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Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.


ABSTRACT: 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.

SUBMITTER: Rheinbay E 

PROVIDER: S-EPMC7054214 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

Rheinbay Esther E   Nielsen Morten Muhlig MM   Abascal Federico F   Wala Jeremiah A JA   Shapira Ofer O   Tiao Grace G   Hornshøj Henrik H   Hess Julian M JM   Juul Randi Istrup RI   Lin Ziao Z   Feuerbach Lars L   Sabarinathan Radhakrishnan R   Madsen Tobias T   Kim Jaegil J   Mularoni Loris L   Shuai Shimin S   Lanzós Andrés A   Herrmann Carl C   Maruvka Yosef E YE   Shen Ciyue C   Amin Samirkumar B SB   Bandopadhayay Pratiti P   Bertl Johanna J   Boroevich Keith A KA   Busanovich John J   Carlevaro-Fita Joana J   Chakravarty Dimple D   Chan Calvin Wing Yiu CWY   Craft David D   Dhingra Priyanka P   Diamanti Klev K   Fonseca Nuno A NA   Gonzalez-Perez Abel A   Guo Qianyun Q   Hamilton Mark P MP   Haradhvala Nicholas J NJ   Hong Chen C   Isaev Keren K   Johnson Todd A TA   Juul Malene M   Kahles Andre A   Kahraman Abdullah A   Kim Youngwook Y   Komorowski Jan J   Kumar Kiran K   Kumar Sushant S   Lee Donghoon D   Lehmann Kjong-Van KV   Li Yilong Y   Liu Eric Minwei EM   Lochovsky Lucas L   Park Keunchil K   Pich Oriol O   Roberts Nicola D ND   Saksena Gordon G   Schumacher Steven E SE   Sidiropoulos Nikos N   Sieverling Lina L   Sinnott-Armstrong Nasa N   Stewart Chip C   Tamborero David D   Tubio Jose M C JMC   Umer Husen M HM   Uusküla-Reimand Liis L   Wadelius Claes C   Wadi Lina L   Yao Xiaotong X   Zhang Cheng-Zhong CZ   Zhang Jing J   Haber James E JE   Hobolth Asger A   Imielinski Marcin M   Kellis Manolis M   Lawrence Michael S MS   von Mering Christian C   Nakagawa Hidewaki H   Raphael Benjamin J BJ   Rubin Mark A MA   Sander Chris C   Stein Lincoln D LD   Stuart Joshua M JM   Tsunoda Tatsuhiko T   Wheeler David A DA   Johnson Rory R   Reimand Jüri J   Gerstein Mark M   Khurana Ekta E   Campbell Peter J PJ   López-Bigas Núria N   Weischenfeldt Joachim J   Beroukhim Rameen R   Martincorena Iñigo I   Pedersen Jakob Skou JS   Getz Gad G  

Nature 20200205 7793


The discovery of drivers of cancer has traditionally focused on protein-coding genes<sup>1-4</sup>. 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) Consortium<sup>5</sup> 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  ...[more]

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