Abstract
Chemoresistance remains a critical challenge in breast cancer (BC) treatment. By integrating multi-omics (single-cell, spatial, and bulk transcriptomics) with clinical validation, we identified a specific COL3Ahigh CAF subset that drives BC chemoresistance. Mechanistically, these CAFs undergo lipid metabolic reprogramming, secreting excess oleic acid via SCD. This oleic acid binds to ENO1 on tumor cells, activating the PI3K/Akt pathway and inhibiting chemotherapy-induced apoptosis. Simultaneously, COL3Ahigh CAFs orchestrate an immunosuppressive niche by recruiting regulatory T cells and impairing cytotoxic CD8+ T cells. Our findings establish COL3Ahigh CAFs as key mediators of resistance through metabolic symbiosis and immune evasion. The strong correlation between COL3Ahigh CAF abundance and clinical poor response highlights their potential as both predictive biomarkers and therapeutic targets to overcome chemoresistance in BC patients.
Data availability
The sequencing data utilized in this study are publicly available from the databases referenced in the manuscript. Other data supporting the findings are available from the corresponding author upon reasonable request.
Code availability
Relevant code is accessible through the corresponding author(s) upon reasonable request.
References
Santucci, C. et al. European cancer mortality predictions for the year 2025 with focus on breast cancer. Ann. Oncol. 36, 460–468 (2025).
Waks, A. G. & Winer, E. P. Breast cancer treatment: a review. Jama 321, 288–300 (2019).
Harbeck, N. et al. Breast cancer. Nat. Rev. Dis. Prim. 5, 66 (2019).
Gascard, P. & Tlsty, T. D. Carcinoma-associated fibroblasts: orchestrating the composition of malignancy. Genes Dev. 30, 1002–1019 (2016).
Liao, Z., Tan, Z. W., Zhu, P. & Tan, N. S. Cancer-associated fibroblasts in tumor microenvironment—accomplices in tumor malignancy. Cell Immunol. 343, 103729 (2019).
Chen, C. et al. Crosstalk between cancer-associated fibroblasts and regulated cell death in tumors: insights into apoptosis, autophagy, ferroptosis, and pyroptosis. Cell Death Discov. 10, 189 (2024).
Öhlund, D. et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J. Exp. Med. 214, 579–596 (2017).
Butti, R., Khaladkar, A., Bhardwaj, P. & Prakasam, G. Heterotypic signaling of cancer-associated fibroblasts in shaping the cancer cell drug resistance. Cancer Drug Resist. 6, 182–204 (2023).
Chen, X., Chen, S. & Yu, D. Metabolic reprogramming of chemoresistant cancer cells and the potential significance of metabolic regulation in the reversal of cancer chemoresistance. Metabolites 10, 289 (2020).
Linares, J., Marín-Jiménez, J. A., Badia-Ramentol, J. & Calon, A. Determinants and functions of CAFs secretome during cancer progression and therapy. Front. Cell Dev. Biol. 8, 621070 (2020).
Maeda, A. et al. The interaction between cancer-associated fibroblasts and cancer cells enhances Bcl-xL and Mcl-1 in colorectal cancer. Anticancer Res. 42, 1277–1288 (2022).
Bian, L., Sun, X., Jin, K. & He, Y. Oral cancer-associated fibroblasts inhibit heat-induced apoptosis in Tca8113 cells through upregulated expression of Bcl-2 through the Mig/CXCR3 axis. Oncol. Rep. 28, 2063–2068 (2012).
Li, Y. et al. Cancer-Associated Fibroblasts Hinder Lung Squamous Cell Carcinoma Oxidative Stress-Induced Apoptosis via METTL3 Mediated m(6)A Methylation of COL10A1. Oxid. Med. Cell. Longev. 2022, 4320809 (2022).
Zhang, Q., An, Z. Y., Jiang, W., Jin, W. L. & He, X. Y. Collagen code in tumor microenvironment: functions, molecular mechanisms, and therapeutic implications. Biomed. Pharmacother. 166, 115390 (2023).
Xu, K. et al. Distinct fibroblast subpopulations associated with bone, brain or intrapulmonary metastasis in advanced non-small-cell lung cancer. Clin. Transl. Med. 14, e1605 (2024).
LaRue, M. M. et al. Metabolic reprogramming of tumor-associated macrophages by collagen turnover promotes fibrosis in pancreatic cancer. Proc. Natl. Acad. Sci. USA 119, e2119168119 (2022).
Chen, Y. et al. Oncogenic collagen I homotrimers from cancer cells bind to α3β1 integrin and impact tumor microbiome and immunity to promote pancreatic cancer. Cancer Cell 40, 818–834.e9 (2022).
Li, G. et al. Collagen-targeted tumor-specific transepithelial penetration enhancer mediated intravesical chemoimmunotherapy for non-muscle-invasive bladder cancer. Biomaterials 283, 121422 (2022).
Zhang, J. Y. et al. Cancer-associated fibroblasts promote oral squamous cell carcinoma progression through LOX-mediated matrix stiffness. J. Transl. Med. 19, 513 (2021).
Zhou, Y., Jiang, Z., Cao, L. & Yang, J. The role of various collagen types in tumor biology: a review. Front. Oncol. 15, 1549797 (2025).
Zhang, H. et al. Data mining-based study of collagen type III alpha 1 (COL3A1) prognostic value and immune exploration in pan-cancer. Bioengineered 12, 3634–3646 (2021).
Stewart, D. C. et al. Prognostic and therapeutic implications of tumor-restrictive type III collagen in the breast cancer microenvironment. NPJ Breast Cancer 10, 86 (2024).
Ren, J., Zhao, S. & Lai, J. Role and mechanism of COL3A1 in regulating the growth, metastasis, and drug sensitivity in cisplatin-resistant non-small cell lung cancer cells. Cancer Biol. Ther. 25, 2328382 (2024).
Sun, Y. et al. Integrative plasma and fecal metabolomics identify functional metabolites in adenoma-colorectal cancer progression and as early diagnostic biomarkers. Cancer Cell 42, 1386–400.e8 (2024).
Chen, Y., McAndrews, K. M. & Kalluri, R. Clinical and therapeutic relevance of cancer-associated fibroblasts. Nat. Rev. Clin. Oncol. 18, 792–804 (2021).
Biffi, G. & Tuveson, D. A. Diversity and biology of cancer-associated fibroblasts. Physiol. Rev. 101, 147–176 (2021).
Costa, A. et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell 33, 463–79.e10 (2018).
Yan, Y. et al. Multi-omic profiling highlights factors associated with resistance to immuno-chemotherapy in non-small-cell lung cancer. Nat. Genet 57, 126–139 (2025).
Xiao, L. et al. Tumor endothelial cells with distinct patterns of TGFβ-driven endothelial-to-mesenchymal transition. Cancer Res. 75, 1244–1254 (2015).
Mousset, A. et al. Neutrophil extracellular traps formed during chemotherapy confer treatment resistance via TGF-β activation. Cancer Cell 41, 757–75.e10 (2023).
Singh, A. & Settleman, J. EMT, cancer stem cells and drug resistance: an emerging axis of evil in the war on cancer. Oncogene 29, 4741–4751 (2010).
Saikia, S. et al. Reprogramming of lipid metabolism in cancer: new insight into pathogenesis and therapeutic strategies. Curr. Pharm. Biotechnol. 24, 1847–1858 (2023).
Liu, S. et al. Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer. Mol. Cancer 23, 261 (2024).
Yang, D. et al. Utilization of adipocyte-derived lipids and enhanced intracellular trafficking of fatty acids contribute to breast cancer progression. Cell Commun. Signal. 16, 32 (2018).
Yu, L. et al. Tumor-derived arachidonic acid reprograms neutrophils to promote immune suppression and therapy resistance in triple-negative breast cancer. Immunity 58, 909–925.e7 (2025).
Roongta, U. V. et al. Cancer cell dependence on unsaturated fatty acids implicates stearoyl-CoA desaturase as a target for cancer therapy. Mol. Cancer Res. 9, 1551–1561 (2011).
Griffiths, B. et al. Sterol regulatory element binding protein-dependent regulation of lipid synthesis supports cell survival and tumor growth. Cancer Metab. 1, 3 (2013).
Williams, K. J. et al. An essential requirement for the SCAP/SREBP signaling axis to protect cancer cells from lipotoxicity. Cancer Res. 73, 2850–2862 (2013).
Lai, J. I., Chao, T. C., Liu, C. Y., Huang, C. C. & Tseng, L. M. A systemic review of taxanes and their side effects in metastatic breast cancer. Front. Oncol. 12, 940239 (2022).
Gradishar, W. J. et al. Breast cancer, version 3.2024, NCCN clinical practice guidelines in oncology. J. Natl. Compr. Cancer Netw. 22, 331–357 (2024).
Huang, T. et al. Current perspectives and trends of CD39-CD73-eAdo/A2aR research in tumor microenvironment: a bibliometric analysis. Front. Immunol. 15, 1427380 (2024).
Luo, L. et al. Single-cell RNA sequencing identifies molecular biomarkers predicting late progression to CDK4/6 inhibition in patients with HR+/HER2- metastatic breast cancer. Mol. Cancer 24, 48 (2025).
Liu, Z. et al. THBS2-producing matrix CAFs promote colorectal cancer progression and link to poor prognosis via the CD47-MAPK axis. Cell Rep. 44, 115555 (2025).
Zhang, L. et al. Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature 564, 268–272 (2018).
Jin, S. et al. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 12, 1088 (2021).
Tran, K. A. et al. Performance of tumour microenvironment deconvolution methods in breast cancer using single-cell simulated bulk mixtures. Nat. Commun. 14, 5758 (2023).
Sun, D. et al. Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data. Nat. Biotechnol. 40, 527–538 (2022).
Chu, T., Wang, Z., Pe’er, D. & Danko, C. G. Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology. Nat. Cancer 3, 505–517 (2022).
Fustero-Torre, C. et al. Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq data. Genome Med. 13, 187 (2021).
Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).
Ru, B., Huang, J., Zhang, Y., Aldape, K. & Jiang, P. Estimation of cell lineages in tumors from spatial transcriptomics data. Nat. Commun. 14, 568 (2023).
Acknowledgements
We would like to express our gratitude to all the patients who participated in this study. This work was supported by National Natural Science Foundation of China (82403430), the Technology Program Joint Fund of Liaoning Province (2023-BSBA-207), Oncology Project of Liaoning Cancer Hospital (2024-ZLKF-09), Tianjin Key Medical Discipline Construction Project (TJYXZDXK-3-003A) and Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0502200).
Author information
Authors and Affiliations
Contributions
P.J.: Conceptualization, methodology, formal analysis, investigation, data curation, visualization, writing—original draft. X.L.: Investigation, methodology, visualization, writing—original draft, funding acquisition. Z.W.: Investigation, methodology; S.L.: Investigation, writing—editing; Y.H.: Clinical samples collection; Y.L.: Funding acquisition, project administration, resources, supervision; Y.C.: Conceptualization, supervision, validation, writing—review. X.S.: Conceptualization, funding acquisition, project administration, supervision, methodology, investigation, writing—review & editing.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Jiang, P., Li, X., Wang, Z. et al. COL3A1high cancer-associated fibroblasts orchestrate metabolic and immune microenvironments to confer chemoresistance in breast cancer. npj Precis. Onc. (2026). https://doi.org/10.1038/s41698-026-01338-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41698-026-01338-9