Cancer omics: from regulatory networks to clinical outcomes

Cancer Lett. 2013 Nov 1;340(2):277-83. doi: 10.1016/j.canlet.2012.11.033. Epub 2012 Nov 29.

Abstract

Current limitation in cancer genomic studies is a lack of the integration of various omics data generated through next generation sequencing technologies, as well as a lack of the sounding and comprehensive epigenomic and genomic information about a particular cancer cell type. In this review, we will discuss main aspects of current genomics research with its application in cancer topics. We will first overview the next-generation sequencing technologies, then outline the major computational approaches, particularly focusing on ChIP-based omics data, and list several remaining open questions facing computational biologists, further present regulatory network analysis inferred from the ChIP-based omics data; finally implicate the clinical outcomes from the network and pathway analysis.

Keywords: Cancer omics; Clinical outcomes; Next generation sequencing; Regulatory networks.

Publication types

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

MeSH terms

  • Animals
  • Biomarkers, Tumor / genetics*
  • Computational Biology
  • DNA Mutational Analysis
  • Evolution, Molecular
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • Genetic Predisposition to Disease
  • Genetic Testing
  • Genome, Human*
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing*
  • Humans
  • Mutation
  • Neoplasms / diagnosis
  • Neoplasms / genetics*
  • Neoplasms / therapy
  • Phenotype
  • Precision Medicine
  • Predictive Value of Tests
  • Prognosis
  • Sequence Analysis, DNA*
  • Systems Integration

Substances

  • Biomarkers, Tumor