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Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma

The standard treatment for glioblastoma involves a combination of surgery, radiation and chemotherapy but have limited impact on survival. The exponential increase in targeted agents directed at pivotal oncogenic pathways now provide new therapeutic opportunities for this tumour type. However, lack...

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Autores principales: Williams, Gareth, Llewelyn, Alexander, Thatcher, Robert, Hardisty, Keeda-Marie, Loddo, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947072/
https://www.ncbi.nlm.nih.gov/pubmed/35324914
http://dx.doi.org/10.1371/journal.pone.0245817
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author Williams, Gareth
Llewelyn, Alexander
Thatcher, Robert
Hardisty, Keeda-Marie
Loddo, Marco
author_facet Williams, Gareth
Llewelyn, Alexander
Thatcher, Robert
Hardisty, Keeda-Marie
Loddo, Marco
author_sort Williams, Gareth
collection PubMed
description The standard treatment for glioblastoma involves a combination of surgery, radiation and chemotherapy but have limited impact on survival. The exponential increase in targeted agents directed at pivotal oncogenic pathways now provide new therapeutic opportunities for this tumour type. However, lack of comprehensive precision oncology testing at diagnosis means such therapeutic opportunities are potentially overlooked. To investigate the role of semiconductor sequencing for detection of predictive biomarkers in routine glioblastoma samples we have undertaken analysis of test trending data generated by a clinically validated next generation sequencing platform designed to capture actionable genomic variants distributed across 505 genes. Analysis was performed across a cohort of 55 glioblastoma patients. Analysis of trending data has revealed a complex and rich actionable mutational landscape in which 166 actionable mutations were detected across 36 genes linked to 17 off label targeted therapy protocols and 111 clinical trials. The majority of patients harboured three or more actionable mutations affecting key cancer related regulatory networks including the PI3K/AKT/MTOR and RAS/RAF/MEK/MAPK signalling pathways, DNA-damage repair pathways and cell cycle checkpoints. Linkage with immunotherapy and PARP inhibitors was identified in 44% of glioblastoma patients as a consequence of alterations in DNA-damage repair genes. Taken together our data indicates that precision oncology testing utilising semiconductor sequencing can be used to identify a broad therapeutic armamentarium of targeted therapies and immunotherapies that can be potentially employed for the improved clinical management of glioblastoma patients.
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spelling pubmed-89470722022-03-25 Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma Williams, Gareth Llewelyn, Alexander Thatcher, Robert Hardisty, Keeda-Marie Loddo, Marco PLoS One Research Article The standard treatment for glioblastoma involves a combination of surgery, radiation and chemotherapy but have limited impact on survival. The exponential increase in targeted agents directed at pivotal oncogenic pathways now provide new therapeutic opportunities for this tumour type. However, lack of comprehensive precision oncology testing at diagnosis means such therapeutic opportunities are potentially overlooked. To investigate the role of semiconductor sequencing for detection of predictive biomarkers in routine glioblastoma samples we have undertaken analysis of test trending data generated by a clinically validated next generation sequencing platform designed to capture actionable genomic variants distributed across 505 genes. Analysis was performed across a cohort of 55 glioblastoma patients. Analysis of trending data has revealed a complex and rich actionable mutational landscape in which 166 actionable mutations were detected across 36 genes linked to 17 off label targeted therapy protocols and 111 clinical trials. The majority of patients harboured three or more actionable mutations affecting key cancer related regulatory networks including the PI3K/AKT/MTOR and RAS/RAF/MEK/MAPK signalling pathways, DNA-damage repair pathways and cell cycle checkpoints. Linkage with immunotherapy and PARP inhibitors was identified in 44% of glioblastoma patients as a consequence of alterations in DNA-damage repair genes. Taken together our data indicates that precision oncology testing utilising semiconductor sequencing can be used to identify a broad therapeutic armamentarium of targeted therapies and immunotherapies that can be potentially employed for the improved clinical management of glioblastoma patients. Public Library of Science 2022-03-24 /pmc/articles/PMC8947072/ /pubmed/35324914 http://dx.doi.org/10.1371/journal.pone.0245817 Text en © 2022 Williams et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Williams, Gareth
Llewelyn, Alexander
Thatcher, Robert
Hardisty, Keeda-Marie
Loddo, Marco
Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title_full Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title_fullStr Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title_full_unstemmed Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title_short Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
title_sort utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947072/
https://www.ncbi.nlm.nih.gov/pubmed/35324914
http://dx.doi.org/10.1371/journal.pone.0245817
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