Advertisement

Breast Cancer Research and Treatment

, Volume 178, Issue 1, pp 185–197 | Cite as

Risk stratification of triple-negative breast cancer with core gene signatures associated with chemoresponse and prognosis

  • Eun-Kyu Kim
  • Ae Kyung Park
  • Eunyoung Ko
  • Woong-Yang Park
  • Kyung-Min Lee
  • Dong-Young Noh
  • Wonshik HanEmail author
Epidemiology

Abstract

Purpose

Neoadjuvant chemotherapy studies have consistently reported a strong correlation between pathologic response and long-term outcome in triple-negative breast cancer (TNBC). We aimed to define minimal gene signatures for predicting chemoresponse by a three-step approach and to further develop a risk-stratification method of TNBC.

Methods

The first step involved the detection of genes associated with resistance to docetaxel in eight TNBC cell lines, leading to identification of thousands of candidate genes. Through subsequent second and third step analyses with gene set enrichment analysis and survival analysis using public expression profiles, the candidate gene list was reduced to prognostic core gene signatures comprising ten or four genes.

Results

The prognostic core gene signatures include three up-regulated (CEBPD, MMP20, and WLS) and seven down-regulated genes (ASF1A, ASPSCR1, CHAF1B, DNMT1, GINS2, GOLGA2P5, and SKA1). We further develop a simple risk-stratification method based on expression profiles of the core genes. Relative expression values of the up-regulated and down-regulated core genes were averaged into two scores, Up and Down scores, respectively; then samples were stratified by a diagonal line in a xy plot of the Up and Down scores. Based on this method, the patients were successfully divided into subgroups with distinct chemoresponse and prognosis. The prognostic power of the method was validated in three independent public datasets containing 230, 141, and 117 TNBC patients with chemotherapy. In multivariable Cox regression analysis, the core gene signatures were significantly associated with prognosis independent of tumor stage and age at diagnosis. In meta-analysis, we found that five core genes (CEBPD, WLS, CHAF1B, GINS2, and SKA1) play opposing roles, either tumor promoter or suppressor, in TNBC and non-TNBC tumors respectively, depending on estrogen receptor status.

Conclusions

The results may provide a promising prognostic tool for predicting chemotherapy responders among TNBC patients prior to initiation of chemotherapeutic treatment.

Keywords

Triple-negative breast cancer Chemoresponse Core gene Risk stratification Prognosis 

Notes

Acknowledgements

We thank all the individuals who took part in the Translational Research Organization in Cancer (TROICA) project and all the researchers who have enabled this work to be carried out.

Funding

This research was funded by grants of the National Research Foundation (NRF) of Korea funded by the Korea government (MSIP), 2015R1A2A2A01008264 (to WH) and 2015R1A4A1041219 (to AKP).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Not applicable.

Supplementary material

10549_2019_5366_MOESM1_ESM.pdf (19.9 mb)
Supplementary material 1 (PDF 20340 kb)
10549_2019_5366_MOESM2_ESM.xlsx (26 kb)
Supplementary material 2 (XLSX 26 kb)

References

  1. 1.
    Bauer KR, Brown M, Cress RD, Parise CA, Caggiano V (2007) Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer Registry. Cancer 109(9):1721–1728.  https://doi.org/10.1002/cncr.22618 CrossRefPubMedGoogle Scholar
  2. 2.
    Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK, Sawka CA, Lickley LA, Rawlinson E, Sun P, Narod SA (2007) Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13(15 Pt 1):4429–4434.  https://doi.org/10.1158/1078-0432.CCR-06-3045 CrossRefPubMedGoogle Scholar
  3. 3.
    Haffty BG, Yang Q, Reiss M, Kearney T, Higgins SA, Weidhaas J, Harris L, Hait W, Toppmeyer D (2006) Locoregional relapse and distant metastasis in conservatively managed triple negative early-stage breast cancer. J Clin Oncol 24(36):5652–5657.  https://doi.org/10.1200/JCO.2006.06.5664 CrossRefGoogle Scholar
  4. 4.
    Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, Senn HJ, Panel M (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol 24(9):2206–2223.  https://doi.org/10.1093/annonc/mdt303 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Rouzier R, Perou CM, Symmans WF, Ibrahim N, Cristofanilli M, Anderson K, Hess KR, Stec J, Ayers M, Wagner P, Morandi P, Fan C, Rabiul I, Ross JS, Hortobagyi GN, Pusztai L (2005) Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin Cancer Res 11(16):5678–5685.  https://doi.org/10.1158/1078-0432.CCR-04-2421 CrossRefPubMedGoogle Scholar
  6. 6.
    Carey LA, Dees EC, Sawyer L, Gatti L, Moore DT, Collichio F, Ollila DW, Sartor CI, Graham ML, Perou CM (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13(8):2329–2334.  https://doi.org/10.1158/1078-0432.CCR-06-1109 CrossRefPubMedGoogle Scholar
  7. 7.
    Bhargava R, Beriwal S, Dabbs DJ, Ozbek U, Soran A, Johnson RR, Brufsky AM, Lembersky BC, Ahrendt GM (2010) Immunohistochemical surrogate markers of breast cancer molecular classes predicts response to neoadjuvant chemotherapy: a single institutional experience with 359 cases. Cancer 116(6):1431–1439.  https://doi.org/10.1002/cncr.24876 CrossRefPubMedGoogle Scholar
  8. 8.
    Liedtke C, Mazouni C, Hess KR, Andre F, Tordai A, Mejia JA, Symmans WF, Gonzalez-Angulo AM, Hennessy B, Green M, Cristofanilli M, Hortobagyi GN, Pusztai L (2008) Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer. J Clin Oncol 26(8):1275–1281.  https://doi.org/10.1200/JCO.2007.14.4147 CrossRefGoogle Scholar
  9. 9.
    Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA (2011) Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 121(7):2750–2767.  https://doi.org/10.1172/JCI45014 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Masuda H, Baggerly KA, Wang Y, Zhang Y, Gonzalez-Angulo AM, Meric-Bernstam F, Valero V, Lehmann BD, Pietenpol JA, Hortobagyi GN, Symmans WF, Ueno NT (2013) Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes. Clin Cancer Res 19(19):5533–5540.  https://doi.org/10.1158/1078-0432.CCR-13-0799 CrossRefPubMedGoogle Scholar
  11. 11.
    Lehmann BD, Jovanovic B, Chen X, Estrada MV, Johnson KN, Shyr Y, Moses HL, Sanders ME, Pietenpol JA (2016) Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PLoS ONE 11(6):e0157368.  https://doi.org/10.1371/journal.pone.0157368 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Rody A, Karn T, Liedtke C, Pusztai L, Ruckhaeberle E, Hanker L, Gaetje R, Solbach C, Ahr A, Metzler D, Schmidt M, Muller V, Holtrich U, Kaufmann M (2011) A clinically relevant gene signature in triple negative and basal-like breast cancer. Breast Cancer Res 13(5):R97.  https://doi.org/10.1186/bcr3035 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Prat A, Lluch A, Albanell J, Barry WT, Fan C, Chacon JI, Parker JS, Calvo L, Plazaola A, Arcusa A, Segui-Palmer MA, Burgues O, Ribelles N, Rodriguez-Lescure A, Guerrero A, Ruiz-Borrego M, Munarriz B, Lopez JA, Adamo B, Cheang MC, Li Y, Hu Z, Gulley ML, Vidal MJ, Pitcher BN, Liu MC, Citron ML, Ellis MJ, Mardis E, Vickery T, Hudis CA, Winer EP, Carey LA, Caballero R, Carrasco E, Martin M, Perou CM, Alba E (2014) Predicting response and survival in chemotherapy-treated triple-negative breast cancer. Br J Cancer 111(8):1532–1541.  https://doi.org/10.1038/bjc.2014.444 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Yam C, Mani SA, Moulder SL (2017) Targeting the molecular subtypes of triple negative breast cancer: understanding the diversity to progress the field. Oncologist 22(9):1086–1093.  https://doi.org/10.1634/theoncologist.2017-0095 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Ring BZ, Hout DR, Morris SW, Lawrence K, Schweitzer BL, Bailey DB, Lehmann BD, Pietenpol JA, Seitz RS (2016) Generation of an algorithm based on minimal gene sets to clinically subtype triple negative breast cancer patients. BMC Cancer 16:143.  https://doi.org/10.1186/s12885-016-2198-0 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Noguchi S (2006) Predictive factors for response to docetaxel in human breast cancers. Cancer Sci 97(9):813–820.  https://doi.org/10.1111/j.1349-7006.2006.00265.x CrossRefPubMedGoogle Scholar
  17. 17.
    Cortes J, Baselga J (2007) Targeting the microtubules in breast cancer beyond taxanes: the epothilones. Oncologist 12(3):271–280.  https://doi.org/10.1634/theoncologist.12-3-271 CrossRefPubMedGoogle Scholar
  18. 18.
    Bedard PL, Di Leo A, Piccart-Gebhart MJ (2010) Taxanes: optimizing adjuvant chemotherapy for early-stage breast cancer. Nat Rev Clin Oncol 7(1):22–36.  https://doi.org/10.1038/nrclinonc.2009.186 CrossRefPubMedGoogle Scholar
  19. 19.
    Hayes DF, Thor AD, Dressler LG, Weaver D, Edgerton S, Cowan D, Broadwater G, Goldstein LJ, Martino S, Ingle JN, Henderson IC, Norton L, Winer EP, Hudis CA, Ellis MJ, Berry DA, Cancer, Leukemia Group BI (2007) HER2 and response to paclitaxel in node-positive breast cancer. N Engl J Med 357(15):1496–1506.  https://doi.org/10.1056/NEJMoa071167 CrossRefPubMedGoogle Scholar
  20. 20.
    Ellis P, Barrett-Lee P, Johnson L, Cameron D, Wardley A, O’Reilly S, Verrill M, Smith I, Yarnold J, Coleman R, Earl H, Canney P, Twelves C, Poole C, Bloomfield D, Hopwood P, Johnston S, Dowsett M, Bartlett JM, Ellis I, Peckitt C, Hall E, Bliss JM, Group TTM, Trialists T (2009) Sequential docetaxel as adjuvant chemotherapy for early breast cancer (TACT): an open-label, phase III, randomised controlled trial. Lancet 373(9676):1681–1692.  https://doi.org/10.1016/S0140-6736(09)60740-6 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4(2):249–264CrossRefGoogle Scholar
  22. 22.
    Karn T, Metzler D, Ruckhaberle E, Hanker L, Gatje R, Solbach C, Ahr A, Schmidt M, Holtrich U, Kaufmann M, Rody A (2010) Data-driven derivation of cutoffs from a pool of 3030 Affymetrix arrays to stratify distinct clinical types of breast cancer. Breast Cancer Res Treat 120(3):567–579.  https://doi.org/10.1007/s10549-009-0416-z CrossRefPubMedGoogle Scholar
  23. 23.
    Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43):15545–15550.  https://doi.org/10.1073/pnas.0506580102 CrossRefPubMedGoogle Scholar
  24. 24.
    Cancer Genome Atlas N (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418):61–70.  https://doi.org/10.1038/nature11412 CrossRefGoogle Scholar
  25. 25.
    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 I, Borresen-Dale AL, Brenton JD, Tavare S, Caldas C, Aparicio S (2012) The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 486(7403):346–352.  https://doi.org/10.1038/nature10983 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Balamurugan K, Sterneck E (2013) The many faces of C/EBPdelta and their relevance for inflammation and cancer. Int J Biol Sci 9(9):917–933.  https://doi.org/10.7150/ijbs.7224 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Zucchi I, Mento E, Kuznetsov VA, Scotti M, Valsecchi V, Simionati B, Vicinanza E, Valle G, Pilotti S, Reinbold R, Vezzoni P, Albertini A, Dulbecco R (2004) Gene expression profiles of epithelial cells microscopically isolated from a breast-invasive ductal carcinoma and a nodal metastasis. Proc Natl Acad Sci USA 101(52):18147–18152.  https://doi.org/10.1073/pnas.0408260101 CrossRefPubMedGoogle Scholar
  28. 28.
    Palmieri C, Monteverde M, Lattanzio L, Gojis O, Rudraraju B, Fortunato M, Syed N, Thompson A, Garrone O, Merlano M, Lo Nigro C, Crook T (2012) Site-specific CpG methylation in the CCAAT/enhancer binding protein delta (CEBPdelta) CpG island in breast cancer is associated with metastatic relapse. Br J Cancer 107(4):732–738.  https://doi.org/10.1038/bjc.2012.308 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    King TD, Suto MJ, Li Y (2012) The Wnt/beta-catenin signaling pathway: a potential therapeutic target in the treatment of triple negative breast cancer. J Cell Biochem 113(1):13–18.  https://doi.org/10.1002/jcb.23350 CrossRefPubMedGoogle Scholar
  30. 30.
    Dey N, Barwick BG, Moreno CS, Ordanic-Kodani M, Chen Z, Oprea-Ilies G, Tang W, Catzavelos C, Kerstann KF, Sledge GW Jr, Abramovitz M, Bouzyk M, De P, Leyland-Jones BR (2013) Wnt signaling in triple negative breast cancer is associated with metastasis. BMC Cancer 13:537.  https://doi.org/10.1186/1471-2407-13-537 CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Bilir B, Kucuk O, Moreno CS (2013) Wnt signaling blockage inhibits cell proliferation and migration, and induces apoptosis in triple-negative breast cancer cells. J Transl Med 11:280.  https://doi.org/10.1186/1479-5876-11-280 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Koval AV, Vlasov P, Shichkova P, Khunderyakova S, Markov Y, Panchenko J, Volodina A, Kondrashov FA, Katanaev VL (2014) Anti-leprosy drug clofazimine inhibits growth of triple-negative breast cancer cells via inhibition of canonical Wnt signaling. Biochem Pharmacol 87(4):571–578.  https://doi.org/10.1016/j.bcp.2013.12.007 CrossRefPubMedGoogle Scholar
  33. 33.
    Ren J, Wang R, Song H, Huang G, Chen L (2014) Secreted frizzled related protein 1 modulates taxane resistance of human lung adenocarcinoma. Mol Med 20:164–178.  https://doi.org/10.2119/molmed.2013.00149 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Voloshanenko O, Erdmann G, Dubash TD, Augustin I, Metzig M, Moffa G, Hundsrucker C, Kerr G, Sandmann T, Anchang B, Demir K, Boehm C, Leible S, Ball CR, Glimm H, Spang R, Boutros M (2013) Wnt secretion is required to maintain high levels of Wnt activity in colon cancer cells. Nat Commun 4:2610.  https://doi.org/10.1038/ncomms3610 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Stewart J, James J, McCluggage GW, McQuaid S, Arthur K, Boyle D, Mullan P, McArt D, Yan B, Irwin G, Harkin DP, Zhengdeng L, Ong CW, Yu J, Virshup DM, Salto-Tellez M (2015) Analysis of wntless (WLS) expression in gastric, ovarian, and breast cancers reveals a strong association with HER2 overexpression. Mod Pathol 28(3):428–436.  https://doi.org/10.1038/modpathol.2014.114 CrossRefPubMedGoogle Scholar
  36. 36.
    Augustin I, Goidts V, Bongers A, Kerr G, Vollert G, Radlwimmer B, Hartmann C, Herold-Mende C, Reifenberger G, von Deimling A, Boutros M (2012) The Wnt secretion protein Evi/Gpr177 promotes glioma tumourigenesis. EMBO Mol Med 4(1):38–51.  https://doi.org/10.1002/emmm.201100186 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Lu D, Li Y, Liu QR, Wu Q, Zhang H, Xie P, Wang Q (2015) Wls promotes the proliferation of breast cancer cells via Wnt signaling. Med Oncol 32(5):140.  https://doi.org/10.1007/s12032-015-0585-z CrossRefPubMedGoogle Scholar
  38. 38.
    Chiou SS, Wang LT, Huang SB, Chai CY, Wang SN, Liao YM, Lin PC, Liu KY, Hsu SH (2014) Wntless (GPR177) expression correlates with poor prognosis in B-cell precursor acute lymphoblastic leukemia via Wnt signaling. Carcinogenesis 35(10):2357–2364.  https://doi.org/10.1093/carcin/bgu166 CrossRefPubMedGoogle Scholar
  39. 39.
    Yoon H, Blaber SI, Li W, Scarisbrick IA, Blaber M (2013) Activation profiles of human kallikrein-related peptidases by matrix metalloproteinases. Biol Chem 394(1):137–147.  https://doi.org/10.1515/hsz-2012-0249 CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Jeyaprakash AA, Santamaria A, Jayachandran U, Chan YW, Benda C, Nigg EA, Conti E (2012) Structural and functional organization of the Ska complex, a key component of the kinetochore-microtubule interface. Mol Cell 46(3):274–286.  https://doi.org/10.1016/j.molcel.2012.03.005 CrossRefPubMedGoogle Scholar
  41. 41.
    Chang YP, Wang G, Bermudez V, Hurwitz J, Chen XS (2007) Crystal structure of the GINS complex and functional insights into its role in DNA replication. Proc Natl Acad Sci USA 104(31):12685–12690.  https://doi.org/10.1073/pnas.0705558104 CrossRefPubMedGoogle Scholar
  42. 42.
    Zhang X, Zhong L, Liu BZ, Gao YJ, Gao YM, Hu XX (2013) Effect of GINS2 on proliferation and apoptosis in leukemic cell line. Int J Med Sci 10(12):1795–1804.  https://doi.org/10.7150/ijms.7025 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Kaufman PD, Kobayashi R, Kessler N, Stillman B (1995) The p150 and p60 subunits of chromatin assembly factor I: a molecular link between newly synthesized histones and DNA replication. Cell 81(7):1105–1114.  https://doi.org/10.1016/s0092-8674(05)80015-7 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Mascolo M, Ilardi G, Merolla F, Russo D, Vecchione ML, de Rosa G, Staibano S (2012) Tissue microarray-based evaluation of Chromatin Assembly Factor-1 (CAF-1)/p60 as tumour prognostic marker. Int J Mol Sci 13(9):11044–11062.  https://doi.org/10.3390/ijms130911044 CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Vieira AF, Schmitt F (2018) An update on breast cancer multigene prognostic tests-emergent clinical biomarkers. Front Med (Lausanne) 5:248.  https://doi.org/10.3389/fmed.2018.00248 CrossRefGoogle Scholar
  46. 46.
    Razek AA, Gaballa G, Denewer A, Nada N (2010) Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors. NMR Biomed 23(6):619–623.  https://doi.org/10.1002/nbm.1503 CrossRefPubMedGoogle Scholar
  47. 47.
    Inwald EC, Klinkhammer-Schalke M, Hofstadter F, Zeman F, Koller M, Gerstenhauer M, Ortmann O (2013) Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res Treat 139(2):539–552.  https://doi.org/10.1007/s10549-013-2560-8 CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Jatoi I, Hilsenbeck SG, Clark GM, Osborne CK (1999) Significance of axillary lymph node metastasis in primary breast cancer. J Clin Oncol 17(8):2334–2340.  https://doi.org/10.1200/JCO.1999.17.8.2334 CrossRefPubMedGoogle Scholar
  49. 49.
    Razek AA, Lattif MA, Denewer A, Farouk O, Nada N (2016) Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging. Breast Cancer 23(3):525–532.  https://doi.org/10.1007/s12282-015-0598-7 CrossRefPubMedGoogle Scholar
  50. 50.
    Lee JH, Kim SH, Suh YJ, Shim BY, Kim HK (2010) Predictors of axillary lymph node metastases (ALNM) in a Korean population with T1-2 breast carcinoma: triple negative breast cancer has a high incidence of ALNM irrespective of the tumor size. Cancer Res Treat 42(1):30–36.  https://doi.org/10.4143/crt.2010.42.1.30 CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Liu Z, Li Z, Qu J, Zhang R, Zhou X, Li L, Sun K, Tang Z, Jiang H, Li H, Xiong Q, Ding Y, Zhao X, Wang K, Liu Z, Tian J (2019) Radiomics of Multiparametric MRI for pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: a Multicenter Study. Clin Cancer Res 25(12):3538–3547.  https://doi.org/10.1158/1078-0432.CCR-18-3190 CrossRefPubMedGoogle Scholar
  52. 52.
    Zhang M, Horvat JV, Bernard-Davila B, Marino MA, Leithner D, Ochoa-Albiztegui RE, Helbich TH, Morris EA, Thakur S, Pinker K (2019) Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy. J Magn Reson Imaging 49(3):864–874.  https://doi.org/10.1002/jmri.26285 CrossRefPubMedGoogle Scholar
  53. 53.
    Abdel Razek AA, Gaballa G, Denewer A, Tawakol I (2010) Diffusion weighted MR imaging of the breast. Acad Radiol 17(3):382–386.  https://doi.org/10.1016/j.acra.2009.10.014 CrossRefPubMedGoogle Scholar
  54. 54.
    Abdel Razek AAK, Zaky M, Bayoumi D, Taman S, Abdelwahab K, Alghandour R (2019) Diffusion tensor imaging parameters in differentiation recurrent breast cancer from post-operative changes in patients with breast-conserving surgery. Eur J Radiol 111:76–80.  https://doi.org/10.1016/j.ejrad.2018.12.022 CrossRefPubMedGoogle Scholar
  55. 55.
    Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, Clark L, Bayani N, Coppe JP, Tong F, Speed T, Spellman PT, DeVries S, Lapuk A, Wang NJ, Kuo WL, Stilwell JL, Pinkel D, Albertson DG, Waldman FM, McCormick F, Dickson RB, Johnson MD, Lippman M, Ethier S, Gazdar A, Gray JW (2006) A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10(6):515–527.  https://doi.org/10.1016/j.ccr.2006.10.008 CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Chin K, DeVries S, Fridlyand J, Spellman PT, Roydasgupta R, Kuo WL, Lapuk A, Neve RM, Qian Z, Ryder T, Chen F, Feiler H, Tokuyasu T, Kingsley C, Dairkee S, Meng Z, Chew K, Pinkel D, Jain A, Ljung BM, Esserman L, Albertson DG, Waldman FM, Gray JW (2006) Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell 10(6):529–541.  https://doi.org/10.1016/j.ccr.2006.10.009 CrossRefGoogle Scholar
  57. 57.
    Wu K, Yang Q, Liu Y, Wu A, Yang Z (2014) Meta-analysis on the association between pathologic complete response and triple-negative breast cancer after neoadjuvant chemotherapy. World J Surg Oncol 12:95.  https://doi.org/10.1186/1477-7819-12-95 CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Kennedy RD, Quinn JE, Mullan PB, Johnston PG, Harkin DP (2004) The role of BRCA1 in the cellular response to chemotherapy. J Natl Cancer Inst 96(22):1659–1668.  https://doi.org/10.1093/jnci/djh312 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of SurgerySeoul National University Bundang Hospital, Seoul National University College of MedicineSeongnamRepublic of Korea
  2. 2.College of Pharmacy and Research Institute of Life and Pharmaceutical SciencesSunchon National UniversitySuncheonRepublic of Korea
  3. 3.Department of Surgical Oncology, Oncology CenterSheikh Khalifa Specialty HospitalRas Al-KhaimahUnited Arab Emirates
  4. 4.Department of Molecular Cell Biology, Samsung Medical Center and Samsung Genome InstituteSungkyunkwan University School of MedicineSeoulRepublic of Korea
  5. 5.Cancer Research InstituteSeoul National University College of MedicineSeoulRepublic of Korea
  6. 6.Department of SurgerySeoul National University Hospital, Seoul National University College of MedicineSeoulRepublic of Korea

Personalised recommendations