Abstract

Human bladder cancer (BCa) is the most common urogenital system malignancy. Patients with BCa have limited treatment efficacy in clinical practice. Novel biomarkers could provide more crucial information conferring to cancer diagnosis, treatment, and prognosis. Here, we aimed to explore and identify novel biomarkers associated with cancer-specific survival of patients with BCa to build a prognostic signature. Based on univariate Cox regression, Lasso regression and multivariate Cox regression analysis, we conducted an integrated analysis in the training set (GSE32894) and established a six-gene signature to predict the cancer-specific survival for human bladder cancer. The six genes were Cyclin Dependent Kinase 4 (CDK4), E2F Transcription Factor 7 (E2F7), Collagen Type XI Alpha 1 Chain (COL11A1), Bradykinin Receptor B2 (BDKRB2), Yip1 Interacting Factor Homolog B (YIF1B), and Zinc Finger Protein 415 (ZNF415). Then we validated the prognostic value of the model by using two other datasets (GSE13507 and TCGA). Also, we conducted univariate and multivariate Cox regression analyses, and results indicated that six-gene signature was an independent prognostic factor of cancer-specific survival of patients with BCa. Functional analysis was performed based on the differentially expressed genes of low- and high-risk patients and we found they were enriched in lipid metabolic and cell division-related biological processes. Meanwhile, the gene set enrichment analysis (GSEA) revealed that high-risk samples were enriched in cell cycle and cancer-related pathways (G2/M checkpoint, E2F targets, mitotic spindle, mTOR signaling, spermatogenesis, epithelial mesenchymal transition (EMT), DNA repair, PI3K/AKT/mTOR signaling, unfolded protein response (UPR) and MYC targets V2). Lastly, we detected the relative expression of each signature in bladder cancer cell lines by quantitative real-time PCR (qRT-PCR). As far as we know, currently, the present study is the first research that developed and validated cancer-specific survival prognostic index based on three independent cohorts. And the results revealed that this six-gene signature has the predictive ability for the cancer-specific prognosis. Moreover, we also verified the relative expression of these six signatures between the bladder cell line and four BCa cell lines by qRT-PCR. Nevertheless, experiments to further explore the function of six genes are lacking.

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