A transcriptional network signature characterizes lung cancer subtypes.

ABSTRACT:

Background

Transcriptional networks play a central role in cancer development. The authors described a systems biology approach to cancer classification based on the reverse engineering of the transcriptional network surrounding the 2 most common types of lung cancer: adenocarcinoma (AC) and squamous cell carcinoma (SCC).

Methods

A transcriptional network classifier was inferred from the molecular profiles of 111 human lung carcinomas. The authors tested its classification accuracy in 7 independent cohorts, for a total of 422 subjects of Caucasian, African, and Asian descent.

Results

The model for distinguishing AC from SCC was a 25-gene network signature. Its performance on the 7 independent cohorts achieved 95.2% classification accuracy. Even more surprisingly, 95%

SUBMITTER: Chang HH 

PROVIDER: S-EPMC3017227 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature