Cargando…

Applications and analysis of targeted genomic sequencing in cancer studies

Next Generation Sequencing (NGS) has dramatically improved the flexibility and outcomes of cancer research and clinical trials, providing highly sensitive and accurate high-throughput platforms for large-scale genomic testing. In contrast to whole-genome (WGS) or whole-exome sequencing (WES), target...

Descripción completa

Detalles Bibliográficos
Autores principales: Bewicke-Copley, Findlay, Arjun Kumar, Emil, Palladino, Giuseppe, Korfi, Koorosh, Wang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861594/
https://www.ncbi.nlm.nih.gov/pubmed/31762958
http://dx.doi.org/10.1016/j.csbj.2019.10.004
_version_ 1783471394023014400
author Bewicke-Copley, Findlay
Arjun Kumar, Emil
Palladino, Giuseppe
Korfi, Koorosh
Wang, Jun
author_facet Bewicke-Copley, Findlay
Arjun Kumar, Emil
Palladino, Giuseppe
Korfi, Koorosh
Wang, Jun
author_sort Bewicke-Copley, Findlay
collection PubMed
description Next Generation Sequencing (NGS) has dramatically improved the flexibility and outcomes of cancer research and clinical trials, providing highly sensitive and accurate high-throughput platforms for large-scale genomic testing. In contrast to whole-genome (WGS) or whole-exome sequencing (WES), targeted genomic sequencing (TS) focuses on a panel of genes or targets known to have strong associations with pathogenesis of disease and/or clinical relevance, offering greater sequencing depth with reduced costs and data burden. This allows targeted sequencing to identify low frequency variants in targeted regions with high confidence, thus suitable for profiling low-quality and fragmented clinical DNA samples. As a result, TS has been widely used in clinical research and trials for patient stratification and the development of targeted therapeutics. However, its transition to routine clinical use has been slow. Many technical and analytical obstacles still remain and need to be discussed and addressed before large-scale and cross-centre implementation. Gold-standard and state-of-the-art procedures and pipelines are urgently needed to accelerate this transition. In this review we first present how TS is conducted in cancer research, including various target enrichment platforms, the construction of target panels, and selected research and clinical studies utilising TS to profile clinical samples. We then present a generalised analytical workflow for TS data discussing important parameters and filters in detail, aiming to provide the best practices of TS usage and analyses.
format Online
Article
Text
id pubmed-6861594
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Research Network of Computational and Structural Biotechnology
record_format MEDLINE/PubMed
spelling pubmed-68615942019-11-22 Applications and analysis of targeted genomic sequencing in cancer studies Bewicke-Copley, Findlay Arjun Kumar, Emil Palladino, Giuseppe Korfi, Koorosh Wang, Jun Comput Struct Biotechnol J Review Article Next Generation Sequencing (NGS) has dramatically improved the flexibility and outcomes of cancer research and clinical trials, providing highly sensitive and accurate high-throughput platforms for large-scale genomic testing. In contrast to whole-genome (WGS) or whole-exome sequencing (WES), targeted genomic sequencing (TS) focuses on a panel of genes or targets known to have strong associations with pathogenesis of disease and/or clinical relevance, offering greater sequencing depth with reduced costs and data burden. This allows targeted sequencing to identify low frequency variants in targeted regions with high confidence, thus suitable for profiling low-quality and fragmented clinical DNA samples. As a result, TS has been widely used in clinical research and trials for patient stratification and the development of targeted therapeutics. However, its transition to routine clinical use has been slow. Many technical and analytical obstacles still remain and need to be discussed and addressed before large-scale and cross-centre implementation. Gold-standard and state-of-the-art procedures and pipelines are urgently needed to accelerate this transition. In this review we first present how TS is conducted in cancer research, including various target enrichment platforms, the construction of target panels, and selected research and clinical studies utilising TS to profile clinical samples. We then present a generalised analytical workflow for TS data discussing important parameters and filters in detail, aiming to provide the best practices of TS usage and analyses. Research Network of Computational and Structural Biotechnology 2019-11-07 /pmc/articles/PMC6861594/ /pubmed/31762958 http://dx.doi.org/10.1016/j.csbj.2019.10.004 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review Article
Bewicke-Copley, Findlay
Arjun Kumar, Emil
Palladino, Giuseppe
Korfi, Koorosh
Wang, Jun
Applications and analysis of targeted genomic sequencing in cancer studies
title Applications and analysis of targeted genomic sequencing in cancer studies
title_full Applications and analysis of targeted genomic sequencing in cancer studies
title_fullStr Applications and analysis of targeted genomic sequencing in cancer studies
title_full_unstemmed Applications and analysis of targeted genomic sequencing in cancer studies
title_short Applications and analysis of targeted genomic sequencing in cancer studies
title_sort applications and analysis of targeted genomic sequencing in cancer studies
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861594/
https://www.ncbi.nlm.nih.gov/pubmed/31762958
http://dx.doi.org/10.1016/j.csbj.2019.10.004
work_keys_str_mv AT bewickecopleyfindlay applicationsandanalysisoftargetedgenomicsequencingincancerstudies
AT arjunkumaremil applicationsandanalysisoftargetedgenomicsequencingincancerstudies
AT palladinogiuseppe applicationsandanalysisoftargetedgenomicsequencingincancerstudies
AT korfikoorosh applicationsandanalysisoftargetedgenomicsequencingincancerstudies
AT wangjun applicationsandanalysisoftargetedgenomicsequencingincancerstudies