Bladder cancer (BC) is a commonly occurring malignant tumor affecting the urinary tract. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and are therefore attractive biomarker candidates for BC prognosis. In this study, we profiled the expression of ZNFs in The Cancer Genome Atlas (TCGA) BC cohort and developed a novel prognostic signature based on 7 ZNF-coding genes. After external validation of the model in the GSE48276 dataset, we integrated the 7-ZNF-gene signature with patient clinicopathological data to construct a nomogram that forecasted 1-, 2-, and 3-year OS with good predictive accuracy. We then accessed The Genomics of Drug Sensitivity in Cancer database to predict the therapeutic drug responses of signature-defined high- and low-risk BC patients in the TCGA cohort. Greater sensitivity to chemotherapy was revealed in the low-risk group. Finally, we conducted gene set enrichment analysis of the signature genes and established, by applying the ESTIMATE algorithm, distinct correlations between the two risk groups and the presence of stromal and immune cell types in the tumor microenvironment. By allowing effective risk stratification of BC patients, our novel ZNF gene signature may enable tailoring more intensive treatment for high-risk patients.
Keywords: bladder cancer; prognosis; treatment; zinc finger proteins.