Medicine and Health Sciences Commons^™

Unlocking The Potential Of Kinase Targets In Cancer: Insights From Canceromicsnet, An Ai-Driven Approach To Drug Response Prediction In Cancer, Manali Singha, Limeng Pu, Gopal Srivastava, Xialong Ni, Brent A. Stanfield, Ifeanyi K. Uche, Paul J.F. Rider, Konstantin G. Kousoulas, J. Ramanujam, Michal Brylinski

School of Medicine Faculty Publications

Deregulated protein kinases are crucial in promoting cancer cell proliferation and driving malignant cell signaling. Although these kinases are essential targets for cancer therapy due to their involvement in cell development and proliferation, only a small part of the human kinome has been targeted by drugs. A comprehensive scoring system is needed to evaluate and prioritize clinically relevant kinases. We recently developed CancerOmicsNet, an artificial intelligence model employing graph-based algorithms to predict the cancer cell response to treatment with kinase inhibitors. The performance of this approach has been evaluated in large-scale benchmarking calculations, followed by the experimental validation of selected …