Breast cancer subtype predictors revisited: from consensus to concordance?

ABSTRACT:

Background

At the molecular level breast cancer comprises a heterogeneous set of subtypes associated with clear differences in gene expression and clinical outcomes. Single sample predictors (SSPs) are built via a two-stage approach consisting of clustering and subtype predictor construction based on the cluster labels of individual cases. SSPs have been criticized because their subtype assignments for the same samples were only moderately concordant (Cohen's κ<0.6).

Methods

We propose a semi-supervised approach where for five datasets, consensus sets were constructed consisting of those samples that were concordantly subtyped by a number of different predictors. Next, nine subtype predictors - three SSPs, three subtype classification models (SCMs) and three novel rule-based

SUBMITTER: Sontrop HMJ 

PROVIDER: S-EPMC4893290 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature