Performance of a PLK1‐based immune risk model for prognosis and treatment response prediction in breast cancer

Author:

Chen Yan1ORCID,You Yiqing1,Wu Qiaoling2,Wu Jing1,Lin Shujing1,Sun Yang2,Cui Zhaolei1ORCID

Affiliation:

1. Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital Fuzhou PR China

2. Department of Gynecologic Oncology Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital Fuzhou PR China

Abstract

AbstractObjectivePolo‐like kinase 1 (PLK1), a serine/threonine‐protein kinase, functions as a potent oncogene in the initiation and progression of tumor. The aim of this study is to assess potential correlations between PLK1 expression and immune infiltration in breast cancer (BRCA) and construct a PLK1‐based immune risk model applicable for prognosis and treatment response prediction in BRCA.MethodsWe collected data on PLK1 gene expression in BRCA patients from The Cancer Genome Atlas (TCGA) database. Thereafter, we analyzed the associations of PLK1 expression with immune cell infiltration and immunomodulators, and established a prognostic risk model based on seven PLK1‐associated immunomodulator genes and a nomogram for survival prediction.ResultsBRCA prognosis, clinical stage progression, and tumor classification were all shown to be substantially correlated with PLK1 expression. The PLK1 gene was significantly enriched in T cell and B cell receptors and molecules of the chemokine signaling pathways. Specifically, PLK1 expression was positively correlated with the CD8+ T cell and regulatory T cell (Tregs) activation and negatively correlated with M2 macrophage infiltration. The seven‐genes‐based risk model could serve as an independent prognostic factor of BRCA. The risk model was markedly correlated with the expression of programmed cell death protein 1/programmed cell death ligand 1 (PD‐1/PD‐L1; both p < 0.001) immune checkpoints, and tumor mutation burden (TMB). High‐ and low‐risk BRCA patients identified by the risk model responded differently to anti‐PD‐1 and/or anti‐CTLA4 therapy, as well as common chemotherapy drugs, like cisplatin, paclitaxel, and gemcitabine.ConclusionThis PLK1‐based immune risk model can effectively predict the prognosis and tumor progression of BRCA, identify gene mutations, and evaluate patient's response toward immunotherapy and chemotherapy regimens.

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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