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Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells

Oncogene volume 43, pages 2927–2937 (2024)Cite this article

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Abstract

Metastasis is responsible for the majority of cancer-related fatalities. We previously identified specific cancer cell populations responsible for metastatic events which are cytokeratin-14 (CK14) and E-cadherin positive in luminal tumors, and E-cadherin and vimentin positive in triple-negative tumors. Since cancer cells evolve within a complex ecosystem comprised of immune cells and stromal cells, we sought to decipher the spatial interactions of these aggressive cancer cell populations within the tumor microenvironment (TME). We used imaging mass cytometry to detect 36 proteins in tumor microarrays containing paired primary and metastatic lesions from luminal or triple-negative breast cancers (TNBC), resulting in a dataset of 1,477,337 annotated cells. Focusing on metastasis-initiating cell populations, we observed close proximity to specific fibroblast and macrophage subtypes, a relationship maintained between primary and metastatic tumors. Notably, high CK14 in luminal cancer cells and high vimentin in TNBC cells correlated with close proximity to specific macrophage subtypes (CD163intCD206intPDL1intHLA-DR+ or PDL1highARG1high). Our in-depth spatial analysis demonstrates that metastasis-initiating cancer cells consistently colocalizes with distinct cell populations within the TME, suggesting a role for these cell-cell interactions in promoting metastasis.

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Fig. 1: Imaging mass cytometry (IMC) for luminal breast cancers (Lum BC) and triple-negative breast cancers (TNBC).
Fig. 2: Single-cell profiling with IMC reveals LUM and TNBC sub-clusters based on CK8 and CK14 expression and tumor microenvironment (TME) compositions.
Fig. 3: Profiles of stromal and macrophage phenotypes within the TME.
Fig. 4: Spatial relationships of CK+ and TME cell types.
Fig. 5: CK+ cells in close proximity with specific macrophage clusters express higher levels of markers associated with metastasis-initiating cancer cells.

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Data availability

IMC data are available at the following https://doi.org/10.5281/zenodo.10688895.

Code availability

Analysis scripts are available at the following repository: github.com/wjhlab/BreastMetIMC.

References

  1. Thennavan A, Beca F, Xia Y, Garcia-Recio S, Allison K, Collins LC, et al. Molecular analysis of TCGA breast cancer histologic types. Cell Genomics. 2021;1:100067.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Wu SZ, Al-Eryani G, Roden DL, Junankar S, Harvey K, Andersson A, et al. A single-cell and spatially resolved atlas of human breast cancers. Nat Genet. 2021;53:1334–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Chung W, Eum HH, Lee HO, Lee KM, Lee HB, Kim KT, et al. Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat Commun. 2017;8:15081.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Lehmann BD, Colaprico A, Silva TC, Chen J, An H, Ban Y, et al. Multi-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes. Nat Commun. 2021;12:6276.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA A Cancer J Clin. 2022;72:7–33.

    Article  Google Scholar 

  6. Massagué J, Ganesh K. Metastasis-initiating cells and ecosystems. Cancer Discov. 2021;11:971–94.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Cheung KJ, Gabrielson E, Werb Z, Ewald AJ. Collective invasion in breast cancer requires a conserved basal epithelial program. Cell. 2013;155:1639–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Padmanaban V, Krol I, Suhail Y, Szczerba BM, Aceto N, Bader JS, et al. E-cadherin is required for metastasis in multiple models of breast cancer. Nature. 2019;573:1–6.

  9. Cheung KJ, Padmanaban V, Silvestri V, Schipper K, Cohen JD, Fairchild AN, et al. Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters. PNAS. 2016;113:E854–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Grasset EM, Dunworth M, Sharma G, Loth M, Tandurella J, Cimino-Mathews A, et al. Triple-negative breast cancer metastasis involves complex epithelial-mesenchymal transition dynamics and requires vimentin. Sci Transl Med. 2022;14:eabn7571.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Azizi E, Carr AJ, Plitas G, Cornish AE, Konopacki C, Prabhakaran S, et al. Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment. Cell. 2018;174:1293–1308.e36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Wu P, Gao W, Su M, Nice EC, Zhang W, Lin J, et al. Adaptive mechanisms of tumor therapy resistance driven by tumor microenvironment. Front Cell Dev Biol. 2021;9. https://www.frontiersin.org/articles/10.3389/fcell.2021.641469.

  13. de Visser KE, Joyce JA. The evolving tumor microenvironment: from cancer initiation to metastatic outgrowth. Cancer Cell. 2023;41:374–403.

    Article  PubMed  Google Scholar 

  14. Chan IS, Knútsdóttir H, Ramakrishnan G, Padmanaban V, Warrier M, Ramirez JC, et al. Cancer cells educate natural killer cells to a metastasis-promoting cell state. J Cell Biol. 2020;219:e202001134.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Danenberg E, Bardwell H, Zanotelli VRT, Provenzano E, Chin SF, Rueda OM, et al. Breast tumor microenvironment structures are associated with genomic features and clinical outcome. Nat Genet. 2022;54:660–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Jackson HW, Fischer JR, Zanotelli VRT, Ali HR, Mechera R, Soysal SD, et al. The single-cell pathology landscape of breast cancer. Nature. 2020;578:615–20.

    Article  CAS  PubMed  Google Scholar 

  17. Ali HR, Jackson HW, Zanotelli VRT, Danenberg E, Fischer JR, Bardwell H, et al. Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer. Nat Cancer. 2020;1:163–75.

    Article  CAS  PubMed  Google Scholar 

  18. Cimino-Mathews A, Hicks JL, Illei PB, Halushka MK, Fetting JH, De Marzo AM, et al. Androgen Receptor expression is usually maintained in initial surgically-resected breast cancer metastases, but often lost in end-stage metastases found at autopsy. Hum Pathol. 2012;43:1003–11.

    Article  CAS  PubMed  Google Scholar 

  19. Cimino-Mathews A, Ye X, Meeker A, Argani P, Emens LA. Metastatic triple-negative breast cancers at first relapse have fewer tumor-infiltrating lymphocytes than their matched primary breast tumors: a pilot study. Hum Pathol. 2013;44:2055–63.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, et al. FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A. 2015;87:636–45.

    Article  PubMed  Google Scholar 

  21. Gusterson BA, Ross DT, Heath VJ, Stein T. Basal cytokeratins and their relationship to the cellular origin and functional classification of breast cancer. Breast Cancer Res. 2005;7:143–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fischer KR, Durrans A, Lee S, Sheng J, Li F, Wong STC, et al. Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance. Nature. 2015;527:472–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Oldford SA, Robb JD, Watson PH, Drover S. HLA-DRB alleles are differentially expressed by tumor cells in breast carcinoma. Int J Cancer. 2004;112:399–406.

    Article  CAS  PubMed  Google Scholar 

  24. Wintzer HO, Benzing M, von Kleist S. Lacking prognostic significance of beta 2-microglobulin, MHC class I and class II antigen expression in breast carcinomas. Br J Cancer. 1990;62:289–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Concha A, Ruiz-Cabello F, Cabrera T, Nogales F, Collado A, Garrido F. Different patterns of HLA-DR antigen expression in normal epithelium, hyperplastic and neoplastic malignant lesions of the breast. Eur J Immunogenet. 1995;22:299–310.

    Article  CAS  PubMed  Google Scholar 

  26. Friedman G, Levi-Galibov O, David E, Bornstein C, Giladi A, Dadiani M, et al. Cancer-associated fibroblast compositions change with breast cancer progression linking the ratio of S100A4+ and PDPN+ CAFs to clinical outcome. Nat Cancer. 2020;1:692–708.

    Article  CAS  PubMed  Google Scholar 

  27. Öhlund D, Handly-Santana A, Biffi G, Elyada E, Almeida AS, Ponz-Sarvise M, et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med. 2017;214:579–96.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Costa A, Kieffer Y, Scholer-Dahirel A, Pelon F, Bourachot B, Cardon M, et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell. 2018;33:463–479.e10.

    Article  CAS  PubMed  Google Scholar 

  29. Wu SZ, Roden DL, Wang C, Holliday H, Harvey K, Cazet AS, et al. Stromal cell diversity associated with immune evasion in human triple‐negative breast cancer. EMBO J. 2020;39:e104063.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mantovani A, Allavena P, Marchesi F, Garlanda C. Macrophages as tools and targets in cancer therapy. Nat Rev Drug Discov. 2022;21:799–820.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wagner J, Rapsomaniki MA, Chevrier S, Anzeneder T, Langwieder C, Dykgers A, et al. A single-cell atlas of the tumor and immune ecosystem of human breast cancer. Cell. 2019;177:1330–45.e18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Denkert C, von Minckwitz G, Darb-Esfahani S, Lederer B, Heppner BI, Weber KE, et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018;19:40–50.

    Article  PubMed  Google Scholar 

  33. Stanton SE, Adams S, Disis ML. Variation in the incidence and magnitude of tumor-infiltrating lymphocytes in breast cancer subtypes: a systematic review. JAMA Oncol. 2016;2:1354–60.

    Article  PubMed  Google Scholar 

  34. Fischer JR, Jackson HW, de Souza N, Varga Z, Schraml P, Moch H, et al. Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers. Cell Rep. Med. 2023;4:100977.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Soliman NA, Yussif SM. Ki-67 as a prognostic marker according to breast cancer molecular subtype. Cancer Biol Med. 2016;13:496–504.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Linde N, Casanova-Acebes M, Sosa MS, Mortha A, Rahman A, Farias E, et al. Macrophages orchestrate breast cancer early dissemination and metastasis. Nat Commun. 2018;9:21.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Su S, Liu Q, Chen J, Chen J, Chen F, He C, et al. A positive feedback loop between mesenchymal-like cancer cells and macrophages is essential to breast cancer metastasis. Cancer Cell. 2014;25:605–20.

    Article  PubMed  Google Scholar 

  38. Yang M, Ma B, Shao H, Clark AM, Wells A. Macrophage phenotypic subtypes diametrically regulate epithelial-mesenchymal plasticity in breast cancer cells. BMC Cancer. 2016;16:419.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Park J, Wysocki RW, Amoozgar Z, Maiorino L, Fein MR, Jorns J, et al. Cancer cells induce metastasis-supporting neutrophil extracellular DNA traps. Sci Transl Med. 2016;8:361–138.

    Article  Google Scholar 

  40. Mousset A, Lecorgne E, Bourget I, Lopez P, Jenovai K, Cherfils-Vicini J, et al. Neutrophil extracellular traps formed during chemotherapy confer treatment resistance via TGF-β activation. Cancer Cell. 2023;41:757–75.e10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Windhager J, Zanotelli VRT, Schulz D, Meyer L, Daniel M, Bodenmiller B, et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc. 2023;18:3565–613.

    Article  CAS  PubMed  Google Scholar 

  42. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006;7:R100.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Berg S, Kutra D, Kroeger T, Straehle CN, Kausler BX, Haubold C, et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods. 2019;16:1226–32.

    Article  CAS  PubMed  Google Scholar 

  44. Schapiro D, Jackson HW, Raghuraman S, Fischer JR, Zanotelli VRT, Schulz D, et al. histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nat Methods. 2017;14:873–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank all members of Andrew Ewald and Won Jin Ho laboratories for fruitful discussions and for their constant support. We thank Philippe Juin (CRCI2NA) for his support and critical feedback on our study. This work was supported by NIH/NCI U01CA284090 (AJE), NIH/NCI U54CA268083 (AJE and WJH), NIH/NCI P30CA006973 (AJE and WJH), NIH/NCI R21CA264004 (WJH.), Hope Scarves Foundation (AJE), JKTG Foundation (AJE), Breast Cancer Research Foundation (23-048, AJE), Emerald Foundation, Inc. (EMG), Break Through Cancer (AD and WJH), and Maryland Cancer Moonshot (AD).

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Authors and Affiliations

  1. Université de Nantes, INSERM, CNRS, CRCI2NA, Nantes, France

    Eloïse M. Grasset

  2. Équipe Labellisée LIGUE Contre le Cancer CRCI2NA, Nantes, France

    Eloïse M. Grasset

  3. Department of Cell Biology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA

    Eloïse M. Grasset & Andrew J. Ewald

  4. Department of Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA

    Atul Deshpande, Jae W. Lee, Yeonju Cho, Sarah M. Shin, Erin M. Coyne, Alexei Hernandez, Xuan Yuan, Zhehao Zhang, Ashley Cimino-Mathews, Andrew J. Ewald & Won Jin Ho

  5. Convergence Institute, Johns Hopkins University, Baltimore, MD, USA

    Atul Deshpande, Andrew J. Ewald & Won Jin Ho

  6. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA

    Atul Deshpande

  7. Department of Pathology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA

    Jae W. Lee & Ashley Cimino-Mathews

  8. Giovanis Institute for Translational Cell Biology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA

    Andrew J. Ewald

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Contributions

EMG, AJE, and WJH conceived the project, led the data interpretation, provided funding for the staining and analysis, and wrote the manuscript. ACM designed the tissue microarrays. JWL and ACM provided histopathological review of the specimens. EMG, YC, AD, ZZ, and WJH performed the analysis. YC, AD, and WJH wrote and revised the analysis codes. SMS, EMC, AH, and XY optimized and performed imaging mass cytometry staining and data acquisition. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Eloïse M. Grasset or Won Jin Ho.

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Competing interests

AJE is a consultant for BioNTech, has unlicensed patents on biomarkers for cancer and on the use of antibodies as anti-cancer therapeutics, and his spouse is an employee of Immunocore. WJH reports patent royalties from Rodeo/Amgen, received grants from Sanofi and NeoTX (to Johns Hopkins), and speaking/travel honoraria from Exelixis and Standard BioTools. AC-M has received research grants from HeritX, Genentech, and Bristol Myers Squibb (to Johns Hopkins) and previously served as a consultant to Bristol Myers Squibb.

Ethics approval and consent to participate

Studies were conducted in accordance with the 1996 Declaration of Helsinki and were approved by the institutional review board (IRB, #NA_00084719) at the Johns Hopkins Hospital. Consents were waived based on IRB review of secondary research of de-identified archived tissue specimens.

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Grasset, E.M., Deshpande, A., Lee, J.W. et al. Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells. Oncogene 43, 2927–2937 (2024). https://doi.org/10.1038/s41388-024-03127-9

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