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多组学分析揭示了癌症相关成纤维细胞表型在物种和组织起源上的保守性。

Multiomic analysis reveals conservation of cancer-associated fibroblast phenotypes across species and tissue of origin.

机构信息

Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Surgery, Stanford University School of Medicine, Stanford CA 94305, USA.

Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA.

出版信息

Cancer Cell. 2022 Nov 14;40(11):1392-1406.e7. doi: 10.1016/j.ccell.2022.09.015. Epub 2022 Oct 20.


DOI:10.1016/j.ccell.2022.09.015
PMID:36270275
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9669239/
Abstract

Cancer-associated fibroblasts (CAFs) are integral to the solid tumor microenvironment. CAFs were once thought to be a relatively uniform population of matrix-producing cells, but single-cell RNA sequencing has revealed diverse CAF phenotypes. Here, we further probed CAF heterogeneity with a comprehensive multiomics approach. Using paired, same-cell chromatin accessibility and transcriptome analysis, we provided an integrated analysis of CAF subpopulations over a complex spatial transcriptomic and proteomic landscape to identify three superclusters: steady state-like (SSL), mechanoresponsive (MR), and immunomodulatory (IM) CAFs. These superclusters are recapitulated across multiple tissue types and species. Selective disruption of underlying mechanical force or immune checkpoint inhibition therapy results in shifts in CAF subpopulation distributions and affected tumor growth. As such, the balance among CAF superclusters may have considerable translational implications. Collectively, this research expands our understanding of CAF biology, identifying regulatory pathways in CAF differentiation and elucidating therapeutic targets in a species- and tumor-agnostic manner.

摘要

癌症相关成纤维细胞(CAFs)是实体瘤微环境的重要组成部分。CAFs 曾经被认为是一种相对均匀的基质产生细胞群体,但单细胞 RNA 测序揭示了 CAF 表型的多样性。在这里,我们使用全面的多组学方法进一步探究 CAF 的异质性。通过对同一细胞染色质可及性和转录组进行配对分析,我们在复杂的空间转录组和蛋白质组学图谱上对 CAF 亚群进行了综合分析,确定了三个超级群:稳态样(SSL)、机械响应(MR)和免疫调节(IM)CAFs。这些超级群在多种组织类型和物种中得到了重现。对潜在机械力的选择性破坏或免疫检查点抑制治疗会导致 CAF 亚群分布的变化,并影响肿瘤生长。因此,CAF 超级群之间的平衡可能具有重要的转化意义。总的来说,这项研究扩展了我们对 CAF 生物学的理解,确定了 CAF 分化的调控途径,并以物种和肿瘤不可知的方式阐明了治疗靶点。

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引用本文的文献

[1]
Cancer-derived mitochondria fuel fibroblasts to become pro-tumorigenic.

Nat Cancer. 2025-8-28

[2]
CAF-Driven Mechanotransduction via Collagen Remodeling Accelerates Tumor Cell Cycle Progression.

Gels. 2025-8-13

[3]
Cancer‑associated fibroblasts in human malignancies, with a particular emphasis on sarcomas (Review).

Int J Oncol. 2025-10

[4]
Lymphoid stroma in all its states.

Front Immunol. 2025-7-16

[5]
Plasticity and Functional Heterogeneity of Cancer-Associated Fibroblasts.

Cancer Res. 2025-7-29

[6]
Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumours to decode genotype-to-phenotype relationships.

Nat Biomed Eng. 2025-7-28

[7]
Hidden forces: the impact of cancer-associated fibroblasts on non-small cell lung cancer development and therapy.

J Transl Med. 2025-7-25

[8]
Artemisinin derivatives maintain fibroblast normalization by acting on tumor-stroma interactions in oral tongue squamous cell carcinoma.

Am J Cancer Res. 2025-6-15

[9]
Bridging the tumor microenvironment: the pivotal role of cancer-associated fibroblasts in tumor cachexia development.

Mol Cancer. 2025-7-14

[10]
Tumour tissue: heterogeneous, but not disordered.

Nat Rev Cancer. 2025-7-14

本文引用的文献

[1]
DOCK2 contributes to pulmonary fibrosis by promoting lung fibroblast to myofibroblast transition.

Am J Physiol Cell Physiol. 2022-7-1

[2]
Multi-omic analysis reveals divergent molecular events in scarring and regenerative wound healing.

Cell Stem Cell. 2022-2-3

[3]
Integrated spatial multiomics reveals fibroblast fate during tissue repair.

Proc Natl Acad Sci U S A. 2021-10-12

[4]
Mesenchymal Lineage Heterogeneity Underlies Nonredundant Functions of Pancreatic Cancer-Associated Fibroblasts.

Cancer Discov. 2022-2

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deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors.

Front Genet. 2021-8-10

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Pancreatic Tumor Microenvironment Factor Promotes Cancer Stemness via SPP1-CD44 Axis.

Gastroenterology. 2021-12

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rPanglaoDB: an R package to download and merge labeled single-cell RNA-seq data from the PanglaoDB database.

Bioinformatics. 2022-1-3

[8]
CODEX multiplexed tissue imaging with DNA-conjugated antibodies.

Nat Protoc. 2021-8

[9]
The Three Rs of Single-Cell RNA Sequencing: Reuse, Refine, and Resource.

J Invest Dermatol. 2021-7

[10]
Detection of differentially abundant cell subpopulations in scRNA-seq data.

Proc Natl Acad Sci U S A. 2021-6-1

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