Annals of Surgical Oncology

, Volume 21, Issue 10, pp 3216–3222 | Cite as

Initial Experience with Genomic Profiling of Heavily Pretreated Breast Cancers

  • Edgar D. Staren
  • Donald Braun
  • Bradford Tan
  • Digant Gupta
  • Seungchan Kim
  • Kim Kramer
  • Maurie Markman
Breast Oncology



Rapidly evolving advances in the understanding of theorized unique driver mutations within individual patient’s cancers, as well as dramatic reduction in the cost of genomic profiling, have stimulated major interest in the role of such testing in routine clinical practice. The aim of this study was to report our initial experience with genomic testing in heavily pretreated breast cancer patients.


Patients with primary or recurrent breast cancer managed at any of our five hospitals and whose malignancy had failed to respond to therapy or had progressed on all recognized standard-of-care options were offered the opportunity to have their cancer undergo next-generation sequencing genomic profiling.


Of a total of 101 patients, 98 (97 %) had at least one specific genomic alteration identified. A total of 465 different somatic genetic abnormalities were revealed in this group of patients. Although 52 % of patients were found to have an abnormality for which an U.S. Food and Drug Administration (FDA)-approved drug was available, 69 % of patients had an FDA-approved agent for an indication other than breast cancer. The most common genomic alterations of potential clinical consequence were PIK3 (25 %), FGFR1 (16 %), AKT (11 %), PTEN (10 %), ERBB2 (8 %), JAK2 (6 %), and RAF1 (5 %).


Almost all advanced breast cancers possess at least one well-characterized genomic alteration that might be actionable at the clinical level. Further, in most cases, a plausible argument can be advanced for the potential biological and clinical relevance of an FDA-approved antineoplastic agent not currently indicated in the treatment of breast cancer.


Breast Cancer Trastuzumab PIK3CA Mutation Genomic Alteration Pertuzumab 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Supported in part by Cancer Treatment Centers of America®.


The authors declare no conflict of interest.


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Copyright information

© Society of Surgical Oncology 2014

Authors and Affiliations

  • Edgar D. Staren
    • 1
    • 2
  • Donald Braun
    • 1
  • Bradford Tan
    • 1
  • Digant Gupta
    • 1
  • Seungchan Kim
    • 2
  • Kim Kramer
    • 1
  • Maurie Markman
    • 1
  1. 1.Cancer Treatment Centers of America® (CTCA)GoodyearUSA
  2. 2.The Translational Genomics Research Institute (TGen)PhoenixUSA

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