Skip to main content

Advertisement

SpringerLink
Log in

Lactate from glycolysis regulates inflammatory macrophage polarization in breast cancer

  • Research
  • Published:
Cancer Immunology, Immunotherapy Aims and scope Submit manuscript

Abstract

Globally, breast cancer is one of the leading causes of cancer death in women. Metabolic reprogramming and immune escape are two important mechanisms supporting the progression of breast cancer. Lactate in tumors mainly comes from glycolysis and glutaminolysis. Using multiomics data analysis, we found that lactate is mainly derived from glycolysis in breast cancer. Single-cell transcriptome analysis found that breast cancer cells with higher malignancy, especially those in the cell cycle, have higher expression levels of glycolytic metabolic enzymes. Combined with clinical data analysis, it was found that the expression of the lactate transporter SLC16A3 is correlated with breast cancer molecular subtypes and immune infiltration. Among 22 immune cells, macrophages are the most abundant immune cells in breast cancer tissues, and the proportion of M1 macrophages is lower in the high SLC16A3 expression group. Finally, in vitro experiments confirmed that lactate could inhibit the expression of M1 macrophage markers at both RNA and protein levels. In conclusion, we found that lactate produced by glycolysis regulates the polarization of inflammatory macrophages in breast cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

All the data in our study are available upon request.

References

  1. Britt KL, Cuzick J, Phillips KA (2020) Key steps for effective breast cancer prevention. Nat Rev Cancer 20(8):417–436

    Article  CAS  PubMed  Google Scholar 

  2. Waks AG, Winer EP (2019) Breast cancer treatment: a review. JAMA 321(3):288–300

    Article  CAS  PubMed  Google Scholar 

  3. Dias AS, Almeida CR, Helguero LA, Duarte IF (2019) Metabolic crosstalk in the breast cancer microenvironment. Eur J Cancer 121:154–171

    Article  CAS  PubMed  Google Scholar 

  4. Zaslona Z, O’Neill LAJ (2020) Cytokine-like roles for metabolites in immunity. Mol Cell 78(5):814–823

    Article  CAS  PubMed  Google Scholar 

  5. Koppenol WH, Bounds PL, Dang CV (2011) Otto Warburg’s contributions to current concepts of cancer metabolism. Nat Rev Cancer 11(5):325–337

    Article  CAS  PubMed  Google Scholar 

  6. Deberardinis RJ, Sayed N, Ditsworth D, Thompson CB (2008) Brick by brick: metabolism and tumor cell growth. Curr Opin Genet Dev 18(1):54–61

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. de la Cruz-Lopez KG, Castro-Munoz LJ, Reyes-Hernandez DO, Garcia-Carranca A, Manzo-Merino J (2019) Lactate in the regulation of tumor microenvironment and therapeutic approaches. Front Oncol 9:1143

    Article  PubMed  PubMed Central  Google Scholar 

  8. Certo M, Tsai CH, Pucino V, Ho PC, Mauro C (2021) Lactate modulation of immune responses in inflammatory versus tumour microenvironments. Nat Rev Immunol 21(3):151–161

    Article  CAS  PubMed  Google Scholar 

  9. Gottfried E, Kunz-Schughart LA, Ebner S, Mueller-Klieser W, Hoves S, Andreesen R, Mackensen A, Kreutz M (2006) Tumor-derived lactic acid modulates dendritic cell activation and antigen expression. Blood 107(5):2013–2021

    Article  CAS  PubMed  Google Scholar 

  10. Fischer K, Hoffmann P, Voelkl S, Meidenbauer N, Ammer J, Edinger M, Gottfried E, Schwarz S, Rothe G, Hoves S et al (2007) Inhibitory effect of tumor cell-derived lactic acid on human T cells. Blood 109(9):3812–3819

    Article  CAS  PubMed  Google Scholar 

  11. Goetze K, Walenta S, Ksiazkiewicz M, Kunz-Schughart LA, Mueller-Klieser W (2011) Lactate enhances motility of tumor cells and inhibits monocyte migration and cytokine release. Int J Oncol 39(2):453–463

    CAS  PubMed  Google Scholar 

  12. Cassetta L, Pollard JW (2018) Targeting macrophages: therapeutic approaches in cancer. Nat Rev Drug Discov 17(12):887–904

    Article  CAS  PubMed  Google Scholar 

  13. Murray PJ, Allen JE, Biswas SK, Fisher EA, Gilroy DW, Goerdt S, Gordon S, Hamilton JA, Ivashkiv LB, Lawrence T et al (2014) Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41(1):14–20

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wang C, Cao M, Jiang X, Yao Y, Liu Z, Luo D (2021) Macrophage balance fraction determines the degree of immunosuppression and metastatic ability of breast cancer. Int Immunopharmacol 97:107682

    Article  CAS  PubMed  Google Scholar 

  15. Colegio OR, Chu NQ, Szabo AL, Chu T, Rhebergen AM, Jairam V, Cyrus N, Brokowski CE, Eisenbarth SC, Phillips GM et al (2014) Functional polarization of tumour-associated macrophages by tumour-derived lactic acid. Nature 513(7519):559–563

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chen P, Zuo H, Xiong H, Kolar MJ, Chu Q, Saghatelian A, Siegwart DJ, Wan Y (2017) Gpr132 sensing of lactate mediates tumor-macrophage interplay to promote breast cancer metastasis. Proc Natl Acad Sci U S A 114(3):580–585

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Mu X, Shi W, Xu Y, Xu C, Zhao T, Geng B, Yang J, Pan J, Hu S, Zhang C et al (2018) Tumor-derived lactate induces M2 macrophage polarization via the activation of the ERK/STAT3 signaling pathway in breast cancer. Cell Cycle 17(4):428–438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang D, Tang Z, Huang H, Zhou G, Cui C, Weng Y, Liu W, Kim S, Lee S, Perez-Neut M et al (2019) Metabolic regulation of gene expression by histone lactylation. Nature 574(7779):575–580

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Vadevoo SMP, Gunassekaran GR, Lee C, Lee N, Lee J, Chae S, Park J-Y, Koo J, Lee B (2021) The macrophage odorant receptor Olfr78 mediates the lactate-induced M2 phenotype of tumor-associated macrophages. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.2102434118

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M (2021) KEGG: integrating viruses and cellular organisms. Nucleic Acids Res 49(D1):D545–D551

    Article  CAS  PubMed  Google Scholar 

  21. Gillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff-Ribeiro A, Griss J, Sevilla C, Matthews L, Gong C et al (2022) The reactome pathway knowledgebase 2022. Nucleic Acids Res 50(D1):D687–D692

    Article  CAS  PubMed  Google Scholar 

  22. Mueckler M, Thorens B (2013) The SLC2 (GLUT) family of membrane transporters. Mol Aspects Med 34(2–3):121–138

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chen LQ, Cheung LS, Feng L, Tanner W, Frommer WB (2015) Transport of sugars. Annu Rev Biochem 84:865–894

    Article  CAS  PubMed  Google Scholar 

  24. Payen VL, Mina E, Van Hee VF, Porporato PE, Sonveaux P (2020) Monocarboxylate transporters in cancer. Mol Metab 33:48–66

    Article  CAS  PubMed  Google Scholar 

  25. Felmlee MA, Jones RS, Rodriguez-Cruz V, Follman KE, Morris ME (2020) Monocarboxylate transporters (SLC16): function, regulation, and role in health and disease. Pharmacol Rev 72(2):466–485

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Najafi M, Hashemi Goradel N, Farhood B, Salehi E, Nashtaei MS, Khanlarkhani N, Khezri Z, Majidpoor J, Abouzaripour M, Habibi M et al (2019) Macrophage polarity in cancer: a review. J Cell Biochem 120(3):2756–2765

    Article  CAS  PubMed  Google Scholar 

  27. Terunuma A, Putluri N, Mishra P, Mathe EA, Dorsey TH, Yi M, Wallace TA, Issaq HJ, Zhou M, Killian JK et al (2014) MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis. J Clin Invest 124(1):398–412

    Article  CAS  PubMed  Google Scholar 

  28. Weinstein JN, Collisson EA, Mills GB, Mills KR, Shaw BA, Ozenberger KE, Shmulevich I, Sander C, Stuart JM (2013) The cancer genome atlas pan-cancer analysis project. Nat Genet 45(10):1113–1120. https://doi.org/10.1038/ng.2764

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gao GF, Parker JS, Reynolds SM, Silva TC, Wang L-B, Zhou W, Akbani R, Bailey M, Balu S, Berman BP et al (2019) Before and after: comparison of legacy and harmonized TCGA genomic data commons’ data. Cell Syst 9(1):24-34.e10. https://doi.org/10.1016/j.cels.2019.06.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Goldman MJ, Craft B, Hastie M, Repecka K, McDade F, Kamath A, Banerjee A, Luo Y, Rogers D, Brooks AN et al (2020) Visualizing and interpreting cancer genomics data via the xena platform. Nat Biotechnol 38(6):675–678

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cancer Genome Atlas N (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418):61–70. https://doi.org/10.1038/nature11412

    Article  CAS  Google Scholar 

  32. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Benjamin Gross S, Sumer O, Sun Y, Jacobsen A, Sinha R, Larsson E, Cerami E, Sander C, Schultz N (2013) Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. https://doi.org/10.1126/scisignal.2004088

    Article  PubMed  PubMed Central  Google Scholar 

  33. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y et al (2012) The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 486(7403):346–352

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Gendoo DM, Ratanasirigulchai N, Schroder MS, Pare L, Parker JS, Prat A, Haibe-Kains B (2016) Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer. Bioinformatics 32(7):1097–1099

    Article  CAS  PubMed  Google Scholar 

  35. Gong TQ, Jiang YZ, Shao C, Peng WT, Liu MW, Li DQ, Zhang BY, Du P, Huang Y, Li FF et al (2022) Proteome-centric cross-omics characterization and integrated network analyses of triple-negative breast cancer. Cell Rep 38(9):110460

    Article  CAS  PubMed  Google Scholar 

  36. Ghergurovich JM, Lang JD, Levin MK, Briones N, Facista SJ, Mueller C, Cowan AJ, McBride MJ, Rodriguez ESR, Killian A et al (2021) Local production of lactate, ribose phosphate, and amino acids within human triple-negative breast cancer. Med (N Y) 2(6):736–754

    CAS  Google Scholar 

  37. Wu SZ, Al-Eryani G, Roden DL, Junankar S, Harvey K, Andersson A, Thennavan A, Wang C, Torpy JR, Bartonicek N et al (2021) A single-cell and spatially resolved atlas of human breast cancers. Nat Genet 53(9):1334–1347

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M et al (2012) NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res 41(D1):D991–D995. https://doi.org/10.1093/nar/gks1193

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Xu M, Wang X, Li Y, Geng X, Jia X, Zhang L, Yang H (2021) Arachidonic acid metabolism controls macrophage alternative activation through regulating oxidative phosphorylation in ppargamma dependent manner. Front Immunol 12:618501

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47

    Article  PubMed  PubMed Central  Google Scholar 

  41. Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9:559

    Article  PubMed  PubMed Central  Google Scholar 

  42. Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK (2019) Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 10(1):1523

    Article  PubMed  PubMed Central  Google Scholar 

  43. Hanzelmann S, Castelo R, Guinney J (2013) GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics 14:7

    Article  PubMed  PubMed Central  Google Scholar 

  44. Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P (2015) The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst 1(6):417–425

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Butler A, Hoffman P, Smibert P, Papalexi E, Satija R (2018) Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol 36(5):411–420

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Yoshihara K, Shahmoradgoli M, Martinez E, Vegesna R, Kim H, Torres-Garcia W, Trevino V, Shen H, Laird PW, Levine DA et al (2013) Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun 4:2612

    Article  PubMed  Google Scholar 

  47. Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA (2018) Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol Biol 1711:243–259

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Calvo MB, Figueroa A, Pulido EG, Campelo RG, Aparicio LA (2010) Potential role of sugar transporters in cancer and their relationship with anticancer therapy. Int J Endocrinol 2010:1–14. https://doi.org/10.1155/2010/205357

    Article  CAS  Google Scholar 

  49. Ancey PB, Contat C, Meylan E (2018) Glucose transporters in cancer-from tumor cells to the tumor microenvironment. FEBS J 285(16):2926–2943

    Article  CAS  PubMed  Google Scholar 

  50. Pavlova NN, Thompson CB (2016) The emerging hallmarks of cancer metabolism. Cell Metab 23(1):27–47

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Pavlova NN, Zhu J, Thompson CB (2022) The hallmarks of cancer metabolism: still emerging. Cell Metab 34(3):355–377

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Liu Y, Beyer A, Aebersold R (2016) On the dependency of cellular protein levels on mRNA abundance. Cell 165(3):535–550

    Article  CAS  PubMed  Google Scholar 

  53. Jang C, Chen L, Rabinowitz JD (2018) Metabolomics and isotope tracing. Cell 173(4):822–837

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Chung W, Eum HH, Lee HO, Lee KM, Lee HB, Kim KT, Ryu HS, Kim S, Lee JE, Park YH et al (2017) Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat Commun 8:15081

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Lee JS, Adler L, Karathia H, Carmel N, Rabinovich S, Auslander N, Keshet R, Stettner N, Silberman A, Agemy L et al (2018) Urea cycle dysregulation generates clinically relevant genomic and biochemical signatures. Cell 174(6):1559-1570.e22. https://doi.org/10.1016/j.cell.2018.07.019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Aikun F, Yao B, Dong T, Chen Y, Jia Yao Y, Liu HL, Bai H, Liu X, Zhang Y et al (2022) Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer. Cell 185(8):1356-1372.e26. https://doi.org/10.1016/j.cell.2022.02.027

    Article  CAS  Google Scholar 

  57. Sonveaux P, Vegran F, Schroeder T, Wergin MC, Verrax J, Rabbani ZN, De Saedeleer CJ, Kennedy KM, Diepart C, Jordan BF et al (2008) Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. J Clin Invest 118(12):3930–3942

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Ho J, de Moura MB, Lin Y, Vincent G, Thorne S, Duncan LM, Hui-Min L, Kirkwood JM, Becker D, Van Houten B et al (2012) Importance of glycolysis and oxidative phosphorylation in advanced melanoma. Mol Cancer 11:76

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Pisarsky L, Bill R, Fagiani E, Dimeloe S, Goosen RW, Hagmann J, Hess C, Christofori G (2016) Targeting metabolic symbiosis to overcome resistance to anti-angiogenic therapy. Cell Rep 15(6):1161–1174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Allen E, Mieville P, Warren CM, Saghafinia S, Li L, Peng MW, Hanahan D (2016) Metabolic symbiosis enables adaptive resistance to anti-angiogenic therapy that is dependent on mTOR signaling. Cell Rep 15(6):1144–1160

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Jimenez-Valerio G, Martinez-Lozano M, Bassani N, Vidal A, Ochoa-de-Olza M, Suarez C, Garcia-Del-Muro X, Carles J, Vinals F, Graupera M et al (2016) Resistance to antiangiogenic therapies by metabolic symbiosis in renal cell carcinoma PDX models and patients. Cell Rep 15(6):1134–1143

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Lin S, Sun L, Lyu X, Ai X, Du D, Su N, Li H, Zhang L, Yu J, Yuan S (2017) Lactate-activated macrophages induced aerobic glycolysis and epithelial-mesenchymal transition in breast cancer by regulation of CCL5-CCR5 axis: a positive metabolic feedback loop. Oncotarget 8(66):110426–110443

    Article  PubMed  PubMed Central  Google Scholar 

  63. Irizarry-Caro RA, McDaniel MM, Overcast GR, Jain VG, Troutman TD, Pasare C (2020) TLR signaling adapter BCAP regulates inflammatory to reparatory macrophage transition by promoting histone lactylation. Proc Natl Acad Sci U S A 117(48):30628–30638

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Cui H, Xie N, Banerjee S, Ge J, Jiang D, Dey T, Matthews QL, Liu RM, Liu G (2021) Lung Myofibroblasts promote macrophage profibrotic activity through lactate-induced histone lactylation. Am J Respir Cell Mol Biol 64(1):115–125

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Mrs. Zhuoqi Liu and Mrs. Xiaohong Yang for their insightful comments during their review of this manuscript.

Funding

This work was supported by National Natural Science Foundation of China (81560464 and 31960152 to D.L.), Applied Research and Cultivation Program of Jiangxi Provincial Department of Science and Technology (20212BAG70036 to S.Z.) and Jiangxi Provincial Education Department foundation Project (GJJ218911 to S.Z.).

Author information

Authors and Affiliations

  1. School of Basic Medical Sciences, Nanchang University, Nanchang, 330006, China

    Chao Wang

  2. Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Nanchang University, Nanchang, 330006, China

    Linxuan Xue, Wenqiang Zhu, Lina Liu & Daya Luo

  3. Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Jiangxi Cardiovascular Research Institute, Nanchang, 330006, China

    Shuhua Zhang

Authors
  1. Chao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Linxuan Xue
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenqiang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lina Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shuhua Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Daya Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CW contributed to Conceptualization, Methodology, Software, Validation, Visualization, Formal analysis, Investigation, Data Curation, Writing-Original Draft; LX contributed to Methodology; Validation; Resources; Writing-Review and Editing; WZ contributed to Methodology; Validation; Resources; LL: Validation; Resources; SZ contributed to Conceptualization, Writing-Review and Editing; DL contributed to Conceptualization, Resources, Writing-Review and Editing, Supervision.

Corresponding author

Correspondence to Daya Luo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 211 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, C., Xue, L., Zhu, W. et al. Lactate from glycolysis regulates inflammatory macrophage polarization in breast cancer. Cancer Immunol Immunother 72, 1917–1932 (2023). https://doi.org/10.1007/s00262-023-03382-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00262-023-03382-x

Keywords

Search

Navigation