Advances in translational research
The ABCSG is also achieving important successes in translational research, particularly through the validation and development of innovative biomarker tests. The identification of specific molecular profiles and the use of advanced (genetic) tests are crucial for individualized therapy decisions and risk assessment in cancer patients.
A notable example is the genetic-based OncoMasTR test, which was validated in collaboration with the ABCSG and Martin Filipits’ research group using data from ABCSG 8 trial. This test enables the classification of breast cancer patients into distinct risk groups, which is essential for determining optimal therapy. It allows clinicians to distinguish between patients with a high risk of recurrence and those with a low risk, which is critical for prognosis and selecting an appropriate treatment strategy.
The results of this translational data analysis were published in “Clinical Cancer Research” in November 2021.
The OncoMasTR Test Predicts Distant Recurrence in Estrogen Receptor-Positive, HER2-Negative Early-Stage Breast Cancer: A Validation Study in ABCSG Trial 8
Filipits et al.
Clin Cancer Res 2021 Nov 1;27(21):5931-5938.
DOI: 10.1158/1078-0432.CCR-21-1023.
Another key project involved the development and validation of the EndoPredict test, also in collaboration with the ABCSG, using study data and samples from ABCSG 6 and ABCSG 8. EndoPredict was designed to accurately assess the individual cancer biology, thereby predicting the risk of breast cancer recurrence.
In a comprehensive follow-up study with extended data collection, it was reaffirmed that EndoPredict provides a precise genetic signature that reliably predicts the risk of recurrence, even in the long term. These accurate predictions facilitate personalized therapy design and help identify patients for whom chemotherapy or prolonged endocrine therapy may be unnecessary. This not only improves patients’ quality of life but also reduces the strain on the healthcare system.
The results of this translational data analysis were published in “Clinical Cancer Research” in May 2019.
Prediction of Distant Recurrence Using EndoPredict Among Women with ERþ, HER2Node-Positive and Node-Negative Breast Cancer Treated with Endocrine Therapy Only
Filipits et al.
Clin Cancer Res 2019 Jul 1;25(13):3865-3872.
DOI 10.1158/1078-0432.CCR-19-0376.
These successes highlight the ABCSG’s leadership in translational research and underscore the importance of collaboration with industry partners and international research groups in developing patient-centered solutions.
Using sample material from the ABCSG 6 study, mRNA expression levels of the genes ESR1, PGR, ERBB2, and MKi67 were measured in postmenopausal women with hormone receptor-positive early breast cancer. The aim was to compare these genetic parameters with the results from standard immunohistochemical (IHC) analyses.
Immunohistochemistry (IHC) is currently the clinical gold standard for evaluating the expression of ER, PR, HER2, and Ki67—key parameters that guide therapeutic decisions in breast cancer. However, mRNA expression analysis may offer an alternative method for assessing these biomarkers.
The study results demonstrate that mRNA expression levels of ESR1, PGR, ERBB2, and MKi67 align with IHC analysis data. This indicates that genetic expression data from mRNA analyses reliably reflect the outcomes of immunohistochemistry.
Notably, mRNA expression of MKi67, a marker of cell proliferation, shows promise as a predictor of disease progression and response to therapy.
The STRAT4 test used in the study, which can be completed in less than two hours, has proven to be a promising new diagnostic tool for clinical practice. STRAT4 may also offer a cost-effective alternative for obtaining standardized diagnostic results for breast cancer patients.
ESR1, PGR, ERBB2, and MKi67 mRNA expression in postmenopausal women with hormone receptor-positive early breast cancer: results from ABCSG Trial 6
M. Filipits et al.
DOI: 10.1016/j.esmoop.2021.100228
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