TY - JOUR
T1 - Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
AU - PCAWG Consortium
AU - PCAWG Drivers and Functional Interpretation Working Group
AU - PCAWG Structural Variation Working Group
AU - Rheinbay, Esther
AU - Nielsen, Morten Muhlig
AU - Abascal, Federico
AU - Wala, Jeremiah A.
AU - Shapira, Ofer
AU - Tiao, Grace
AU - Hornshøj, Henrik
AU - Hess, Julian M.
AU - Juul, Randi Istrup
AU - Lin, Ziao
AU - Feuerbach, Lars
AU - Sabarinathan, Radhakrishnan
AU - Madsen, Tobias
AU - Kim, Jaegil
AU - Mularoni, Loris
AU - Shuai, Shimin
AU - Lanzós, Andrés
AU - Herrmann, Carl
AU - Maruvka, Yosef E.
AU - Shen, Ciyue
AU - Amin, Samirkumar B.
AU - Bandopadhayay, Pratiti
AU - Bertl, Johanna
AU - Boroevich, Keith A.
AU - Busanovich, John
AU - Carlevaro-Fita, Joana
AU - Chakravarty, Dimple
AU - Chan, Calvin Wing Yiu
AU - Craft, David
AU - Dhingra, Priyanka
AU - Diamanti, Klev
AU - Fonseca, Nuno A.
AU - Gonzalez-Perez, Abel
AU - Guo, Qianyun
AU - Hamilton, Mark P.
AU - Haradhvala, Nicholas J.
AU - Hong, Chen
AU - Isaev, Keren
AU - Johnson, Todd A.
AU - Juul, Malene
AU - Kahles, Andre
AU - Kahraman, Abdullah
AU - Kim, Youngwook
AU - Komorowski, Jan
AU - Kumar, Kiran
AU - Kumar, Sushant
AU - Lee, Donghoon
AU - Lehmann, Kjong Van
AU - Li, Yilong
AU - Raphael, Benjamin J.
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/2/6
Y1 - 2020/2/6
N2 - The discovery of drivers of cancer has traditionally focused on protein-coding genes1–4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53, in the 3′ untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
AB - The discovery of drivers of cancer has traditionally focused on protein-coding genes1–4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53, in the 3′ untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
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U2 - 10.1038/s41586-020-1965-x
DO - 10.1038/s41586-020-1965-x
M3 - Article
C2 - 32025015
AN - SCOPUS:85079047263
SN - 0028-0836
VL - 578
SP - 102
EP - 111
JO - Nature
JF - Nature
IS - 7793
ER -