CENPW as a biological indicator: predicting prognosis and guiding treatment in a patient with Kidney Renal Clear Cell Carcinoma

Abstract

Abstract Purpose: Employing data obtained from The Cancer Genome Atlas (TCGA)and GEO database to investigate whether the centromere protein W(CENPW) gene can be used as a biological marker for prognosis and guiding therapy for kidney renal clear cell carcinoma (KIRC). Methods: KIRC patient’s transcriptome profiling data and clinical data were downloaded from the TCGA and GEO database. Thereafter, TIMER2.0 was used to analyze the expression of CENPW in normal and tumor tissues. Single-gene differential analysis and survival analysis were used to demonstrate the relationship between CENPW expression and prognosis. Clinical correlation analysis and univariate and multivariate analysis were utilized to identify the expression relationship of target genes in clinical features. Receiver operating characteristic curves ROC was harnessed to assess the reliability and sensitivity of CENPW as a predictor of prognosis. Further, Nomo plots and prognostic nomograms were established to predict probable 1-, 3-, and 5-year overall KIRC patient survival. Moreover, gene co-expression analysis was used to analyze the relationship between target genes and co-expressed genes. In addition, functional enrichment analysis was employed to identify the biological functions of CENPW. GSEA was performed to explore underlying biological processes and cellular pathways. Finally, immune cell infiltration analysis, clustered KIRC patients were performed according to the expression of CD8(+)T cells and performed immunotherapy analysis and drug sensitivity tests among the two clusters. At the same time, we also performed HE staining and CD8 immunochemical staining in tumor tissues and normal tissues. The results of IHC staining were quantified for differential and survival analysis. Results: We constructed and validated the CENPW prognostic signature of KIRC patients in the TCGA and GEOdatabase. It was thereafter confirmed that patients with high CENPW expression had a poor prognosis, while the ROC curve (AUC at 5 years: 0.658) indicated that CENPW had reliable predictive power. Subsequently,a prognostic nomogram was built and achieved strong predictive accuracy. Some chemical drugs such as 17-AAG, CCT018159 and CI-1040 were more sensitive in cluster 1 than in cluster 2. In addition，there was significant difference between cluster 1 and cluster 2 in PD-1 and CTLA4 immunotherapy. Conclusion: CENPW may be employed as a biological indicator for prognosis and guiding treatment in KIRC patients.