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Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing

The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next...

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Autores principales: Rosenthal, Sun Hee, Sun, Weimin, Zhang, Ke, Liu, Yan, Nguyen, Quoclinh, Gerasimova, Anna, Nery, Camille, Cheng, Linda, Castonguay, Carolyn, Hiller, Elaine, Li, James, Elzinga, Christopher, Wolfson, David, Smolgovsky, Alla, Chen, Rebecca, Buller-Burckle, Arlene, Catanese, Joseph, Grupe, Andrew, Lacbawan, Felicitas, Owen, Renius
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998746/
https://www.ncbi.nlm.nih.gov/pubmed/32090079
http://dx.doi.org/10.1155/2020/3289023
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author Rosenthal, Sun Hee
Sun, Weimin
Zhang, Ke
Liu, Yan
Nguyen, Quoclinh
Gerasimova, Anna
Nery, Camille
Cheng, Linda
Castonguay, Carolyn
Hiller, Elaine
Li, James
Elzinga, Christopher
Wolfson, David
Smolgovsky, Alla
Chen, Rebecca
Buller-Burckle, Arlene
Catanese, Joseph
Grupe, Andrew
Lacbawan, Felicitas
Owen, Renius
author_facet Rosenthal, Sun Hee
Sun, Weimin
Zhang, Ke
Liu, Yan
Nguyen, Quoclinh
Gerasimova, Anna
Nery, Camille
Cheng, Linda
Castonguay, Carolyn
Hiller, Elaine
Li, James
Elzinga, Christopher
Wolfson, David
Smolgovsky, Alla
Chen, Rebecca
Buller-Burckle, Arlene
Catanese, Joseph
Grupe, Andrew
Lacbawan, Felicitas
Owen, Renius
author_sort Rosenthal, Sun Hee
collection PubMed
description The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next-generation sequencing (NGS). The panel incorporates genes underlying well-characterized cancer syndromes, such as BRCA1 and BRCA2 (BRCA1/2), along with more recently discovered genes associated with increased cancer risk. We performed a validation study on 133 unique specimens, including 33 with known variant status; known variants included single nucleotide variants (SNVs) and small insertions and deletions (Indels), as well as copy-number variants (CNVs). The analytical validation study achieved 100% sensitivity and specificity for SNVs and small Indels, with 100% sensitivity and 98.0% specificity for CNVs using in-house developed CNV flagging algorithm. We employed a microarray comparative genomic hybridization (aCGH) method for all specimens that the algorithm flags as CNV-positive for confirmation. In combination with aCGH confirmation, CNV detection specificity improved to 100%. We additionally report results of the first 500 consecutive specimens submitted for clinical testing with the 34-gene panel, identifying 53 deleterious variants in 13 genes in 49 individuals. Half of the detected pathogenic/likely pathogenic variants were found in BRCA1 (23%), BRCA2 (23%), or the Lynch syndrome-associated genes PMS2 (4%) and MLH1 (2%). The other half were detected in 9 other genes: MUTYH (17%), CHEK2 (15%), ATM (4%), PALB2 (4%), BARD1 (2%), CDH1 (2%), CDKN2A (2%), RAD51C (2%), and RET (2%). Our validation studies and initial clinical data demonstrate that a 34-gene inherited cancer predisposition panel can provide clinically significant information for cancer risk assessment.
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spelling pubmed-69987462020-02-23 Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing Rosenthal, Sun Hee Sun, Weimin Zhang, Ke Liu, Yan Nguyen, Quoclinh Gerasimova, Anna Nery, Camille Cheng, Linda Castonguay, Carolyn Hiller, Elaine Li, James Elzinga, Christopher Wolfson, David Smolgovsky, Alla Chen, Rebecca Buller-Burckle, Arlene Catanese, Joseph Grupe, Andrew Lacbawan, Felicitas Owen, Renius Biomed Res Int Research Article The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next-generation sequencing (NGS). The panel incorporates genes underlying well-characterized cancer syndromes, such as BRCA1 and BRCA2 (BRCA1/2), along with more recently discovered genes associated with increased cancer risk. We performed a validation study on 133 unique specimens, including 33 with known variant status; known variants included single nucleotide variants (SNVs) and small insertions and deletions (Indels), as well as copy-number variants (CNVs). The analytical validation study achieved 100% sensitivity and specificity for SNVs and small Indels, with 100% sensitivity and 98.0% specificity for CNVs using in-house developed CNV flagging algorithm. We employed a microarray comparative genomic hybridization (aCGH) method for all specimens that the algorithm flags as CNV-positive for confirmation. In combination with aCGH confirmation, CNV detection specificity improved to 100%. We additionally report results of the first 500 consecutive specimens submitted for clinical testing with the 34-gene panel, identifying 53 deleterious variants in 13 genes in 49 individuals. Half of the detected pathogenic/likely pathogenic variants were found in BRCA1 (23%), BRCA2 (23%), or the Lynch syndrome-associated genes PMS2 (4%) and MLH1 (2%). The other half were detected in 9 other genes: MUTYH (17%), CHEK2 (15%), ATM (4%), PALB2 (4%), BARD1 (2%), CDH1 (2%), CDKN2A (2%), RAD51C (2%), and RET (2%). Our validation studies and initial clinical data demonstrate that a 34-gene inherited cancer predisposition panel can provide clinically significant information for cancer risk assessment. Hindawi 2020-01-22 /pmc/articles/PMC6998746/ /pubmed/32090079 http://dx.doi.org/10.1155/2020/3289023 Text en Copyright © 2020 Sun Hee Rosenthal et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Rosenthal, Sun Hee
Sun, Weimin
Zhang, Ke
Liu, Yan
Nguyen, Quoclinh
Gerasimova, Anna
Nery, Camille
Cheng, Linda
Castonguay, Carolyn
Hiller, Elaine
Li, James
Elzinga, Christopher
Wolfson, David
Smolgovsky, Alla
Chen, Rebecca
Buller-Burckle, Arlene
Catanese, Joseph
Grupe, Andrew
Lacbawan, Felicitas
Owen, Renius
Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title_full Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title_fullStr Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title_full_unstemmed Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title_short Development and Validation of a 34-Gene Inherited Cancer Predisposition Panel Using Next-Generation Sequencing
title_sort development and validation of a 34-gene inherited cancer predisposition panel using next-generation sequencing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998746/
https://www.ncbi.nlm.nih.gov/pubmed/32090079
http://dx.doi.org/10.1155/2020/3289023
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