Foundation-model-guided radiogenomic discovery linking cancer genomes to cancer scans
The function of many genes is still unknown, and conventional driver-discovery methods, which rely on how frequently a gene is mutated, cannot assess genes that are only rarely affected. Here we pair Evo~2-based genome analysis with routine clinical imaging to identify gene--phenotype associations at genome-wide scale. For every somatic mutation across three TCGA cohorts (cRCC=clear cell renal cell carcinoma, HCC=hepatocellular carcinoma, and BC=breast cancer; $n = 340$ total), Evo~2 predicts a severity score, with no task-specific training. Per-gene severity summaries are then correlated with radiomic features extracted from paired tumor segmentations, controlling for total mutation burd...
| Authors | Frederik Hauke, Jeremias Krause, Patrick Wienholt et al. |
|---|---|
| Primary category | q-bio.GN |
| Published | 22 July 2026 |
| Last updated at source | 22 July 2026 |
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