Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics analysis

作者：Zhaokai Zhou, Yajun Chen, Zhan Wang, Shuai Yang, Zhengrui Li, Run Shi, Ruizhi Wang, Kui Liu, Xiaojuan Tang, Qi Li, Ran Xu · 发表于：Frontiers in Immunology · 年份：2025 · DOI：10.3389/fimmu.2025.1580986 · 被引用次数：4 · 研究领域：Single-cell and spatial transcriptomics、Ferroptosis and cancer prognosis、Bladder and Urothelial Cancer Treatments

Background: Bladder cancer (BLCA) continues to be a significant cause of cancer mortality in the urinary tract, with therapeutic resistance representing a major barrier to improving patient outcomes. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) are pivotal drivers of BLCA progression, contributing to immune evasion and therapy resistance. This study leverages single-cell analysis to delineate CAF subclusters and explore the immune characteristics of CAFs-based BLCA classification. Materials and methods: Signal-cell RNA sequencing (scRNA-seq) datasets were used to identify CAF subpopulations in BLCA, and bulk RNA-seq datasets were used to construct CAFs-based BLCA classification. Next, we comprehensively explored the distinct heterogeneity and characteristics for four CAFs-based BLCA subtypes. Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects. Results: This study identified CAFs closely associated with BLCA development based on scRNA-seq datasets. Through further systematic clustering and functional analysis of CAFs, we successfully identified 10 distinct CAF sub-clusters, including PSCA+ Pericyte, ISG15+ Pericyte, ACTA2+ Smooth muscle cell (SMC), ACTG2+ SMC, CCL21+ inflammatory Pericyte, CD74+ apCAF, STMN1+ pCAF, CXCL14+ mCAF, APOD+ iCAF, CFD+ iCAF. The study identified four pCAFs-based BLCA distinct subtypes with different molecular, functional, a...