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Cited by 826Single-cell and spatial transcriptomicsCancer Cells and MetastasisPancreatic and Hepatic Oncology Research

Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing

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Bartoschek, Michael, Oskolkov, Nikolay, Bocci, Matteo, Lövrot, John, Larsson, Christer, Sommarin, Mikael, Madsen, Chris D., Lindgren, David +6 more·2018·Nature Communications
DOI 10.1038/s41467-018-07582-3PMC PMC6279758
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Abstract

Cancer-associated fibroblasts (CAFs) are a major constituent of the tumor microenvironment, although their origin and roles in shaping disease initiation, progression and treatment response remain unclear due to significant heterogeneity. Here, following a negative selection strategy combined with single-cell RNA sequencing of 768 transcriptomes of mesenchymal cells from a genetically engineered mouse model of breast cancer, we define three distinct subpopulations of CAFs. Validation at the transcriptional and protein level in several experimental models of cancer and human tumors reveal spatial separation of the CAF subclasses attributable to different origins, including the peri-vascular niche, the mammary fat pad and the transformed epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs and hold independent prognostic capability in clinical cohorts by association to metastatic disease. In conclusion, the improved resolution of the widely defined CAF population opens the possibility for biomarker-driven development of drugs for precision targeting of CAFs.

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  • There is a recurrent observation of distinct CAFs exhibiting either a matrix-producing contractile phenotype or an immunomodulating secretome, often termed myoCAFs and iCAFs.

    “Nonetheless, there is a recurrent observation of distinct CAFs exhibiting either a matrix-producing contractile phenotype or an immunomodulating secretome — often termed ‘myoCAFs’ and ‘iCAFs’, with the prefixes alluding to a myofibroblast phenotype and regulation of inflammation, respectively.”

    From A framework for advancing our understanding of cancer-associated fibroblasts (2020) · cites this paper as [48]

    The Results section on mCAFs (page unavailable) identifies a CAF subset with strong matrix-production gene expression, supporting that part of the claim. But the Discussion (page unavailable) says immunomodulatory function was not a distinguishing feature of any subset identified in this study. The paper classifies its subsets as mCAFs, vCAFs and dCAFs; it does not establish the claimed myoCAF/iCAF pairing or a contractile phenotype. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Evidence for pericyte conversion into CAFs is relatively sparse, with tumorigenesis studies targeting pericytes specifically not revealing large-scale differences in the tumour microenvironment.

    “Evidence for pericyte conversion into CAFs is relatively sparse48, with tumorigenesis studies that targeted pericytes specifically not revealing large-scale differences in the tumour microenvironment.”

    From A framework for advancing our understanding of cancer-associated fibroblasts (2020) · cites this paper as [48]

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Research works printed but not linked: 38

  1. [1]Kalluri R The biology and function of fibroblasts in cancer Nat. Rev. Cancer 2016 16 582 598 10.1038/nrc.2016.73 27550820 · DOI · Paper page
  2. [2]Pietras K Östman A Hallmarks of cancer: interactions with the tumor stroma Exp. Cell Res. 2010 316 1324 1331 10.1016/j.yexcr.2010.02.045 20211171 · DOI
  3. [4]Cortez E Roswall P Pietras K Functional subsets of mesenchymal cell types in the tumor microenvironment Semin. Cancer Biol. 2014 25 3 9 10.1016/j.semcancer.2013.12.010 24412106 · DOI
  4. [6]Brechbuhl HM Fibroblast subtypes regulate responsiveness of luminal breast cancer to estrogen Clin. Cancer Res. 2017 23 1710 1721 10.1158/1078-0432.CCR-15-2851 27702820 PMC5378660 · DOI
  5. [7]Cazet AS Targeting stromal remodeling and cancer stem cell plasticity overcomes chemoresistance in triple negative breast cancer Nat. Commun. 2018 9 2897 10.1038/s41467-018-05220-6 30042390 PMC6057940 · DOI · Paper page
  6. [9]Li H Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors Nat. Genet. 2017 49 708 718 10.1038/ng.3818 28319088 · DOI · Paper page
  7. [10]Su S CD10(+)GPR77(+) cancer-associated fibroblasts promote cancer formation and chemoresistance by sustaining cancer stemness Cell 2018 172 841 856 10.1016/j.cell.2018.01.009 29395328 · DOI · Paper page
  8. [11]Zeisberg EM Potenta S Xie L Zeisberg M Kalluri R Discovery of endothelial to mesenchymal transition as a source for carcinoma-associated fibroblasts Cancer Res. 2007 67 10123 10128 10.1158/0008-5472.CAN-07-3127 17974953 · DOI · Paper page
  9. [12]Anderberg C Pietras K On the origin of cancer-associated fibroblasts Cell Cycle 2009 8 1461 1462 10.4161/cc.8.10.8557 19395855 · DOI
  10. [13]Tirosh I Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq Science 2016 352 189 196 10.1126/science.aad0501 27124452 PMC4944528 · DOI · Paper page
  11. [14]Guy CT Expression of the neu protooncogene in the mammary epithelium of transgenic mice induces metastatic disease Proc. Natl. Acad. Sci. U.S.A. 1992 89 10578 10582 10.1073/pnas.89.22.10578 1359541 PMC50384 · DOI
  12. [15]Lin EY Progression to malignancy in the polyoma middle T oncoprotein mouse breast cancer model provides a reliable model for human diseases Am. J. Pathol. 2003 163 2113 2126 10.1016/S0002-9440(10)63568-7 14578209 PMC1892434 · DOI
  13. [17]Kiselev VY SC3: consensus clustering of single-cell RNA-seq data Nat. Methods 2017 14 483 486 10.1038/nmeth.4236 28346451 PMC5410170 · DOI · Paper page
  14. [18]Naba A The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices Mol. Cell. Proteomics 2012 11 M111.014647 10.1074/mcp.M111.014647 22159717 PMC3322572 · DOI · Paper page
  15. [20]Kharchenko PV Silberstein L Scadden DT Bayesian approach to single-cell differential expression analysis Nat. Methods 2014 11 740 742 10.1038/nmeth.2967 24836921 PMC4112276 · DOI · Paper page
  16. [21]Robinson MD McCarthy DJ Smyth GK edgeR: a bioconductor package for differential expression analysis of digital gene expression data Bioinformatics 2009 26 139 140 10.1093/bioinformatics/btp616 19910308 PMC2796818 · DOI · Paper page
  17. [23]Mann HB Whitney DR On a test of whether one of two random variables is stochastically larger than the other Ann. Math. Stat. 1947 18 50 60 10.1214/aoms/1177730491 · DOI · Paper page
  18. [24]Scialdone A Computational assignment of cell-cycle stage from single-cell transcriptome data Methods 2015 85 54 61 10.1016/j.ymeth.2015.06.021 26142758 · DOI
  19. [25]Uhlen M Proteomics. Tissue-based map of the human proteome Science 2015 347 1260419 10.1126/science.1260419 25613900 · DOI · Paper page
  20. [26]Koboldt DC Comprehensive molecular portraits of human breast tumours Nature 2012 490 61 70 10.1038/nature11412 23000897 PMC3465532 · DOI · Paper page
  21. [27]Winslow S Lindquist KE Edsjö A Larsson C The expression pattern of matrix-producing tumor stroma is of prognostic importance in breast cancer BMC Cancer 2016 16 841 10.1186/s12885-016-2864-2 27809802 PMC5095990 · DOI
  22. [28]Lindstrom LS Abstract P6-06-17: gene signature model predicts metastatic onset better than standard clinical markers—nested case-control design uniquely enables enrichment for biologically relevant features Cancer Res. 2014 73 P6-06-17 10.1158/0008-5472.SABCS13-P6-06-17 · DOI
  23. [29]Tobin NP An endothelial gene signature score predicts poor outcome in patients with endocrine-treated, low genomic grade breast tumors Clin. Cancer Res. 2016 22 2417 2426 10.1158/1078-0432.CCR-15-1691 26769751 · DOI
  24. [30]Desmedt C Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes Clin. Cancer Res. 2008 14 5158 5165 10.1158/1078-0432.CCR-07-4756 18698033 · DOI
  25. [31]Farmer P A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer Nat. Med. 2009 15 68 74 10.1038/nm.1908 19122658 · DOI
  26. [32]Nielsen TO A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer Clin. Cancer Res. 2010 16 5222 5232 10.1158/1078-0432.CCR-10-1282 20837693 PMC2970720 · DOI
  27. [34]Viré E The breast cancer oncogene EMSY represses transcription of antimetastatic microRNA miR-31 Mol. Cell 2014 53 806 818 10.1016/j.molcel.2014.01.029 24582497 PMC3988886 · DOI
  28. [35]Pereira B The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes Nat. Commun. 2016 7 11479 10.1038/ncomms11479 27161491 PMC4866047 · DOI
  29. [36]Christian S Endosialin (Tem1) is a marker of tumor-associated myofibroblasts and tumor vessel-associated mural cells Am. J. Pathol. 2008 172 486 494 10.2353/ajpath.2008.070623 18187565 PMC2312374 · DOI
  30. [37]LeBleu VS Origin and function of myofibroblasts in kidney fibrosis Nat. Med. 2013 19 1047 1053 10.1038/nm.3218 23817022 PMC4067127 · DOI
  31. [38]Hyun KA Epithelial-to-mesenchymal transition leads to loss of EpCAM and different physical properties in circulating tumor cells from metastatic breast cancer Oncotarget 2016 7 24677 24687 10.18632/oncotarget.8250 27013581 PMC5029733 · DOI
  32. [39]Özdemir BC Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival Cancer Cell 2014 25 719 734 10.1016/j.ccr.2014.04.005 24856586 PMC4180632 · DOI · Paper page
  33. [40]Rhim AD Stromal elements act to restrain, rather than support, pancreatic ductal adenocarcinoma Cancer Cell 2014 25 735 747 10.1016/j.ccr.2014.04.021 24856585 PMC4096698 · DOI · Paper page
  34. [41]Roswall P Microenvironmental control of breast cancer subtype elicited through paracrine platelet-derived growth factor-CC signaling Nat. Med. 2018 24 463 473 10.1038/nm.4494 29529015 PMC5896729 · DOI
  35. [42]Hamilton TG Klinghoffer RA Corrin PD Soriano P Evolutionary divergence of platelet-derived growth factor alpha receptor signaling mechanisms Mol. Cell. Biol. 2003 23 4013 4025 10.1128/MCB.23.11.4013-4025.2003 12748302 PMC155222 · DOI
  36. [46]Lun ATL McCarthy DJ Marioni JC A step-by-step workflow for low-level analysis of single-cell RNA-seq data with bioconductor F1000Research 2016 5 2122 27909575 PMC5112579
  37. [48]Saal LH The Sweden Cancerome Analysis Network—Breast (SCAN-B) Initiative: a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine Genome Med. 2015 7 20 10.1186/s13073-015-0131-9 25722745 PMC4341872 · DOI · Paper page
  38. [49]Cunha SI Endothelial ALK1 is a therapeutic target to block metastatic dissemination of breast cancer Cancer Res. 2015 75 2445 2456 10.1158/0008-5472.CAN-14-3706 26077471 · DOI

Cited by

Sorted by citations

Authors
Bartoschek, M., Oskolkov, N., Bocci, M., Lövrot, J., Larsson, C., Sommarin, M., Madsen, C. D., Lindgren, D., Pekar, G., Karlsson, G., Ringnér, M., Bergh, J., Björklund, Å., & Pietras, K.
Affiliations
  • Lund University (SE)
  • Karolinska University Hospital (SE)
  • Uppsala University (SE)
Corresponding author
Pietras, Kristian
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-12-04
Volume
9
Issue
1
Pages
5150-5150
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-07582-3
PMC
PMC6279758
OpenAlex
W2902447942
Cited by
826
References
10
Citations by year
2026: 81 · 2025: 124 · 2024: 124 · 2023: 134 · 2022: 115 · 2021: 127 · 2020: 94 · 2019: 27
FWCI
22.06
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Lund University Publications (Lund University) (submittedVersion)
Funders
  • Biltema Foundation
  • Cancerfonden
  • Lunds Universitet
  • Vetenskapsrådet
  • Fru Berta Kamprads Stiftelse
  • Science for Life Laboratory
  • Region Skåne
  • FP7 Ideas: European Research Council (309322)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
  • Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
Keywords
cancer-associated fibroblasts, breast cancer, tumor microenvironment, CAF heterogeneity, CAF subpopulations, CAF origin, mammary fat pad, metastasis, prognostic factors, single-cell RNA sequencing, genetically engineered mouse models, mesenchymal cells
MeSH terms
Cancer-Associated Fibroblasts, Adipose Tissue, Animals, Breast, Breast Neoplasms, Cell Cycle, Epithelium, Female, Fibroblasts, Humans, Intercellular Junctions, Mice, Transgenic, Prognosis, Transcription Factors, Biomarkers, Tumor, Gene Expression Regulation, Neoplastic, Cluster Analysis, Logistic Models, Sequence Analysis, RNA, Disease Progression, Gene Expression Profiling, Cell Line, Tumor, Mice, Transcriptome

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