Advertisement

Breast Cancer Research and Treatment

, Volume 170, Issue 2, pp 351–360 | Cite as

Mutational analysis of triple-negative breast cancers within the International Breast Cancer Study Group (IBCSG) Trial 22-00

  • Elisabetta Munzone
  • Kathryn P. Gray
  • Caterina Fumagalli
  • Elena Guerini-Rocco
  • István Láng
  • Thomas Ruhstaller
  • Lorenzo Gianni
  • Roswitha Kammler
  • Giuseppe Viale
  • Angelo Di Leo
  • Alan S. Coates
  • Richard D. Gelber
  • Meredith M. Regan
  • Aron Goldhirsch
  • Massimo Barberis
  • Marco Colleoni
Clinical trial

Abstract

Purpose

We investigated the occurrence and the prognostic and predictive relationship of a selected number of somatic mutations in triple-negative breast cancer (TNBC) patients having known clinical outcomes treated within the IBCSG Trial 22-00.

Methods

A matched case–control sampling selected patients enrolled in the IBCSG Trial 22-00 who had TNBC tumors, based on local assessment. Cases had invasive breast cancer recurrence (at local, regional, or distant site) according to the protocol definition. Matched controls had not recurred. Mutational analysis was performed with OncoCarta panel v1.0 using Mass Array System. The panel includes 19 genes belonging to different functional pathways as PI3K pathway, receptor tyrosine kinase, and cell cycle-metabolic group. Conditional logistic regression assessed the association of mutation status with breast cancer recurrence.

Results

Mutation assessment was successful for 135 patients (49 cases, 86 controls). A total of 37 (27.4%) of the 135 patients had at least one mutation in the selected genes. PIK3CA was the most common mutated gene (18/135; 13.3%), followed by BRAF, KIT and PDGFRA (each 4/135, 3.0%) and AKT1 (3/135; 2.2%). TNBC patients with at least one mutation had increased odds of recurrence compared with those with wild-type tumors (odds ratio (OR) 2.28; 95% CI 0.88–5.92), though this difference was not statistically significant (p = 0.09). We found no evidence that these mutations were predictive for the value of maintenance metronomic chemotherapy.

Conclusions

Mutations in the tested oncogenes were not associated with breast cancer recurrence in this TNBC subset of patients. The question of whether any of these mutated genes (e.g., PIK3CA) may represent a useful therapeutic target in TNBC may be answered by ongoing clinical trials and/or larger dataset analysis.

Keywords

Triple-negative breast cancer Somatic mutation PIK3CA Mass array system Prognosis 

Notes

Acknowledgements

We thank the patients, physicians, nurses, and data managers who participated in the International Breast Cancer Study Group (IBCSG) Trial 22-00, which was supported by the IBCSG and participating centers. Support for Trial 22-00 central coordination, data management and statistics was provided by the Swedish Cancer League; The Cancer Council Australia; Australia & New Zealand Breast Cancer Trials Group; the Frontier Science and Technology Research Foundation; the Swiss Group for Clinical Cancer Research; the Swiss Cancer League/Oncosuisse. Funding for this study was provided by Italian Ministry of Health, Ricerca Finalizzata, RF-2009-1536545.

Compliance with ethical standards

Conflicts of interest

The authors declare no conflict of interest related to this study.

References

  1. 1.
    Sotiriou C, Pusztai L (2009) Gene-expression signatures in breast cancer. N Engl J Med 360(8):790–800.  https://doi.org/10.1056/NEJMra0801289 CrossRefPubMedGoogle Scholar
  2. 2.
    Coates AS, Winer EP, Goldhirsch A et al (2015) Tailoring therapies—improving the management of early breast cancer: St Gallen international expert consensus on the primary therapy of early breast cancer 2015. Ann Oncol 26(8):1533–1546.  https://doi.org/10.1093/annonc/mdv221 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Carey L, Winer E, Viale G, Cameron D, Gianni L (2010) Triple-negative breast cancer: disease entity or title of convenience? Nat Rev Clin Oncol 7(12):683–692.  https://doi.org/10.1038/nrclinonc.2010.154 CrossRefPubMedGoogle Scholar
  4. 4.
    Guiu S, Michiels S, André F et al (2012) Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 working group statement. Ann Oncol 23:2997–3006.  https://doi.org/10.1093/annonc/mds586 CrossRefPubMedGoogle Scholar
  5. 5.
    Haffty BG, Yang Q, Reiss M et al (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 CrossRefPubMedGoogle Scholar
  6. 6.
    Dent R, Trudeau M, Pritchard KI et al (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
  7. 7.
    Gluz O, Liedtke C, Gottschalk N, Pusztai L, Nitz U, Harbeck N (2009) Triple-negative breast cancer–current status and future directions. Ann Oncol 20(12):1913–1927.  https://doi.org/10.1093/annonc/mdp492 CrossRefPubMedGoogle Scholar
  8. 8.
    Prat A, Perou CM (2011) Deconstructing the molecular portraits of breast cancer. Mol Oncol 5(1):5–23.  https://doi.org/10.1016/j.molonc.2010.11.003 CrossRefPubMedGoogle Scholar
  9. 9.
    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(7):2750–2767.  https://doi.org/10.1172/JCI45014 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Burstein MD, Tsimelzon A, Poage GM et al (2015) Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin Cancer Res 21(7):1688–1698.  https://doi.org/10.1158/1078-0432.CCR-14-0432 CrossRefPubMedGoogle Scholar
  11. 11.
    Curtis C, Shah SP, Chin S-F et al (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486(7403):346–352.  https://doi.org/10.1038/nature10983 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Shah SP, Roth A, Goya R et al (2012) The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 486(7403):395–399.  https://doi.org/10.1038/nature10933 CrossRefPubMedGoogle Scholar
  13. 13.
    Stephens PJ, Tarpey PS, Davies H et al (2012) The landscape of cancer genes and mutational processes in breast cancer. Nature 486(7403):400–404.  https://doi.org/10.1038/nature11017 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kalimutho M, Parsons K, Mittal D, López JA, Srihari S, Khanna KK (2015) Targeted therapies for triple-negative breast cancer: combating a stubborn disease. Trends Pharmacol Sci 36(12):822–846.  https://doi.org/10.1016/j.tips.2015.08.009 CrossRefPubMedGoogle Scholar
  15. 15.
    Jurinke C, Oeth P, van den Boom D (2004) MALDI-TOF mass spectrometry: a versatile tool for high-performance DNA analysis. Mol Biotechnol 26(2):147–164.  https://doi.org/10.1385/MB:26:2:147 CrossRefPubMedGoogle Scholar
  16. 16.
    Colleoni M, Gray KP, Gelber S et al (2016) Low-dose oral cyclophosphamide and methotrexate maintenance for hormone receptor-negative early breast cancer: International Breast Cancer Study Group Trial 22-00. J Clin Oncol.  https://doi.org/10.1200/JCO.2015.65.6595 Google Scholar
  17. 17.
    Dupont WD. (1988) Power calculations for matched case-control studies. Biometrics. 44(4):1157–1168. http://www.ncbi.nlm.nih.gov/pubmed/3233252
  18. 18.
    Santarpia L, Qi Y, Stemke-Hale K et al (2012) Mutation profiling identifies numerous rare drug targets and distinct mutation patterns in different clinical subtypes of breast cancers. Breast Cancer Res Treat 134(1):333–343.  https://doi.org/10.1007/s10549-012-2035-3 CrossRefPubMedGoogle Scholar
  19. 19.
    Nowell PC. (1976) The clonal evolution of tumor cell populations. Science. 194(4260):23–28. http://www.ncbi.nlm.nih.gov/pubmed/959840
  20. 20.
    Stemke-Hale K, Gonzalez-Angulo AM, Lluch A et al (2008) An integrative genomic and proteomic analysis of PIK3CA, PTEN, and AKT mutations in breast cancer. Cancer Res 68(15):6084–6091.  https://doi.org/10.1158/0008-5472.CAN-07-6854 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Millis SZ, Gatalica Z, Winkler J et al (2015) Predictive biomarker profiling of < 6000 breast cancer patients shows heterogeneity in TNBC, with treatment implications. Clin Breast Cancer. 15(6):473–481.  https://doi.org/10.1016/j.clbc.2015.04.008 CrossRefPubMedGoogle Scholar
  22. 22.
    Zhu Y, Wang Y, Guan B, et al. (2014) C-kit and PDGFRA gene mutations in triple negative breast cancer. Int J Clin Exp Pathol. 7(7):4280–4285. http://www.ncbi.nlm.nih.gov/pubmed/25120810
  23. 23.
    Network Cancer Genome Atlas (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418):61–70.  https://doi.org/10.1038/nature11412 CrossRefGoogle Scholar
  24. 24.
    Fouqué A, Jean M, van de Weghe P, Legembre P. (2016) Review of PI3K/mTOR inhibitors entering clinical trials to treat triple negative breast cancers. Recent Pat Anticancer Drug Discov. http://www.ncbi.nlm.nih.gov/pubmed/27194555
  25. 25.
    Massihnia D, Galvano A, Fanale D et al (2016) Triple negative breast cancer: shedding light onto the role of pi3k/akt/mtor pathway. Oncotarget 5:60712Google Scholar
  26. 26.
    Pang B, Cheng S, Sun S-P et al (2014) Prognostic role of PIK3CA mutations and their association with hormone receptor expression in breast cancer: a meta-analysis. Sci Rep 4:6255.  https://doi.org/10.1038/srep06255 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Takeshita T, Yamamoto Y, Yamamoto-Ibusuki M et al (2015) Prognostic role of PIK3CA mutations of cell-free DNA in early-stage triple negative breast cancer. Cancer Sci 106(11):1582–1589.  https://doi.org/10.1111/cas.12813 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Kurose K, Ohue Y, Wada H et al (2015) Phase Ia study of FoxP3 + CD4 treg depletion by infusion of a humanized Anti-CCR4 antibody, KW-0761, in Cancer Patients. Clin Cancer Res 21(19):4327–4336.  https://doi.org/10.1158/1078-0432.CCR-15-0357 CrossRefPubMedGoogle Scholar
  29. 29.
    Sobhani N, Roviello G, Corona SP et al (2018) The prognostic value of PI3 K mutational status in breast cancer: a meta-analysis. J Cell Biochem.  https://doi.org/10.1002/jcb.26687 PubMedPubMedCentralGoogle Scholar
  30. 30.
    Pang B, Cheng S, Sun SP et al (2014) Prognostic role of PIK3CA mutations and their association with hormone receptor expression in breast cancer: a meta-analysis. Sci Rep. 1(4):6255.  https://doi.org/10.1038/srep06255 Google Scholar
  31. 31.
    Kim J-Y, Park K, Jung HH et al (2016) Association between mutation and expression of TP53 as a potential prognostic marker of triple-negative breast cancer. Cancer Res Treat.  https://doi.org/10.4143/crt.2015.430 Google Scholar
  32. 32.
    André F, Bachelot T, Commo F et al (2014) Comparative genomic hybridisation array and DNA sequencing to direct treatment of metastatic breast cancer: a multicentre, prospective trial (SAFIR01/UNICANCER). Lancet Oncol 15(3):267–274.  https://doi.org/10.1016/S1470-2045(13)70611-9 CrossRefPubMedGoogle Scholar
  33. 33.
    Ellard SL, Clemons M, Gelmon KA et al (2009) Randomized phase II study comparing two schedules of everolimus in patients with recurrent/metastatic breast cancer: nCIC Clinical Trials Group IND.163. J Clin Oncol 27(27):4536–4541.  https://doi.org/10.1200/JCO.2008.21.3033 CrossRefPubMedGoogle Scholar
  34. 34.
    Cortes J, O’Shaughnessy J, Loesch D et al (2011) Eribulin monotherapy versus treatment of physician’s choice in patients with metastatic breast cancer (EMBRACE): a phase 3 open-label randomised study. Lancet 377(9769):914–923.  https://doi.org/10.1016/S0140-6736(11)60070-6 CrossRefPubMedGoogle Scholar
  35. 35.
    de Dueñas EM, Hernández AL, Zotano AG et al (2014) Prospective evaluation of the conversion rate in the receptor status between primary breast cancer and metastasis: results from the GEICAM 2009-03 ConvertHER study. Breast Cancer Res Treat 143(3):507–515CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Maetens M, Brown D, Irrthum A et al (2017) The AURORA pilot study for molecular screening of patients with advanced breast cancer-a study of the breast international group. NPJ Breast Cancer. 29(3):23.  https://doi.org/10.1038/s41523-017-0026-6 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Elisabetta Munzone
    • 1
  • Kathryn P. Gray
    • 2
  • Caterina Fumagalli
    • 3
  • Elena Guerini-Rocco
    • 4
  • István Láng
    • 5
  • Thomas Ruhstaller
    • 6
  • Lorenzo Gianni
    • 7
  • Roswitha Kammler
    • 8
  • Giuseppe Viale
    • 9
  • Angelo Di Leo
    • 10
  • Alan S. Coates
    • 11
  • Richard D. Gelber
    • 12
  • Meredith M. Regan
    • 13
  • Aron Goldhirsch
    • 14
  • Massimo Barberis
    • 15
  • Marco Colleoni
    • 16
  1. 1.Division of Medical SenologyEuropean Institute of OncologyMilanItaly
  2. 2.International Breast Cancer Study Group Statistical CenterDana-Farber Cancer Institute, and Harvard T.H Chan School of Public HealthBostonUSA
  3. 3.Division of Pathology and Laboratory MedicineEuropean Institute of OncologyMilanItaly
  4. 4.Division of Pathology and Laboratory Medicine, Department of Oncology and Hemato-oncologyEuropean Institute of Oncology and University of MilanMilanItaly
  5. 5.National Institute of OncologyBudapestHungary
  6. 6.Breast Center St. Gallen, Switzerland, Swiss Group for Clinical Cancer Research (SAKK)BernSwitzerland
  7. 7.Divisione di Oncologia, Ospedale degli Infermi, Rimini, Dipartimento di Oncologia ed EmatologiaAUSL della RomagnaRiminiItaly
  8. 8.Translational Research Coordination and Central Pathology OfficeInternational Breast Cancer Study Group Coordinating CenterBernSwitzerland
  9. 9.Division of Pathology and Laboratory MedicineEuropean Institute of Oncology, University of Milan and International Breast Cancer Study Group Central Pathology OfficeMilanItaly
  10. 10.Hospital of Prato-AUSL Toscana Centro, Istituto Toscano Tumori, and International Breast Cancer Study GroupPratoItaly
  11. 11.International Breast Cancer Study Group and University of SydneySydneyAustralia
  12. 12.International Breast Cancer Study Group Statistical CenterDana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Harvard Medical School and Frontier Science & Technology Research FoundationBostonUSA
  13. 13.International Breast Cancer Study Group Statistical CenterDana-Farber Cancer Institute and Harvard Medical SchoolBostonUSA
  14. 14.Scientific & Clinical Evaluation BoardEuropean Institute of Oncology and International Breast Cancer Study GroupMilanItaly
  15. 15.Division of Pathology and Laboratory MedicineEuropean Institute of Oncology and University of MilanMilanItaly
  16. 16.Division of Medical SenologyEuropean Institute of Oncology, and International Breast Cancer Study GroupMilanItaly

Personalised recommendations