Abstract 166: Spatial subtypes and cellular interactions of cancer-associated fibroblasts revealed by single-cell spatial omics

Abstract Background: Cancer-associated fibroblasts (CAFs) are a highly diverse cell population that plays a crucial role in shaping the tumor microenvironment (TME). Their spatial interactions within the TME remain to be systematically characterized, and the factors driving their phenotypic heterogeneity are not yet fully understood. Recent advancements in single-cell spatial transcriptomics technologies and cell segmentation approaches enable the precise measurement of thousands of transcripts at subcellular resolution. Combined with innovative bioinformatics, these advancements have unlocked unprecedented opportunities for in-depth characterization of CAFs and their interactions within the TME. Methods: We conducted a comprehensive spatial transcriptomic analysis of CAFs across 8 cancer types, using the CosMx and MERSCOPE platforms to profile nearly 6 million cells as part of our discovery cohorts. We developed a novel computational method to spatially cluster CAF subpopulations and defined four distinct spatial CAF subtypes. We further examined their phenotypic differences, spatial niche organization, and interactions with neighboring cells. Additionally, we investigated the influence of CAF subtypes on immune cell phenotypes and infiltration levels. To validate our findings, we employed multiple spatial platforms, including Visium, Xenium, COMET, CODEX, and IMC, to ensure reproducibility across diverse technologies. Moreover, we performed correlative studies in large-cohorts with rich clinical data to evaluate the clinical significance of these CAF subtypes. Results: Our approach provided an unprecedented high-resolution examination of the spatial phenotypes of CAFs in large, complex tissues, uncovering novel insights. We comprehensively characterized CAFs across various solid tumor types and identified four conserved spatial CAF subtypes. These subtypes are characterized by distinct cell organizational patterns, neighboring cell compositions, interaction networks, and transcriptomic features. Moreover, they demonstrate significant correlations with the abundance, distribution, and phenotypes of tumor-infiltrating immune cells, as well as associations with tumor histopathological features and clinical outcomes. Conclusions: Our study provides a pan-cancer, high-resolution characterization of CAF spatial organization and interactions in solid tumors and identified conserved spatial CAF subtypes linked to distinct organizational patterns. Our findings reveal that the transcriptomic states and phenotypes of CAFs are significantly shaped by their interactions with neighboring cancer and immune cells. Beyond offering novel insights into the spatial heterogeneity of CAFs, this work paves the way for developing strategies to effectively target and modulate CAFs for therapeutic benefit. Citation Format: Yunhe Liu, Ansam Sinjab, Jimin Min, Guangchun Han, Francesca Paradiso, Yuanyuan Zhang, Yang Liu, Ruiping Wang, Guangsheng Pei, Kyung Serk Cho, Enyu Dai, Akshay Basi, Jared K. Burks, Kimal I. Rajapakshe, Yanshuo Chu, Jiahui Jiang, Daiwei Zhang, Xinmiao Yan, Paola A. Guerrero, Alejandra Serrano, Mingyao Li, Tae Hyun Hwang, Andrew Futreal, Jaffer A. Ajani, Luisa M Solis Soto, Amir A. Jazaeri, Humam Kadara, Anirban Maitra, Linghua Wang. Spatial subtypes and cellular interactions of cancer-associated fibroblasts revealed by single-cell spatial omics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 166.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-166
Primary Topic
Single-cell and spatial transcriptomics
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article
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article

Abstract 166: Spatial subtypes and cellular interactions of cancer-associated fibroblasts revealed by single-cell spatial omics

Amir A. Jazaeri, Enyu Dai, Jared K. Burks, Kyung Serk Cho et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 166: Spatial subtypes and cellular interactions of cancer-associated fibroblasts revealed by single-cell spatial omics

Amir A. Jazaeri, Enyu Dai, Jared K. Burks, Kyung Serk Cho, Francesca Paradiso, Ansam Sinjab, Kimal Rajapakshe, Guangchun Han, Alejandra G. Serrano, Jaffer A. Ajani, Anirban Maitra, Humam Kadara, Linghua Wang, Guangsheng Pei, Paola A. Guerrero, P. Andrew Futreal, Daiwei Zhang, Jimin Min, Xinmiao Yan, Luisa M. Solis Soto, Yanshuo Chu, Akshay Basi, Yang Liu, Ruiping Wang, Yunhe Liu, Mingyao Li, Jiahui Jiang, Yuanyuan Zhang, Tae Hyun Hwang
article en

Abstract

Abstract Background: Cancer-associated fibroblasts (CAFs) are a highly diverse cell population that plays a crucial role in shaping the tumor microenvironment (TME). Their spatial interactions within the TME remain to be systematically characterized, and the factors driving their phenotypic heterogeneity are not yet fully understood. Recent advancements in single-cell spatial transcriptomics technologies and cell segmentation approaches enable the precise measurement of thousands of transcripts at subcellular resolution. Combined with innovative bioinformatics, these advancements have unlocked unprecedented opportunities for in-depth characterization of CAFs and their interactions within the TME. Methods: We conducted a comprehensive spatial transcriptomic analysis of CAFs across 8 cancer types, using the CosMx and MERSCOPE platforms to profile nearly 6 million cells as part of our discovery cohorts. We developed a novel computational method to spatially cluster CAF subpopulations and defined four distinct spatial CAF subtypes. We further examined their phenotypic differences, spatial niche organization, and interactions with neighboring cells. Additionally, we investigated the influence of CAF subtypes on immune cell phenotypes and infiltration levels. To validate our findings, we employed multiple spatial platforms, including Visium, Xenium, COMET, CODEX, and IMC, to ensure reproducibility across diverse technologies. Moreover, we performed correlative studies in large-cohorts with rich clinical data to evaluate the clinical significance of these CAF subtypes. Results: Our approach provided an unprecedented high-resolution examination of the spatial phenotypes of CAFs in large, complex tissues, uncovering novel insights. We comprehensively characterized CAFs across various solid tumor types and identified four conserved spatial CAF subtypes. These subtypes are characterized by distinct cell organizational patterns, neighboring cell compositions, interaction networks, and transcriptomic features. Moreover, they demonstrate significant correlations with the abundance, distribution, and phenotypes of tumor-infiltrating immune cells, as well as associations with tumor histopathological features and clinical outcomes. Conclusions: Our study provides a pan-cancer, high-resolution characterization of CAF spatial organization and interactions in solid tumors and identified conserved spatial CAF subtypes linked to distinct organizational patterns. Our findings reveal that the transcriptomic states and phenotypes of CAFs are significantly shaped by their interactions with neighboring cancer and immune cells. Beyond offering novel insights into the spatial heterogeneity of CAFs, this work paves the way for developing strategies to effectively target and modulate CAFs for therapeutic benefit. Citation Format: Yunhe Liu, Ansam Sinjab, Jimin Min, Guangchun Han, Francesca Paradiso, Yuanyuan Zhang, Yang Liu, Ruiping Wang, Guangsheng Pei, Kyung Serk Cho, Enyu Dai, Akshay Basi, Jared K. Burks, Kimal I. Rajapakshe, Yanshuo Chu, Jiahui Jiang, Daiwei Zhang, Xinmiao Yan, Paola A. Guerrero, Alejandra Serrano, Mingyao Li, Tae Hyun Hwang, Andrew Futreal, Jaffer A. Ajani, Luisa M Solis Soto, Amir A. Jazaeri, Humam Kadara, Anirban Maitra, Linghua Wang. Spatial subtypes and cellular interactions of cancer-associated fibroblasts revealed by single-cell spatial omics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 166.

Cancer ResearchVol. 85(8_Supplement_1)
Mayo Clinic (US), The University of Texas MD Anderson Cancer Center (US), University of Pennsylvania (US)
Openalex Percentile: Top 92%
Single-cell and spatial transcriptomics
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