breastCancerSurv: gene signature for breast cancer survival

In eNetXplorer: Quantitative Exploration of Elastic Net Families for Generalized Linear Models

Description

Gene signature proposed by Desmedt et al associated with breast cancer survival. Microarray data from van't Veer et al and van de Vijver et al. Dataset adapted from Schroeder et al.

Usage

data(breastCancerSurv)

Format

A numerical matrix of predictors is provided with subjects as rows and genes as columns. The response is a two-column matrix with survival time (in days) and status (0=censored, 1=dead).

Details

Desmedt et al proposed a gene signature associated with breast cancer clinical outcome that captures different biological processes: AURKA (proliferation), PLAU (tumor invasion/metastasis), STAT1 (immune response), VEGFA (angiogenesis), CASP3 (apoptosis), ESR1 (ER signaling) and ERBB2 (HER2 signaling). Microarray data was obtained from van't Veer et al and van de Vijver et al. The dataset was adapted from Schroeder et al. Missing predictor data was imputed using the missForest package. Subjects with missing survival data were removed.

References

Desmedt C et al. Biological Processes Associated with Breast Cancer Clinical Outcome Depend on the Molecular Subtypes, Clinical Cancer Research (2008) 14(16):5158-5165.

Schroeder MS et al. survcomp: an R/Bioconductor package for performance assessment and comparison of survival models, Bioinformatics (2011) 27(22):3206-3208.

van de Vijver MJ et al. A Gene Expression Signature as a Predictor of Survival in Breast Cancer, New England Journal of Medicine (2002) 347(25):1999-2009.

van't Veer LJ et al. Gene expression profiling predicts clinical outcome of breast cancer, Nature (2002) 415:530-536.

eNetXplorer documentation built on Aug. 30, 2020, 1:06 a.m.