Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.
Creators: name: Rheinbay, Esther
name: Nielsen, Morten Muhlig
name: Abascal, Federico
name: Wala, Jeremiah A
name: Shapira, Ofer
name: Tiao, Grace
name: Hornshøj, Henrik
name: Hess, Julian M
name: Juul, Randi Istrup
name: Lin, Ziao
name: Feuerbach, Lars
name: Sabarinathan, Radhakrishnan
name: Madsen, Tobias
name: Kim, Jaegil
name: Mularoni, Loris
name: Shuai, Shimin
name: Lanzós, Andrés
name: Herrmann, Carl
name: Maruvka, Yosef E
name: Shen, Ciyue
name: Amin, Samirkumar B
name: Bandopadhayay, Pratiti
name: Bertl, Johanna
name: Boroevich, Keith A
name: Busanovich, John
name: Carlevaro-Fita, Joana
name: Chakravarty, Dimple
name: Chan, Calvin Wing Yiu
name: Craft, David
name: Dhingra, Priyanka
name: Diamanti, Klev
name: Fonseca, Nuno A
name: Gonzalez-Perez, Abel
name: Guo, Qianyun
name: Hamilton, Mark P
name: Haradhvala, Nicholas J
name: Hong, Chen
name: Isaev, Keren
name: Johnson, Todd A
name: Juul, Malene
name: Kahles, Andre
name: Kahraman, Abdullah
name: Kim, Youngwook
name: Komorowski, Jan
name: Kumar, Kiran
name: Kumar, Sushant
name: Lee, Donghoon
name: Lehmann, Kjong-Van
name: Li, Yilong
name: Liu, Eric Minwei
name: Lochovsky, Lucas
name: Park, Keunchil
name: Pich, Oriol
name: Roberts, Nicola D
name: Saksena, Gordon
name: Schumacher, Steven E
name: Sidiropoulos, Nikos
name: Sieverling, Lina
name: Sinnott-Armstrong, Nasa
name: Stewart, Chip
name: Tamborero, David
name: MC Tubio, Jose
name: Umer, Husen M
name: Uusküla-Reimand, Liis
name: Wadelius, Claes
name: Wadi, Lina
name: Yao, Xiaotong
name: Zhang, Cheng-Zhong
name: Zhang, Jing
name: Haber, James E
name: Hobolth, Asger
name: Imielinski, Marcin
name: Kellis, Manolis
name: Lawrence, Michael S
name: von Mering, Christian
name: Nakagawa, Hidewaki
name: Raphael, Benjamin J
name: Rubin, Mark A
name: Sander, Chris
name: Stein, Lincoln D
name: Stuart, Joshua M
name: Tsunoda, Tatsuhiko
name: Wheeler, David A
name: Johnson, Rory
name: Reimand, Jüri
name: Gerstein, Mark
name: Khurana, Ekta
name: Campbell, Peter J
name: López-Bigas, Núria
name: Group, PCAWG Drivers and Functional Interpretation Working
name: Group, PCAWG Structural Variation Working
name: Weischenfeldt, Joachim
name: Beroukhim, Rameen
name: Martincorena, Iñigo
name: Pedersen, Jakob Skou
name: Getz, Gad
name: Consortium, PCAWG
Publisher: name: The Francis Crick Institute
Year: 2023
Subjects: classificationCode: Tumour Biology
subject: Tumour Biology
classificationCode: Ecology,Evolution & Ethology
subject: Ecology,Evolution &amp; Ethology
classificationCode: Genetics & Genomics
subject: Genetics &amp; Genomics
classificationCode: Computational & Systems Biology
subject: Computational &amp; Systems Biology
classificationCode: Human Biology & Physiology
subject: Human Biology &amp; Physiology
classificationCode: Structural Biology & Biophysics
subject: Structural Biology &amp; Biophysics

description: 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.