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CancerEnD: A database of cancer associated enhancers.

Authors
  • Kumar, Rajesh1
  • Lathwal, Anjali2
  • Kumar, Vinod3
  • Patiyal, Sumeet4
  • Raghav, Pawan Kumar5
  • Raghava, Gajendra P S6
  • 1 Bioinformatics Centre, CSIR - Institute of Microbial Technology, Chandigarh, India. Electronic address: [email protected] , (India)
  • 2 Department of Computational Biology, Indraprastha Institute of Information Technology, New-Delhi, India. Electronic address: [email protected] , (India)
  • 3 Bioinformatics Centre, CSIR - Institute of Microbial Technology, Chandigarh, India. Electronic address: [email protected] , (India)
  • 4 Department of Computational Biology, Indraprastha Institute of Information Technology, New-Delhi, India. Electronic address: [email protected] , (India)
  • 5 Department of Computational Biology, Indraprastha Institute of Information Technology, New-Delhi, India. Electronic address: [email protected] , (India)
  • 6 Department of Computational Biology, Indraprastha Institute of Information Technology, New-Delhi, India. Electronic address: [email protected] , (India)
Type
Published Article
Journal
Genomics
Publisher
Elsevier
Publication Date
May 01, 2020
Identifiers
DOI: 10.1016/j.ygeno.2020.04.028
PMID: 32360910
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

CancerEnD is an integrated resource developed for annotating 8524 unique expressed enhancers, associated genes, somatic mutations and copy number variations of 8063 cancer samples from 18 cancer types of TCGA. Somatic mutation data was taken from the COSMIC repository. To delineate the relationship of change in copy number of enhancer elements with the prognosis of cancer patients, survival analysis was done using the survival package in R. We identified 1762 overall survival associated enhancers, which can be used for prognostic purposes of cancer patients in a tissue-specific manner. CancerEnD (https://webs.iiitd.edu.in/raghava/cancerend/) is developed on a user-friendly responsive template, that enables searching, browsing and downloading of the annotated enhancer elements in terms of gene expression, copy number variation and survival association. We hope it provides a promising avenue for researchers to facilitate the understanding of enhancer deregulation in tumorigenesis, and to identify new biomarkers for therapy and disease-diagnosis. Copyright © 2020 Elsevier Inc. All rights reserved.

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