Skip to main content

Advertisement

SpringerLink
Log in

Infiltrating S100A8+ myeloid cells promote metastatic spread of human breast cancer and predict poor clinical outcome

  • Preclinical Study
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

The mechanisms by which breast cancer (BrC) can successfully metastasize are complex and not yet fully understood. Our goal was to identify tumor-induced stromal changes that influence metastatic cell behavior, and may serve as better targets for therapy. To identify stromal changes in cancer-bearing tissue, dual-species gene expression analysis was performed for three different metastatic BrC xenograft models. Results were confirmed by immunohistochemistry, flow cytometry, and protein knockdown. These results were validated in human clinical samples at the mRNA and protein level by retrospective analysis of cohorts of human BrC specimens. In pre-clinical models of BrC, systemic recruitment of S100A8+ myeloid cells—including myeloid-derived suppressor cells (MDSCs)—was promoted by tumor-derived factors. Recruitment of S100A8+ myeloid cells was diminished by inhibition of tumor-derived factors or depletion of MDSCs, resulting in fewer metastases and smaller primary tumors. Importantly, these MDSCs retain their ability to suppress T cell proliferation upon co-culture. Secretion of macrophage inhibitory factor (MIF) activated the recruitment of S100A8+ myeloid cells systemically. Inhibition of MIF, or depletion of MDSCs resulted in delayed tumor growth and lower metastatic burden. In human BrC specimens, increased mRNA and protein levels of S100A8+ infiltrating cells are highly associated with poor overall survival and shorter metastasis free survival of BrC patients, respectively. Furthermore, analysis of nine different human gene expression datasets confirms the association of increased levels of S100A8 transcripts with an increased risk of death. Recruitment of S100A8+ myeloid cells to primary tumors and secondary sites in xenograft models of BrC enhances cancer progression independent of their suppressive activity on T cells. In clinical samples, infiltrating S100A8+ cells are associated with poor overall survival. Targeting these molecules or associated pathways in cells of the tumor microenvironment may translate into novel therapeutic interventions and benefit patient outcome.

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

References

  1. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144(5):646–674. doi:10.1016/j.cell.2011.02.013

    Article  PubMed  CAS  Google Scholar 

  2. Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H, Chen H, Omeroglu G, Meterissian S, Omeroglu A, Hallett M, Park M (2008) Stromal gene expression predicts clinical outcome in breast cancer. Nat Med 14(5):518–527. doi:10.1038/nm1764

    Article  PubMed  CAS  Google Scholar 

  3. Iorns E, Drews-Elger K, Ward TM, Dean S, Clarke J, Berry D, El-Ashry D, Lippman M (2012) A new mouse model for the study of human breast cancer metastasis. PLoS ONE 7(10):e47995. doi:10.1371/journal.pone.0047995

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  4. Sartelet H, Durrieu L, Fontaine F, Nyalendo C, Haddad E (2012) Description of a new xenograft model of metastatic neuroblastoma using NOD/SCID/Il2rg null (NSG) mice. In Vivo 26(1):19–29

    PubMed  Google Scholar 

  5. Quintana H, Piskounova E, Shackleton M, Weinberg D, Eskiocak U, Fullen DR, Johnson TM, Morrison SJ (2012) Human melanoma metastasis in NSG mice correlates with clinical outcome in patients. Sci Transl Med 4(159):159ra149. doi:10.1126/scitranslmed.3004599

    Article  PubMed  Google Scholar 

  6. Iorns E, Clarke J, Ward T, Dean S, Lippman M (2012) Simultaneous analysis of tumor and stromal gene expression profiles from xenograft models. Breast Cancer Res Treat 131(1):321–324. doi:10.1007/s10549-011-1784-8

    Article  PubMed  Google Scholar 

  7. Murdoch C, Muthana M, Coffelt SB, Lewis CE (2008) The role of myeloid cells in the promotion of tumour angiogenesis. Nat Rev Cancer 8(8):618–631. doi:10.1038/nrc2444

    Article  PubMed  CAS  Google Scholar 

  8. Nagaraj S, Gabrilovich DI (2010) Myeloid-derived suppressor cells in human cancer. Cancer J 16(4):348–353. doi:10.1097/PPO.0b013e3181eb3358

    Article  PubMed  CAS  Google Scholar 

  9. Youn JI, Nagaraj S, Collazo M, Gabrilovich DI (2008) Subsets of myeloid-derived suppressor cells in tumor-bearing mice. J Immunol 181(8):5791–5802

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  10. Cuenca AG, Delano MJ, Kelly-Scumpia KM, Moreno C, Scumpia PO, Laface DM, Heyworth PG, Efron PA, Moldawer LL (2011) A paradoxical role for myeloid-derived suppressor cells in sepsis and trauma. Mol Med 17(3–4):281–292. doi:10.2119/molmed.2010.00178

    PubMed  CAS  PubMed Central  Google Scholar 

  11. Diaz-Montero CM, Salem ML, Nishimura MI, Garrett-Mayer E, Cole DJ, Montero AJ (2009) Increased circulating myeloid-derived suppressor cells correlate with clinical cancer stage, metastatic tumor burden, and doxorubicin-cyclophosphamide chemotherapy. Cancer Immunol Immunother 58(1):49–59. doi:10.1007/s00262-008-0523-4

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  12. Srivastava MK, Sinha P, Clements VK, Rodriguez P, Ostrand-Rosenberg S (2010) Myeloid-derived suppressor cells inhibit T-cell activation by depleting cystine and cysteine. Cancer Res 70(1):68–77. doi:10.1158/0008-5472.CAN-09-2587

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  13. Bunt SK, Yang L, Sinha P, Clements VK, Leips J, Ostrand-Rosenberg S (2007) Reduced inflammation in the tumor microenvironment delays the accumulation of myeloid-derived suppressor cells and limits tumor progression. Cancer Res 67(20):10019–10026. doi:10.1158/0008-5472.CAN-07-2354

    Article  PubMed  CAS  Google Scholar 

  14. Sinha P, Clements VK, Bunt SK, Albelda SM, Ostrand-Rosenberg S (2007) Cross-talk between myeloid-derived suppressor cells and macrophages subverts tumor immunity toward a type 2 response. J Immunol 179(2):977–983

    Article  PubMed  CAS  Google Scholar 

  15. Ostrand-Rosenberg S, Sinha P (2009) Myeloid-derived suppressor cells: linking inflammation and cancer. J Immunol 182(8):4499–4506. doi:10.4049/jimmunol.0802740

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  16. Odink K, Cerletti N, Bruggen J, Clerc RG, Tarcsay L, Zwadlo G, Gerhards G, Schlegel R, Sorg C (1987) Two calcium-binding proteins in infiltrate macrophages of rheumatoid arthritis. Nature 330(6143):80–82. doi:10.1038/330080a0

    Article  PubMed  CAS  Google Scholar 

  17. Vogl T, Tenbrock K, Ludwig S, Leukert N, Ehrhardt C, van Zoelen MA, Nacken W, Foell D, van der Poll T, Sorg C, Roth J (2007) Mrp8 and Mrp14 are endogenous activators of Toll-like receptor 4, promoting lethal, endotoxin-induced shock. Nat Med 13(9):1042–1049. doi:10.1038/nm1638

    Article  PubMed  CAS  Google Scholar 

  18. Wang L, Chang EW, Wong SC, Ong SM, Chong DQ, Ling KL (2013) Increased myeloid-derived suppressor cells in gastric cancer correlate with cancer stage and plasma S100A8/A9 proinflammatory proteins. J Immunol 190(2):794–804. doi:10.4049/jimmunol.1202088

    Article  PubMed  CAS  Google Scholar 

  19. Zhao F, Hoechst B, Duffy A, Gamrekelashvili J, Fioravanti S, Manns MP, Greten TF, Korangy F (2012) S100A9 a new marker for monocytic human myeloid-derived suppressor cells. Immunology 136(2):176–183. doi:10.1111/j.1365-2567.2012.03566.x

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  20. Arai K, Takano S, Teratani T, Ito Y, Yamada T, Nozawa R (2008) S100A8 and S100A9 overexpression is associated with poor pathological parameters in invasive ductal carcinoma of the breast. Curr Cancer Drug Targets 8(4):243–252

    Article  PubMed  CAS  Google Scholar 

  21. Ott HW, Lindner H, Sarg B, Mueller-Holzner E, Abendstein B, Bergant A, Fessler S, Schwaerzler P, Zeimet A, Marth C, Illmensee K (2003) Calgranulins in cystic fluid and serum from patients with ovarian carcinomas. Cancer Res 63(21):7507–7514

    PubMed  CAS  Google Scholar 

  22. Vogl T, Gharibyan AL, Morozova-Roche LA (2012) Pro-inflammatory S100A8 and S100A9 proteins: self-assembly into multifunctional native and amyloid complexes. Int J Mol Sci 13(3):2893–2917. doi:10.3390/ijms13032893

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  23. Sinha P, Okoro C, Foell D, Freeze HH, Ostrand-Rosenberg S, Srikrishna G (2008) Proinflammatory S100 proteins regulate the accumulation of myeloid-derived suppressor cells. J Immunol 181(7):4666–4675

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  24. Bunt SK, Clements VK, Hanson EM, Sinha P, Ostrand-Rosenberg S (2009) Inflammation enhances myeloid-derived suppressor cell cross-talk by signaling through Toll-like receptor 4. J Leukoc Biol 85(6):996–1004. doi:10.1189/jlb.0708446

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  25. Yin C, Li H, Zhang B, Liu Y, Lu G, Lu S, Sun L, Qi Y, Li X, Chen W (2013) RAGE-binding S100A8/A9 promotes the migration and invasion of human breast cancer cells through actin polymerization and epithelial–mesenchymal transition. Breast Cancer Res Treat 142(2):297–309. doi:10.1007/s10549-013-2737-1

    Article  PubMed  CAS  Google Scholar 

  26. Ye XZ, Yu SC, Bian XW (2010) Contribution of myeloid-derived suppressor cells to tumor-induced immune suppression, angiogenesis, invasion and metastasis. J Genet Genomics = Yi chuan xue bao 37(7):423–430. doi:10.1016/S1673-8527(09)60061-8

    Article  CAS  Google Scholar 

  27. Hiratsuka S, Watanabe A, Aburatani H, Maru Y (2006) Tumour-mediated upregulation of chemoattractants and recruitment of myeloid cells predetermines lung metastasis. Nat Cell Biol 8(12):1369–1375. doi:10.1038/ncb1507

    Article  PubMed  CAS  Google Scholar 

  28. Zhang J, Liu J (2013) Tumor stroma as targets for cancer therapy. Pharmacol Ther 137(2):200–215. doi:10.1016/j.pharmthera.2012.10.003

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  29. Drews-Elger K, Brinkman JA, Miller P, Shah SH, Harrell JC, da Silva TG, Ao Z, Schlater A, Azzam DJ, Diehl K, Thomas D, Slingerland JM, Perou CM, Lippman ME, El-Ashry D (2014) Primary breast tumor-derived cellular models: characterization of tumorigenic, metastatic, and cancer-associated fibroblasts in dissociated tumor (DT) cultures. Breast Cancer Res Treat. doi:10.1007/s10549-014-2887-9

    Google Scholar 

  30. Simpson KD, Templeton DJ, Cross JV (2012) Macrophage migration inhibitory factor promotes tumor growth and metastasis by inducing myeloid-derived suppressor cells in the tumor microenvironment. J Immunol 189(12):5533–5540. doi:10.4049/jimmunol.1201161

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  31. Ichikawa M, Williams R, Wang L, Vogl T, Srikrishna G (2011) S100A8/A9 activate key genes and pathways in colon tumor progression. Mol Cancer Res 9(2):133–148. doi:10.1158/1541-7786.MCR-10-0394

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. Freund A, Chauveau C, Brouillet JP, Lucas A, Lacroix M, Licznar A, Vignon F, Lazennec G (2003) IL-8 expression and its possible relationship with estrogen-receptor-negative status of breast cancer cells. Oncogene 22(2):256–265. doi:10.1038/sj.onc.1206113

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Pederson L, Winding B, Foged NT, Spelsberg TC, Oursler MJ (1999) Identification of breast cancer cell line-derived paracrine factors that stimulate osteoclast activity. Cancer Res 59(22):5849–5855

    PubMed  CAS  Google Scholar 

  34. Verjans E, Noetzel E, Bektas N, Schutz AK, Lue H, Lennartz B, Hartmann A, Dahl E, Bernhagen J (2009) Dual role of macrophage migration inhibitory factor (MIF) in human breast cancer. BMC Cancer 9:230. doi:10.1186/1471-2407-9-230

    Article  PubMed  PubMed Central  Google Scholar 

  35. McAllister SS, Gifford AM, Greiner AL, Kelleher SP, Saelzler MP, Ince TA, Reinhardt F, Harris LN, Hylander BL, Repasky EA, Weinberg RA (2008) Systemic endocrine instigation of indolent tumor growth requires osteopontin. Cell 133(6):994–1005. doi:10.1016/j.cell.2008.04.045

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  36. Kurebayashi J, Otsuki T, Kunisue H, Mikami Y, Tanaka K, Yamamoto S, Sonoo H (1999) Expression of vascular endothelial growth factor (VEGF) family members in breast cancer. Jpn J Cancer Res Gann 90(9):977–981

    Article  CAS  Google Scholar 

  37. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Lonning PE, Borresen-Dale AL (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874. doi:10.1073/pnas.191367098

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  38. Karnoub AE, Dash AB, Vo AP, Sullivan A, Brooks MW, Bell GW, Richardson AL, Polyak K, Tubo R, Weinberg RA (2007) Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature 449(7162):557–563. doi:10.1038/nature06188

    Article  PubMed  CAS  Google Scholar 

  39. Diaz-Cano SJ (2012) Tumor heterogeneity: mechanisms and bases for a reliable application of molecular marker design. Int J Mol Sci 13(2):1951–2011. doi:10.3390/ijms13021951

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  40. Zardavas D, Baselga J, Piccart M (2013) Emerging targeted agents in metastatic breast cancer. Nat Rev Clin Oncol 10(4):191–210. doi:10.1038/nrclinonc.2013.29

    Article  PubMed  CAS  Google Scholar 

  41. Mahmoud SM, Paish EC, Powe DG, Macmillan RD, Grainge MJ, Lee AH, Ellis IO, Green AR (2011) Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. J Clin Oncol Off J Am Soc Clin Oncol 29(15):1949–1955. doi:10.1200/JCO.2010.30.5037

    Article  Google Scholar 

  42. Condamine T, Gabrilovich DI (2011) Molecular mechanisms regulating myeloid-derived suppressor cell differentiation and function. Trends Immunol 32(1):19–25. doi:10.1016/j.it.2010.10.002

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  43. Sumida K, Wakita D, Narita Y, Masuko K, Terada S, Watanabe K, Satoh T, Kitamura H, Nishimura T (2012) Anti-IL-6 receptor mAb eliminates myeloid-derived suppressor cells and inhibits tumor growth by enhancing T-cell responses. Eur J Immunol 42(8):2060–2072. doi:10.1002/eji.201142335

    Article  PubMed  CAS  Google Scholar 

  44. Morales JK, Kmieciak M, Knutson KL, Bear HD, Manjili MH (2010) GM-CSF is one of the main breast tumor-derived soluble factors involved in the differentiation of CD11b−Gr1− bone marrow progenitor cells into myeloid-derived suppressor cells. Breast Cancer Res Treat 123(1):39–49. doi:10.1007/s10549-009-0622-8

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  45. Xu X, Wang B, Ye C, Yao C, Lin Y, Huang X, Zhang Y, Wang S (2008) Overexpression of macrophage migration inhibitory factor induces angiogenesis in human breast cancer. Cancer Lett 261(2):147–157. doi:10.1016/j.canlet.2007.11.028

    Article  PubMed  CAS  Google Scholar 

  46. Acharyya S, Oskarsson T, Vanharanta S, Malladi S, Kim J, Morris PG, Manova-Todorova K, Leversha M, Hogg N, Seshan VE, Norton L, Brogi E, Massague J (2012) A CXCL1 paracrine network links cancer chemoresistance and metastasis. Cell 150(1):165–178. doi:10.1016/j.cell.2012.04.042

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  47. Resetkova E, Reis-Filho JS, Jain RK, Mehta R, Thorat MA, Nakshatri H, Badve S (2010) Prognostic impact of ALDH1 in breast cancer: a story of stem cells and tumor microenvironment. Breast Cancer Res Treat 123(1):97–108. doi:10.1007/s10549-009-0619-3

    Article  PubMed  Google Scholar 

  48. Nocito A, Kononen J, Kallioniemi OP, Sauter G (2001) Tissue microarrays (TMAs) for high-throughput molecular pathology research. Int J Cancer 94(1):1–5. doi:10.1002/ijc.1385

    Article  PubMed  CAS  Google Scholar 

  49. Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z, Quackenbush JF, Stijleman IJ, Palazzo J, Marron JS, Nobel AB, Mardis E, Nielsen TO, Ellis MJ, Perou CM, Bernard PS (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol Off J Am Soc Clin Oncol 27(8):1160–1167. doi:10.1200/JCO.2008.18.1370

    Article  Google Scholar 

  50. Cooper A, van Doorninck J, Ji L, Russell D, Ladanyi M, Shimada H, Krailo M, Womer RB, Hsu JH, Thomas D, Triche TJ, Sposto R, Lawlor ER (2011) Ewing tumors that do not overexpress BMI-1 are a distinct molecular subclass with variant biology: a report from the Children’s Oncology Group. Clin Cancer Res Off J Am Assoc Cancer Res 17(1):56–66. doi:10.1158/1078-0432.CCR-10-1417

    Article  CAS  Google Scholar 

  51. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Graf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S, Group M, Langerod A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Borresen-Dale AL, Brenton JD, Tavare S, Caldas C, Aparicio S (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486(7403):346–352. doi:10.1038/nature10983

    PubMed  CAS  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the members of the Oncogenomics Core Facility, Flow Cytometry Core Facility, and the Division of Veterinary Resources at the University of Miami Miller School of Medicine for their assistance during the course of the study. The authors would also like to thank Nanette Bishopric, MD and Barry I. Hudson PhD for helpful discussion of the manuscript. This Project was funded by Breast Cancer Research Foundation (BrCRF) awards to MEL and JMR. Part of these studies was conducted at the Lombardi Comprehensive Cancer Center Histopathology and Tissue Shared Resource which is supported in part by NIH/NCI Grant P30-CA051008. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

Conflict of interest

All authors have no conflicts of interest to declare.

Author information

Authors and Affiliations

  1. Department of Medicine, University of Miami Miller School of Medicine, 1120 N.W. 14th Street, CRB 620, Miami, FL, 33136, USA

    Katherine Drews-Elger, Alexandra Dias, Philip Miller, Sonja Dean, Jennifer Clarke, Dorraya El-Ashry & Marc E. Lippman

  2. Science Exchange, Palo Alto, CA, USA

    Elizabeth Iorns

  3. Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA

    Toby M. Ward

  4. Breakthrough Breast Cancer Research Center, The Institute of Cancer Research, Fulham Road, London, SW3 6JB, UK

    Adriana Campion-Flora & Daniel Nava Rodrigues

  5. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA

    Jorge S. Reis-Filho

  6. Breast Oncology Program, 6312 CCGC, University of Michigan Medical School, Ann Arbor, MI, 48109, USA

    James M. Rae

  7. Department of Pathology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA

    Dafydd Thomas

  8. Histopathology & Tissue Shared Resource, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, 20057, USA

    Deborah Berry

Authors
  1. Katherine Drews-Elger
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elizabeth Iorns
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexandra Dias
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Philip Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Toby M. Ward
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sonja Dean
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jennifer Clarke
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Adriana Campion-Flora
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Daniel Nava Rodrigues
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jorge S. Reis-Filho
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. James M. Rae
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Dafydd Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Deborah Berry
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Dorraya El-Ashry
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Marc E. Lippman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Katherine Drews-Elger.

Additional information

Katherine Drews-Elger and Elizabeth Iorns have contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 733 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Drews-Elger, K., Iorns, E., Dias, A. et al. Infiltrating S100A8+ myeloid cells promote metastatic spread of human breast cancer and predict poor clinical outcome. Breast Cancer Res Treat 148, 41–59 (2014). https://doi.org/10.1007/s10549-014-3122-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-014-3122-4

Keywords

Search

Navigation