Multi-Omics Analysis Reveals m7G Methylation-Related Genes May Be Involved in TGF-β Signaling-Mediated Anti-PD-L1 Response in Bladder Cancer

Hai-Qi Liang,1,* Yu-Jian Li,1,* Jia-Yin Yu,1,* Qi-Zhou Mo,1 Qiu-Ju Wei,2 Yu-Qi Liang,2 Fa-Ye Wei,1 Xiao-Ping Zhang,3 Jia-Wen Zhao,1 Yu-Xian He,2 Xin-Dong Feng,2 Bin-Tong Yin,1 Xin-Wen Liang,1 Ren-Jun Nong,1 Yao-Yu Wang,1 Min Qin,4 Ji-Wen Cheng1 1Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 2Guangxi Medical University, Nanning, Guangxi, People’s Republic of China; 3Department of Urology, Liuzhou Traditional Chinese Medical Hospital, Liuzhou, Guangxi, People’s Republic of China; 4Human Sperm Bank, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ji-Wen Cheng, Department of Urology, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi, 530021, People’s Republic of China, Email [email protected] Min Qin, Human Sperm Bank, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi, 530021, People’s Republic of China, Email [email protected]: Immunotherapy resistance is a significant challenge in bladder cancer treatment. The role of N7-methylguanosine (m7G) methylation in this process remains unclear. This study aims to investigate the potential role of m7G methylation-related genes (m7GRGs) in immunotherapy resistance using a multi-omics approach.Methods: This study integrated bioinformatics analysis with in vitro experimental validation. We obtained bulk, single-cell, and spatial transcriptomics data from multiple bladder cancer cohorts in public databases, including TCGA, GEO and IMvigor210. Machine learning models were performed to identify molecular clusters and screen signature genes. Gene ontology analysis was used for gene function enrichment. siRNA transfection knocked down the expression of characteristic genes in bladder cancer cell lines to validate their roles in signaling regulation. Gene expression was assessed using qRT-PCR, Western blot, and immunohistochemistry. Additionally, CCK-8 and wound healing assays were performed to evaluate the effects of characteristic genes on the proliferation and migration of bladder cancer cells.Results: Two bladder cancer molecular clusters were identified, with the C1 cluster exhibiting worse prognosis, higher m7GRGs expression, and an immunosuppressive microenvironment. NUDT10 was a key prognostic gene distinguishing molecular clusters. A subset of differentially methylated genes correlated with anti-PD-L1 resistance were enriched in the TGF-β signaling pathway. Single-cell and spatial transcriptomics revealed that NUDT10 was co-expressed with TGF-β activator LRRC32. IMvigor210 and GSE176307 datasets found that expression of NUDT10 and LRRC32 was associated with poor response to anti-PD-L1 therapy. Knockdown of NUDT10 in bladder cancer cells inhibited the expression of LRRC32 and reduced the proliferation and migration abilities of the cancer cells.Conclusion: This study identifies NUDT10 as a key gene associated with poor prognosis based on m7GRGs-defined molecular clusters in bladder cancer. NUDT10 expression may regulate TGF-β signaling and is associated with poor response to anti-PD-L1 therapy in advanced or metastatic bladder cancer.Keywords: bladder cancer, m7G methylation, immune checkpoint blockade, immunotherapy, TGF-&#x03B2