A Four-gene Decision Tree Signature Classification of Triple-negative Breast Cancer: Implications for Targeted Therapeutics.

ABSTRACT: The molecular complexity of triple-negative breast cancers (TNBCs) provides a challenge for patient management. We set out to characterize this heterogeneous disease by combining transcriptomics and genomics data, with the aim of revealing convergent pathway dependencies with the potential for treatment intervention. A Bayesian algorithm was used to integrate molecular profiles in two TNBC cohorts, followed by validation using five independent cohorts (n = 1,168), including three clinical trials. A four-gene decision tree signature was identified, which robustly classified TNBCs into six subtypes. All four genes in the signature (EXO1, TP53BP2, FOXM1, and RSU1) are associated with either genomic instability, malignant growth, or treatment response. One of the six subty

SUBMITTER: Quist J 

PROVIDER: S-EPMC6330084 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature