Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era

Biomed Res Int. 2013:2013:901578. doi: 10.1155/2013/901578. Epub 2013 Jul 15.

Abstract

The discovery of prostate cancer biomarkers has been boosted by the advent of next-generation sequencing (NGS) technologies. Nevertheless, many challenges still exist in exploiting the flood of sequence data and translating them into routine diagnostics and prognosis of prostate cancer. Here we review the recent developments in prostate cancer biomarkers by high throughput sequencing technologies. We highlight some fundamental issues of translational bioinformatics and the potential use of cloud computing in NGS data processing for the improvement of prostate cancer treatment.

Publication types

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

MeSH terms

  • Computational Biology / methods*
  • Genome, Human
  • Genomics
  • High-Throughput Nucleotide Sequencing*
  • Humans
  • Male
  • Prognosis
  • Prostatic Neoplasms / diagnosis
  • Prostatic Neoplasms / genetics*
  • Prostatic Neoplasms / pathology
  • Protein Biosynthesis*