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

• DOI: 10.7717/peerj.7515
• Publication Date: 2019-09-03T08:41:36Z
• Authors: Cui Jiang; Shuo Wu; Lei Jiang; Zhichao Gao; Xiaorui Li; Yangyang Duan; Na Li; Tao Sun
• Keywords: KEGG; Taxane; FOXA1

Objective This study aims to identify effective gene networks and biomarkers predict response prognosis for HER2-negative breast cancer patients who received sequential taxane-anthracycline neoadjuvant chemotherapy. Materials Methods Transcriptome data of training dataset including 310 treatment an independent validation set with 198 samples were analyzed by weighted co-expression network analysis (WGCNA) approach in R language. Gene ontology (GO) terms Kyoto Encyclopedia Genes Genomes (KEGG) pathways performed the selected genes. Module-clinical trait relationships explore genes that associated clinicopathological parameters. Log-rank tests COX regression used prognosis-related Results We found a significant correlation expression module distant relapse–free survival (HR = 0.213, 95% CI [0.131–0.347], P 4.80E−9). blue contained enriched biological process hormone levels regulation, reproductive system, estradiol, cell growth mammary gland development as well estrogen, apelin, cAMP, PPAR signaling pathway fatty acid metabolism. From this module, we further screened validated six hub (CA12, FOXA1, MLPH, XBP1, GATA3 MAGED2), which significantly both better chemotherapeutic favorable BC patients. Conclusion WGCNA reveal regulate chemotherapy, estrogen signaling, apelin cAMP In addition, CA12, MAGED2 might serve novel predicting cancer.