IGCS 2022 Master Session: Uterine Cancer - Management of Endometrial Cancer in The Molecular Era-Master Session: Uterine

Video Transcription

Video Summary

The first summary discusses the development of AI algorithms to analyze histopathology slides for molecular subtype classification. These algorithms can eliminate the need for expensive molecular testing and could be useful in low-resource settings. Liquid biopsy approaches, which involve analyzing blood biomarkers, are also being explored as a less invasive method for molecular classification. The challenges of cost and accessibility need to be addressed, but algorithm-based testing and AI algorithms show promise in overcoming these barriers.<br /><br />The second summary summarizes the Uterine Cancer Master Session, which emphasizes the importance of molecular classification in the diagnosis and treatment of endometrial cancer. The session highlights the four molecular subgroups identified by the TCGA and their different prognoses and responses to treatment. It suggests incorporating molecular testing into clinical practice to guide treatment decisions, particularly in cases of microsatellite instability-high (MMR) cancer, which may benefit from immunotherapy. The session also discusses platinum resistance and the potential for new therapies such as immune checkpoint inhibitors and targeted therapies. More research and clinical trials are needed to improve outcomes and develop targeted treatments for endometrial cancer.<br /><br />No specific credits are mentioned in the summary.

Keywords

AI algorithms

histopathology slides

molecular subtype classification

expensive molecular testing

low-resource settings

liquid biopsy approaches

molecular classification

algorithm-based testing

barriers

molecular subgroups

TCGA

prognoses

treatment decisions

immunotherapy

endometrial cancer