Multiple Datasets Revealed T Cell Pathway Related Genes Associated with Better Prognosis and Chemotherapy in Breast Cancer

Abstract

Ping Chen, Shuhui Lai, Junping Deng, Sixuan Guo, Yangjuan Huang, Jian Li, Xiaowen Fang, Yaping Xie,Yao Zhou

Breast cancer (BC) is the most frequent cancer diagnosed in women, and the second foremost source of cancer-related death. Despite conventional treatment, patients experience metastasis and poor survival. This study aimed to systematically validate the data of previous studies on BC to fill the gaps in large-scale meta-analyses and evaluate pivotal genes. We conducted meta-analysis on target genes chosen from the Gene Expression Omnibus (GEO) database to classify the differently expressed genes (DEGs). Then pathway enrichment study of the Kyoto Encyclopedia of Genes and Genomics (KEGG) and proteinproteins interaction (PPI) were performed to investigate the biological pathway leading to DEGs. Survival analysis and logistic regression of the receiver operating characteristics (ROC) were used to evaluate the ability of core gene expression to predict treatment efficacy. The KEGG pathway study revealed that 222 DEGs were enriched in the pathways associated with the cell cycle and T-cell. Kaplan-Meier analysis of total survival showed that hub genes (CD247, ZAP70, LCK, PRKCQ) were associated with better prognosis in BC patients. Pharmacodynamics data, ROC curve, and logistic regression analysis showed that PRKCQ is associated with T-cell pathways and its expression could predict treatment efficacy. It can therefore be used as a biomarker of BC prognosis.

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