Interesting Research in the Endometrial Cancer Space

Casey M. Cosgrove, MD, an assistant professor in the Department of Gynecologic Oncology at The Ohio State University College of Medicine in Columbus, discusses research exploring precision medicine concepts for endometrial cancer treatment.

Cosgrove notes that the Proactive Molecular Risk Classifier for Endometrial Cancer System (ProMisE) is directly impacting treatment decision-making among oncologists who treat endometrial cancer.

TRANSCRIPT:

0:08 | There are several ongoing clinical trials…that are trying to refine the way we take care of a patient with endometrial cancer. What I hope we can see through all these clinical trials is that we have some easily applied clinical markers that are going to directly impact our decision-making. The ProMisE [Proactive Molecular Risk Classifier for Endometrial Cancer system] from the University of British Columbia, which establishes endometrial cancer into 4…molecular groups, has the most traction right now throughout the gynecologic oncology community.1 This is testing for dMMR, POLE mutations, as well as p53 [positivity], and grouping endometrial cancers into 1 of 4 groups.

0:52 | Depending on which group [patients] fall into, the next question is, what’s the best treatment for those individuals? This has been evaluated through several trials right now. There’s a lot of excitement that hopefully we’ll be getting some answers in the next couple of years. I think the endometrial cancer [setting] has a lot of opportunity for growth in patient care. And [we] as clinicians are going to have to start integrating a lot of this information quickly as it becomes more available. With the improvements in technology, we’re going to be getting more information for each cancer type…than we’ve ever had before. I can see assimilating that information into the clinical setting as a major barrier for patients and clinicians. But hopefully, we’ll have some standardized protocols that allow us to have the right way to take care of each individual patient.