A study from Cornell researchers could enable a quantum leap forward in identifying and deciphering cancer-driving genetic mutations, the first step in developing effective therapeutics.
Cells become cancerous when they develop genetic mutations that drive uncontrolled growth. They then can replicate quickly and accumulate many more mutations. For researchers hoping to combat cancer, it’s critical to differentiate between the mutations that are driving disease and the mutations that are just riding along.
The study, published Jan. 24 in Nature Communications, describes a comprehensive framework for analyzing such mutations. Called NetFlow3D, the framework has been applied to 33 different cancer types, leveraging the 3D structures of every human protein and all known interactions between proteins to decipher how…