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DOI 10.1007/s10142-026-01988-9

Медицинская библиотека · Functional & integrative genomics · 2026

Single-cell and spatial transcriptomics identify CAPG as a key driver of cisplatin resistance in bladder cancer.

Yang Jianwei, Li Xiaoran, Wang Li, Wan Shun, Li Kunpeng, Chen Siyu, Liu Shanhui, Yang Li

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Аннотация

Cisplatin-based chemotherapy is widely used for bladder cancer, yet therapeutic resistance remains a major clinical obstacle. Here, by integrating cisplatin-related single-cell RNA sequencing datasets with spatial transcriptomics, we identified distinct malignant cell populations associated with cisplatin resistance. These resistant states exhibited enhanced stemness features, increased intercellular communication, and metabolic adaptation. Building on these resistance-associated cellular programs, we applied a cross-platform screening strategy incorporating urinary proteomics and transcriptomic profiling of cisplatin-resistant bladder cancer cells to prioritize clinically relevant resistance-associated genes. Through this approach, macrophage capping protein (CAPG) emerged as a key resistance-associated regulator. CAPG expression was consistently elevated in cisplatin-resistant tumors and cell models. Functional studies demonstrated that CAPG depletion suppressed malignant phenotypes, restored cisplatin sensitivity, and reduced IC50 values in vitro, with concordant tumor-suppressive effects observed in xenograft models. Mechanistically, CAPG promoted cisplatin resistance, at least in part, through activation of the PI3K-AKT signaling pathway. Together, our study links resistance-associated cellular states to a functionally validated regulator and provides an integrative framework for identifying clinically relevant regulators of chemotherapy resistance in bladder cancer.

Для цитирования: Yang Jianwei, Li Xiaoran, Wang Li, Wan Shun, Li Kunpeng, Chen Siyu, Liu Shanhui, Yang Li. Single-cell and spatial transcriptomics identify CAPG as a key driver of cisplatin resistance in bladder cancer.. Functional & integrative genomics. 2026. DOI: 10.1007/s10142-026-01988-9.

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