European Radiology

, Volume 25, Issue 2, pp 419–427 | Cite as

Heterogeneity of triple-negative breast cancer: mammographic, US, and MR imaging features according to androgen receptor expression

  • Min Sun Bae
  • So Yeon Park
  • Sung Eun Song
  • Won Hwa Kim
  • Su Hyun Lee
  • Wonshik Han
  • In-Ae Park
  • Dong-Young Noh
  • Woo Kyung MoonEmail author



Our aim was to determine whether triple-negative breast cancers (TNBCs) with and without androgen receptor (AR) expression have distinguishing imaging features on mammography, breast ultrasound (US), and magnetic resonance (MR) imaging.


AR expression was assessed immunohistochemically in 125 patients with TNBC from a consecutive series of 1,086 operable invasive breast cancers. Two experienced radiologists blinded to clinicopathological findings reviewed all imaging studies in consensus using the BI-RADS lexicon. The imaging and pathological features of 33 AR-positive TNBCs were compared with those of 92 AR-negative TNBCs.


The presence of mammographic calcifications with or without a mass (p < 0.001), non-mass enhancement on MR imaging (p < 0.001), and masses with irregular shape or spiculated margins on US (p < 0.001 and p = 0.002) and MR imaging (p = 0.001 and p < 0.001) were significantly associated with AR-positive TNBC. Compared with AR-negative TNBC, AR-positive TNBC was more likely to have a ductal carcinoma in situ component (59.8 % vs. 90.9 %, p = 0.001) and low Ki-67 expression (30.4 % vs. 51.5 %, p = 0.030).


AR-positive and AR-negative TNBCs have different imaging features, and certain imaging findings can be useful to predict AR status in TNBC.

Key points

Triple-negative breast cancers have distinguishing imaging features according to AR expression.

AR-positive TNBC is associated with calcifications, spiculated masses, and non-mass enhancement.

Multimodality imaging can help predict androgen receptor status in TNBC.


Triple-negative breast cancer Immunohistochemistry Androgen receptor Mammography MR imaging 



The scientific guarantor of this publication is Woo Kyung Moon. The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (grant no. 2012R1A1A2009414). No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, observational, performed at one institution.


  1. 1.
    Lin NU, Vanderplas A, Hughes ME et al (2012) Clinicopathologic features, patterns of recurrence, and survival among women with triple-negative breast cancer in the National Comprehensive Cancer Network. Cancer 118:5463–5472PubMedCentralPubMedCrossRefGoogle Scholar
  2. 2.
    Carey LA, Dees EC, Sawyer L et al (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13:2329–2334PubMedCrossRefGoogle Scholar
  3. 3.
    Shah SP, Roth A, Goya R et al (2012) The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486:395–399PubMedGoogle Scholar
  4. 4.
    Lehmann BD, Bauer JA, Chen X et al (2011) Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 121:2750–2767PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Prat A, Adamo B, Cheang MC, Anders CK, Carey LA, Perou CM (2013) Molecular characterization of basal-like and non-basal-like triple-negative breast cancer. Oncologist 18:123–133PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Turner NC, Reis-Filho JS (2013) Tackling the diversity of triple-negative breast cancer. Clin Cancer Res 19:6380–6388PubMedCrossRefGoogle Scholar
  7. 7.
    Masuda H, Baggerly KA, Wang Y et al (2013) Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes. Clin Cancer Res 19:5533–5540PubMedCrossRefGoogle Scholar
  8. 8.
    Yu KD, Zhu R, Zhan M et al (2013) Identification of prognosis-relevant subgroups in patients with chemoresistant triple-negative breast cancer. Clin Cancer Res 19:2723–2733PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Shah PD, Gucalp A, Traina TA (2013) The role of the androgen receptor in triple-negative breast cancer. Womens Health (Lond Engl) 9:351–360CrossRefGoogle Scholar
  10. 10.
    Vera-Badillo FE, Templeton AJ, de Gouveia P et al (2014) Androgen receptor expression and outcomes in early breast cancer: a systematic review and meta-analysis. J Natl Cancer Inst 106:1–11CrossRefGoogle Scholar
  11. 11.
    Park S, Koo J, Park HS et al (2010) Expression of androgen receptors in primary breast cancer. Ann Oncol 21:488–492PubMedCrossRefGoogle Scholar
  12. 12.
    Hu R, Dawood S, Holmes MD et al (2011) Androgen receptor expression and breast cancer survival in postmenopausal women. Clin Cancer Res 17:1867–1874PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Thike AA, Yong-Zheng Chong L, Cheok PY et al (2014) Loss of androgen receptor expression predicts early recurrence in triple-negative and basal-like breast cancer. Mod Pathol 27:352–360PubMedGoogle Scholar
  14. 14.
    Gucalp A, Tolaney S, Isakoff SJ et al (2013) Phase II trial of bicalutamide in patients with androgen receptor-positive, estrogen receptor-negative metastatic breast cancer. Clin Cancer Res 19:5505–5512PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Luck AA, Evans AJ, James JJ et al (2008) Breast carcinoma with basal phenotype: mammographic findings. AJR Am J Roentgenol 191:346–351PubMedCrossRefGoogle Scholar
  16. 16.
    Krizmanich-Conniff KM, Paramagul C, Patterson SK et al (2012) Triple receptor-negative breast cancer: imaging and clinical characteristics. AJR Am J Roentgenol 199:458–464PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Ryu EB, Chang JM, Seo M, Kim SA, Lim JH, Moon WK (2014) Tumour volume doubling time of molecular breast cancer subtypes assessed by serial breast ultrasound. Eur Radiol 24:2227–2235PubMedCrossRefGoogle Scholar
  18. 18.
    Uematsu T, Kasami M, Yuen S (2009) Triple-negative breast cancer: correlation between MR imaging and pathologic findings. Radiology 250:638–647PubMedCrossRefGoogle Scholar
  19. 19.
    Sung JS, Jochelson MS, Brennan S et al (2013) MR imaging features of triple-negative breast cancers. Breast J 19:643–649PubMedCrossRefGoogle Scholar
  20. 20.
    Chen JH, Agrawal G, Feig B et al (2007) Triple-negative breast cancer: MRI features in 29 patients. Ann Oncol 18:2042–2043PubMedCrossRefGoogle Scholar
  21. 21.
    American College of Radiology (2003) Breast Imaging and Reporting Data System (BIRADS). American College of Radiology, RestonGoogle Scholar
  22. 22.
    Hammond ME, Hayes DF, Dowsett M et al (2010) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol 28:2784–2795PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Dowsett M, Nielsen TO, A’Hern R et al (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer working group. J Natl Cancer Inst 103:1656–1664PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Keam B, Im SA, Lee KH et al (2011) Ki-67 can be used for further classification of triple negative breast cancer into two subtypes with different response and prognosis. Breast Cancer Res 13:R22PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Wolff AC, Hammond ME, Schwartz JN et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25:118–145PubMedCrossRefGoogle Scholar
  26. 26.
    Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19:403–410PubMedCrossRefGoogle Scholar
  27. 27.
    Bae MS, Moon WK, Chang JM et al (2013) Mammographic features of calcifications in DCIS: correlation with oestrogen receptor and human epidermal growth factor receptor 2 status. Eur Radiol 23:2072–2078PubMedCrossRefGoogle Scholar
  28. 28.
    Bullier B, MacGrogan G, Bonnefoi H et al (2013) Imaging features of sporadic breast cancer in women under 40 years old: 97 cases. Eur Radiol 23:3237–3245PubMedCrossRefGoogle Scholar
  29. 29.
    Costantini M, Belli P, Distefano D et al (2012) Magnetic resonance imaging features in triple-negative breast cancer: comparison with luminal and HER2-overexpressing tumors. Clin Breast Cancer 12:331–339PubMedCrossRefGoogle Scholar
  30. 30.
    Bae MS, Seo M, Kim KG, Park IA, Moon WK (2014) Quantitative MRI morphology of invasive breast cancer: correlation with immunohistochemical biomarkers and subtypes. Acta RadiolGoogle Scholar
  31. 31.
    Greenwood HI, Heller SL, Kim S, Sigmund EE, Shaylor SD, Moy L (2013) Ductal carcinoma in situ of the breasts: review of MR imaging features. Radiographics 33:1569–1588PubMedCrossRefGoogle Scholar
  32. 32.
    Agoff SN, Swanson PE, Linden H, Hawes SE, Lawton TJ (2003) Androgen receptor expression in estrogen receptor-negative breast cancer: immunohistochemical, clinical, and prognostic associations. Am J Clin Pathol 120:725–731PubMedCrossRefGoogle Scholar
  33. 33.
    Aho M, Irshad A, Ackerman SJ et al (2013) Correlation of sonographic features of invasive ductal mammary carcinoma with age, tumor grade, and hormone-receptor status. J Clin Ultrasound 41:10–17PubMedCrossRefGoogle Scholar
  34. 34.
    Wojcinski S, Stefanidou N, Hillemanns P, Degenhardt F (2013) The biology of malignant breast tumors has an impact on the presentation in ultrasound: an analysis of 315 cases. BMC Womens Health 13:47PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    McNamara KM, Yoda T, Miki Y et al (2013) Androgenic pathway in triple negative invasive ductal tumors: its correlation with tumor cell proliferation. Cancer Sci 104:639–646PubMedCrossRefGoogle Scholar
  36. 36.
    Lehmann BD, Pietenpol JA (2014) Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes. J Pathol 232:142–150PubMedCentralPubMedCrossRefGoogle Scholar
  37. 37.
    Mukhtar RA, Yau C, Rosen M et al (2013) Clinically meaningful tumor reduction rates vary by prechemotherapy MRI phenotype and tumor subtype in the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Ann Surg Oncol 20:3823–3830PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    Yi A, Cho N, Im SA et al (2013) Survival outcomes of breast cancer patients who receive neoadjuvant chemotherapy: association with dynamic contrast-enhanced MR imaging with computer-aided evaluation. Radiology 268:662–672PubMedCrossRefGoogle Scholar
  39. 39.
    Yamamoto S, Maki DD, Korn RL, Kuo MD (2012) Radiogenomic analysis of breast cancer using MRI: a preliminary study to define the landscape. AJR Am J Roentgenol 199:654–663PubMedCrossRefGoogle Scholar
  40. 40.
    Jaffe CC (2012) Imaging and genomics: is there a synergy? Radiology 264:329–331PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Min Sun Bae
    • 1
  • So Yeon Park
    • 2
  • Sung Eun Song
    • 1
  • Won Hwa Kim
    • 1
  • Su Hyun Lee
    • 1
  • Wonshik Han
    • 3
  • In-Ae Park
    • 2
  • Dong-Young Noh
    • 3
  • Woo Kyung Moon
    • 1
    Email author
  1. 1.Department of RadiologySeoul National University College of MedicineSeoulKorea
  2. 2.Department of PathologySeoul National University College of MedicineSeoulKorea
  3. 3.Department of SurgerySeoul National University College of MedicineSeoulKorea

Personalised recommendations