoint (a “principal” surrogate) based on causal effects. We introduce an estimand for evaluating a principal surrogate, the causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. Although the CEP surface is not identifiable due to missing potential outcomes, it can be identified by incorporating a baseline covariate(s) that predicts the biomarker. Given case–cohort sampling of such a baseline predictor and the biomarker in a large blinded randomized clinical trial, we develop an estimated likelihood method for estimating the CEP surface. This estimation assesses the “surrogate value” of the biomarker for reliably predicting clinical treatment effects for the same or similar setting as the trial. A CEP surface plot provides a way to compare the surrogate value of multiple biomarkers. The approach is illustrated by the problem of assessing an immune response to a vaccine as a surrogate endpoint for infection. PMID:18363776

Oral biomarkers in exercise-induced neuroplasticity in Parkinson's disease.

PubMed

Mougeot, J-Lc; Hirsch, M A; Stevens, C B; Mougeot, Fkb

2016-11-01

In this article, we review candidate biomarkers for Parkinson's disease (PD) in oral cavity, potential of oral biomarkers as markers of neuroplasticity, and literature on the effects of exercise on oral cavity biomarkers in PD. We first describe how pathophysiological pathways of PD may be transduced from brain stem and ganglia to oral cavity through the autonomic nervous system or transduced by a reverse path. Next we describe the effects of exercise in PD and potential impact on oral cavity. We propose that biomarkers in oral cavity may be useful targets for describing exercise-induced brain neuroplasticity in PD. Nevertheless, much research remains to be carried out before applying these biomarkers for the determination of disease state and therapeutic response to develop strategies to mitigate motor or non-motor symptoms in PD. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

PubMed Central

Arellano-Garcia, Martha E.; Li, Roger; Liu, Xiaojun; Xie, Yongming; Yan, Xiaofei; Loo, Joseph A.; Hu, Shen

2010-01-01

Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC). A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B). We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients. PMID:20957082

Genomic analysis, cytokine expression, and microRNA profiling reveal biomarkers of human dietary zinc depletion and homeostasis.

PubMed

Ryu, Moon-Suhn; Langkamp-Henken, Bobbi; Chang, Shou-Mei; Shankar, Meena N; Cousins, Robert J

2011-12-27

Implementation of zinc interventions for subjects suspected of being zinc-deficient is a global need, but is limited due to the absence of reliable biomarkers. To discover molecular signatures of human zinc deficiency, a combination of transcriptome, cytokine, and microRNA analyses was applied to a dietary zinc depletion/repletion protocol with young male human subjects. Concomitant with a decrease in serum zinc concentration, changes in buccal and blood gene transcripts related to zinc homeostasis occurred with zinc depletion. Microarray analyses of whole blood RNA revealed zinc-responsive genes, particularly, those associated with cell cycle regulation and immunity. Responses of potential signature genes of dietary zinc depletion were further assessed by quantitative real-time PCR. The diagnostic properties of specific serum microRNAs for dietary zinc deficiency were identified by acute responses to zinc depletion, which were reversible by subsequent zinc repletion. Depression of immune-stimulated TNFα secretion by blood cells was observed after low zinc consumption and may serve as a functional biomarker. Our findings introduce numerous novel candidate biomarkers for dietary zinc status assessment using a variety of contemporary technologies and which identify changes that occur prior to or with greater sensitivity than the serum zinc concentration which represents the current zinc status assessment marker. In addition, the results of gene network analysis reveal potential clinical outcomes attributable to suboptimal zinc intake including immune function defects and predisposition to cancer. These demonstrate through a controlled depletion/repletion dietary protocol that the illusive zinc biomarker(s) can be identified and applied to assessment and intervention strategies.

Emerging biomarkers in breast cancer care.

PubMed

Napieralski, Rudolf; Brünner, Nils; Mengele, Karin; Schmitt, Manfred

2010-08-01

Currently, decision-making for breast cancer treatment in the clinical setting is mainly based on clinical data, histomorphological features of the tumor tissue and a few cancer biomarkers such as steroid hormone receptor status (estrogen and progesterone receptors) and oncoprotein HER2 status. Although various therapeutic options were introduced into the clinic in recent decades, with the objective of improving surgery, radiotherapy, biochemotherapy and chemotherapy, varying response of individual patients to certain types of therapy and therapy resistance is still a challenge in breast cancer care. Therefore, since breast cancer treatment should be based on individual features of the patient and her tumor, tailored therapy should be an option by integrating cancer biomarkers to define patients at risk and to reliably predict their course of the disease and/or response to cancer therapy. Recently, candidate-marker approaches and genome-wide transcriptomic and epigenetic screening of different breast cancer tissues and bodily fluids resulted in new promising biomarker panels, allowing breast cancer prognosis, prediction of therapy response and monitoring of therapy efficacy. These biomarkers are now subject of validation in prospective clinical trials.

Biomarkers in Autism

PubMed Central

Goldani, Andre A. S.; Downs, Susan R.; Widjaja, Felicia; Lawton, Brittany; Hendren, Robert L.

2014-01-01

Autism spectrum disorders (ASDs) are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression, and measures of the body’s metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers. PMID:25161627

Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.

PubMed

Mallik, Saurav; Bhadra, Tapas; Maulik, Ujjwal

2017-01-01

Epigenetic Biomarker discovery is an important task in bioinformatics. In this article, we develop a new framework of identifying statistically significant epigenetic biomarkers using maximal-relevance and minimal-redundancy criterion based feature (gene) selection for multi-omics dataset. Firstly, we determine the genes that have both expression as well as methylation values, and follow normal distribution. Similarly, we identify the genes which consist of both expression and methylation values, but do not follow normal distribution. For each case, we utilize a gene-selection method that provides maximal-relevant, but variable-weighted minimum-redundant genes as top ranked genes. For statistical validation, we apply t-test on both the expression and methylation data consisting of only the normally distributed top ranked genes to determine how many of them are both differentially expressed andmethylated. Similarly, we utilize Limma package for performing non-parametric Empirical Bayes test on both expression and methylation data comprising only the non-normally distributed top ranked genes to identify how many of them are both differentially expressed and methylated. We finally report the top-ranking significant gene-markerswith biological validation. Moreover, our framework improves positive predictive rate and reduces false positive rate in marker identification. In addition, we provide a comparative analysis of our gene-selection method as well as othermethods based on classificationperformances obtained using several well-known classifiers.

Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

PubMed Central

Bii, Victor M.; Trobridge, Grant D.

2016-01-01

Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types. PMID:27792127

Selection on plant male function genes identifies candidates for reproductive isolation of yellow monkeyflowers.

PubMed

Aagaard, Jan E; George, Renee D; Fishman, Lila; Maccoss, Michael J; Swanson, Willie J

2013-01-01

Understanding the genetic basis of reproductive isolation promises insight into speciation and the origins of biological diversity. While progress has been made in identifying genes underlying barriers to reproduction that function after fertilization (post-zygotic isolation), we know much less about earlier acting pre-zygotic barriers. Of particular interest are barriers involved in mating and fertilization that can evolve extremely rapidly under sexual selection, suggesting they may play a prominent role in the initial stages of reproductive isolation. A significant challenge to the field of speciation genetics is developing new approaches for identification of candidate genes underlying these barriers, particularly among non-traditional model systems. We employ powerful proteomic and genomic strategies to study the genetic basis of conspecific pollen precedence, an important component of pre-zygotic reproductive isolation among yellow monkeyflowers (Mimulus spp.) resulting from male pollen competition. We use isotopic labeling in combination with shotgun proteomics to identify more than 2,000 male function (pollen tube) proteins within maternal reproductive structures (styles) of M. guttatus flowers where pollen competition occurs. We then sequence array-captured pollen tube exomes from a large outcrossing population of M. guttatus, and identify those genes with evidence of selective sweeps or balancing selection consistent with their role in pollen competition. We also test for evidence of positive selection on these genes more broadly across yellow monkeyflowers, because a signal of adaptive divergence is a common feature of genes causing reproductive isolation. Together the molecular evolution studies identify 159 pollen tube proteins that are candidate genes for conspecific pollen precedence. Our work demonstrates how powerful proteomic and genomic tools can be readily adapted to non-traditional model systems, allowing for genome-wide screens towards the

Detection of an endogenous urinary biomarker associated with CYP2D6 activity using global metabolomics.

PubMed

Tay-Sontheimer, Jessica; Shireman, Laura M; Beyer, Richard P; Senn, Taurence; Witten, Daniela; Pearce, Robin E; Gaedigk, Andrea; Gana Fomban, Cletus L; Lutz, Justin D; Isoherranen, Nina; Thummel, Kenneth E; Fiehn, Oliver; Leeder, J Steven; Lin, Yvonne S

2014-12-01

We sought to discover endogenous urinary biomarkers of human CYP2D6 activity. Healthy pediatric subjects (n = 189) were phenotyped using dextromethorphan and randomized for candidate biomarker selection and validation. Global urinary metabolomics was performed using liquid chromatography quadrupole time-of-flight mass spectrometry. Candidate biomarkers were tested in adults receiving fluoxetine, a CYP2D6 inhibitor. A biomarker, M1 (m/z 444.3102) was correlated with CYP2D6 activity in both the pediatric training and validation sets. Poor metabolizers had undetectable levels of M1, whereas it was present in subjects with other phenotypes. In adult subjects, a 9.56-fold decrease in M1 abundance was observed during CYP2D6 inhibition. Identification and validation of M1 may provide a noninvasive means of CYP2D6 phenotyping.

Prognostic biomarkers in osteoarthritis

PubMed Central

Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

2013-01-01

Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

Cardiovascular risk assessment of dyslipidemic children: analysis of biomarkers to identify monogenic dyslipidemia[S

PubMed Central

Medeiros, Ana Margarida; Alves, Ana Catarina; Aguiar, Pedro; Bourbon, Mafalda

2014-01-01

The distinction between a monogenic dyslipidemia and a polygenic/environmental dyslipidemia is important for the cardiovascular risk assessment, counseling, and treatment of these patients. The present work aims to perform the cardiovascular risk assessment of dyslipidemic children to identify useful biomarkers for clinical criteria improvement in clinical settings. Main cardiovascular risk factors were analyzed in a cohort of 237 unrelated children with clinical diagnosis of familial hypercholesterolemia (FH). About 40% carried at least two cardiovascular risk factors and 37.6% had FH, presenting mutations in LDLR and APOB. FH children showed significant elevated atherogenic markers and lower concentration of antiatherogenic particles. Children without a molecular diagnosis of FH had higher levels of TGs, apoC2, apoC3, and higher frequency of BMI and overweight/obesity, suggesting that environmental factors can be the underlying cause of their hypercholesterolem≥ia. An apoB/apoA1 ratio ≥0.68 was identified as the best biomarker (area under the curve = 0.835) to differentiate FH from other dyslipidemias. The inclusion in clinical criteria of a higher cut-off point for LDL cholesterol or an apoB/apoA1 ratio ≥0.68 optimized the criteria sensitivity and specificity. The correct identification, at an early age, of all children at-risk is of great importance so that specific interventions can be implemented. apoB/apoA1 can improve the identification of FH patients. PMID:24627126

Biomarker discovery and development in pediatric critical care medicine

PubMed Central

Kaplan, Jennifer M.; Wong, Hector R.

2010-01-01

Objective To frame the general process of biomarker discovery and development, and to describe a proposal for the development of a multi-biomarker based risk model for pediatric septic shock. Data Source Narrative literature review and author generated data. Main Results Biomarkers can be grouped into four broad classes, based on the intended function: diagnostic, monitoring, surrogate, and stratification. Biomarker discovery and development requires a rigorous process, which is frequently not well followed in the critical care medicine literature. Very few biomarkers have successfully transitioned from the candidate stage to the true biomarker stage. There is great interest in developing diagnostic and stratification biomarkers for sepsis. Procalcitonin is currently the most promising diagnostic biomarker for sepsis. Recent evidence suggests that interleukin-8 can be used to stratify children with septic shock having a high likelihood of survival with standard care. Currently, there is a multi-institutional effort to develop a multi-biomarker based sepsis risk model intended to predict outcome and illness severity for individual children with septic shock. Conclusions Biomarker discovery and development is an important portion of the pediatric critical care medicine translational research agenda. This effort will require collaboration across multiple institutions and investigators. Rigorous conduct of biomarker-focused research holds the promise of transforming our ability to care for individual patients and our ability to conduct clinical trials in a more effective manner. PMID:20473243

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.

Diagnostic function of the neuroinflammatory biomarker YKL-40 in Alzheimer's disease and other neurodegenerative diseases.

PubMed

Baldacci, Filippo; Lista, Simone; Cavedo, Enrica; Bonuccelli, Ubaldo; Hampel, Harald

2017-04-01

Neuroinflammation is a crucial mechanism in the pathophysiology of neurodegenerative diseases pathophysiology. Cerebrospinal fluid (CSF) YKL-40 - an indicator of microglial activation - has recently been identified by proteomic studies as a candidate biomarker for Alzheimer's disease (AD). Areas covered: We review the impact of CSF YKL-40 as a pathophysiological biomarker for AD and other neurodegenerative diseases. CSF YKL-40 concentrations have been shown to predict progression from prodromal mild cognitive impairment to AD dementia. Moreover, a positive association between CSF YKL-40 and other biomarkers of neurodegeneration - particularly total tau protein - has been reported during the asymptomatic preclinical stage of AD and other neurodegenerative diseases. Albeit preliminary, current data do not support an association between APOE-ε4 status and CSF YKL-40 concentrations. When interpreting the diagnostic/prognostic significance of CSF YKL-40 concentrations in neurodegenerative diseases, potential confounders - including age, metabolic and cardiovascular risk factors, diagnostic criteria for selecting cases/controls - need to be considered. Expert opinion/commentary: CSF YKL-40 represents a pathophysiological biomarker reflecting immune/inflammatory mechanisms in neurodegenerative diseases, associated with tau protein pathology. Besides being associated with tau pathology, CSF YKL-40 adds to the growing array of biomarkers reflecting distinct molecular brain mechanisms potentially useful for stratifying individuals for biomarker-guided, targeted anti-inflammatory therapies emerging from precision medicine.

Nonclinical safety biomarkers of drug-induced vascular injury: current status and blueprint for the future.

PubMed

Mikaelian, Igor; Cameron, Mark; Dalmas, Deidre A; Enerson, Bradley E; Gonzalez, Raymond J; Guionaud, Silvia; Hoffmann, Peter K; King, Nicholas M P; Lawton, Michael P; Scicchitano, Marshall S; Smith, Holly W; Thomas, Roberta A; Weaver, James L; Zabka, Tanja S

2014-06-01

Better biomarkers are needed to identify, characterize, and/or monitor drug-induced vascular injury (DIVI) in nonclinical species and patients. The Predictive Safety Testing Consortium (PSTC), a precompetitive collaboration of pharmaceutical companies and the U.S. Food and Drug Administration (FDA), formed the Vascular Injury Working Group (VIWG) to develop and qualify translatable biomarkers of DIVI. The VIWG focused its research on acute DIVI because early detection for clinical and nonclinical safety monitoring is desirable. The VIWG developed a strategy based on the premise that biomarkers of DIVI in rat would be translatable to humans due to the morphologic similarity of vascular injury between species regardless of mechanism. The histomorphologic lexicon for DIVI in rat defines degenerative and adaptive findings of the vascular endothelium and smooth muscles, and characterizes inflammatory components. We describe the mechanisms of these changes and their associations with candidate biomarkers for which advanced analytical method validation was completed. Further development is recommended for circulating microRNAs, endothelial microparticles, and imaging techniques. Recommendations for sample collection and processing, analytical methods, and confirmation of target localization using immunohistochemistry and in situ hybridization are described. The methods described are anticipated to aid in the identification and qualification of translational biomarkers for DIVI. © 2014 by The Author(s).

Epitope presentation is an important determinant of the utility of antigens identified from protein arrays in the development of autoantibody diagnostic assays.

PubMed

Murphy, Mairead A; O'Connell, David J; O'Kane, Sara L; O'Brien, John K; O'Toole, Sharon; Martin, Cara; Sheils, Orla; O'Leary, John J; Cahill, Dolores J

2012-08-03

Autoantibodies represent an attractive biomarker for diagnostic assays principally due to the stability of immunoglobulin in patient serum facilitating measurement with conventional assays. Immune responses to tumorigenesis may facilitate detection of ovarian cancer in the early stages of the disease with identification of a panel of tumour specific autoantibodies. Despite the reporting of many tumour associated autoantibodies using arrays of tumour antigens, this has not led to the advance in diagnostic capability as rapidly as was initially expected. Here we examine the potential diagnostic utility of candidate autoantibody biomarkers identified via screening of serum samples on a high content human protein array from a unique cohort of early stage and late stage ovarian cancer patients. We analyse the performance of autoantibodies to the tumour suppressor protein p53 and the novel autoantigens alpha adducin and endosulfine alpha identified in our array screen. Each antigen has different performance characteristics using conventional ELISA format and Western blot immunoassay. The high attrition rate of promising autoantigens identified by array screening can in part be explained by the presentation of the epitope of the antigen in the subsequent method of validation and this study provides directions on maximising the potential of candidate biomarkers. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Exome Sequencing and Linkage Analysis Identified Novel Candidate Genes in Recessive Intellectual Disability Associated with Ataxia.

PubMed

Jazayeri, Roshanak; Hu, Hao; Fattahi, Zohreh; Musante, Luciana; Abedini, Seyedeh Sedigheh; Hosseini, Masoumeh; Wienker, Thomas F; Ropers, Hans Hilger; Najmabadi, Hossein; Kahrizi, Kimia

2015-10-01

Intellectual disability (ID) is a neuro-developmental disorder which causes considerable socio-economic problems. Some ID individuals are also affected by ataxia, and the condition includes different mutations affecting several genes. We used whole exome sequencing (WES) in combination with homozygosity mapping (HM) to identify the genetic defects in five consanguineous families among our cohort study, with two affected children with ID and ataxia as major clinical symptoms. We identified three novel candidate genes, RIPPLY1, MRPL10, SNX14, and a new mutation in known gene SURF1. All are autosomal genes, except RIPPLY1, which is located on the X chromosome. Two are housekeeping genes, implicated in transcription and translation regulation and intracellular trafficking, and two encode mitochondrial proteins. The pathogenesis of these variants was evaluated by mutation classification, bioinformatic methods, review of medical and biological relevance, co-segregation studies in the particular family, and a normal population study. Linkage analysis and exome sequencing of a small number of affected family members is a powerful new technique which can be used to decrease the number of candidate genes in heterogenic disorders such as ID, and may even identify the responsible gene(s).

Whole-exome sequencing identifies novel candidate predisposition genes for familial polycythemia vera.

PubMed

Hirvonen, Elina A M; Pitkänen, Esa; Hemminki, Kari; Aaltonen, Lauri A; Kilpivaara, Outi

2017-04-20

Polycythemia vera (PV), characterized by massive production of erythrocytes, is one of the myeloproliferative neoplasms. Most patients carry a somatic gain-of-function mutation in JAK2, c.1849G > T (p.Val617Phe), leading to constitutive activation of JAK-STAT signaling pathway. Familial clustering is also observed occasionally, but high-penetrance predisposition genes to PV have remained unidentified. We studied the predisposition to PV by exome sequencing (three cases) in a Finnish PV family with four patients. The 12 shared variants (maximum allowed minor allele frequency <0.001 in Finnish population in ExAC database) predicted damaging in silico and absent in an additional control set of over 500 Finns were further validated by Sanger sequencing in a fourth affected family member. Three novel predisposition candidate variants were identified: c.1254C > G (p.Phe418Leu) in ZXDC, c.1931C > G (p.Pro644Arg) in ATN1, and c.701G > A (p.Arg234Gln) in LRRC3. We also observed a rare, predicted benign germline variant c.2912C > G (p.Ala971Gly) in BCORL1 in all four patients. Somatic mutations in BCORL1 have been reported in myeloid malignancies. We further screened the variants in eight PV patients in six other Finnish families, but no other carriers were found. Exome sequencing provides a powerful tool for the identification of novel variants, and understanding the familial predisposition of diseases. This is the first report on Finnish familial PV cases, and we identified three novel candidate variants that may predispose to the disease.

Biomarker Discovery for Early Detection of Hepatocellular Carcinoma in Hepatitis C–infected Patients*

PubMed Central

Mustafa, Mehnaz G.; Petersen, John R.; Ju, Hyunsu; Cicalese, Luca; Snyder, Ned; Haidacher, Sigmund J.; Denner, Larry; Elferink, Cornelis

2013-01-01

Chronic hepatic disease damages the liver, and the resulting wound-healing process leads to liver fibrosis and the subsequent development of cirrhosis. The leading cause of hepatic fibrosis and cirrhosis is infection with hepatitis C virus (HCV), and of the patients with HCV-induced cirrhosis, 2% to 5% develop hepatocellular carcinoma (HCC), with a survival rate of 7%. HCC is one of the leading causes of cancer-related death worldwide, and the poor survival rate is largely due to late-stage diagnosis, which makes successful intervention difficult, if not impossible. The lack of sensitive and specific diagnostic tools and the urgent need for early-stage diagnosis prompted us to discover new candidate biomarkers for HCV and HCC. We used aptamer-based fractionation technology to reduce serum complexity, differentially labeled samples (six HCV and six HCC) with fluorescent dyes, and resolved proteins in pairwise two-dimensional difference gel electrophoresis. DeCyder software was used to identify differentially expressed proteins and spots picked, and MALDI-MS/MS was used to determine that ApoA1 was down-regulated by 22% (p < 0.004) in HCC relative to HCV. Differential expression quantified via two-dimensional difference gel electrophoresis was confirmed by means of 18O/16O stable isotope differential labeling with LC-MS/MS zoom scans. Technically independent confirmation was demonstrated by triple quadrupole LC-MS/MS selected reaction monitoring (SRM) assays with three peptides specific to human ApoA1 (DLATVYVDVLK, WQEEMELYR, and VSFLSALEEYTK) using 18O/16O-labeled samples and further verified with AQUA peptides as internal standards for quantification. In 50 patient samples (24 HCV and 26 HCC), all three SRM assays yielded highly similar differential expression of ApoA1 in HCC and HCV patients. These results validated the SRM assays, which were independently confirmed by Western blotting. Thus, ApoA1 is a candidate member of an SRM biomarker panel for early diagnosis

Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes.

PubMed

Kebede, Aida Z; Johnston, Anne; Schneiderman, Danielle; Bosnich, Whynn; Harris, Linda J

2018-02-09

Gibberella ear rot (GER) is one of the most economically important fungal diseases of maize in the temperate zone due to moldy grain contaminated with health threatening mycotoxins. To develop resistant genotypes and control the disease, understanding the host-pathogen interaction is essential. RNA-Seq-derived transcriptome profiles of fungal- and mock-inoculated developing kernel tissues of two maize inbred lines were used to identify differentially expressed transcripts and propose candidate genes mapping within GER resistance quantitative trait loci (QTL). A total of 1255 transcripts were significantly (P ≤ 0.05) up regulated due to fungal infection in both susceptible and resistant inbreds. A greater number of transcripts were up regulated in the former (1174) than the latter (497) and increased as the infection progressed from 1 to 2 days after inoculation. Focusing on differentially expressed genes located within QTL regions for GER resistance, we identified 81 genes involved in membrane transport, hormone regulation, cell wall modification, cell detoxification, and biosynthesis of pathogenesis related proteins and phytoalexins as candidate genes contributing to resistance. Applying droplet digital PCR, we validated the expression profiles of a subset of these candidate genes from QTL regions contributed by the resistant inbred on chromosomes 1, 2 and 9. By screening global gene expression profiles for differentially expressed genes mapping within resistance QTL regions, we have identified candidate genes for gibberella ear rot resistance on several maize chromosomes which could potentially lead to a better understanding of Fusarium resistance mechanisms.

Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study

PubMed Central

Wu, Hongyu; Yu, Zhijie; Qi, Qibin; Li, Huaixing; Sun, Qi

2011-01-01

Objective Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. Methods Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). Results Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). Conclusions These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation. PMID:22021786

Sparse Feature Selection Identifies H2A.Z as a Novel, Pattern-Specific Biomarker for Asymmetrically Self-Renewing Distributed Stem Cells

PubMed Central

Huh, Yang Hoon; Noh, Minsoo; Burden, Frank R.; Chen, Jennifer C.; Winkler, David A.; Sherley, James L.

2015-01-01

There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs) in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow). Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify DSC such useful and specific biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel “pattern-specific biomarker” for asymmetrically self-renewing cells with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ. PMID:25636161

Biomarkers intersect with the exposome

PubMed Central

Rappaport, Stephen M.

2016-01-01

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment. PMID:22672124

Genome-Wide Association Analysis of Blood Biomarkers in Chronic Obstructive Pulmonary Disease

PubMed Central

Kim, Deog Kyeom; Cho, Michael H.; Hersh, Craig P.; Lomas, David A.; Miller, Bruce E.; Kong, Xiangyang; Bakke, Per; Gulsvik, Amund; Agustí, Alvar; Wouters, Emiel; Celli, Bartolome; Coxson, Harvey; Vestbo, Jørgen; MacNee, William; Yates, Julie C.; Rennard, Stephen; Litonjua, Augusto; Qiu, Weiliang; Beaty, Terri H.; Crapo, James D.; Riley, John H.; Tal-Singer, Ruth

2012-01-01

Rationale: A genome-wide association study (GWAS) for circulating chronic obstructive pulmonary disease (COPD) biomarkers could identify genetic determinants of biomarker levels and COPD susceptibility. Objectives: To identify genetic variants of circulating protein biomarkers and novel genetic determinants of COPD. Methods: GWAS was performed for two pneumoproteins, Clara cell secretory protein (CC16) and surfactant protein D (SP-D), and five systemic inflammatory markers (C-reactive protein, fibrinogen, IL-6, IL-8, and tumor necrosis factor-α) in 1,951 subjects with COPD. For genome-wide significant single nucleotide polymorphisms (SNPs) (P < 1 × 10−8), association with COPD susceptibility was tested in 2,939 cases with COPD and 1,380 smoking control subjects. The association of candidate SNPs with mRNA expression in induced sputum was also elucidated. Measurements and Main Results: Genome-wide significant susceptibility loci affecting biomarker levels were found only for the two pneumoproteins. Two discrete loci affecting CC16, one region near the CC16 coding gene (SCGB1A1) on chromosome 11 and another locus approximately 25 Mb away from SCGB1A1, were identified, whereas multiple SNPs on chromosomes 6 and 16, in addition to SNPs near SFTPD, had genome-wide significant associations with SP-D levels. Several SNPs affecting circulating CC16 levels were significantly associated with sputum mRNA expression of SCGB1A1 (P = 0.009–0.03). Several SNPs highly associated with CC16 or SP-D levels were nominally associated with COPD in a collaborative GWAS (P = 0.001–0.049), although these COPD associations were not replicated in two additional cohorts. Conclusions: Distant genetic loci and biomarker-coding genes affect circulating levels of COPD-related pneumoproteins. A subset of these protein quantitative trait loci may influence their gene expression in the lung and/or COPD susceptibility. Clinical trial registered with www.clinicaltrials.gov (NCT 00292552). PMID

The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

PubMed Central

2014-01-01

In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment. PMID:24708694

Transcriptomic biomarkers of altered erythropoiesis to detect autologous blood transfusion.

PubMed

Salamin, Olivier; Mignot, Jonathan; Kuuranne, Tiia; Saugy, Martial; Leuenberger, Nicolas

2018-03-01

Autologous blood transfusion is a powerful means of improving performance and remains one of the most challenging methods to detect. Recent investigations have identified 3 candidate reticulocytes genes whose expression was significantly influenced by blood transfusion. Using quantitative reverse transcription polymerase chain reaction as an alternative quantitative method, the present study supports that delta-aminolevulinate synthase 2 (ALAS2), carbonic anhydrase (CA1), and solute carrier family 4 member 1 (SLC4A1) genes are down-regulated post-transfusion. The expression of these genes exhibited stronger correlation with immature reticulocyte fraction than with reticulocytes percentage. Moreover, the repression of reticulocytes' gene expression was more pronounced than the diminution of immature reticulocyte fraction and reticulocyte percentage following blood transfusion. It suggests that the 3 candidate genes are reliable predictors of bone marrow's response to blood transfusion and that they represent potential biomarkers for the detection of this method prohibited in sports. Copyright © 2017 John Wiley & Sons, Ltd.

Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

PubMed

Xu, Rengyi; Mesaros, Clementina; Weng, Liwei; Snyder, Nathaniel W; Vachani, Anil; Blair, Ian A; Hwang, Wei-Ting

2017-07-01

We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure. Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance. Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control. Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.

Targeted metabolomics: new insights into pathobiology of retained placenta in dairy cows and potential risk biomarkers.

PubMed

Dervishi, E; Zhang, G; Mandal, R; Wishart, D S; Ametaj, B N

2018-05-01

A targeted quantitative metabolomics approach was used to study temporal changes of serum metabolites in cows that normally released their fetal membranes and those that retained the placenta. We identified and measured serum concentrations of 128 metabolites including amino acids, acylcarnitines, biogenic amines, glycerophospholipids, sphingolipids and hexose at -8 and -4 weeks before parturition, during the week of retained placenta (RP) diagnosis, and at +4 and +8 weeks after parturition. In addition, we aimed at identifying metabolite signatures of pre-RP in the serum that might be used as predictive biomarkers for risk of developing RP in dairy cows. Results revealed major alterations in the metabolite fingerprints of pre-RP cows starting as early as -8 weeks before parturition and continuing as far as +8 weeks after calving. Biomarker candidates found in this study are mainly biomarkers of inflammation which might not be specific to RP. Therefore, the relevance of serum Lys, Orn, acetylornithine, lysophophatidylcholine LysoPC a C28:0, Asp, Leu and Ile as potential serum biomarkers for prediction of risk of RP in dairy cows will have to be tested in the future. In addition, lower concentrations of LysoPCs, Trp, and higher kynurenine in the serum during prepartum and the week of occurrence of RP suggest involvement of inflammation in the pathobiology of RP.

Circulating miRNAs in Pediatric Pulmonary Hypertension Show Promise as Biomarkers of Vascular Function

PubMed Central

Sucharov, Carmen C.; Truong, Uyen; Dunning, Jamie; Ivy, Dunbar; Miyamoto, Shelley; Shandas, Robin

2017-01-01

Background/Objectives The objective of this study was to evaluate the utility of circulating miRNAs as biomarkers of vascular function in pediatric pulmonary hypertension. Method Fourteen pediatric pulmonary arterial hypertension patients underwent simultaneous right heart catheterization (RHC) and blood biochemical analysis. Univariate and stepwise multivariate linear regression was used to identify and correlate measures of reactive and resistive afterload with circulating miRNA levels. Furthermore, circulating miRNA candidates that classified patients according to a 20% decrease in resistive afterload in response to oxygen (O2) or inhaled nitric oxide (iNO) were identified using receiver-operating curves. Results Thirty-two circulating miRNAs correlated with the pulmonary vascular resistance index (PVRi), pulmonary arterial distensibility, and PVRi decrease in response to O2 and/or iNO. Multivariate models, combining the predictive capability of multiple promising miRNA candidates, revealed a good correlation with resistive (r = 0.97, P2−tailed < 0.0001) and reactive (r = 0.86, P2−tailed < 0.005) afterloads. Bland-Altman plots showed that 95% of the differences between multivariate models and RHC would fall within 0.13 (mmHg−min/L)m2 and 0.0085/mmHg for resistive and reactive afterloads, respectively. Circulating miR-663 proved to be a good classifier for vascular responsiveness to acute O2 and iNO challenges. Conclusion This study suggests that circulating miRNAs may be biomarkers to phenotype vascular function in pediatric PAH. PMID:28819545

Analysis of angiogenesis biomarkers for ramucirumab efficacy in patients with metastatic colorectal cancer from RAISE, a global, randomized, double-blind, phase III study.

PubMed

Tabernero, J; Hozak, R R; Yoshino, T; Cohn, A L; Obermannova, R; Bodoky, G; Garcia-Carbonero, R; Ciuleanu, T-E; Portnoy, D C; Prausová, J; Muro, K; Siegel, R W; Konrad, R J; Ouyang, H; Melemed, S A; Ferry, D; Nasroulah, F; Van Cutsem, E

2018-03-01

The phase III RAISE trial (NCT01183780) demonstrated that the vascular endothelial growth factor (VEGF) receptor (VEGFR)-2 binding monoclonal antibody ramucirumab plus 5-fluororuracil, leucovorin, and irinotecan (FOLFIRI) significantly improved overall survival (OS) and progression-free survival (PFS) compared with placebo + FOLFIRI as second-line metastatic colorectal cancer (mCRC) treatment. To identify patients who benefit the most from VEGFR-2 blockade, the RAISE trial design included a prospective and comprehensive biomarker program that assessed the association of biomarkers with ramucirumab efficacy outcomes. Plasma and tumor tissue collection was mandatory. Overall, 1072 patients were randomized 1 : 1 to the addition of ramucirumab or placebo to FOLFIRI chemotherapy. Patients were then randomized 1 : 2, for the biomarker program, to marker exploratory (ME) and marker confirmatory (MC) groups. Analyses were carried out using exploratory assays to assess the correlations of baseline marker levels [VEGF-C, VEGF-D, sVEGFR-1, sVEGFR-2, sVEGFR-3 (plasma), and VEGFR-2 (tumor tissue)] with clinical outcomes. Cox regression analyses were carried out for each candidate biomarker with stratification factor adjustment. Biomarker results were available from >80% (n = 894) of patients. Analysis of the ME subset determined a VEGF-D level of 115 pg/ml was appropriate for high/low subgroup analyses. Evaluation of the combined ME + MC populations found that the median OS in the ramucirumab + FOLFIRI arm compared with placebo + FOLFIRI showed an improvement of 2.4 months in the high VEGF-D subgroup [13.9 months (95% CI 12.5-15.6) versus 11.5 months (95% CI 10.1-12.4), respectively], and a decrease of 0.5 month in the low VEGF-D subgroup [12.6 months (95% CI 10.7-14.0) versus 13.1 months (95% CI 11.8-17.0), respectively]. PFS results were consistent with OS. No trends were evident with the other antiangiogenic candidate biomarkers. The

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

PubMed

Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Plasma biomarkers of depressive symptoms in older adults.

PubMed

Arnold, S E; Xie, S X; Leung, Y-Y; Wang, L-S; Kling, M A; Han, X; Kim, E J; Wolk, D A; Bennett, D A; Chen-Plotkin, A; Grossman, M; Hu, W; Lee, V M-Y; Mackin, R Scott; Trojanowski, J Q; Wilson, R S; Shaw, L M

2012-01-03

The pathophysiology of negative affect states in older adults is complex, and a host of central nervous system and peripheral systemic mechanisms may play primary or contributing roles. We conducted an unbiased analysis of 146 plasma analytes in a multiplex biochemical biomarker study in relation to number of depressive symptoms endorsed by 566 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) at their baseline and 1-year assessments. Analytes that were most highly associated with depressive symptoms included hepatocyte growth factor, insulin polypeptides, pregnancy-associated plasma protein-A and vascular endothelial growth factor. Separate regression models assessed contributions of past history of psychiatric illness, antidepressant or other psychotropic medicine, apolipoprotein E genotype, body mass index, serum glucose and cerebrospinal fluid (CSF) τ and amyloid levels, and none of these values significantly attenuated the main effects of the candidate analyte levels for depressive symptoms score. Ensemble machine learning with Random Forests found good accuracy (~80%) in classifying groups with and without depressive symptoms. These data begin to identify biochemical biomarkers of depressive symptoms in older adults that may be useful in investigations of pathophysiological mechanisms of depression in aging and neurodegenerative dementias and as targets of novel treatment approaches.

Translating golden retriever muscular dystrophy microarray findings to novel biomarkers for cardiac/skeletal muscle function in Duchenne muscular dystrophy.

PubMed

Galindo, Cristi L; Soslow, Jonathan H; Brinkmeyer-Langford, Candice L; Gupte, Manisha; Smith, Holly M; Sengsayadeth, Seng; Sawyer, Douglas B; Benson, D Woodrow; Kornegay, Joe N; Markham, Larry W

2016-04-01

In Duchenne muscular dystrophy (DMD), abnormal cardiac function is typically preceded by a decade of skeletal muscle disease. Molecular reasons for differences in onset and progression of these muscle groups are unknown. Human biomarkers are lacking. We analyzed cardiac and skeletal muscle microarrays from normal and golden retriever muscular dystrophy (GRMD) dogs (ages 6, 12, or 47+ mo) to gain insight into muscle dysfunction and to identify putative DMD biomarkers. These biomarkers were then measured using human DMD blood samples. We identified GRMD candidate genes that might contribute to the disparity between cardiac and skeletal muscle disease, focusing on brain-derived neurotropic factor (BDNF) and osteopontin (OPN/SPP1, hereafter indicated as SPP1). BDNF was elevated in cardiac muscle of younger GRMD but was unaltered in skeletal muscle, while SPP1 was increased only in GRMD skeletal muscle. In human DMD, circulating levels of BDNF were inversely correlated with ventricular function and fibrosis, while SPP1 levels correlated with skeletal muscle function. These results highlight gene expression patterns that could account for differences in cardiac and skeletal disease in GRMD. Most notably, animal model-derived data were translated to DMD and support use of BDNF and SPP1 as biomarkers for cardiac and skeletal muscle involvement, respectively.

Urinary biomarkers in hydronephrosis.

PubMed

Madsen, Mia Gebauer

2013-02-01

Hydronephrosis is diagnosed in 0.5-1% of all newborns, and ureteropelvic junction obstruction (UPJO) accounts for 35% of those cases. A urinary tract obstruction that occurs during early kidney development affects renal morphogenesis, maturation, and growth, and in the most severe cases, this will ultimately lead to progressive renal tubular atrophy and interstitial fibrosis with the loss of nephrons. The clinical management of these patients remains a controversial topic. The aim is to preserve renal function by identifying the 15-20% of children who require early surgical intervention from those for whom watchful waiting may be appropriate because of spontaneous resolving/stabilization without significant loss of renal function. Although the patients attend regular follow-ups, including repetitive blood tests, ultrasonographies, and the more invasive diuretic renograms, the surgeons still miss reliably biomarkers that could be used as predictors for renal parenchymal damage and decreased renal function, and thereby provide more clear indications for surgical intervention. The aim of this PhD thesis was to further elucidate the pathophysiology of obstructive nephropathy (study I) and to search for potential candidate biomarkers that may have a predictive and/or diagnostic value in the management of hydronephrosis (study II). Study I: Urine and kidney cytokine profiles in experimental unilateral acute and chronic hydronephrosis. To study the dynamics of the urinary secretion of cytokines after the release of unilateral ureteral obstruction, and to study whether the urinary concentrations of these compounds reliably reflects changes in the renal parenchyma. This was tested in 2 experimental rat models: an acute obstruction model and a chronic obstruction model. The acute obstruction model demonstrated significant differences in the renal levels of IL-1β, IL-6, TNF-α, and IL-10 in comparison with controls, and these differences were associated with similar

Novel Biomarkers of Abdominal Aortic Aneurysm Disease: Identifying Gaps and Dispelling Misperceptions

PubMed Central

Moris, Demetrios; Avgerinos, Efthymios; Makris, Marinos; Bakoyiannis, Chris; Pikoulis, Emmanuel; Georgopoulos, Sotirios

2014-01-01

Abdominal aortic aneurysm (AAA) is a prevalent and potentially life-threatening disease. Early detection by screening programs and subsequent surveillance has been shown to be effective at reducing the risk of mortality due to aneurysm rupture. The aim of this review is to summarize the developments in the literature concerning the latest biomarkers (from 2008 to date) and their potential screening and therapeutic values. Our search included human studies in English and found numerous novel biomarkers under research, which were categorized in 6 groups. Most of these studies are either experimental or hampered by their low numbers of patients. We concluded that currently no specific laboratory markers allow screeing for the disease and monitoring its progression or the results of treatment. Further studies and studies in larger patient groups are required in order to validate biomarkers as cost-effective tools in the AAA disease. PMID:24967416

Genomic and Histopathological Tissue Biomarkers That Predict Radiotherapy Response in Localised Prostate Cancer

PubMed Central

Wilkins, Anna; Dearnaley, David; Somaiah, Navita

2015-01-01

Localised prostate cancer, in particular, intermediate risk disease, has varied survival outcomes that cannot be predicted accurately using current clinical risk factors. External beam radiotherapy (EBRT) is one of the standard curative treatment options for localised disease and its efficacy is related to wide ranging aspects of tumour biology. Histopathological techniques including immunohistochemistry and a variety of genomic assays have been used to identify biomarkers of tumour proliferation, cell cycle checkpoints, hypoxia, DNA repair, apoptosis, and androgen synthesis, which predict response to radiotherapy. Global measures of genomic instability also show exciting capacity to predict survival outcomes following EBRT. There is also an urgent clinical need for biomarkers to predict the radiotherapy fraction sensitivity of different prostate tumours and preclinical studies point to possible candidates. Finally, the increased resolution of next generation sequencing (NGS) is likely to enable yet more precise molecular predictions of radiotherapy response and fraction sensitivity. PMID:26504789

Evaluating biomarkers to model cancer risk post cosmic ray exposure.

PubMed

Sridharan, Deepa M; Asaithamby, Aroumougame; Blattnig, Steve R; Costes, Sylvain V; Doetsch, Paul W; Dynan, William S; Hahnfeldt, Philip; Hlatky, Lynn; Kidane, Yared; Kronenberg, Amy; Naidu, Mamta D; Peterson, Leif E; Plante, Ianik; Ponomarev, Artem L; Saha, Janapriya; Snijders, Antoine M; Srinivasan, Kalayarasan; Tang, Jonathan; Werner, Erica; Pluth, Janice M

2016-06-01

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing

Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization.

PubMed

Amur, S; LaVange, L; Zineh, I; Buckman-Garner, S; Woodcock, J

2015-07-01

The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration. © 2015 American Society for Clinical Pharmacology and Therapeutics.

USING ARRAY TECHNOLOGY TO IDENTIFY POTENTIAL BIOMARKERS FOR PYRETHROID INSECTICIDES.

EPA Science Inventory

Pyrethroid insecticides affect nervous system function by disruption of sodium channels in nerve membranes. FQPA requirements for assessing cumulative risk have increased the need for rapid and sensitive biomarkers of effect. This project aims to develop biochemical markers of n...

Empirical evaluation demonstrated importance of validating biomarkers for early detection of cancer in screening settings to limit the number of false-positive findings.

PubMed

Chen, Hongda; Knebel, Phillip; Brenner, Hermann

2016-07-01

Search for biomarkers for early detection of cancer is a very active area of research, but most studies are done in clinical rather than screening settings. We aimed to empirically evaluate the role of study setting for early detection marker identification and validation. A panel of 92 candidate cancer protein markers was measured in 35 clinically identified colorectal cancer patients and 35 colorectal cancer patients identified at screening colonoscopy. For each case group, we selected 38 controls without colorectal neoplasms at screening colonoscopy. Single-, two- and three-marker combinations discriminating cases and controls were identified in each setting and subsequently validated in the alternative setting. In all scenarios, a higher number of predictive biomarkers were initially detected in the clinical setting, but a substantially lower proportion of identified biomarkers could subsequently be confirmed in the screening setting. Confirmation rates were 50.0%, 84.5%, and 74.2% for one-, two-, and three-marker algorithms identified in the screening setting and were 42.9%, 18.6%, and 25.7% for algorithms identified in the clinical setting. Validation of early detection markers of cancer in a true screening setting is important to limit the number of false-positive findings. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry.

PubMed

Tsutsui, Haruhito; Maeda, Toshio; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki; Toyo'oka, Toshimasa

2011-05-12

The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study. The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB. Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on

New Biomarkers of Coffee Consumption Identified by the Non-Targeted Metabolomic Profiling of Cohort Study Subjects

PubMed Central

Martin, Jean-François; Lyan, Bernard; Pujos-Guillot, Estelle; Fezeu, Leopold; Hercberg, Serge; Comte, Blandine; Galan, Pilar; Touvier, Mathilde; Manach, Claudine

2014-01-01

Coffee contains various bioactives implicated with human health and disease risk. To accurately assess the effects of overall consumption upon health and disease, individual intake must be measured in large epidemiological studies. Metabolomics has emerged as a powerful approach to discover biomarkers of intake for a large range of foods. Here we report the profiling of the urinary metabolome of cohort study subjects to search for new biomarkers of coffee intake. Using repeated 24-hour dietary records and a food frequency questionnaire, 20 high coffee consumers (183–540 mL/d) and 19 low consumers were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject were profiled by high-resolution mass spectrometry. Partial least-square discriminant analysis of multidimensional liquid chromatography-mass spectrometry data clearly distinguished high consumers from low via 132 significant (p-value<0.05) discriminating features. Ion clusters whose intensities were most elevated in the high consumers were annotated using online and in-house databases and their identities checked using commercial standards and MS-MS fragmentation. The best discriminants, and thus potential markers of coffee consumption, were the glucuronide of the diterpenoid atractyligenin, the diketopiperazine cyclo(isoleucyl-prolyl), and the alkaloid trigonelline. Some caffeine metabolites, such as 1-methylxanthine, were also among the discriminants, however caffeine may be consumed from other sources and its metabolism is subject to inter-individual variation. Receiver operating characteristics curve analysis showed that the biomarkers identified could be used effectively in combination for increased sensitivity and specificity. Once validated in other cohorts or intervention studies, these specific single or combined biomarkers will become a valuable alternative to assessment of coffee intake by dietary survey and finally lead to a better understanding of the health

Chemical and metabolomic screens identify novel biomarkers and antidotes for cyanide exposure

PubMed Central

Nath, Anjali K.; Roberts, Lee D.; Liu, Yan; Mahon, Sari B.; Kim, Sonia; Ryu, Justine H.; Werdich, Andreas; Januzzi, James L.; Boss, Gerry R.; Rockwood, Gary A.; MacRae, Calum A.; Brenner, Matthew; Gerszten, Robert E.; Peterson, Randall T.

2013-01-01

Exposure to cyanide causes a spectrum of cardiac, neurological, and metabolic dysfunctions that can be fatal. Improved cyanide antidotes are needed, but the ideal biological pathways to target are not known. To understand better the metabolic effects of cyanide and to discover novel cyanide antidotes, we developed a zebrafish model of cyanide exposure and scaled it for high-throughput chemical screening. In a screen of 3120 small molecules, we discovered 4 novel antidotes that block cyanide toxicity. The most potent antidote was riboflavin. Metabolomic profiling of cyanide-treated zebrafish revealed changes in bile acid and purine metabolism, most notably by an increase in inosine levels. Riboflavin normalizes many of the cyanide-induced neurological and metabolic perturbations in zebrafish. The metabolic effects of cyanide observed in zebrafish were conserved in a rabbit model of cyanide toxicity. Further, humans treated with nitroprusside, a drug that releases nitric oxide and cyanide ions, display increased circulating bile acids and inosine. In summary, riboflavin may be a novel treatment for cyanide toxicity and prophylactic measure during nitroprusside treatment, inosine may serve as a biomarker of cyanide exposure, and metabolites in the bile acid and purine metabolism pathways may shed light on the pathways critical to reversing cyanide toxicity.—Nath, A. K., Roberts, L. D., Liu, Y., Mahon, S. B., Kim, S., Ryu, J. H., Werdich, A., Januzzi, J. L., Boss, G. R., Rockwood, G. A., MacRae, C. A., Brenner, M., Gerszten, R. E., Peterson, R. T. Chemical and metabolomic screens identify novel biomarkers and antidotes for cyanide exposure. PMID:23345455

Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis.

PubMed

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2009-01-01

Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

Biomarkers for Cognitive Impairment in Parkinson Disease

PubMed Central

Shi, Min; Huber, Bertrand R.; Zhang, Jing

2010-01-01

Cognitive impairment, including dementia, is commonly seen in those afflicted with Parkinson disease (PD), particularly at advanced disease stages. Pathologically, PD with dementia (PD-D) is most often associated with the presence of cortical Lewy bodies, as is the closely related dementia with Lewy bodies (DLB). Both PD-D and DLB are also frequently complicated by the presence of neurofibrillary tangles and amyloid plaques, features most often attributed to Alzheimer disease. Biomarkers are urgently needed to differentiate among these disease processes and predict dementia in PD as well as monitor responses of patients to new therapies. A few clinical assessments, along with structural and functional neuroimaging, have been utilized in the last few years with some success in this area. Additionally, a number of other strategies have been employed to identify biochemical/molecular biomarkers associated with cognitive impairment and dementia in PD, e.g., targeted analysis of candidate proteins known to be important to PD pathogenesis and progression in cerebrospinal fluid or blood. Finally, interesting results are emerging from preliminary studies with unbiased and high throughput genomic, proteomic and metabolomic techniques. The current findings and perspectives of applying these strategies and techniques are reviewed in this article, together with potential areas of advancement. PMID:20522092

Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits

PubMed Central

Benton, Miles C.; Lea, Rod A.; Macartney-Coxson, Donia; Carless, Melanie A.; Göring, Harald H.; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K.; Curran, Joanne E.; Harper, Jacquie L.; Blangero, John; Griffiths, Lyn R.

2013-01-01

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10−7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations. PMID:24314549

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

PubMed Central

Yamada, Takashi; Hashimoto, Ryu-ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Abstract Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. PMID:28977523

Emerging infection and sepsis biomarkers: will they change current therapies?

PubMed Central

Jacobs, Lauren

2016-01-01

Introduction Sepsis is a heterogeneous syndrome characterized by both immune hyperactivity and relative immune suppression. Biomarkers have the potential to improve recognition and management of sepsis through three main applications: diagnosis, monitoring response to treatment, and stratifying patients based on prognosis or underlying biological response. Areas Covered This review focuses on specific examples of well-studied, evidence-supported biomarkers, and discusses their role in clinical practice with special attention to antibiotic stewardship and cost-effectiveness. Biomarkers were selected based on availability of robust prospective trials and meta-analyses which supported their role as emerging tools to improve the clinical management of sepsis. Expert Commentary Great strides have been made in candidate sepsis biomarker discovery and testing, with the biomarkers in this review showing promise. Yet sepsis remains a dynamic illness with a great degree of biological heterogeneity – heterogeneity which may be further resolved by recently discovered gene expression-based endotypes in septic shock. PMID:27533847

Genome-Wide Transcriptome Analysis of Cotton (Gossypium hirsutum L.) Identifies Candidate Gene Signatures in Response to Aflatoxin Producing Fungus Aspergillus flavus.

PubMed

Bedre, Renesh; Rajasekaran, Kanniah; Mangu, Venkata Ramanarao; Sanchez Timm, Luis Eduardo; Bhatnagar, Deepak; Baisakh, Niranjan

2015-01-01

Aflatoxins are toxic and potent carcinogenic metabolites produced from the fungi Aspergillus flavus and A. parasiticus. Aflatoxins can contaminate cottonseed under conducive preharvest and postharvest conditions. United States federal regulations restrict the use of aflatoxin contaminated cottonseed at >20 ppb for animal feed. Several strategies have been proposed for controlling aflatoxin contamination, and much success has been achieved by the application of an atoxigenic strain of A. flavus in cotton, peanut and maize fields. Development of cultivars resistant to aflatoxin through overexpression of resistance associated genes and/or knocking down aflatoxin biosynthesis of A. flavus will be an effective strategy for controlling aflatoxin contamination in cotton. In this study, genome-wide transcriptome profiling was performed to identify differentially expressed genes in response to infection with both toxigenic and atoxigenic strains of A. flavus on cotton (Gossypium hirsutum L.) pericarp and seed. The genes involved in antifungal response, oxidative burst, transcription factors, defense signaling pathways and stress response were highly differentially expressed in pericarp and seed tissues in response to A. flavus infection. The cell-wall modifying genes and genes involved in the production of antimicrobial substances were more active in pericarp as compared to seed. The genes involved in auxin and cytokinin signaling were also induced. Most of the genes involved in defense response in cotton were highly induced in pericarp than in seed. The global gene expression analysis in response to fungal invasion in cotton will serve as a source for identifying biomarkers for breeding, potential candidate genes for transgenic manipulation, and will help in understanding complex plant-fungal interaction for future downstream research.

Biomarkers of sepsis

PubMed Central

2013-01-01

Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. A hyper-inflammatory response is followed by an immunosuppressive phase during which multiple organ dysfunction is present and the patient is susceptible to nosocomial infection. Biomarkers to diagnose sepsis may allow early intervention which, although primarily supportive, can reduce the risk of death. Although lactate is currently the most commonly used biomarker to identify sepsis, other biomarkers may help to enhance lactate’s effectiveness; these include markers of the hyper-inflammatory phase of sepsis, such as pro-inflammatory cytokines and chemokines; proteins such as C-reactive protein and procalcitonin which are synthesized in response to infection and inflammation; and markers of neutrophil and monocyte activation. Recently, markers of the immunosuppressive phase of sepsis, such as anti-inflammatory cytokines, and alterations of the cell surface markers of monocytes and lymphocytes have been examined. Combinations of pro- and anti-inflammatory biomarkers in a multi-marker panel may help identify patients who are developing severe sepsis before organ dysfunction has advanced too far. Combined with innovative approaches to treatment that target the immunosuppressive phase, these biomarkers may help to reduce the mortality rate associated with severe sepsis which, despite advances in supportive measures, remains high. PMID:23480440

Biomarkers in the Diagnosis and Prognosis of Alzheimer's Disease.

PubMed

Schaffer, Cole; Sarad, Nakia; DeCrumpe, Ashton; Goswami, Disha; Herrmann, Sara; Morales, Jose; Patel, Parth; Osborne, Jim

2015-10-01

Alzheimer's disease (AD) is a neurodegenerative disease that inhibits cognitive functions and has no cure. This report reviews the current diagnostic standards for AD with an emphasis on early diagnosis using the cerebrospinal fluid (CSF) biomarkers amyloid-beta, t-tau, and p-tau and fluorodeoxyglucose positron emission tomography imaging. Abnormal levels of these CSF biomarkers and decreased cerebral uptake of glucose have recently been used in the early diagnosis of AD in experimental studies. These promising biomarkers can be measured using immunoassays performed in singleplex or multiplex formats. Although presently, there are no Food and Drug Administration-approved in vitro diagnostics (IVDs) for early detection of AD, a multiplex immunoassay measuring a panel of promising AD biomarkers in CSF may be a likely IVD candidate for the clinical AD diagnostic market. Specifically, the INNO-BIA AlzBio3 immunoassay kit, performed using bead arrays on the xMAP Luminex analyzer, allows simultaneous quantification of amyloid-beta, t-tau, and p-tau biomarkers. AD biomarkers can also be screened using enzyme-linked immunosorbent assays that are offered as laboratory-developed tests. © 2014 Society for Laboratory Automation and Screening.

Biomarkers for monitoring clinical efficacy of allergen immunotherapy for allergic rhinoconjunctivitis and allergic asthma: an EAACI Position Paper.

PubMed

Shamji, M H; Kappen, J H; Akdis, M; Jensen-Jarolim, E; Knol, E F; Kleine-Tebbe, J; Bohle, B; Chaker, A M; Till, S J; Valenta, R; Poulsen, L K; Calderon, M A; Demoly, P; Pfaar, O; Jacobsen, L; Durham, S R; Schmidt-Weber, C B

2017-08-01

Allergen immunotherapy (AIT) is an effective treatment for allergic rhinoconjunctivitis (AR) with or without asthma. It is important to note that due to the complex interaction between patient, allergy triggers, symptomatology and vaccines used for AIT, some patients do not respond optimally to the treatment. Furthermore, there are no validated or generally accepted candidate biomarkers that are predictive of the clinical response to AIT. Clinical management of patients receiving AIT and efficacy in randomised controlled trials for drug development could be enhanced by predictive biomarkers. The EAACI taskforce reviewed all candidate biomarkers used in clinical trials of AR patients with/without asthma in a literature review. Biomarkers were grouped into seven domains: (i) IgE (total IgE, specific IgE and sIgE/Total IgE ratio), (ii) IgG-subclasses (sIgG1, sIgG4 including SIgE/IgG4 ratio), (iii) Serum inhibitory activity for IgE (IgE-FAB and IgE-BF), (iv) Basophil activation, (v) Cytokines and Chemokines, (vi) Cellular markers (T regulatory cells, B regulatory cells and dendritic cells) and (vii) In vivo biomarkers (including provocation tests?). All biomarkers were reviewed in the light of their potential advantages as well as their respective drawbacks. Unmet needs and specific recommendations on all seven domains were addressed. It is recommended to explore the use of allergen-specific IgG4 as a biomarker for compliance. sIgE/tIgE and IgE-FAB are considered as potential surrogate candidate biomarkers. Cytokine/chemokines and cellular reponses provided insight into the mechanisms of AIT. More studies for confirmation and interpretation of the possible association with the clinical response to AIT are needed. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort

PubMed Central