Dr Kalinsky on Unanswered Questions Regarding Genomic Testing in HR+ Breast Cancer

Kevin Kalinsky, MD, MS, associate professor, Department of Hematology and Medical Oncology, Emory University School of Medicine, director, the Glenn Family Breast Center, Breast Medical Oncology, Louisa and Rand Glenn Family Chair in Breast Cancer Research, Winship Cancer Institute of Emory University, discusses remaining questions regarding the utility and implementation of genomic testing approaches in patients with early-stage hormone receptor (HR)–positive breast cancer.

The use of genomic assays in guiding treatment decisions for patients with HR-positive, HER2-negative breast cancer presents several ongoing challenges, particularly in pre-menopausal patients and those with more than 3 involved lymph nodes, Kalinsky begins.

In node-negative disease, the benefit of chemotherapy in this patient population is not yet confirmed, he says. Uncertainty exists regarding whether the observed benefits stem from direct tumor biology differences between pre-menopausal and post-menopausal patients or from the induction of menopause by chemotherapy, Kalinsky explains. This raises questions surrounding the applicability of genomic assays, which are often developed and validated in post-menopausal populations, to pre-menopausal patients. Moreover, the role of genomic assays in guiding treatment decisions for patients with more than 3 involved lymph nodes remains unclear due to the limited prospective data available, Kalinsky adds.

Globally, disparities in access to genomic assays pose challenges to equitable cancer care, Kalinsky continues. Not all countries have equal access to these assays, leading to discrepancies in treatment decision-making and outcomes across different regions and populations, he says.

Addressing these challenges requires efforts to standardize the use of genomic assays and ensure equitable access to these technologies worldwide, Kalinsky states. He identifies the utilization of artificial intelligence (AI) as 1 potential solution to standardize and optimize genomic assay approaches. AI-driven algorithms can analyze large datasets and identify patterns in tumor biology, helping to tailor treatment decisions based on individual patient characteristics more effectively, he explains.

Overall, genomic assays hold promise in guiding treatment decisions for HR-positive, HER2-negative breast cancer, but controversies and challenges remain. Standardizing genomic assay approaches and addressing global disparities in access to these technologies are essential steps toward improving the effectiveness and equity of breast cancer care, Kalinsky concludes.