Oncogenomic portals for the visualization and analysis of genome-wide cancer data

Oncotarget. 2016 Jan 5;7(1):176-92. doi: 10.18632/oncotarget.6128.

Abstract

Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice.

Keywords: COSMIC; IntOGen; PPISURV/MIRUMIR; Tumorscape; cBioPortal.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Computational Biology / methods*
  • Computational Biology / statistics & numerical data
  • DNA Copy Number Variations
  • Data Mining / methods*
  • Gene Expression Regulation, Neoplastic
  • Genome-Wide Association Study / methods*
  • Genome-Wide Association Study / statistics & numerical data
  • Genomics / methods*
  • Genomics / statistics & numerical data
  • Humans
  • Mutation
  • Neoplasms / genetics*
  • Reproducibility of Results