Dataset Information

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma.

ABSTRACT: Esophageal cancer (EC) is the eighth most aggressive malignancy and its treatment remains a challenge due to the lack of biomarkers that can facilitate early detection. EC is identified in two major histological forms namely - Adenocarcinoma (EAC) and Squamous cell carcinoma (ESCC), each showing differences in the incidence among populations that are geographically separated. Hence the detection of potential drug target and biomarkers demands a population-centric understanding of the molecular and cellular mechanisms of EC. To provide an adequate impetus to the biomarker discovery for ESCC, which is the most prevalent esophageal cancer worldwide, here we have developed ESCC ATLAS, a manually curated database that integrates genetic, epigenetic, transcriptomic, and proteomic ESCC-related genes from the published literature. It consists of 3475 genes associated to molecular signatures such as, altered transcription (2600), altered translation (560), contain copy number variation/structural variations (233), SNPs (102), altered DNA methylation (82), Histone modifications (16) and miRNA based regulation (261). We provide a user-friendly web interface ( http://www.esccatlas.org , freely accessible for academic, non-profit users) that facilitates the exploration and the analysis of genes among different populations. We anticipate it to be a valuable resource for the population specific investigation and biomarker discovery for ESCC.

SUBMITTER: Tungekar A

PROVIDER: S-EPMC6109081 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma.

Tungekar Asna A Mandarthi Sumana S Mandaviya Pooja Rajendra PR Gadekar Veerendra P VP Tantry Ananthajith A Kotian Sowmya S Reddy Jyotshna J Prabha Divya D Bhat Sushma S Sahay Sweta S Mascarenhas Roshan R Badkillaya Raghavendra Rao RR Nagasampige Manoj Kumar MK Yelnadu Mohan M Pawar Harsh H Hebbar Prashantha P Kashyap Manoj Kumar MK

Scientific reports 20180824 1

Esophageal cancer (EC) is the eighth most aggressive malignancy and its treatment remains a challenge due to the lack of biomarkers that can facilitate early detection. EC is identified in two major histological forms namely - Adenocarcinoma (EAC) and Squamous cell carcinoma (ESCC), each showing differences in the incidence among populations that are geographically separated. Hence the detection of potential drug target and biomarkers demands a population-centric understanding of the molecular a ...[more]

PMID: 30143675

Similar Datasets

Project description:Background:DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC). Methods:A high-throughput DNA methylation dataset (100 samples) of ESCC from The Cancer Genome Atlas (TCGA) project was analyzed and validated along with another independent dataset (12 samples) from the Gene Expression Omnibus (GEO) database. The methylation status of peripheral blood mononuclear cells and peripheral blood leukocytes from healthy controls was also utilized for biomarker selection. The candidate CpG sites as well as their adjacent regions were further validated in 94 pairs of ESCC tumor and adjacent normal tissues from the Chinese Han population using the targeted bisulfite sequencing method. Logistic regression and several machine learning methods were applied for evaluation of the diagnostic ability of our panel. Results:In the discovery stage, five hyper-methylated CpG sites were selected as candidate biomarkers for further analysis as shown below: cg15830431, P?=?2.20?×?10-4; cg19396867, P?=?3.60?×?10-4; cg20655070, P?=?3.60?×?10-4; cg26671652, P?=?5.77?×?10-4; and cg27062795, P?=?3.60?×?10-4. In the validation stage, the methylation status of both the five CpG sites and their adjacent genomic regions were tested. The diagnostic model based on the combination of these five genomic regions yielded a robust performance (sensitivity?=?0.75, specificity?=?0.88, AUC?=?0.85). Eight statistical models along with five-fold cross-validation were further applied, in which the SVM model reached the best accuracy in both training and test dataset (accuracy?=?0.82 and 0.80, respectively). In addition, subgroup analyses revealed a significant difference in diagnostic performance between the alcohol use and non-alcohol use subgroups. Conclusions:Methylation profiles of the five genomic regions covering cg15830431 (STK3), cg19396867, cg20655070, cg26671652 (ZNF418), and cg27062795 (ZNF542) can be used for effective methylation-based testing for ESCC diagnosis.

Project description:MicroRNAs (miRNAs) are an endogenous conserved class of non-coding 20–22 nt small RNAs that regulate gene expression at post-transcriptional level by mostly binding to 3′-UTR of target mRNAs, leading to mRNA degradation or translation inhibition. Recent reports demonstrate a role for miRNA expression in the disease progression and outcome. By now, many researcher focusing on miRNA expression profiles in Barrett's esophagus and esophageal adenocarcinoma have been reported. Nevertheless, there is still a little information available about specific miRNA expression pattern and their roles in ESCC. To develop novel diagnostic and therapeutic targets for esophageal squamous cancer, we first investigated the expression profile of miRNA in three pairs of ESCC clinical samples. Tissues of ESCC and the matched normal counterparts were obtained from surgical specimens immediately after resection from patients undergoing primary surgical treatment of esophageal carcinoma from the Department of Tumor Surgery of Shantou Central Hospital, China. RNA labeling and hybridization were completed by KangChen Bio-tech Inc. (Shanghai, China) according to the manufacturer's instructions. Briefly, total RNA from three pairs of esophageal carcinoma and matched normal tissues were isolated by Trizol (Invitrogen, USA) and purified by RNeasy mini kit (QIAGEN, German). The concentration and quality of total RNA were measured by NanoDrop ND-1000 at 260 and 280 nm (A260/280) and checked by gel electrophoresis. Each RNA sample from three pairs of ESCC was separately labeled either using the miRCURY Hy3/Hy5 labeling kit and hybridized on the six miRCURYTM locked nucleic acid (LNA) array version 11.0 (Exiqon, Denmark), which contains probes for 1700 mature miRNA. Scans were quantified by using GenePix software (Molecular Devices). The data were exported to Microsoft Excel worksheets, log2 transformed, normalized using global Lowess (Locally Weighted Scatter plot Smoothing) regression algorithm (MIDAS, TIGR Microarray Data Analysis System).

Project description:BackgroundEstrogen therapy has positively impact the treatment of several cancers, such as prostate, lung and breast cancers. Moreover, several groups have reported the importance of estrogen induced gene regulation in esophageal cancer (EC). This suggests that there could be a potential for estrogen therapy for EC. The efficient design of estrogen therapies requires as complete as possible list of genes responsive to estrogen. Our study develops a systems biology methodology using esophageal squamous cell carcinoma (ESCC) as a model to identify estrogen responsive genes. These genes, on the other hand, could be affected by estrogen therapy in ESCC.ResultsBased on different sources of information we identified 418 genes implicated in ESCC. Putative estrogen responsive elements (EREs) mapped to the promoter region of the ESCC genes were used to initially identify candidate estrogen responsive genes. EREs mapped to the promoter sequence of 30.62% (128/418) of ESCC genes of which 43.75% (56/128) are known to be estrogen responsive, while 56.25% (72/128) are new candidate estrogen responsive genes. EREs did not map to 290 ESCC genes. Of these 290 genes, 50.34% (146/290) are known to be estrogen responsive. By analyzing transcription factor binding sites (TFBSs) in the promoters of the 202 (56+146) known estrogen responsive ESCC genes under study, we found that their regulatory potential may be characterized by 44 significantly over-represented co-localized TFBSs (cTFBSs). We were able to map these cTFBSs to promoters of 32 of the 72 new candidate estrogen responsive ESCC genes, thereby increasing confidence that these 32 ESCC genes are responsive to estrogen since their promoters contain both: a/mapped EREs, and b/at least four cTFBSs characteristic of ESCC genes that are responsive to estrogen. Recent publications confirm that 47% (15/32) of these 32 predicted genes are indeed responsive to estrogen.ConclusionTo the best of our knowledge our study is the first to use a cancer disease model as the framework to identify hormone responsive genes. Although we used ESCC as the disease model and estrogen as the hormone, the methodology can be extended analogously to other diseases as the model and other hormones. We believe that our results provide useful information for those interested in genes responsive to hormones and in the design of hormone-based therapies.

Dataset Information

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma.

Publications

ESCC ATLAS: A population wide compendium of biomarkers for Esophageal Squamous Cell Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets