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Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel

BACKGROUND: The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acut...

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Autores principales: Tan, Jaymi, Chow, Yock Ping, Zainul Abidin, Norziha, Chang, Kian Meng, Selvaratnam, Veena, Tumian, Nor Rafeah, Poh, Yang Ming, Veerakumarasivam, Abhi, Laffan, Michael Arthur, Wong, Chieh Lee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760696/
https://www.ncbi.nlm.nih.gov/pubmed/35033063
http://dx.doi.org/10.1186/s12920-021-01145-0
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author Tan, Jaymi
Chow, Yock Ping
Zainul Abidin, Norziha
Chang, Kian Meng
Selvaratnam, Veena
Tumian, Nor Rafeah
Poh, Yang Ming
Veerakumarasivam, Abhi
Laffan, Michael Arthur
Wong, Chieh Lee
author_facet Tan, Jaymi
Chow, Yock Ping
Zainul Abidin, Norziha
Chang, Kian Meng
Selvaratnam, Veena
Tumian, Nor Rafeah
Poh, Yang Ming
Veerakumarasivam, Abhi
Laffan, Michael Arthur
Wong, Chieh Lee
author_sort Tan, Jaymi
collection PubMed
description BACKGROUND: The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acute myeloid leukaemia; often resulting in fatality. Although driver mutations have been identified in these MPNs, subtype-specific markers of the disease have yet to be discovered. Next-generation sequencing (NGS) technology can potentially improve the clinical management of MPNs by allowing for the simultaneous screening of many disease-associated genes. METHODS: The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline. RESULTS: The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs ≥ 15% were confirmed via Sanger sequencing. CONCLUSIONS: The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-01145-0.
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spelling pubmed-87606962022-01-18 Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel Tan, Jaymi Chow, Yock Ping Zainul Abidin, Norziha Chang, Kian Meng Selvaratnam, Veena Tumian, Nor Rafeah Poh, Yang Ming Veerakumarasivam, Abhi Laffan, Michael Arthur Wong, Chieh Lee BMC Med Genomics Research BACKGROUND: The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acute myeloid leukaemia; often resulting in fatality. Although driver mutations have been identified in these MPNs, subtype-specific markers of the disease have yet to be discovered. Next-generation sequencing (NGS) technology can potentially improve the clinical management of MPNs by allowing for the simultaneous screening of many disease-associated genes. METHODS: The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline. RESULTS: The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs ≥ 15% were confirmed via Sanger sequencing. CONCLUSIONS: The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-01145-0. BioMed Central 2022-01-15 /pmc/articles/PMC8760696/ /pubmed/35033063 http://dx.doi.org/10.1186/s12920-021-01145-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Tan, Jaymi
Chow, Yock Ping
Zainul Abidin, Norziha
Chang, Kian Meng
Selvaratnam, Veena
Tumian, Nor Rafeah
Poh, Yang Ming
Veerakumarasivam, Abhi
Laffan, Michael Arthur
Wong, Chieh Lee
Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title_full Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title_fullStr Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title_full_unstemmed Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title_short Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
title_sort analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760696/
https://www.ncbi.nlm.nih.gov/pubmed/35033063
http://dx.doi.org/10.1186/s12920-021-01145-0
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