Virtual Tumors Enable Prediction of Personalized Therapeutic Combinations for Non-Small Cell Lung Cancer.

Virtual tumor models accurately predict personalized therapeutic combinations for NSCLC, identifying 53BP1 as a promising target and stratifying patients for radiotherapy.

• Why it matters: Personalized treatment options for NSCLC are limited by the high genetic variability and time-consuming experimental testing, hindering effective patient outcomes.
• What they did: An interpretable mechanistic virtual tumor model was developed to simulate key signaling pathways, testing over 10,000 therapeutic strategies across diverse genetic profiles.
• The result: The model successfully predicted effective drug and radiotherapy combinations, identified new targets like 53BP1, and stratified patients with a 19-gene signature, enabling improved clinical decision-making.