Oncotarget

Research Papers:

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

Olga Y. Gorlova _, Marek Kimmel, Spiridon Tsavachidis, Christopher I. Amos and Ivan P. Gorlov

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Abstract

Olga Y. Gorlova1, Marek Kimmel2, Spiridon Tsavachidis1, Christopher I. Amos1 and Ivan P. Gorlov1

1 Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA

2 Department of Statistics, Rice University, Houston, TX 77005, USA

Correspondence to:

Olga Y. Gorlova, email: Olga.Gorlova@bcm.edu

Keywords: lung cancer; somatic mutations; driver genes; Catalog Of Somatic Mutations In Cancer (COSMIC)

Received: March 13, 2022     Accepted: May 03, 2022     Published: May 25, 2022

Copyright: © 2022 Gorlova et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ABSTRACT

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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