Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen

Cancer Biology & Therapy
Rong LiuHong-Hao Zhou

Abstract

This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this appro...Continue Reading

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Sep 15, 2016·Cancer Informatics·Wenying YanGuang Hu
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Aug 20, 2021·Frontiers in Genetics·Christina Y Yu, Antonina Mitrofanova

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Datasets Mentioned

BETA
GSE6532
GSE2990

Methods Mentioned

BETA
profilers
xenograft
xenografts

Software Mentioned

R ‘ wgcna ’
DAVID
WGCNA
R

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