Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer.

ABSTRACT:

Background

Molecular heterogeneity of tumors suggests the presence of multiple different subclones that may limit response to targeted therapies and contribute to acquisition of drug resistance, but its quantification has remained challenging.

Results

We performed simulations to evaluate statistical measures that best capture the molecular diversity within a group of tumors for either continuous (gene expression) or discrete (mutations, copy number alterations) molecular data. Dispersion based metrics in the principal component space best captured the underlying heterogeneity. To demonstrate utility of these measures, we characterized the diversity in transcriptional and genomic profiles of different breast tumor subtypes, and showed that basal-like or triple-negative breast

SUBMITTER: Jiang T 

PROVIDER: S-EPMC4197225 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature