Remodeling of the tumor microenvironment in muscle-invasive bladder cancer: insights from single-cell and spatial transcriptomics after neoadjuvant immunochemotherapy

BACKGROUND: Neoadjuvant immunochemotherapy (nICT), defined in this study as PD-L1 blockade combined with cisplatin-based chemotherapy, provides substantial clinical benefits in muscle-invasive bladder cancer (MIBC). However, the tumor immune microenvironment (TIME) is highly heterogeneous, resulting in variable patient responses and persistent therapy resistance. This study investigates key immune cell subsets, intercellular communication networks, and spatial distributions within the TIME of MIBC, with a focus on cellular and spatial features associated with nICT response. METHODS: Patients were classified into responder and non-responder groups according to RECIST 1.1-based radiological evaluation. Responders were defined as patients achieving complete or partial response, whereas non-responders were defined as patients with stable or progressive disease after adequate nICT exposure and evaluable imaging. Representative computed tomography images and fresh tissue samples were collected from four no-treatment controls (NT), three nICT responders (R), and three nICT non-responders (NR). Samples underwent single-cell RNA sequencing and spatial transcriptomics sequencing. Cell populations were annotated to assess infiltration abundance, cell-cell communication networks, and pseudotime trajectories. Resistance-associated cell subsets and their spatial niches were identified. RESULTS: Following quality control, the tumor microenvironment (TME) was classified into ten major cell subsets based on canonical markers. Cross-sectional group comparative analyses showed significant remodeling of the TME in the NR and R groups. B-cell infiltration was elevated in the NR group, whereas macrophages, fibroblasts, and mast cells were enriched in the R group. Functional alterations in activated CD4 + T cells and impaired differentiation of naive CD8 + T cells were identified as key drivers of acquired therapy resistance. Accumulation of macrophage-derived CXCL8 was also observed as a resistance driver. Cancer-associated fibroblasts (CAFs) served as a physical barrier, contributing to the establishment of an immunosuppressive TME. Notably, strong spatial co-localization between macrophage-derived CXCL8 and CAFs was observed in NR tumors, suggesting a cooperative role in mediating resistance to nICT. Further cell-cell communication analysis using spatial transcriptomics indicated that SPP1 signaling from macrophages (CXCL8) to CAFs contributes to TME reprogramming and resistance to nICT. CONCLUSION: The integrated analysis identifies distinct immunological features that underlie differential nICT responses in MIBC. These findings provide a theoretical basis for optimizing personalized neoadjuvant therapy strategies.

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Journal
Molecular Cancer
Published
2026-07-17
DOI
https://doi.org/10.1186/s12943-026-02738-y
Primary Topic
Single-cell and spatial transcriptomics
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article
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article

Remodeling of the tumor microenvironment in muscle-invasive bladder cancer: insights from single-cell and spatial transcriptomics after neoadjuvant immunochemotherapy

Yiqing You, Deyu Zuo, Gautam Sethi, Yuanyuan Bai et al.
Molecular Cancer
Single-cell and spatial transcriptomics
article

Remodeling of the tumor microenvironment in muscle-invasive bladder cancer: insights from single-cell and spatial transcriptomics after neoadjuvant immunochemotherapy

Yiqing You, Deyu Zuo, Gautam Sethi, Yuanyuan Bai, Haoyu Xu, Zhu Y, Weiyang He, W Tang, Xin Chen, Hai Chang, Junwu Li, Lei Yang, Guozhi Zhao
article en

Abstract

BACKGROUND: Neoadjuvant immunochemotherapy (nICT), defined in this study as PD-L1 blockade combined with cisplatin-based chemotherapy, provides substantial clinical benefits in muscle-invasive bladder cancer (MIBC). However, the tumor immune microenvironment (TIME) is highly heterogeneous, resulting in variable patient responses and persistent therapy resistance. This study investigates key immune cell subsets, intercellular communication networks, and spatial distributions within the TIME of MIBC, with a focus on cellular and spatial features associated with nICT response. METHODS: Patients were classified into responder and non-responder groups according to RECIST 1.1-based radiological evaluation. Responders were defined as patients achieving complete or partial response, whereas non-responders were defined as patients with stable or progressive disease after adequate nICT exposure and evaluable imaging. Representative computed tomography images and fresh tissue samples were collected from four no-treatment controls (NT), three nICT responders (R), and three nICT non-responders (NR). Samples underwent single-cell RNA sequencing and spatial transcriptomics sequencing. Cell populations were annotated to assess infiltration abundance, cell-cell communication networks, and pseudotime trajectories. Resistance-associated cell subsets and their spatial niches were identified. RESULTS: Following quality control, the tumor microenvironment (TME) was classified into ten major cell subsets based on canonical markers. Cross-sectional group comparative analyses showed significant remodeling of the TME in the NR and R groups. B-cell infiltration was elevated in the NR group, whereas macrophages, fibroblasts, and mast cells were enriched in the R group. Functional alterations in activated CD4 + T cells and impaired differentiation of naive CD8 + T cells were identified as key drivers of acquired therapy resistance. Accumulation of macrophage-derived CXCL8 was also observed as a resistance driver. Cancer-associated fibroblasts (CAFs) served as a physical barrier, contributing to the establishment of an immunosuppressive TME. Notably, strong spatial co-localization between macrophage-derived CXCL8 and CAFs was observed in NR tumors, suggesting a cooperative role in mediating resistance to nICT. Further cell-cell communication analysis using spatial transcriptomics indicated that SPP1 signaling from macrophages (CXCL8) to CAFs contributes to TME reprogramming and resistance to nICT. CONCLUSION: The integrated analysis identifies distinct immunological features that underlie differential nICT responses in MIBC. These findings provide a theoretical basis for optimizing personalized neoadjuvant therapy strategies.

Molecular Cancer
National University of Singapore (SG), The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), First People's Hospital of Chongqing (CN), Chongqing Medical University (CN)
Good health and well-being, Zero hunger
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
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