The application of a novel computational algorithm called  HotNet2 to a pan-cancer cohort comprising somatic alterations from 12 tumor types has resulted in the detection of combinations of rare somatic mutations that contribute to tumorigenesis.

The novelty of the algorithm consists in the analysis of somatic alterations across genes taking into account the interactions of their products in the development of biological functions, rather than individual genes. By pooling together alterations affecting interacting genes, the statistical power to detect driver element modules increases. Furthermore, it is possible to gain new insights into the biological processes involved in tumorigenesis. This is an essential step to develop therapeutic strategies to fight tumors.

Researchers of the  Biomedical Informatics group of GRIB (IMIM-UPF) led by  Nuria Lopez-Bigas have participated on this work published in  Nature Genetics. The study was a team effort from an array of research groups, led by Benjamin Raphael (Director of the Center for Computational Molecular Biology at Brown University, USA).

Pub. Reference: Leiserson MD, Vandin F, Wu HT, Dobson JR, Eldridge JV, Thomas JL, Papoutsaki A, Kim Y, Niu B, McLellan M, Lawrence MS,  Gonzalez-Perez A,  Tamborero D, Cheng Y, Ryslik GA,  Lopez-Bigas N, Getz G, Ding L, Raphael BJ.  Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat Genet, 2014.  PMID: 25501392 . DOI: 10.1038/ng.3168.