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...
Autores principales: | , , , , |
---|---|
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 |