Tumor Biology

, Volume 37, Issue 8, pp 11385–11395 | Cite as

c-Met and ERβ expression differences in basal-like and non-basal-like triple-negative breast cancer

  • Xinyu Ren
  • Li Yuan
  • Songjie Shen
  • Hanwen Wu
  • Junliang Lu
  • Zhiyong Liang
Original Article


Basal-like breast cancer (BLBC) and triple-negative breast cancer (TNBC) are two entities of breast cancer that share similar poor prognosis. Even though both cancers have overlaps, there are still some differences between those two types. It has been reported that the c-Met high expression was associated with poor prognosis not only in breast cancer but also in many other cancers. The role of ERβ in pathogenesis and treatment of breast cancer has remained controversial. In this study, we firstly distinguished basal-like from nonbasal-like cancer patients in TNBC patients using CK5/6 and EGFR as markers and next determined the relationship of basal-like breast cancer with c-Met or ERβ expression levels and prognosis in TNBC patients. One hundred twenty-seven patients who had been diagnosed with TNBC were enrolled. The clinical and pathological characteristics of the patients were recorded. The expression of EGFR, CK5/6, ERβ, and c-Met were evaluated with immunohistochemical methods using paraffin blocks. The median age of patients was 50.7 years. CK5/6 immunopositivity was 31.5 % (40/127), and EGFR was 40.2 % (51/127). Of the TNBC cases, 55.1 % (71/127) were positive for either CK5/6 or EGFR and were thus classified as basal-like breast cancer. C-Met (P < 0.001) and ERβ (P = 0.002) overexpression, small tumor sizes, a ductal subtype, and high-grade tumor were significantly correlated with BLBC. High c-Met expression was detected in 43.3 % patients. Metastatic lymph nodes and tumor size (>5 cm), which were both important prognostic predictors, were significantly associated with recurrence and mortality. BLBC typically demonstrates a unique profile. CK5/6 and EGFR expression combination indicates a higher basal-like phenotype possibility. The expression of c-Met and ERβ were significantly related to the basal-like phenotype. The classical markers, lymph node metastasis, and tumor size were found to have important prognostic value. However, high c-Met expression and basal-like phenotypes did not show a direct correlation with poor prognosis.


Triple-negative breast cancer Basal-like breast cancer CK5/6 EGFR c-Met ERβ 


Compliance with ethical standard

The study was approved by the ethics committee of Peking Union Medical College Hospital.

Supplementary material

13277_2016_5010_Fig4_ESM.gif (1.9 mb)
Supplementary Figure 1

Immunohistochemical staining of Triple-negative markers. A. Isotype control for anti-ER-alpha antibody on breast cancer tissue. B. Positive control of ER-alpha staining on breast cancer tissue nuclear staining pattern. C. Isotype control for anti-PR antibody on breast cancer tissue. D. Positive control of PR staining on breast cancer tissue showing nuclear staining pattern. E. Isotype control for anti-Her-2 antibody on breast cancer tissue. F. Positive control of Her-2 staining showing membranous staining pattern. ER, estrogen receptor; PR, progesterone receptor. (GIF 1927 kb)

13277_2016_5010_MOESM1_ESM.tif (33.6 mb)
High resolution image (TIF 34441 kb)
13277_2016_5010_Fig5_ESM.gif (1 mb)
Supplementary Figure 2

Immunohistochemical staining for basal markers. A. Isotype control for anti-CK5/6 antibody on mesothelioma. B. Positive control of CK5/6 staining on mesothelioma showing cytoplasmic staining pattern. C. Isotype control for anti-EGFR antibody on skin tissue. D. Positive control of EGFR staining on skin tissue showing a membranous and cytoplasmic staining pattern. CK, cytokeratin; EGFR, epithelial growth factor receptor. (GIF 1036 kb)

13277_2016_5010_MOESM2_ESM.tif (19 mb)
High resolution image (TIF 19449 kb)
13277_2016_5010_Fig6_ESM.gif (1.1 mb)
Supplementary Figure 3

Immunohistochemical staining for Ki-67 and p53. A. Isotype control for Ki-67 index on breast cancer tissue. B. Positive control of Ki-67 staining on breast cancer tissue showing nuclear staining pattern. C. Isotype control for anti-p53 antibody on colon cancer. D. Positive control of p53 staining on colon cancer tissue showing nuclear staining pattern. (GIF 1138 kb)

13277_2016_5010_MOESM3_ESM.tif (22.4 mb)
High resolution image (TIF 22984 kb)
13277_2016_5010_Fig7_ESM.gif (1.2 mb)
Supplementary Figure 4

Immunohistochemical staining for c-Met and ERβ. A. Isotype control for c-Met on tissue of high differentiated squamous cell carcinoma of the scalp. B. Positive control of c-Met staining on high differentiated squamous cell carcinoma of the scalp showing membranous and cytoplasmic staining pattern. C. Isotype control for anti-ERβ antibody on breast cancer tissue. D. Positive control of ERβ staining on breast cancer tissue showing nuclear staining pattern (GIF 1275 kb)

13277_2016_5010_MOESM4_ESM.tif (23.1 mb)
High resolution image (TIF 23632 kb)


  1. 1.
    Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–52.CrossRefPubMedGoogle Scholar
  2. 2.
    Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869–74.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98:262–72.CrossRefPubMedGoogle Scholar
  4. 4.
    Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A. 2003;100:8418–23.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A. 2003;100:10393–8.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Rakha EA, El-Sayed ME, Green AR, Lee AH, Robertson JF, Ellis IO. Prognostic markers in triple-negative breast cancer. Cancer. 2007;109:25–32.CrossRefPubMedGoogle Scholar
  7. 7.
    Rouzier R, Perou CM, Symmans WF, Ibrahim N, Cristofanilli M, Anderson K, et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res. 2005;11:5678–85.CrossRefPubMedGoogle Scholar
  8. 8.
    Calza S, Hall P, Auer G, Bjöhle J, Klaar S, Kronenwett U, et al. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients. Breast Cancer Res. 2006;8:R34.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Jumppanen M, Gruvberger-Saal S, Kauraniemi P, Tanner M, Bendahl PO, Lundin M, et al. Basal-like phenotype is not associated with patient survival in estrogen-receptornegative breast cancers. Breast Cancer Res. 2007;9:R16.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Bertucci F, Finetti P, Cervera N, Esterni B, Hermitte F, Viens P, et al. How basal are triple-negative breast cancers? Int J Cancer. 2008;123:236–40.CrossRefPubMedGoogle Scholar
  11. 11.
    Tischkowitz M, Brunet JS, Begin LR, Huntsman DG, Cheang MC, Akslen LA, et al. Use of immunohistochemical markers can refine prognosis in triple negative breast cancer. BMC Cancer. 2007;7:134.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Bidard FC, Conforti R, Boulet T, Michiels S, Delaloge S, André F. Does triple-negative phenotype accurately identify basal-like tumour? An immunohistochemical analysis based on 143 ‘triple-negative’ breast cancers. Ann Oncol. 2007;18:1285–6.CrossRefPubMedGoogle Scholar
  13. 13.
    Tan DS, Marchio C, Jones RL, Savage K, Smith IE, Dowsett M, et al. Triple negative breast cancer: molecular profiling and prognostic impact in adjuvant anthracyclinetreated patients. Breast Cancer Res Treat. 2008;111:27–44.CrossRefPubMedGoogle Scholar
  14. 14.
    Tanizaki J, Okamoto I, Sakai K, Nakagawa K. Differential roles of trans-phosphorylated EGFR, HER-2, HER3, and RET as heterodimerisation partners of MET in lung cancer with MET amplification. Br J Cancer. 2011;105(6):807–13.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Lee HE, Kim MA, Lee HS, Jung EJ, Yang HK, Lee BL, et al. MET in gastric carcinomas: comparison between protein expression and gene copy number and impact on clinical outcome. Br J Cancer. 2012;107(2):325–33.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Yan S, Jiao X, Zou H, Li K. Prognostic significance of c-Met in breast cancer: a meta-analysis of 6010 cases. Diagn Pathol. 2015;10:62.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Du Y, Yamaguchi H, Wei Y, Hsu JL. Wang HL2, Hsu YH1, et al. Blocking c-Met-mediated PARP1 phosphorylation enhances anti-tumor effects of PARP inhibitors. Nat Med. 2016;22(2):194–201.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Balfe P, McCann A, McGoldrick A, McAllister K, Kennedy M, Dervan P, et al. Estrogen receptor alpha and beta profiling in human breast cancer. Eur J Surg Oncol. 2004;30:469–74.CrossRefPubMedGoogle Scholar
  19. 19.
    O’Neill PA, Davies MPA, Shaaban AM, Innes H, Torevell A, Sibson DR, et al. Wild-type oestrogen receptor beta (ERbeta1) mRNA and protein expression in tamoxifen-treated postmenopausal breast cancers. Br J Cancer. 2004;91:1694–702.PubMedPubMedCentralGoogle Scholar
  20. 20.
    Esslimani-Sahla M, Simony-Lafontaine J, Kramar A, Lavaill R, Mollevi C, Warner M, et al. Estrogen receptor beta (ERbeta) level but not its ERbetacx variant helps to predict tamoxifenresistance in breast cancer. Clin Cancer Res. 2004;10:5769–76.CrossRefPubMedGoogle Scholar
  21. 21.
    Wolff AC, Hammond ME, Hicks DG, Dowsett M, McShane LM, Allison KH, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol. 2013;3l(31):3997–4013.CrossRefGoogle Scholar
  22. 22.
    HER2 test guide (2014 Edition)" writing group. HER2 test guide for breast cancer. Chin J Pathol. 2014;43(4):262–7.Google Scholar
  23. 23.
    National Health Service Breast Screening Programme (NHSBSP) and The Royal College of Pathologists(2005) Pathology Reporting of Breast Disease. Sheffield: NHSBSP and The Royal College of Pathologists; NHSBSP Pub. No 58Google Scholar
  24. 24.
    Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res. 2004;10:5367–74.CrossRefPubMedGoogle Scholar
  25. 25.
    Cheang MC, Voduc D, Bajdik C, Leung S, McKinney S, Chia SK, et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res. 2008;14:1368–76.CrossRefPubMedGoogle Scholar
  26. 26.
    Badve S, Dabbs DJ, Schnitt SJ, Baehner FL, Decker T, Eusebi V, et al. Basal-like and triple-negative breast cancers: a critical review with an emphasis on the implications for pathologists and oncologists. Mod Pathol. 2011;24:157–67.CrossRefPubMedGoogle Scholar
  27. 27.
    Kim MJ, Ro JY, Ahn SH, Kim HH, Kim SB, Gong G. Clinicopathologic significance of the basal-like subtype of breast cancer: a comparison with hormone receptor and Her2/neu-overexpressing phenotypes. Hum Pathol. 2006;37(9):1217–26.CrossRefPubMedGoogle Scholar
  28. 28.
    Livasy CA, Karaca G, Nanda R, Tretiakova MS, Olopade OI, Moore DT, et al. Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol. 2006;19(2):264–71.CrossRefPubMedGoogle Scholar
  29. 29.
    Rakha EA, Elsheikh SE, Aleskandarany MA, Habashi HO, Green AR, Powe DG, et al. Triple-negative breast cancer: distinguishing between basal and nonbasal subtypes. Clin Cancer Res. 2009;15(7):2302–10.CrossRefPubMedGoogle Scholar
  30. 30.
    Ho-Yen CM, Green AR, Rakha EA, Brentnall AR, Ellis IO, Kermorgant S, et al. C-Met in invasive breast cancer: is there a relationship with the basal-like subtype? Cancer. 2014;120(2):163–71.CrossRefPubMedGoogle Scholar
  31. 31.
    Charafe-Jauffret E, Ginestier C, Monville F, Finetti P, Adélaïde J, Cervera N, et al. Gene expression profiling of breast cell lines identifies potential new basal markers. Oncogene. 2006;25:2273–84.CrossRefPubMedGoogle Scholar
  32. 32.
    Graveel CR, DeGroot JD, Su Y, Koeman J, Dykema K, Leung S, et al. Met induces diverse mammary carcinomas in mice and is associated with human basal breast cancer. Proc Natl Acad Sci U S A. 2009;106:12909–14.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Garcia S, Dale’s JP, Charafe-Jauffret E, Carpentier-Meunier S, Andrac-Meyer L, Jacquemier J, et al. Poor prognosis in breast carcinomas correlates with increased expression of targetable CD146 and c-Met and with proteomic basal-like phenotype. Hum Pathol. 2007;38:830–41.CrossRefPubMedGoogle Scholar
  34. 34.
    Mevlude I, Metin O, Halit K, Veli B, Oktay B, Ayse Ocak D, et al. Cytokeratin 5/6, c-Met expressions, and PTEN loss prognostic indicators in triple-negative breast cancer. Med Oncol. 2014;31:801.CrossRefGoogle Scholar
  35. 35.
    Moghul A, Lin L, Beedle A, Kanbour-Shakir A, DeFrances MC, Liu Y, et al. Modulation of c-MET proto-oncogene (HGF receptor) mRNA abundance by cytokines and hormones: evidence for rapid decay of the 8 kb c-MET transcript. Oncogene. 1994;9(7):2045–52.PubMedGoogle Scholar
  36. 36.
    Huang B, Warner M, Gustafsson JÅ. Estrogen receptors in breast carcinogenesis and endocrine therapy. Mol Cell Endocrinol. 2015;418(Pt 3):240–4.CrossRefPubMedGoogle Scholar
  37. 37.
    Sareddy GR, Vadlamudi RK. Cancer therapy using natural ligands that target estrogen receptor beta. Chin J Nat Med. 2015;13(11):801–7.PubMedPubMedCentralGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2016

Authors and Affiliations

  • Xinyu Ren
    • 1
  • Li Yuan
    • 1
  • Songjie Shen
    • 2
  • Hanwen Wu
    • 1
  • Junliang Lu
    • 1
  • Zhiyong Liang
    • 1
  1. 1.Department of PathologyPeking Union Medical College Hospital, Chinese Academy of Medical SciencesBeijingChina
  2. 2.Department of Breast SurgeryPeking Union Medical College Hospital, Chinese Academy of Medical SciencesBeijingChina

Personalised recommendations