1. Department of Urology, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101, Yunnan, People's Republic of China.
2. Urological disease clinical medical center of Yunnan province, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101, Yunnan, People's Republic of China.
3. Scientific and Technological Innovation Team of Basic and Clinical Research of Bladder Cancer in Yunnan Universities, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101, Yunnan, People's Republic of China.
4. Department of Kidney Transplantation, The Third Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
#These authors contributed equally to this work.
Background: Patients with bladder cancer (BLCA) have a poor prognosis and little progress has been made in treatment. Therefore, the purpose of this work was to employ Mendelian randomization (MR) and transcriptome analysis to identify a novel biomarker that could be used to reliably diagnose BLCA.
Methods: TCGA-BLCA and GSE121711 datasets were obtained from public databases. Genome-wide association study (GWAS) data of BLCA outcome (373,295 samples containing 9,904,926 single nucleotide polymorphisms) were obtained through the IEU OpenGWAS database. Differentially expressed genes were applied as exposure factors, and MR analysis was performed to identify genes that had a causal relationship with BLCA. Then, the patients were divided into high and low expression groups according to the expression levels of candidate genes, and genes with survival differences were identified. Univariate and multivariate Cox regression were used to investigate the prognostic value of the expression of these genes. A nomogram was constructed based on independent prognostic factors, and we analyzed the functions and pathways associated with the identified genes as well as their relationship with the immune microenvironment.
Results: HES4 was identified as a biomarker. HES4 status, age, and stage were identified as independent prognostic factors, and an excellent nomogram was established. Bioinformatic analysis suggested that HES4 might be associated with the activation of the immune response, bone development, and cancer pathways. The BLCA samples were divided into high and low HES4 groups. The stromal score and 33 immune cells were remarkably different between the two groups, with HES4 expression being negatively correlated with macrophages and mast cells, and positively correlated with eosinophils and central memory CD4+ T cells. Finally, HES4 was up-regulated in cancer samples in both TCGA-BLCA and GSE121711 datasets.
Conclusion: This study identified HES4 as an independent prognostic factor for BLCA outcome based on MR and transcriptome analysis, which provides useful information for future research on and treatment of BLCA.
Keywords: Bladder cancer, Mendelian randomization, Biomarker, Tumor immune microenvironment