Integrated genomic analysis identifies subclasses and prognosis signatures of kidney cancer.

ABSTRACT:

Purpose

To define robust miRNA-based molecular classifiers for human clear cell renal cell carcinoma (ccRCC) subgrouping and prognostication.

Experimental design

Multidimensional data of over 500 clear cell renal cell carcinoma (ccRCC) patients were retrieved from The Cancer Genome Atlas (TCGA) archive. Data analysis was based on a novel computational approach that selectively considers patients with extreme expression values of miRNAs to detect survival-associated molecular signatures.

Results

Our in silico analysis unveiled a novel ccRCC-specific 5-miRNA (miR-10b, miR-21, miR-143, miR-183, and miR-192) signature able, when combined with information from conventional TNM staging and the age of the patient, to prognosticate ccRCC outcome more accurately than known ccR

SUBMITTER: Christinat Y 

PROVIDER: S-EPMC4496372 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature