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Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine

Massively parallel sequencing, also referred to as “next-generation sequencing” (NGS) provides not only information about simple, single nucleotide alterations, but it can also provide information on complex variations, such as insertions and deletions, copy number alterations, and structural varian...

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Detalles Bibliográficos
Autores principales: Parilla, Megan, Ritterhouse, Lauren L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248322/
https://www.ncbi.nlm.nih.gov/pubmed/32509788
http://dx.doi.org/10.3389/fcell.2020.00370
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author Parilla, Megan
Ritterhouse, Lauren L.
author_facet Parilla, Megan
Ritterhouse, Lauren L.
author_sort Parilla, Megan
collection PubMed
description Massively parallel sequencing, also referred to as “next-generation sequencing” (NGS) provides not only information about simple, single nucleotide alterations, but it can also provide information on complex variations, such as insertions and deletions, copy number alterations, and structural variants. In addition to identifying individual alterations, genome-wide biomarkers can be discerned from somatic cancer NGS data, broadly termed mutational patterns and signatures. This review will focus on several of the most common genome-wide biomarkers such as tumor mutational burden, microsatellite instability, homologous recombination deficiency, and mutational signatures.
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spelling pubmed-72483222020-06-05 Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine Parilla, Megan Ritterhouse, Lauren L. Front Cell Dev Biol Cell and Developmental Biology Massively parallel sequencing, also referred to as “next-generation sequencing” (NGS) provides not only information about simple, single nucleotide alterations, but it can also provide information on complex variations, such as insertions and deletions, copy number alterations, and structural variants. In addition to identifying individual alterations, genome-wide biomarkers can be discerned from somatic cancer NGS data, broadly termed mutational patterns and signatures. This review will focus on several of the most common genome-wide biomarkers such as tumor mutational burden, microsatellite instability, homologous recombination deficiency, and mutational signatures. Frontiers Media S.A. 2020-05-19 /pmc/articles/PMC7248322/ /pubmed/32509788 http://dx.doi.org/10.3389/fcell.2020.00370 Text en Copyright © 2020 Parilla and Ritterhouse. http://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
Parilla, Megan
Ritterhouse, Lauren L.
Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title_full Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title_fullStr Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title_full_unstemmed Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title_short Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine
title_sort beyond the variants: mutational patterns in next-generation sequencing data for cancer precision medicine
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248322/
https://www.ncbi.nlm.nih.gov/pubmed/32509788
http://dx.doi.org/10.3389/fcell.2020.00370
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