Abstract
BACKGROUND: The integration of multi-omics approaches provides a powerful strategy for understanding cancer. By combining these methods, researchers gain insights into tumor diversity, gene activity, and the tumor microenvironment, which are essential for advancing cancer biology, improving early detection, refining prognostic tools, and developing targeted treatments. This study aims to explore key biomarkers in muscle-invasive bladder cancer (MIBC) and to develop a predictive model for better understanding disease progression and therapeutic responses. METHODS: Single-cell analysis of MIBC samples from public datasets identified basal-related genes. Using Cox analysis of The Cancer Genome Atlas (TCGA)-bladder urothelial carcinoma (BLCA) clinical data and the expression matrix, and combining it with weighted gene co-expression network analysis (WGCNA) of another MIBC dataset, a disintegrin and metalloprotease protein 17 (ADAM17) was identified as a key target gene. We collected BLCA patient samples from TCGA, Shanghai Tenth People's Hospital (STPH), and Guangdong Second Provincial General Hospital (GD2H) to develop the pathomics model for predicting ADAM17 expression. Single-cell validation of ADAM17 expression was performed using GD2H MIBC samples. RESULTS: ADAM17 was highly expressed in MIBC and associated with poor prognosis. Its expression correlated with clinical features such as non-papillary subtype, advanced pathological stage, and higher tissue grade. ADAM17 overexpression was linked to immune reprogramming and drug resistance. The pathomics model effectively predicted ADAM17 expression in BLCA samples. Single-cell analysis of GD2H MIBC samples confirmed ADAM17 overexpression in epithelial cells and identified key pathways in cell communication, matrix remodeling, tumor invasion, and immune regulation. CONCLUSIONS: Multi-omics approaches effectively identify biomarkers for MIBC, with ADAM17 emerging as a key biomarker. Further research is needed to clarify its role in MIBC progression.