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Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm
Cancer driver gene is a type of gene with abnormal alterations that initiate or promote tumorigenesis. Driver genes can be used to reveal the fundamental pathological mechanisms of tumorigenesis. These genes may have pathological changes at different omics levels. Thus, identifying cancer driver gen...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826452/ https://www.ncbi.nlm.nih.gov/pubmed/35155435 http://dx.doi.org/10.3389/fcell.2022.825272 |
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author | Yuan, Fei Cao, Xiaoyu Zhang, Yu-Hang Chen, Lei Huang, Tao Li, ZhanDong Cai, Yu-Dong |
author_facet | Yuan, Fei Cao, Xiaoyu Zhang, Yu-Hang Chen, Lei Huang, Tao Li, ZhanDong Cai, Yu-Dong |
author_sort | Yuan, Fei |
collection | PubMed |
description | Cancer driver gene is a type of gene with abnormal alterations that initiate or promote tumorigenesis. Driver genes can be used to reveal the fundamental pathological mechanisms of tumorigenesis. These genes may have pathological changes at different omics levels. Thus, identifying cancer driver genes involving two or more omics levels is essential. In this study, a computational investigation was conducted on lung cancer driver genes. Four omics levels, namely, epigenomics, genomics, transcriptomics, and post-transcriptomics, were involved. From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. A following screen procedure was performed to extract essential driver genes, which contained three tests: permutation, association, and function tests, which can exclude false-positive genes and screen essential ones. Finally, the intersection operation was performed to obtain novel driver genes involving two omic levels. The analyses on obtained genes indicated that they were associated with fundamental pathological mechanisms of lung cancer at two corresponding omics levels. |
format | Online Article Text |
id | pubmed-8826452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88264522022-02-10 Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm Yuan, Fei Cao, Xiaoyu Zhang, Yu-Hang Chen, Lei Huang, Tao Li, ZhanDong Cai, Yu-Dong Front Cell Dev Biol Cell and Developmental Biology Cancer driver gene is a type of gene with abnormal alterations that initiate or promote tumorigenesis. Driver genes can be used to reveal the fundamental pathological mechanisms of tumorigenesis. These genes may have pathological changes at different omics levels. Thus, identifying cancer driver genes involving two or more omics levels is essential. In this study, a computational investigation was conducted on lung cancer driver genes. Four omics levels, namely, epigenomics, genomics, transcriptomics, and post-transcriptomics, were involved. From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. A following screen procedure was performed to extract essential driver genes, which contained three tests: permutation, association, and function tests, which can exclude false-positive genes and screen essential ones. Finally, the intersection operation was performed to obtain novel driver genes involving two omic levels. The analyses on obtained genes indicated that they were associated with fundamental pathological mechanisms of lung cancer at two corresponding omics levels. Frontiers Media S.A. 2022-01-26 /pmc/articles/PMC8826452/ /pubmed/35155435 http://dx.doi.org/10.3389/fcell.2022.825272 Text en Copyright © 2022 Yuan, Cao, Zhang, Chen, Huang, Li and Cai. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Yuan, Fei Cao, Xiaoyu Zhang, Yu-Hang Chen, Lei Huang, Tao Li, ZhanDong Cai, Yu-Dong Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title | Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title_full | Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title_fullStr | Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title_full_unstemmed | Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title_short | Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm |
title_sort | identification of novel lung cancer driver genes connecting different omics levels with a heat diffusion algorithm |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826452/ https://www.ncbi.nlm.nih.gov/pubmed/35155435 http://dx.doi.org/10.3389/fcell.2022.825272 |
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