Personalized Cancer Therapy Prioritization Based on Driver Alteration Co-occurrence Patterns
L. Mateo, M. Duran-Frigola, A. Gris-Oliver, M. Palafox, M. Scaltriti, P. Razavi, S. Chandarlapaty, J. Arribas, M. Bellet, V. Serra, P. Aloy
The paper identifies actionable genomic vulnerabilities in cancer by analyzing driver alteration co-occurrence patterns and validates predictions in mice, improving drug response modeling from patient data.
bioRxiv · Sep 18, 2020Cancer Biology