摘要
Invasive breast carcinoma(BRCA)is associated with poor prognosis and high risk of mortality.Therefore,it is critical to identify novel biomarkers for the prognostic assessment of BRCA.Methods:The expression data of polo-like kinase 1(PLK1)in BRCA and the corresponding clinical information were extracted from TCGA and GEO databases.PLK1 expression was validated in diverse breast cancer cell lines by quantitative real-time polymerase chain reaction(qRT-PCR)and western blotting.Single sample gene set enrichment analysis(ssGSEA)was performed to evaluate immune infiltration in the BRCA microenvironment,and the random forest(RF)and support vector machine(SVM)algorithms were used to screen for the hub infiltrating cells and calculate the immunophenoscore(IPS).The RF algorithm and COX regression model were applied to calculate survival risk scores based on the PLK1 expression and immune cell infiltration.Finally,a prognostic nomogram was constructed with the risk score and pathological stage,and its clinical potential was evaluated by plotting calibration charts and DCA curves.The application of the nomogram was further validated in an immunotherapy cohort.Results:PLK1 expression was significantly higher in the tumor samples in TCGA-BRCA cohort.Furthermore,PLK1 expression level,age and stage were identified as independent prognostic factors of BRCA.While the IPS was unaffected by PLK1 expression,the TMB and MATH scores were higher in the PLK1-high group,and the TIDE scores were higher for the PLK1-low patients.We also identified 6 immune cell types with high infiltration,along with 11 immune cell types with low infiltration in the PLK1-high tumors.A risk score was devised using PLK1 expression and hub immune cells,which predicted the prognosis of BRCA patients.In addition,a nomogram was constructed based on the risk score and pathological staging,and showed good predictive performance.Conclusions:PLK1 expression and immune cell infiltration can predict post-immunotherapy prognosis of BRCA patients.
基金
funded by the Natural Science Foundation of Higher Education Institutions of Auhui Province(Grant No.KJ2021A0352)
the Research Fund Project of Anhui Medical University(Grant No.2020xkj236)
Applied Medicine Research Project of Hefei Health Commission(Grant No.HWKJ2019-172-14).
