Integrative analysis reveals disease-associated genes and biomarkers for prostate cancer progression.

ABSTRACT:

Background

Prostate cancer is one of the most common complex diseases with high leading cause of death in men. Identifications of prostate cancer associated genes and biomarkers are thus essential as they can gain insights into the mechanisms underlying disease progression and advancing for early diagnosis and developing effective therapies.

Methods

In this study, we presented an integrative analysis of gene expression profiling and protein interaction network at a systematic level to reveal candidate disease-associated genes and biomarkers for prostate cancer progression. At first, we reconstructed the human prostate cancer protein-protein interaction network (HPC-PPIN) and the network was then integrated with the prostate cancer gene expression data to identify modules rel

SUBMITTER: Li Y 

PROVIDER: S-EPMC4110715 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature