结直肠癌
人工智能
计算机科学
癌症
医学
内科学
出处
期刊:PubMed
日期:2025-08-20
卷期号:63 (10): 866-872
标识
DOI:10.3760/cma.j.cn112139-20250327-00162
摘要
Microsatellite instability (MSI) serves as a molecular marker for DNA mismatch repair deficiency (dMMR), present in approximately 15% of colorectal cancer patients. The MSI status provides predictive information guiding treatment decisions; for instance, patients with microsatellite instability-high colorectal cancer demonstrate better responses to immune checkpoint inhibitor therapy. Currently, MSI testing requires methods such as immunohistochemistry or next-generation sequencing. Although multiple clinical guidelines recommend routine MSI testing, its widespread adoption within China remains limited due to various constraints. Deep learning algorithms offer a novel AI-driven pattern recognition classification strategy, presenting a feasible approach to overcome limitations in MSI testing and enhance immunotherapy efficacy evaluation. Consequently, the Colorectal Surgery Group of the Surgery Branch of the Chinese Medical Association, in collaboration with Beihang University and drawing on current research utilizing artificial intelligence systems to assess colorectal cancer immunotherapy efficacy, has formulated the "Expert consensus on clinical application of immunotherapy intelligent prediction for colorectal cancer based on artificial intelligence platform (2025 version)". This consensus aims to facilitate the prediction of MSI status and other relevant indicators in colorectal cancer patients, while also supporting clinical decision-making regarding the selection and application of immunotherapy regimens.
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