Researchers Yonsei University College of Medicine and Gangnam Severance Hospital in Seoul, South Korea, have collaborated to develop a deep learning model called MSI-SEER that is designed to accurately detect microsatellite instability-high (MSI-H) status and predict response to immune checkpoint inhibitor (ICI) therapies in gastric and colorectal cancers. The findings, published in npj Digital Medicine , detail how the tool could overcome the cost, time, and access challenges associated with current MSI testing to make it more broadly available.

“Determining tumor microsatellite status has significant clinical value because tumors that are microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) respond well to immune checkpoint inhibitors (ICIs) and oftentimes n

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