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Mutation profiling identifies numerous rare drug targets and distinct mutation patterns in different clinical subtypes of breast cancers

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Abstract

The mutation pattern of breast cancer molecular subtypes is incompletely understood. The purpose of this study was to identify mutations in genes that may be targeted with currently available investigational drugs in the three major breast cancer subtypes (ER+/HER2−, HER2+, and Triple Negative). We extracted DNA from fine needle aspirations of 267 stage I–III breast cancers. These tumor specimens typically consisted of >80 % neoplastic cells. We examined 28 genes for 163 known cancer-related nucleic acid variations by Sequenom technology. We observed at least one mutation in 38 alleles corresponding to 15 genes in 108 (40 %) samples, including PIK3CA (16.1 % of all samples), FBXW7 (8 %), BRAF (3.0 %), EGFR (2.6 %), AKT1 and CTNNB1 (1.9 % each), KIT and KRAS (1.5 % each), and PDGFR-α (1.1 %). We also checked for the polymorphism in PHLPP2 that is known to activate AKT and it was found at 13.5 % of the patient samples. PIK3CA mutations were more frequent in estrogen receptor-positive cancers compared to triple negative breast cancer (TNBC) (19 vs. 8 %, p = 0.001). High frequency of PIK3CA mutations (28 %) were also found in HER2+ breast tumors. In TNBC, FBXW7 mutations were significantly more frequent compared to ER+ tumors (13 vs. 5 %, p = 0.037). We performed validation for all mutated alleles with allele-specific PCR or direct sequencing; alleles analyzed by two different sequencing techniques showed 95–100 % concordance for mutation status. In conclusion, different breast cancer subtypes harbor different type of mutations and approximately 40 % of tumors contained individually rare mutations in signaling pathways that can be potentially targeted with drugs. Simultaneous testing of many different mutations in a single needle biopsy is feasible and allows the design of prospective clinical trials that could test the functional importance of these mutations in the future.

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Acknowledgments

This study was supported by Grants from Associazione Italiana per la Ricerca sul Cancro (AIRC–Grant 6251) e Foundation Sandro Pitigliani (LS) and the Safeway Foundation and the Breast Cancer Research Foundation (WFS and LP), National Cancer Institute 1K23CA121994-01 (AMG), Susan G. Komen Foundation KGKG081099 (AMG, KSH).

Author Contributions

LP and LS designed the study, oversaw all of its conduct, and finalized the manuscript. LS and YQ carried out the analysis of data and performed statistical analysis, LS drafted the manuscript; BW and KS-H performed molecular studies on specimens. DJH, FAH, JO’Sm GH, JP, TV, HG, VV, GNH, AMG accrued patients to the study, made biopsy materials available for molecular analyis and provided clinical input. EJY maintained the clinical data base. WFS obtained many of the cancer biopsies for this study. ADL participated in the design and provided intellectual input into interpretation of results. GB provided intellectual input into interpretation of results. All authors have read and approved the final version.

Conflict of interest

The authors declare no conflicting or competing commercial interests.

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Authors and Affiliations

  1. Department of Oncology, Translational Research Unit, Hospital of Prato and Istituto Toscano Tumori, 59100, Prato, Italy

    Libero Santarpia, Giulia Bottai & Angelo Di Leo

  2. Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77230-1439, USA

    Libero Santarpia & W. Fraser Symmans

  3. Department of Breast Medical Oncology, Unit 1354, The University of Texas MD Anderson Cancer Center, PO Box 301439, Houston, TX, 77230-1439, USA

    Libero Santarpia, Bailiang Wang, Elliana J. Young, Daniel J. Booser, Vicente Valero, Gabriel N. Hortobagyi, Ana M. Gonzalez-Angulo & Lajos Pusztai

  4. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77230-1439, USA

    Yuan Qi

  5. Department of System Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77230-1439, USA

    Katherine Stemke-Hale & Ana M. Gonzalez-Angulo

  6. Texas Oncology/US Oncology, Houston, TX, 75246, USA

    Frankie A. Holmes, Joyce O’Shaughnessy & John Pippen

  7. Baylor Sammons Cancer Center, Texas Oncology, US Oncology, Dallas, TX, 75246, USA

    Joyce O’Shaughnessy & John Pippen

  8. Department of Oncological Medicine, Instituto Nacional de Enfermedades Neoplasicas, Lima 34, Peru

    Tatiana Vidaurre & Henry Gomez

  9. Texas Oncology/US Oncology, Austin, TX, 78745, USA

    Beth Hellerstedt

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  1. Libero Santarpia
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  2. Yuan Qi
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  3. Katherine Stemke-Hale
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  6. Daniel J. Booser
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  7. Frankie A. Holmes
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  8. Joyce O’Shaughnessy
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  9. Beth Hellerstedt
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  10. John Pippen
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  11. Tatiana Vidaurre
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  12. Henry Gomez
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  13. Vicente Valero
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  14. Gabriel N. Hortobagyi
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  15. W. Fraser Symmans
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  16. Giulia Bottai
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  17. Angelo Di Leo
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  18. Ana M. Gonzalez-Angulo
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  19. Lajos Pusztai
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Correspondence to Libero Santarpia or Lajos Pusztai.

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Santarpia, L., Qi, Y., Stemke-Hale, K. et al. Mutation profiling identifies numerous rare drug targets and distinct mutation patterns in different clinical subtypes of breast cancers. Breast Cancer Res Treat 134, 333–343 (2012). https://doi.org/10.1007/s10549-012-2035-3

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  • DOI: https://doi.org/10.1007/s10549-012-2035-3

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