Four potential prognostic markers for breast cancer identified by hybrid gene and module expression analysis

Abstract

With the aim of screening the prognostic genes for breast cancer (BRCA) and exploring the possible mechanism and clinical value of these genes in the growth and regression stage of disease, we study the genes in the public gene expression omnibus (GEO) GSE22820 and the cancer genome atlas (TCGA). To achieve high-confidence gene candidates for BRCA, we present a hybrid gene and module analysis pipeline that strategically considers data mining on different datasets. Ultimately, four gene candidates, i.e., PLIN1, GPD1, LIPE, and CHRDL1, are targeted for BRCA. Afterwards, Kaplan-Meier survival analysis is performed on these genes for verification, revealing that the overall survival time of patients with low expression of these genes was shorter than that of patients with high expression (with P<0.05). Moreover, in order to study the role of these genes in the mechanisms and functionality related to cytoplasmic lipid metabolism, functional enrichment and pathway analysis are implemented. The results indicate that the expression of the four discovered genes plays an adverse role in BRCA development and could serve as effective biomarkers for predicting the formation and progression of BRCA.