Skip to main content
Conference Coverage

Static and Dynamic Biomarkers to Optimize Adjuvant Therapy in Luminal Early Breast Cancer

Featuring Oleg Gluz, MD

 

Oleg Gluz, MD, Evangelical Bethesda Hospital, Breast Center Niederrhein, Mönchengladbach, Germany, discusses results from the prospective WSG-ADAPT HR+/HER- trial where static and dynamic biomarkers were combined to optimize adjuvant therapy in luminal early breast cancer.

Results showed that use of recurrence score in combination with other clinical and genetic factors is effective and improves prognostic ability. Additionally, Dr Gluz noted these results showed worse prognosis for patients with invasive lobular high-risk breast cancer that is associated with distinct biological features.

Dr Gluz presented these results at the 2023 ESMO Congress in Madrid, Spain.

Transcript:

Hi everybody, my name is Oleg Gluz, I’m a Chief Physician at the Breast Center Niederrhein in Mönchengladbach in Germany and one of Scientific Coordinators of the West German Study Group. Here at ESMO 2023 it’s our pleasure to present the data from the ADAPT trial, here at the meeting.

The whole trial was focused on patients with intermediate to high-risk hormone receptor-positive, HER2-negative, early breast cancer. We applied some complicated approach for risk definition because we looked on the Oncotype DX, the core biopsy, and on the endocrine response after 3 weeks of standard endocrine treatment before the surgery to combine risk assessment for patients and to select patients to standard chemotherapy or to endocrine therapy.

One very important finding of the study presented also a couple of years ago and published in the meantime in the Journal of Clinical Oncology is that we have looked at patients with intermediate risk disease by Oncotype DX and have shown that patients with combination of onco-low or intermediate Oncotype DX and excellent response to endocrine treatment had excellent survival after 5 years, irrespective of the menopausal status without chemotherapy. This was one clinical finding of the study presented already a couple of years ago, and the focus of the talk at ESMO is that we have looked on the whole study, so on patients treated by endocrine therapy and patients treated by chemotherapy, in case of higher clinical or genomic risk, and we have looked on the prognostic score based on different features. For example, tumor size, nodule status, expression of progesterone receptor, histology data, and then we have looked with machine learning methods, we're able to predict outcome in the multi-variable way.

In the patients with high-risk disease for the first time, we were able in fact, to build different prognostic groups based on tumor stage, nodule status, expression of progesterone receptor—these are factors which are already known, but one finding was new. We have shown that patients with invasive global histology and high genomic risk, this is a relatively small group of patients, about 7% but the rest are still there, and these patients appear to have increased risk for relapse, irrespective of chemotherapy in case of high risk.

To summarize, it's very important in the clinical practice to combine all the factors together: stage of patients, expression of progesterone receptor, recurrent scores, genomic profile, and also histology data to have a more precise risk prediction for our patients with early hormone receptor-positive, HER2-negative disease.


Source:

Gluz O, Christgen M, Eulenburg CZ, et al. Multiparametric prognostic score in early HR+/HER2- breast cancer: Impact of recurrence score, clinical-pathological factors, gene mutations and histology. Presented at 2023 ESMO Annual Congress; October 20-24, 2023; Madrid, Spain. Abstract LBA24.

© 2023 HMP Global. All Rights Reserved.
Any views and opinions expressed are those of the author(s) and/or participants and do not necessarily reflect the views, policy, or position of Oncology Learning Network or HMP Global, their employees, and affiliates.