Researchers at Cornell University's College of Agriculture and Life Sciences have developed a new framework called NetFlow3D to analyze cancer-driving genetic mutations. The study, published on January 24 in Nature Communications, applies the framework to 33 different cancer types. Researchers used the three-dimensional structures of all human proteins and every known protein-protein interaction to determine how specific mutations may drive cancer.

The team used 3D clustering techniques within protein structures to distinguish mutations that contribute to cancer from those that do not. NetFlow3D is the first framework to incorporate the complete 3D structures of all known human proteins along with the full network of protein-protein interactions.

The research builds on decades of work by governmental, academic, and industry scientists. The genetic and molecular mapping for the 33 cancer types was provided by The Cancer Genome Atlas Program, an initiative of the U.S. National Institutes of Health. The use of 3D protein models, which began with Cambridge University researchers in the 1950s, has played a key role in advancing the study of protein structures and their role in disease.

Source: Cornell University

Source Type: College

Source Location: Ithaca

Ithaca, NY

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