AI mapping reveals drug targets in MSS colorectal cancer
An international team studied 2,000 patient tumor samples from microsatellite-stable colorectal cancer, the most common form, using genetic, metabolic, protein and clinical data. They developed an AI approach called iPhenMap to map tumor biology and identify vulnerabilities that could be targeted by existing or new drug combinations. The work aims to support more personalized treatment for patients with limited options.
MSS disease represents about 80%–85% of colorectal cancers newly diagnosed in Ireland each year, but it frequently shows little response to newer targeted or immune-based therapies. Trials pairing chemotherapy with these agents have yielded only modest improvements over standard treatment.
The team analyzed 2,000 patient samples with iPhenMap, linking genomic, metabolic, proteomic and clinical information to reveal vulnerabilities missed when such data were examined separately. In laboratory models, trametinib—approved for certain melanomas, lung and thyroid cancers with a specific mutation—curbed tumor growth and lengthened survival when combined with other drugs.
If preclinical findings translate, patients with limited treatment options could gain access to combinations built from already-approved drugs, potentially speeding trials and offering more personalized choices. Health systems may benefit if repurposed medicines prove effective, though laboratory results require clinical validation. Researchers in other cancers could also use the mapping approach to prioritize targets.