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Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
Published on: May 18, 2020
Predicting endocrine therapy responsiveness in breast cancer
Cynthia X Ma1, Cesar G Sanchez, Matthew J Ellis
1Section of Medical Oncology, Division of Oncology, Department of Internal Medicine, Siteman Comprehensive Cancer Center, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Oncology (Williston Park, N.Y.)
|March 28, 2009
Summary
Predicting breast cancer recurrence after endocrine therapy remains challenging. On-treatment tumor profiling, like the Preoperative Endocrine Prognostic Index (PEPI), shows promise in identifying patients likely to benefit from treatment.
Area of Science:
- Oncology
- Endocrinology
- Genomics
Background:
- Endocrine therapy is crucial for estrogen receptor (ER)-positive breast cancer but has limited efficacy in 40-50% of patients who relapse.
- Current predictors like ER and HER2 status need improvement, especially for ER-positive, HER2-negative disease.
- Genomic technologies offer risk stratification, but their predictive value for endocrine therapy response requires further investigation.
Purpose of the Study:
- To review progress in identifying predictors of endocrine therapy responsiveness in breast cancer.
- To discuss the utility of pre-treatment versus on-treatment tumor profiling for outcome prediction.
- To highlight the prognostic value of the Preoperative Endocrine Prognostic Index (PEPI).
Main Methods:
- Review of neoadjuvant endocrine therapy studies and genomic technology advancements.
- Analysis of the Preoperative Endocrine Prognostic Index (PEPI) based on tumor staging and biomarker expression (ER, Ki67).
- Comparison of pre-treatment and on-treatment tumor profiling strategies.
Main Results:
- Long-term follow-up of neoadjuvant endocrine therapy indicates in vivo efficacy assessment predicts outcomes.
- The PEPI score, derived from on-treatment measurements, reproducibly predicts long-term outcomes for hormone receptor-positive breast cancer.
- On-treatment profiling may offer superior predictive value compared to pre-treatment assessments.
Conclusions:
- Accurate prediction of endocrine therapy response is essential for optimizing breast cancer treatment.
- On-treatment tumor profiling, exemplified by PEPI, provides valuable prognostic information.
- Further research into predictive biomarkers is needed to improve outcomes for patients with ER-positive breast cancer.
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