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A virome-wide clonal integration analysis platform for discovering cancer viral etiology

Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral...

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Autores principales: Chen, Xun, Kost, Jason, Sulovari, Arvis, Wong, Nathalie, Liang, Winnie S., Cao, Jian, Li, Dawei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499315/
https://www.ncbi.nlm.nih.gov/pubmed/30872350
http://dx.doi.org/10.1101/gr.242529.118
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author Chen, Xun
Kost, Jason
Sulovari, Arvis
Wong, Nathalie
Liang, Winnie S.
Cao, Jian
Li, Dawei
author_facet Chen, Xun
Kost, Jason
Sulovari, Arvis
Wong, Nathalie
Liang, Winnie S.
Cao, Jian
Li, Dawei
author_sort Chen, Xun
collection PubMed
description Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral sequence contamination and noncausal viruses complicate the process of identifying genuine oncoviruses. Here, we propose a novel strategy to address these challenges by performing virome-wide screening of early-stage clonal viral integrations. To implement this strategy, we developed VIcaller, a novel platform for identifying viral integrations that are derived from any characterized viruses and shared by a large proportion of tumor cells using whole-genome sequencing (WGS) data. The sensitivity and precision were confirmed with simulated and benchmark cancer data sets. By applying this platform to cancer WGS data sets with proven or speculated viral etiology, we newly identified or confirmed clonal integrations of hepatitis B virus (HBV), human papillomavirus (HPV), Epstein-Barr virus (EBV), and BK Virus (BKV), suggesting the involvement of these viruses in early stages of tumorigenesis in affected tumors, such as HBV in TERT and KMT2B (also known as MLL4) gene loci in liver cancer, HPV and BKV in bladder cancer, and EBV in non-Hodgkin's lymphoma. We also showed the capacity of VIcaller to identify integrations from some uncharacterized viruses. This is the first study to systematically investigate the strategy and method of virome-wide screening of clonal integrations to identify oncoviruses. Searching clonal viral integrations with our platform has the capacity to identify virus-caused cancers and discover cancer viral etiologies.
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spelling pubmed-64993152019-11-01 A virome-wide clonal integration analysis platform for discovering cancer viral etiology Chen, Xun Kost, Jason Sulovari, Arvis Wong, Nathalie Liang, Winnie S. Cao, Jian Li, Dawei Genome Res Method Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral sequence contamination and noncausal viruses complicate the process of identifying genuine oncoviruses. Here, we propose a novel strategy to address these challenges by performing virome-wide screening of early-stage clonal viral integrations. To implement this strategy, we developed VIcaller, a novel platform for identifying viral integrations that are derived from any characterized viruses and shared by a large proportion of tumor cells using whole-genome sequencing (WGS) data. The sensitivity and precision were confirmed with simulated and benchmark cancer data sets. By applying this platform to cancer WGS data sets with proven or speculated viral etiology, we newly identified or confirmed clonal integrations of hepatitis B virus (HBV), human papillomavirus (HPV), Epstein-Barr virus (EBV), and BK Virus (BKV), suggesting the involvement of these viruses in early stages of tumorigenesis in affected tumors, such as HBV in TERT and KMT2B (also known as MLL4) gene loci in liver cancer, HPV and BKV in bladder cancer, and EBV in non-Hodgkin's lymphoma. We also showed the capacity of VIcaller to identify integrations from some uncharacterized viruses. This is the first study to systematically investigate the strategy and method of virome-wide screening of clonal integrations to identify oncoviruses. Searching clonal viral integrations with our platform has the capacity to identify virus-caused cancers and discover cancer viral etiologies. Cold Spring Harbor Laboratory Press 2019-05 /pmc/articles/PMC6499315/ /pubmed/30872350 http://dx.doi.org/10.1101/gr.242529.118 Text en © 2019 Chen et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Method
Chen, Xun
Kost, Jason
Sulovari, Arvis
Wong, Nathalie
Liang, Winnie S.
Cao, Jian
Li, Dawei
A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title_full A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title_fullStr A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title_full_unstemmed A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title_short A virome-wide clonal integration analysis platform for discovering cancer viral etiology
title_sort virome-wide clonal integration analysis platform for discovering cancer viral etiology
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499315/
https://www.ncbi.nlm.nih.gov/pubmed/30872350
http://dx.doi.org/10.1101/gr.242529.118
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