Frontiers in bioinformatics · 2026
A vasculogenic mimicry subtype unveiled by integrated multi-omics predicts prognosis and guides immunotherapy in MIBC.
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Wei Luqing, Liao Shuzhen, Feng Xin, Tang Zhenyou, Tang Zhenyu, Tao Yuting, Zheng Youwen, Liu Tao, Qin Zezu, Cao Xuancheng, Tang Zhenkun, Liu Yuxin, Cai Yiwei, Li Tianyu, Feng Chao, Wang Qiuyan, Tang Zhong
Аннотация
INTRODUCTION: The progression, recurrence, and metastasis of muscle-invasive bladder cancer (MIBC) are closely associated with vasculogenic mimicry (VM). Establishing a VM-based molecular subtyping system and clarifying its regulatory network are essential to overcome current therapeutic limitations in MIBC.
METHODS: This study collected 1,489 previously reported VM-related genes and identified differentially expressed genes between tumor cells and endothelial cells using single-cell transcriptomic analysis. The intersection of these gene sets yielded VM-related genes, of which 12 were selected to construct a prognostic model validated by multi-omics data, including bulk transcriptomic, genomic, mass cytometry, spatial transcriptomic, and metabolomic datasets. Single-cell and bulk RNA sequencing data were integrated to develop a VM-based molecular subtyping system.
RESULTS: MIBC patients were classified into three subtypes: VM, Mixed-VM, and Non-VM, each showing distinct prognostic outcomes consistently validated across multiple independent cohorts. The VM subtype demonstrated the most aggressive clinical behavior, characterized by high cellular plasticity and extensive metabolic reprogramming. Compared to the Non-VM subtype, VM-subtype patients exhibited an immunosuppressive tumor microenvironment and elevated tumor mutational burden (TMB), indicating a potentially favorable response to immunotherapy. Combined treatment with the MEK inhibitor TAK-733 and immune checkpoint inhibitors was proposed as a promising therapeutic strategy for this subgroup.
CONCLUSION: This novel VM-based molecular subtyping system for MIBC shows strong potential for clinical application in prognosis prediction, immunotherapy response evaluation, and targeted drug discovery, providing a framework to guide personalized treatment strategies for MIBC patients.
METHODS: This study collected 1,489 previously reported VM-related genes and identified differentially expressed genes between tumor cells and endothelial cells using single-cell transcriptomic analysis. The intersection of these gene sets yielded VM-related genes, of which 12 were selected to construct a prognostic model validated by multi-omics data, including bulk transcriptomic, genomic, mass cytometry, spatial transcriptomic, and metabolomic datasets. Single-cell and bulk RNA sequencing data were integrated to develop a VM-based molecular subtyping system.
RESULTS: MIBC patients were classified into three subtypes: VM, Mixed-VM, and Non-VM, each showing distinct prognostic outcomes consistently validated across multiple independent cohorts. The VM subtype demonstrated the most aggressive clinical behavior, characterized by high cellular plasticity and extensive metabolic reprogramming. Compared to the Non-VM subtype, VM-subtype patients exhibited an immunosuppressive tumor microenvironment and elevated tumor mutational burden (TMB), indicating a potentially favorable response to immunotherapy. Combined treatment with the MEK inhibitor TAK-733 and immune checkpoint inhibitors was proposed as a promising therapeutic strategy for this subgroup.
CONCLUSION: This novel VM-based molecular subtyping system for MIBC shows strong potential for clinical application in prognosis prediction, immunotherapy response evaluation, and targeted drug discovery, providing a framework to guide personalized treatment strategies for MIBC patients.