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Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes

Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutati...

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Autores principales: Gorlova, Olga Y., Kimmel, Marek, Tsavachidis, Spiridon, Amos, Christopher I., Gorlov, Ivan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9132259/
https://www.ncbi.nlm.nih.gov/pubmed/35634240
http://dx.doi.org/10.18632/oncotarget.28231
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author Gorlova, Olga Y.
Kimmel, Marek
Tsavachidis, Spiridon
Amos, Christopher I.
Gorlov, Ivan P.
author_facet Gorlova, Olga Y.
Kimmel, Marek
Tsavachidis, Spiridon
Amos, Christopher I.
Gorlov, Ivan P.
author_sort Gorlova, Olga Y.
collection PubMed
description Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutations in a gene is an indicator of its cancer relevance. To identify genes with an excess of potentially functional missense or nonsense mutations one needs to compare the observed and expected numbers of mutations in the gene. We estimated the expected numbers of missense and nonsense mutations in individual human genes using (i) the number of potential sites for missense and nonsense mutations in individual transcripts and (ii) histology-specific nucleotide context-dependent mutation rates. To estimate mutation rates defined as the number of mutations per site per tumor we used silent mutations reported in the Catalog Of Somatic Mutations In Cancer (COSMIC). The estimates were nucleotide context dependent. We have identified 26 genes with an excess of missense and/or nonsense mutations for lung adenocarcinoma, 18 genes for small cell lung cancer, and 26 genes for squamous cell carcinoma of the lung. These genes include known genes and novel lung cancer gene candidates.
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spelling pubmed-91322592022-05-27 Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes Gorlova, Olga Y. Kimmel, Marek Tsavachidis, Spiridon Amos, Christopher I. Gorlov, Ivan P. Oncotarget Research Paper Largely, cancer development is driven by acquisition and positive selection of somatic mutations that increase proliferation and survival of tumor cells. As a result, genes related to cancer development tend to have an excess of somatic mutations in them. An excess of missense and/or nonsense mutations in a gene is an indicator of its cancer relevance. To identify genes with an excess of potentially functional missense or nonsense mutations one needs to compare the observed and expected numbers of mutations in the gene. We estimated the expected numbers of missense and nonsense mutations in individual human genes using (i) the number of potential sites for missense and nonsense mutations in individual transcripts and (ii) histology-specific nucleotide context-dependent mutation rates. To estimate mutation rates defined as the number of mutations per site per tumor we used silent mutations reported in the Catalog Of Somatic Mutations In Cancer (COSMIC). The estimates were nucleotide context dependent. We have identified 26 genes with an excess of missense and/or nonsense mutations for lung adenocarcinoma, 18 genes for small cell lung cancer, and 26 genes for squamous cell carcinoma of the lung. These genes include known genes and novel lung cancer gene candidates. Impact Journals LLC 2022-05-25 /pmc/articles/PMC9132259/ /pubmed/35634240 http://dx.doi.org/10.18632/oncotarget.28231 Text en Copyright: © 2022 Gorlova et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Gorlova, Olga Y.
Kimmel, Marek
Tsavachidis, Spiridon
Amos, Christopher I.
Gorlov, Ivan P.
Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title_full Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title_fullStr Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title_full_unstemmed Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title_short Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
title_sort identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9132259/
https://www.ncbi.nlm.nih.gov/pubmed/35634240
http://dx.doi.org/10.18632/oncotarget.28231
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