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Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer
SIMPLE SUMMARY: A lack of sensitive biomarkers hinders lung cancer detection and monitoring, resulting in late diagnosis and missed treatment response. Liquid biopsies have recently emerged as a promising method of detecting biomarkers in lung cancer patients without the need to conduct invasive pro...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10136462/ https://www.ncbi.nlm.nih.gov/pubmed/37190212 http://dx.doi.org/10.3390/cancers15082275 |
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author | Brockley, Liam J. Souza, Vanessa G. P. Forder, Aisling Pewarchuk, Michelle E. Erkan, Melis Telkar, Nikita Benard, Katya Trejo, Jessica Stewart, Matt D. Stewart, Greg L. Reis, Patricia P. Lam, Wan L. Martinez, Victor D. |
author_facet | Brockley, Liam J. Souza, Vanessa G. P. Forder, Aisling Pewarchuk, Michelle E. Erkan, Melis Telkar, Nikita Benard, Katya Trejo, Jessica Stewart, Matt D. Stewart, Greg L. Reis, Patricia P. Lam, Wan L. Martinez, Victor D. |
author_sort | Brockley, Liam J. |
collection | PubMed |
description | SIMPLE SUMMARY: A lack of sensitive biomarkers hinders lung cancer detection and monitoring, resulting in late diagnosis and missed treatment response. Liquid biopsies have recently emerged as a promising method of detecting biomarkers in lung cancer patients without the need to conduct invasive procedures. New approaches for biomarker discovery have emerged due to advances in high-throughput sequencing technologies and bioinformatics tools. In this review, we comprehensively describe established and emerging methods for identifying lung cancer biomarkers using liquid biopsy. Furthermore, we highlight advanced bioinformatics tools and methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection. ABSTRACT: Lung cancer detection and monitoring are hampered by a lack of sensitive biomarkers, which results in diagnosis at late stages and difficulty in tracking response to treatment. Recent developments have established liquid biopsies as promising non-invasive methods for detecting biomarkers in lung cancer patients. With concurrent advances in high-throughput sequencing technologies and bioinformatics tools, new approaches for biomarker discovery have emerged. In this article, we survey established and emerging biomarker discovery methods using nucleic acid materials derived from bodily fluids in the context of lung cancer. We introduce nucleic acid biomarkers extracted from liquid biopsies and outline biological sources and methods of isolation. We discuss next-generation sequencing (NGS) platforms commonly used to identify novel biomarkers and describe how these have been applied to liquid biopsy. We highlight emerging biomarker discovery methods, including applications of long-read sequencing, fragmentomics, whole-genome amplification methods for single-cell analysis, and whole-genome methylation assays. Finally, we discuss advanced bioinformatics tools, describing methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection, which holds promise for early diagnosis of lung cancer. |
format | Online Article Text |
id | pubmed-10136462 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101364622023-04-28 Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer Brockley, Liam J. Souza, Vanessa G. P. Forder, Aisling Pewarchuk, Michelle E. Erkan, Melis Telkar, Nikita Benard, Katya Trejo, Jessica Stewart, Matt D. Stewart, Greg L. Reis, Patricia P. Lam, Wan L. Martinez, Victor D. Cancers (Basel) Review SIMPLE SUMMARY: A lack of sensitive biomarkers hinders lung cancer detection and monitoring, resulting in late diagnosis and missed treatment response. Liquid biopsies have recently emerged as a promising method of detecting biomarkers in lung cancer patients without the need to conduct invasive procedures. New approaches for biomarker discovery have emerged due to advances in high-throughput sequencing technologies and bioinformatics tools. In this review, we comprehensively describe established and emerging methods for identifying lung cancer biomarkers using liquid biopsy. Furthermore, we highlight advanced bioinformatics tools and methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection. ABSTRACT: Lung cancer detection and monitoring are hampered by a lack of sensitive biomarkers, which results in diagnosis at late stages and difficulty in tracking response to treatment. Recent developments have established liquid biopsies as promising non-invasive methods for detecting biomarkers in lung cancer patients. With concurrent advances in high-throughput sequencing technologies and bioinformatics tools, new approaches for biomarker discovery have emerged. In this article, we survey established and emerging biomarker discovery methods using nucleic acid materials derived from bodily fluids in the context of lung cancer. We introduce nucleic acid biomarkers extracted from liquid biopsies and outline biological sources and methods of isolation. We discuss next-generation sequencing (NGS) platforms commonly used to identify novel biomarkers and describe how these have been applied to liquid biopsy. We highlight emerging biomarker discovery methods, including applications of long-read sequencing, fragmentomics, whole-genome amplification methods for single-cell analysis, and whole-genome methylation assays. Finally, we discuss advanced bioinformatics tools, describing methods for processing NGS data, as well as recently developed software tailored for liquid biopsy biomarker detection, which holds promise for early diagnosis of lung cancer. MDPI 2023-04-13 /pmc/articles/PMC10136462/ /pubmed/37190212 http://dx.doi.org/10.3390/cancers15082275 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Brockley, Liam J. Souza, Vanessa G. P. Forder, Aisling Pewarchuk, Michelle E. Erkan, Melis Telkar, Nikita Benard, Katya Trejo, Jessica Stewart, Matt D. Stewart, Greg L. Reis, Patricia P. Lam, Wan L. Martinez, Victor D. Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title | Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title_full | Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title_fullStr | Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title_full_unstemmed | Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title_short | Sequence-Based Platforms for Discovering Biomarkers in Liquid Biopsy of Non-Small-Cell Lung Cancer |
title_sort | sequence-based platforms for discovering biomarkers in liquid biopsy of non-small-cell lung cancer |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10136462/ https://www.ncbi.nlm.nih.gov/pubmed/37190212 http://dx.doi.org/10.3390/cancers15082275 |
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