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Titel:

Comprehensive Characterization of Cancer Driver Genes and Mutations.

Dokumenttyp:
journal article
Autor(en):
Bailey, Matthew H; Tokheim, Collin; Porta-Pardo, Eduard; Sengupta, Sohini; Bertrand, Denis; Weerasinghe, Amila; Colaprico, Antonio; Wendl, Michael C; Kim, Jaegil; Reardon, Brendan; Ng, Patrick Kwok-Shing; Jeong, Kang Jin; Cao, Song; Wang, Zixing; Gao, Jianjiong; Gao, Qingsong; Wang, Fang; Liu, Eric Minwei; Mularoni, Loris; Rubio-Perez, Carlota; Nagarajan, Niranjan; Cortés-Ciriano, Isidro; Zhou, Daniel Cui; Liang, Wen-Wei; Hess, Julian M; Yellapantula, Venkata D; Tamborero, David; Gonzalez-Perez,...     »
Abstract:
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and...     »
Zeitschriftentitel:
Cell
Jahr:
2018
Band / Volume:
173
Heft / Issue:
2
Seitenangaben Beitrag:
371-385.e18
Sprache:
eng
Volltext / DOI:
doi:10.1016/j.cell.2018.02.060
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/29625053
Print-ISSN:
0092-8674
TUM Einrichtung:
Institut für Allgemeine Pathologie und pathologische Anatomie
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