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Comprehensive Analysis of Hypermutation in Human Cancer.

Campbell, Brittany B; Light, Nicholas; Fabrizio, David; Zatzman, Matthew; Fuligni, Fabio; de Borja, Richard; Davidson, Scott; Edwards, Melissa; Elvin, Julia A; Hodel, Karl P; Zahurancik, Walter J; Suo, Zucai; Lipman, Tatiana; Wimmer, Katharina; Kratz, Christian P; Bowers, Daniel C; Laetsch, Theodore W; Dunn, Gavin P; Johanns, Tanner M; Grimmer, Matthew R; Smirnov, Ivan V; Larouche, Valérie; Samuel, David; Bronsema, Annika; Osborn, Michael; Stearns, Duncan; Raman, Pichai; Cole, Kristina A; Storm, Phillip B; Yalon, Michal; Opocher, Enrico; Mason, Gary; Thomas, Gregory A; Sabel, Magnus; George, Ben; Ziegler, David S; Lindhorst, Scott; Issai, Vanan Magimairajan; Constantini, Shlomi; Toledano, Helen; Elhasid, Ronit; Farah, Roula; Dvir, Rina; Dirks, Peter; Huang, Annie; Galati, Melissa A; Chung, Jiil; Ramaswamy, Vijay; Irwin, Meredith S; Aronson, Melyssa.
Cell; 171(5): 1042-1056.e10, 2017 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-29056344
We present an extensive assessment of mutation burden through sequencing analysis of >81,000 tumors from pediatric and adult patients, including tumors with hypermutation caused by chemotherapy, carcinogens, or germline alterations. Hypermutation was detected in tumor types not previously associated with high mutation burden. Replication repair deficiency was a major contributing factor. We uncovered new driver mutations in the replication-repair-associated DNA polymerases and a distinct impact of microsatellite instability and replication repair deficiency on the scale of mutation load. Unbiased clustering, based on mutational context, revealed clinically relevant subgroups regardless of the tumors' tissue of origin, highlighting similarities in evolutionary dynamics leading to hypermutation. Mutagens, such as UV light, were implicated in unexpected cancers, including sarcomas and lung tumors. The order of mutational signatures identified previous treatment and germline replication repair deficiency, which improved management of patients and families. These data will inform tumor classification, genetic testing, and clinical trial design.
Selo DaSilva