肿瘤微环境中的成纤维细胞：空间转录组学揭示的肿瘤进展中的异质性与动态相互作用

Cancer-associated fibroblasts (CAFs) constitute the most abundant and functionally versatile stromal component of the tumor microenvironment (TME), with their phenotype and spatial location jointly governing tumor growth, immune evasion, metastasis, and therapeutic resistance. While traditional single-cell RNA sequencing has unveiled CAF transcriptional heterogeneity, it forfeits crucial tissue-contextual information; the advent of high-resolution spatial transcriptomics (ST)—encompassing platforms such as 10xVisium, Slide-seq, Stereo-seq, and MERFISH—now overcomes this limitation by preserving native tissue architecture while simultaneously capturing whole-transcriptome data and single-cell spatial coordinates, enabling comprehensive mapping of CAF “spatial atlases. ” Recent literature has consolidated CAFs into five functional subtypes: myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), antigen-presenting CAFs (apCAFs), matrix-remodeling CAFs (matCAFs), and proliferative CAFs (pCAFs), each exhibiting spatial preferences and dynamic plasticity within tumor cores, hypoxic niches, invasive fronts, and tertiary lymphoid structures.

Distinct subpopulations form sub-micron-scale interaction networks with SPP1+ macrophages, CXCL13+ CD8+ T cells, natural killer cells, or endothelial cells to orchestrate either immune exclusion or activation. Multi-cancer investigations in colorectal, pancreatic, hepatic, and lung malignancies demonstrate that peri-tumoral enrichment of POSTN+ myCAFs predicts immune exclusion and shortened survival, whereas therapeutic targeting of CAF-immune or CAF-cancer signaling axes—such as IL-34/CSF1R, TGF-β/LOXL2, and JAG1/NOTCH1—can reverse immunotherapy resistance.

Looking forward, integrative multi-omics, subcellular-resolution in-vivo tracking, and AI-driven spatial interaction modeling will further decode CAF spatial phenotypes and expedite their incorporation into precision oncology frameworks.