DeCAF defines clinical fibroblast subtypes and multidimensional tumor-stroma crosstalk shaping prognosis and immunotherapy response
Single-cell RNA sequencing (scRNA-seq) studies have uncovered distinct cancer-associated fibroblast (CAF) populations. While useful as a biological framework, no studies have conclusively defined CAF subtypes with clinical significance. We define restraining (rest) and promoting (pro) CAFs in patient samples that are both prognostic and predictive of therapy response in multiple tumor types. We uncover distinct clinical and spatial interactions between pro- and restCAF subtypes and basal-like and classical tumor subtypes that support tumor-stroma crosstalk. Finally, we find striking differences in the immune contexture of pro- and restCAF tumors where restCAF-dominant tumors are more responsive to immune checkpoint inhibition and proCAF-dominant tumors are more responsive to myeloid inhibition in clinical trials. This work defines CAF subtypes that are clinically robust, prognostic, and predictive of immunotherapy response and provides a single-sample classifier, determination of pro- and restCAF subtypes (DeCAF), which is clinically actionable.
Authors
- Nancy P. Kren
- Brian Belt
- Alina C. Iuga (ORCID: https://orcid.org/0000-0002-2351-8289)
- Arthi Hariharan
- Roheena Z. Panni (ORCID: https://orcid.org/0000-0002-8144-6869)
- Changfei Luan
- Silvia G. Herera Loeza
- David C. Linehan
- Justin Su
- Xianlu Laura Peng
- Ian C. McCabe
- Priscilla S. Chan
- Yi Xu
- William Y. Kim
- Elena V. Kharitonova
- Jaewon J. Lee
- Ryan T. Zhao
- Yuliya Pylayeva-Gupta
- Hong Jin Kim
- Jeffrey S. Damrauer
- Ashley Cliff
- Susan Tsai
- Michelle E. LaBella
- Naim U. Rashid
- Ashley B. Morrison
- Jen Jen Yeh
Institutions
- University of North Carolina at Chapel Hill (US)
- Washington University in St. Louis (US)
- The Ohio State University (US)
- University of Rochester (US)
Publication Details
- Journal
- Cell Reports Medicine
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1016/j.xcrm.2026.102611
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00