OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations

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Abstract

Distinguishing the driver mutations from somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is more acute and far from solved for non-coding mutations. Here we present OncodriveFML, a method designed to analyze the pattern of somatic mutations across tumors in both coding and non-coding genomic regions to identify signals of positive selection, and therefore, their involvement in tumorigenesis. We describe the method and illustrate its usefulness to identify protein-coding genes, promoters, untranslated regions, intronic splice regions, and lncRNAs-containing driver mutations in several malignancies.

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The online version of this article (doi:10.1186/s13059-016-0994-0) contains supplementary material, which is available to authorized users.

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Most cited references 21

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Cell-of-origin chromatin organization shapes the mutational landscape of cancer

Paz Polak, Rosa Karlic, Amnon Koren … (2015)

Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the genome. Instead, different genomic regions vary by up to 5-fold in the local density of somatic mutations 1 , posing a fundamental problem for statistical methods of cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape 1-5 . However, both somatic mutagenesis and epigenomic features are highly cell-type-specific 6,7 . We investigated the distribution of mutations in multiple samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here, we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. Overwhelmingly, the best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of cognate cancer cell lines. We show further that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.

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Genome-wide analysis of non-coding regulatory mutations in cancer

Nils Weinhold, Anders Jacobsen, Nikolaus Schultz … (2014)

Cancer primarily develops due to somatic alterations in the genome. Advances in sequencing have enabled large-scale sequencing studies across many tumor types, emphasizing discovery of alterations in protein-coding genes. However, the protein-coding exome comprises less than 2% of the human genome. Here, we analyze complete genome sequences of 863 human tumors from The Cancer Genome Atlas and other sources to systematically identify non-coding regions that are recurrently mutated in cancer. We utilize novel frequency and sequence-based approaches to comprehensively scan the genome for non-coding mutations with potential regulatory impact. We identified recurrent mutations in regulatory elements upstream of PLEKHS1, WDR74, and SDHD, as well as previously identified mutations in the TERT promoter. SDHD promoter mutations are frequent in melanoma and associated with reduced gene expression and poor patient prognosis. The non-protein-coding cancer genome remains widely unexplored and our findings represent a step towards targeting the entire genome for clinical purposes.

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Inactivation of LKB1/STK11 is a common event in adenocarcinomas of the lung.

Montserrat Sánchez, Manel Esteller, BARRY TRINK … (2002)

Frequent losses of chromosome 19p have recently been observed in sporadic lung adenocarcinomas, targeting the location of a critical tumor suppressor gene. Here we performed fine mapping of the short arm of chromosome 19 and found that the LKB1/STK11 gene mapped in the minimal-deleted region. Because germ-line mutations at LKB1/STK11 result in the Peutz-Jeghers syndrome and an increased risk of cancer, we performed a detailed genetic screen of the LKB1/STK11 gene in lung tumors. We detected a high frequency of somatic alterations (mainly nonsense mutations) in primary lung adenocarcinomas and in lung cancer cell lines. Thus, our findings demonstrate for the first time that LKB1/STK11 inactivation is a very common event and may be integrally involved in the development of sporadic lung adenocarcinoma.

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Author and article information

Contributors

Núria López-Bigas: nuria.lopez@upf.edu

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 16 June 2016

Publication date PMC-release: 16 June 2016

Publication date Collection: 2016

Volume: 17

Electronic Location Identifier: 128

Affiliations

[ ]Research Program on Biomedical Informatics, IMIM Hospital del Mar Medical Research Institute and Universitat Pompeu Fabra, Doctor Aiguader 88, 08003 Barcelona, Catalonia Spain

[ ]Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, 08010 Barcelona, Spain

Article

Publisher ID: 994

DOI: 10.1186/s13059-016-0994-0

PMC ID: 4910259

PubMed ID: 27311963

SO-VID: 3dee96c5-7905-4d8e-be54-254a2e001e5b

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 11 February 2016

Date accepted : 31 May 2016

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100003043, EMBO;

Award ID: ALTF 568-2014

Award Recipient : Radhakrishnan Sabarinathan

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ScienceOpen disciplines: Genetics

Keywords: cancer drivers,non-coding regions,local functional mutations bias,non-coding drivers

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ScienceOpen disciplines: Genetics

Keywords: cancer drivers, non-coding regions, local functional mutations bias, non-coding drivers

OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations

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Abstract

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Genome Engineering using CRISPR

Most cited references 21

Cell-of-origin chromatin organization shapes the mutational landscape of cancer

Genome-wide analysis of non-coding regulatory mutations in cancer

Inactivation of LKB1/STK11 is a common event in adenocarcinomas of the lung.

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