10 Oct Breast Cancer: Gene Expression of Receptors on a Chip Can Enhance Precision Diagnosis

MedicalResearch.com Interview with:
Univ.- Prof. Dr. Wolfgang Schreiner
Section Biosimulation and Bioinformatics
Center for Medical Statistics, Informatics, and Intelligent Systems
Medical University of Vienna
General Hospital
WIEN / AUSTRIA

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: The choice of correct individualized therapy for breast cancer depends on correct diagnosis: receptors for estrogen, progesterone and HER2 are determined routinely. However 5-10% of these routine diagnostics are inaccurate and may entail suboptimal therapy.

We have paved the way for additional diagnostics from gene expression data so as to increase precision of diagnostics.

MedicalResearch.com: What should readers take away from your report?

Response: Classical diagnostics used as gold standard may be enriched by information from genome data. Cutting edge mathematical methods allow to combine the outcome of gold standard with additional information: results are either confirmed, or rendered to be rechecked, in both cases enhancing patient safety towards precision medicine.

MedicalResearch.com: What recommendations do you have for future research as a result of this work?

Response: We have considered just two genes for each receptor. Many more genome data items would lend themselves to be included in the future – calling for a rigid mathematical model for doing so. This we have provided.

MedicalResearch.com: Is there anything else you would like to add?

Response: Many cutting edge mathematical methods have been developed within the technical sciences. In a most efficient way this can be transferred into the medical field with extraordinary benefit for patient welfare. Our informatics department tries to foster such initiatives in close cooperation with clinical partners.

Citation:

Breast Cancer Res Treat. 2018 Aug 16. doi: 10.1007/s10549-018-4920-x. [Epub ahead of print]

Co-expressed genes enhance precision of receptor status identification in breast cancer patients.

Kenn M¹, Cacsire Castillo-Tong D², Singer CF², Cibena M¹, Kölbl H³, Schreiner W⁴.

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Last Updated on October 10, 2018 by Marie Benz MD FAAD