USC Study Reveals Genetic Mutations Impact Cancer Treatment Efficacy: Personalized Medicine Advances with Predictive Machine Learning Tool

USC research identifies how genetic mutations affect cancer treatment efficacy. * Analysis of 78,000+ patients across 20 cancer types. * Identified 95 genes linked to survival rates in breast, ovarian, skin, and gastrointestinal cancers. * KRAS gene mutations correlate with poor response to EGFR inhibitors in NSCLC. * NF1 gene mutations improve immunotherapy response but compromise targeted therapy efficacy. * Developed machine-learning tool to predict immunotherapy response in advanced lung cancer.