Specific Gene Set Scores in Prognostic Prediction of Muscle Invasive Bladder Cancer

Abstract

Background: Bladder cancer is one of the most common urogenital tract tumor worldwide. The convenient access to The Cancer Genome Atlas (TCGA) database enables us to explore the genes that have a predictive role in overall survival through genome-wide expression profiles. The prediction may provide help for easier classification of subtypes, so as to make better diagnosis and prognosis prediction. Methods: Tumor microenvironments, including immune cells and stromal cells, have been shown to be closely related to tumor progression and prognosis. By leveraging the ESTIMATE algorithm, we could calculate the immune and stromal scores in the tumor, thus quantifying its composition in the tumor tissue. To better understand the genes' role in tumor prognosis in immune and stromal sets, patients with bladder cancer in TCGA database were divided into immune and stromal high/low groups, and the differentially expressed genes (DEGs) were obtained. Functional enrichment analysis and protein-protein analysis demonstrated the roles of these genes. Then Gene Set Variation Analysis (GSVA) was used to comprehensively score these DEGs to verify their predictive effect on the prognosis of bladder cancer. Finally, these screened DEGs and scores were used to verify their universality in an external database in GEO database (GSE48277-GPL6947). Results: ACTC1, SFRP2, and OMD were screened and independently predicted prognosis (log-rank test p=0*0118, 0*0391, 0*0441, respectively), and their GSVA scores also significantly predicted prognosis (log-rank test p<0*05). Conclusions: By synthetic analysis of individual DEGs and DEG sets, we obtained tumor microenvironment-related genes and gene sets that could predict the prognosis of bladder cancer. Funding Statement: This study was funded by the National Natural Science Foundation of China (81802535, 81972388, 81772710), China postdoctoral fund(223427), Nanjing Medical Science and technique Development Foundation (YKK 18064), The Project of Invigorating Health Care through Science, Technology and Education, Jiangsu Provincial Key Medical Discipline (Laboratory) (ZDXKB2016014). Declaration of Interests: The authors stated: None. Ethics Approval Statement: Not required.