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Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel

BACKGROUND: The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However,...

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Autores principales: Yan, Kangpeng, Niu, Li, Wu, Boyu, He, Chongwu, Deng, Lei, Chen, Chuan, Lan, Zhangzhang, Lin, Chao, Kuang, Weihua, Lin, Huihong, Zou, Jun, Zhang, Wenyong, Luo, Zhiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653745/
https://www.ncbi.nlm.nih.gov/pubmed/37967237
http://dx.doi.org/10.1080/07853890.2023.2280708
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author Yan, Kangpeng
Niu, Li
Wu, Boyu
He, Chongwu
Deng, Lei
Chen, Chuan
Lan, Zhangzhang
Lin, Chao
Kuang, Weihua
Lin, Huihong
Zou, Jun
Zhang, Wenyong
Luo, Zhiqiang
author_facet Yan, Kangpeng
Niu, Li
Wu, Boyu
He, Chongwu
Deng, Lei
Chen, Chuan
Lan, Zhangzhang
Lin, Chao
Kuang, Weihua
Lin, Huihong
Zou, Jun
Zhang, Wenyong
Luo, Zhiqiang
author_sort Yan, Kangpeng
collection PubMed
description BACKGROUND: The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood. METHODS: We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs. RESULTS: We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs. CONCLUSION: The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type.
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spelling pubmed-106537452023-11-15 Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel Yan, Kangpeng Niu, Li Wu, Boyu He, Chongwu Deng, Lei Chen, Chuan Lan, Zhangzhang Lin, Chao Kuang, Weihua Lin, Huihong Zou, Jun Zhang, Wenyong Luo, Zhiqiang Ann Med Oncology BACKGROUND: The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood. METHODS: We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs. RESULTS: We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs. CONCLUSION: The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type. Taylor & Francis 2023-11-15 /pmc/articles/PMC10653745/ /pubmed/37967237 http://dx.doi.org/10.1080/07853890.2023.2280708 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Oncology
Yan, Kangpeng
Niu, Li
Wu, Boyu
He, Chongwu
Deng, Lei
Chen, Chuan
Lan, Zhangzhang
Lin, Chao
Kuang, Weihua
Lin, Huihong
Zou, Jun
Zhang, Wenyong
Luo, Zhiqiang
Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title_full Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title_fullStr Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title_full_unstemmed Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title_short Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel
title_sort copy number variants landscape of multiple cancers and clinical applications based on ngs gene panel
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10653745/
https://www.ncbi.nlm.nih.gov/pubmed/37967237
http://dx.doi.org/10.1080/07853890.2023.2280708
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