Spatial characterization of macrophage-enriched tumor regions in triple-negative breast cancer

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

BACKGROUND: The spatial organization of immune cells within tumors is an important area of investigation in studies of interactions between tumor cells and the tumor microenvironment. This is particularly relevant because some immune cells function through direct contact with their target cells, whereas others communicate over a distance via paracrine signaling involving cytokines. Thus, the topography of tumor cells and microenvironmental cells may determine the possibility and nature of intercellular interactions and thereby influence the functional effects of immune cells.

AIM: This study aimed to compare the spatial transcriptomic profiles of tumor and stromal regions enriched in macrophages in triple-negative breast cancer.

METHODS: Eight patients with triple-negative breast cancer were included. Spatial transcriptomic analysis was performed on formalin-fixed, paraffin-embedded tissue sections using high-throughput RNA sequencing with the 10X Visium platform. The annotated spots enriched in intraepithelial and stromal macrophages were used for downstream bioinformatic analysis.

RESULTS: A total of 437 differentially expressed genes were identified between the two groups of spots containing macrophages with distinct spatial localization. Spots with intraepithelial macrophages were characterized by activation of processes related to cytokine and chemokine signaling, regulation of regulatory T-cell differentiation, organization of cell–cell contacts, wound healing, and inhibition of viral activity. Spots enriched in stromal macrophages demonstrated activation of biological processes associated with the regulation of angiogenesis, cell migration and recruitment, cell adhesion, and stromal remodeling.

CONCLUSION: Macrophage topography within primary tumors of triple-negative breast cancer is associated with their functional characteristics. These fundamental findings may be useful for developing prognostic criteria and therapeutic approaches aimed at modulating the tumor microenvironment to improve long-term outcomes in patients with triple-negative breast cancer.

About the authors

Ivan A. Patskan

Tomsk National Research Medical Center of the Russian Academy of Science

Author for correspondence.
Email: packanivan59@gmail.com
ORCID iD: 0009-0008-4437-6583
SPIN-code: 4880-3416
Russian Federation, Tomsk

Anna Yu. Kalinchuk

Tomsk National Research Medical Center of the Russian Academy of Science

Email: annakalinchuk2022@gmail.com
ORCID iD: 0000-0003-2106-3513
SPIN-code: 3763-0291
Russian Federation, Tomsk

Elisaveta A. Tsarenkova

Tomsk National Research Medical Center of the Russian Academy of Science

Email: lisatsarenkova@mail.ru
ORCID iD: 0009-0009-7955-1625
SPIN-code: 2631-7770
Russian Federation, Tomsk

Evgeniia S. Grigoryeva

Tomsk National Research Medical Center of the Russian Academy of Science

Email: grigoryeva.es@gmail.com
ORCID iD: 0000-0003-4671-6306
SPIN-code: 7396-7570

MD, Cand. Sci. (Medicine)

Russian Federation, Tomsk

Irina V. Larionova

Tomsk National Research Medical Center of the Russian Academy of Science

Email: larionovaiv@onco.tnimc.ru
ORCID iD: 0000-0001-5758-7330
SPIN-code: 6272-8422

MD, Cand. Sci. (Medicine)

Russian Federation, Tomsk

Nataliya O. Popova

Tomsk National Research Medical Center of the Russian Academy of Science

Email: popova75tomsk@mail.ru
ORCID iD: 0000-0001-5294-778X
SPIN-code: 7672-1029

MD, Cand. Sci. (Medicine)

Russian Federation, Tomsk

Liubov A. Tashireva

Tomsk National Research Medical Center of the Russian Academy of Science

Email: tashireva@oncology.tomsk.ru
ORCID iD: 0000-0003-2061-8417
SPIN-code: 4371-5340

MD, Dr. Sci. (Medicine)

Russian Federation, Tomsk

References

  1. Bianchini G, De Angelis C, Licata L, Gianni L. Treatment landscape of triple-negative breast cancer — expanded options, evolving needs. Nat Rev Clin Oncol. 2022;19(2):91–113. doi: 10.1038/s41571-021-00565-2 EDN: SGQCCK
  2. Abdou Y, Goudarzi A, Yu JX, et al. Immunotherapy in triple negative breast cancer: beyond checkpoint inhibitors. NPJ Breast Cancer. 2022;8(1):121. doi: 10.1038/s41523-022-00486-y
  3. Marra A, Trapani D, Viale G, et al. Practical classification of triple-negative breast cancer: intratumoral heterogeneity, mechanisms of drug resistance, and novel therapies. NPJ Breast Cancer. 2020;6:54. doi: 10.1038/s41523-020-00197-2 EDN: CCHKJE
  4. Wang XQ, Danenberg E, Huang CS, et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature. 2023;621(7980):868–876. doi: 10.1038/s41586-023-06498-3 EDN: JYDCVM
  5. Mateiou C, Lokhande L, Diep LH, et al. Spatial tumor immune microenvironment phenotypes in ovarian cancer. NPJ Precis Oncol. 2024;8(1):148. doi: 10.1038/s41698-024-00640-8 EDN: YMZZEH
  6. Andersson A, Larsson L, Stenbeck L, et al. Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions. Nat Commun. 2021;12(1):6012. doi: 10.1038/s41467-021-26271-2 EDN: CDDRXX
  7. Bareche Y, Buisseret L, Gruosso T, et al. Unraveling triple-negative breast cancer tumor microenvironment heterogeneity: towards an optimized treatment approach. J Natl Cancer Inst. 2020;112(7):708–719. doi: 10.1093/jnci/djz208 EDN: RWVOIQ
  8. Bareham B, Dibble M, Parsons M. Defining and modeling dynamic spatial heterogeneity within tumor microenvironments. Curr Opin Cell Biol. 2024;90:102422. doi: 10.1016/j.ceb.2024.102422 EDN: XJLEFI
  9. Cheng X, Cao Y, Liu X, et al. Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis. Clin Transl Med. 2024;14(10):e70036. doi: 10.1002/ctm2.70036 EDN: TEJAIU
  10. Ben-Chetrit N, Niu X, Sotelo J, et al. Breast Cancer macrophage heterogeneity and self-renewal are determined by spatial localization. bioRxiv [Preprint]. 2023. doi: 10.1101/2023.10.24.563749
  11. Chu X, Tian Y, Lv C. Decoding the spatiotemporal heterogeneity of tumor-associated macrophages. Mol Cancer. 2024 Jul 27;23(1):150. doi: 10.1186/s12943-024-02064-1
  12. Hsieh WC, Budiarto BR, Wang YF, et al. Spatial multi-omics analyses of the tumor immune microenvironment. J Biomed Sci. 2022;29(1):96. doi: 10.1186/s12929-022-00879-y EDN: KAPUNM
  13. Tashireva L, Grigoryeva E, Alifanov V, et al. Spatial heterogeneity of integrins and their ligands in primary breast tumors. Discov Med. 2023;35(178):910–920. doi: 10.24976/Discov.Med.202335178.86 EDN: SOBBRS
  14. Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets — update. Nucleic Acids Res. 2013;41(Database issue):D991–5. doi: 10.1093/nar/gks1193
  15. Hao Y, Stuart T, Kowalski MH, et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat Biotechnol. 2024;42(2):293–304. doi: 10.1038/s41587-023-01767-y EDN: FSLREQ
  16. Hafemeister C, Satija R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 2019;20(1):296. doi: 10.1186/s13059-019-1874-1 EDN: TOZJIU
  17. Korsunsky I, Millard N, Fan J, et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019;16(12):1289–1296. doi: 10.1038/s41592-019-0619-0 EDN: XWCHRN
  18. Mages S, Moriel N, Avraham-Davidi I, et al. TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics. Nat Biotechnol. 2023;41(10):1465–1473. doi: 10.1038/s41587-023-01657-3 EDN: YMTDTX
  19. Wu SZ, Al-Eryani G, Roden DL, et al. A single-cell and spatially resolved atlas of human breast cancers. Nat Genet. 2021;53(9):1334–1347. doi: 10.1038/s41588-021-00911-1 EDN: ODYYFW
  20. Blighe K, Rana S, Lewis M. EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling. CitHub. 2018. Available at: https://github.com/kevinblighe/EnhancedVolcano
  21. Kuleshov MV, Jones MR, Rouillard AD, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44(W1):W90–W97. doi: 10.1093/nar/gkw377
  22. Liu M, Bertolazzi G, Sridhar S, et al. Spatially-resolved transcriptomics reveal macrophage heterogeneity and prognostic significance in diffuse large B-cell lymphoma. Nat Commun. 2024;15(1):2113. doi: 10.1038/s41467-024-46220-z EDN: HOZJWS
  23. Lemaitre L, Adeniji N, Suresh A, et al. Spatial analysis reveals targetable macrophage-mediated mechanisms of immune evasion in hepatocellular carcinoma minimal residual disease. Nat Cancer. 2024;5(10):1534–1556. doi: 10.1038/s43018-024-00828-8 EDN: EFJFBW
  24. Yang C, Wei C, Wang S, et al. Elevated CD163+/CD68+ ratio at tumor invasive front is closely associated with aggressive phenotype and poor prognosis in Colorectal Cancer. Int J Biol Sci. 2019;15(5):984–998. doi: 10.7150/ijbs.29836
  25. Liu T, Larionova I, Litviakov N, et al. Tumor-associated macrophages in human breast cancer produce new monocyte attracting and pro-angiogenic factor YKL-39 indicative for increased metastasis after neoadjuvant chemotherapy. Oncoimmunology. 2018;7(6):e1436922. doi: 10.1080/2162402X.2018.1436922 EDN: XXISCL
  26. Gruosso T, Gigoux M, Manem VSK, et al. Spatially distinct tumor immune microenvironments stratify triple-negative breast cancers. J Clin Invest. 2019;129(4):1785–1800. doi: 10.1172/JCI96313
  27. Abdul-Rahman T, Ghosh S, Badar SM, et al. The paradoxical role of cytokines and chemokines at the tumor microenvironment: a comprehensive review. Eur J Med Res. 2024;29(1):124. doi: 10.1186/s40001-024-01711-z EDN: GZSNQP
  28. Vitiello GAF, Ferreira WAS, Cordeiro de Lima VC, Medina TDS. Antiviral responses in cancer: boosting antitumor immunity through activation of interferon pathway in the tumor microenvironment. Front Immunol. 2021;12:782852. doi: 10.3389/fimmu.2021.782852 EDN: WBMWYF
  29. Wang Y, Li J, Nakahata S, Iha H. Complex role of regulatory T Cells (Tregs) in the tumor microenvironment: their molecular mechanisms and bidirectional effects on cancer progression. Int J Mol Sci. 2024;25(13):7346. doi: 10.3390/ijms25137346 EDN: DHMKJI
  30. Zhou G, Yang L, Gray A, et al. The role of desmosomes in carcinogenesis. Onco Targets Ther. 2017;10:4059–4063. doi: 10.2147/OTT.S136367
  31. Oshi M, Newman S, Tokumaru Y, et al. Intra-tumoral angiogenesis is associated with inflammation, immune reaction and metastatic recurrence in breast cancer. Int J Mol Sci. 2020;21(18):6708. doi: 10.3390/ijms21186708 EDN: ORZLIH
  32. Uddin MN, Wang X. Identification of key tumor stroma-associated transcriptional signatures correlated with survival prognosis and tumor progression in breast cancer. Breast Cancer. 2022;29(3):541–561. doi: 10.1007/s12282-022-01332-6 EDN: GGCWRN
  33. Wohlfeil SA, Olsavszky A, Irkens AL, et al. Deficiency of stabilin-1 in the context of hepatic melanoma metastasis. Cancers (Basel). 2024;16(2):441. doi: 10.3390/cancers16020441 EDN: NZYMVI
  34. Hu J, Ma Y, Ma J, et al. Macrophage-derived SPARC attenuates M2-mediated pro-tumour phenotypes. J Cancer. 2020;11(10):2981–2992. doi: 10.7150/jca.39651 EDN: BRYUHQ
  35. Marigo I, Trovato R, Hofer F, et al. Disabled homolog 2 controls prometastatic activity of tumor-associated macrophages. Cancer Discov. 2020;10(11):1758–1773. doi: 10.1158/2159-8290.CD-20-0036 EDN: NMLBVW
  36. Gu X, Li D, Wu P, et al. Revisiting the CXCL13/CXCR5 axis in the tumor microenvironment in the era of single-cell omics: Implications for immunotherapy. Cancer Lett. 2024;605:217278. doi: 10.1016/j.canlet.2024.217278 EDN: VOLQRD
  37. Tokunaga R, Zhang W, Naseem M, et al. CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation — A target for novel cancer therapy. Cancer Treat Rev. 2018;63:40–47. doi: 10.1016/j.ctrv.2017.11.007
  38. Li Y, Liang M, Lin Y, et al. Transcriptional expressions of CXCL9/10/12/13 as prognosis factors in breast cancer. J Oncol. 2020;2020:4270957. doi: 10.1155/2020/4270957 EDN: GJACFU
  39. Cardoso AP, Pinto ML, Castro F, et al. The immunosuppressive and pro-tumor functions of CCL18 at the tumor microenvironment. Cytokine Growth Factor Rev. 2021;60:107–119. doi: 10.1016/j.cytogfr.2021.03.005 EDN: RLLHBK
  40. Winkler J, Tan W, Diadhiou CM, et al. Single-cell analysis of breast cancer metastasis reveals epithelial-mesenchymal plasticity signatures associated with poor outcomes. J Clin Invest. 2024;134(17):e164227. doi: 10.1172/JCI164227 EDN: WYURDT
  41. Sharma N, Atolagbe OT, Ge Z, Allison JP. LILRB4 suppresses immunity in solid tumors and is a potential target for immunotherapy. J Exp Med. 2021;218(7):e20201811. doi: 10.1084/jem.20201811 EDN: LRYYKP
  42. Liu H, Yang J, Zhang J, et al. Molecular regulatory mechanism of LILRB4 in the immune response. Cent Eur J Immunol. 2023;48(1):43–47. doi: 10.5114/ceji.2023.125238 EDN: LLHZWY
  43. Yang T, Qian Y, Liang X, et al. LILRB4, an immune checkpoint on myeloid cells. Blood Sci. 2022;4(2):49–56. doi: 10.1097/BS9.0000000000000109 EDN: APHCPT
  44. Huang X, Xie X, Kang N, et al. SERPINB5 is a novel serum diagnostic biomarker for gastric high-grade intraepithelial neoplasia and plays a role in regulation of macrophage phenotypes. Transl Oncol. 2023;37:101757. doi: 10.1016/j.tranon.2023.101757 EDN: ZNQZUQ

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2026 Eco-Vector

License URL: https://eco-vector.com/for_authors.php#07

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).