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Predictors of response to aromatase inhibitors

Helen Anderson1, Serdar Bulun, Ian Smith

  • 1Academic Department of Biochemistry, Royal Marsden Hospital, London SW3 6JJ, UK. helen.anderson@icr.ac.uk

The Journal of Steroid Biochemistry and Molecular Biology
|July 3, 2007
PubMed

Insights

Predicting response to aromatase inhibitors in breast cancer is crucial. Researchers are exploring biomarkers like estrogen receptor, progesterone receptor, and Ki67 to identify patients who will benefit most from this endocrine therapy.

Area of Science:

  • Oncology
  • Endocrinology
  • Pharmacology

Background:

  • Aromatase inhibitors are a cornerstone of endocrine therapy for hormone receptor-positive breast cancer in post-menopausal women.
  • Intrinsic resistance to aromatase inhibitors affects up to 50% of patients, necessitating the identification of predictive biomarkers.
  • Accurate prediction of response is essential for personalized treatment strategies and to offer alternative therapies to non-responders.

Purpose of the Study:

  • To review and elucidate the role of potential biomarkers in predicting response to aromatase inhibitors in breast cancer.
  • To assess the utility of conventional tumor markers (estrogen receptor, progesterone receptor) and proliferation markers (Ki67) in predicting treatment outcomes.
  • To explore the impact of HER-2 overexpression and gene expression profiling on aromatase inhibitor efficacy.

Main Methods:

  • Review of existing clinical data and studies on aromatase inhibitor treatment in breast cancer.
  • Analysis of the correlation between tumor markers (ER, PR, HER-2) and treatment response.
  • Evaluation of the predictive value of the proliferation marker Ki67 and gene expression analysis in response to neoadjuvant aromatase inhibitors.

Main Results:

  • Estrogen receptor and progesterone receptor show potential as response predictors, though their utility in the adjuvant setting requires further elucidation.
  • HER-2 overexpression does not appear to negatively impact response to aromatase inhibitors.
  • Ki67 levels significantly correlate with relapse-free survival, indicating its potential as a predictive marker for response.

Conclusions:

  • Identifying reliable predictors of response to aromatase inhibitors is critical for optimizing breast cancer treatment.
  • Ki67 and potentially dynamic markers of response, along with gene expression analysis, offer promising avenues for predicting treatment efficacy.
  • Further research is needed to fully establish the clinical utility of these markers, particularly in the adjuvant setting.

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