Network-based approach to identify biomarkers predicting response and prognosis for HER2-negative breast cancer treatment with taxane-anthracycline neoadjuvant chemotherapy.

ABSTRACT:

Objective

This study aims to identify effective gene networks and biomarkers to predict response and prognosis for HER2-negative breast cancer patients who received sequential taxane-anthracycline neoadjuvant chemotherapy.

Materials and methods

Transcriptome data of training dataset including 310 HER2-negative breast cancer who received taxane-anthracycline treatment and an independent validation set with 198 samples were analyzed by weighted gene co-expression network analysis (WGCNA) approach in R language. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were performed for the selected genes. Module-clinical trait relationships were analyzed to explore the genes and pathways that associated with clinicopathological parameters.

SUBMITTER: Jiang C 

PROVIDER: S-EPMC6730536 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature