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A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients

BACKGROUND: With the recent emergence of immune checkpoint inhibitors, microsatellite instability (MSI) status has become an important biomarker for immune checkpoint blockade therapy. There are growing technical demands for the integration of different genomic alterations profiling including MSI an...

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Autores principales: Zheng, Kai, Wan, Hua, Zhang, Jie, Shan, Guangyu, Chai, Ningning, Li, Dongdong, Fang, Nan, Liu, Lina, Zhang, Jingbo, Du, Rong, Wu, Qixi, Li, Xichuan, Zhang, Chunze
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257555/
https://www.ncbi.nlm.nih.gov/pubmed/32466784
http://dx.doi.org/10.1186/s12967-020-02373-1
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author Zheng, Kai
Wan, Hua
Zhang, Jie
Shan, Guangyu
Chai, Ningning
Li, Dongdong
Fang, Nan
Liu, Lina
Zhang, Jingbo
Du, Rong
Wu, Qixi
Li, Xichuan
Zhang, Chunze
author_facet Zheng, Kai
Wan, Hua
Zhang, Jie
Shan, Guangyu
Chai, Ningning
Li, Dongdong
Fang, Nan
Liu, Lina
Zhang, Jingbo
Du, Rong
Wu, Qixi
Li, Xichuan
Zhang, Chunze
author_sort Zheng, Kai
collection PubMed
description BACKGROUND: With the recent emergence of immune checkpoint inhibitors, microsatellite instability (MSI) status has become an important biomarker for immune checkpoint blockade therapy. There are growing technical demands for the integration of different genomic alterations profiling including MSI analysis in a single assay for full use of the limited tissues. METHODS: Tumor and paired control samples from 64 patients with primary colorectal cancer were enrolled in this study, including 14 MSI-high (MSI-H) cases and 50 microsatellite stable (MSS) cases determined by MSI-PCR. All the samples were sequenced by a customized NGS panel covering 2.2 MB. A training dataset of 28 samples was used for selection of microsatellite loci and a novel NGS-based MSI status classifier, USCI-msi, was developed. NGS-based MSI status, single nucleotide variant (SNV) and tumor mutation burden (TMB) were detected for all patients. Most of the patients were also independently detected by immunohistochemistry (IHC) staining. RESULTS: A 9-loci model for detecting microsatellite instability was able to correctly predict MSI status with 100% sensitivity and specificity compared with MSI-PCR, and 84.3% overall concordance with IHC staining. Mutations in cancer driver genes (APC, TP53, and KRAS) were dispersed in MSI-H and MSS cases, while BRAF p.V600E and frameshifts in TCF7L2 gene occurred only in MSI-H cases. Mismatch repair (MMR)-related genes are highly mutated in MSI-H samples. CONCLUSION: We established a new NGS-based MSI classifier, USCI-msi, with as few as 9 microsatellite loci for detecting MSI status in CRC cases. This approach possesses 100% sensitivity and specificity, and performed robustly in samples with low tumor purity.
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spelling pubmed-72575552020-06-07 A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients Zheng, Kai Wan, Hua Zhang, Jie Shan, Guangyu Chai, Ningning Li, Dongdong Fang, Nan Liu, Lina Zhang, Jingbo Du, Rong Wu, Qixi Li, Xichuan Zhang, Chunze J Transl Med Research BACKGROUND: With the recent emergence of immune checkpoint inhibitors, microsatellite instability (MSI) status has become an important biomarker for immune checkpoint blockade therapy. There are growing technical demands for the integration of different genomic alterations profiling including MSI analysis in a single assay for full use of the limited tissues. METHODS: Tumor and paired control samples from 64 patients with primary colorectal cancer were enrolled in this study, including 14 MSI-high (MSI-H) cases and 50 microsatellite stable (MSS) cases determined by MSI-PCR. All the samples were sequenced by a customized NGS panel covering 2.2 MB. A training dataset of 28 samples was used for selection of microsatellite loci and a novel NGS-based MSI status classifier, USCI-msi, was developed. NGS-based MSI status, single nucleotide variant (SNV) and tumor mutation burden (TMB) were detected for all patients. Most of the patients were also independently detected by immunohistochemistry (IHC) staining. RESULTS: A 9-loci model for detecting microsatellite instability was able to correctly predict MSI status with 100% sensitivity and specificity compared with MSI-PCR, and 84.3% overall concordance with IHC staining. Mutations in cancer driver genes (APC, TP53, and KRAS) were dispersed in MSI-H and MSS cases, while BRAF p.V600E and frameshifts in TCF7L2 gene occurred only in MSI-H cases. Mismatch repair (MMR)-related genes are highly mutated in MSI-H samples. CONCLUSION: We established a new NGS-based MSI classifier, USCI-msi, with as few as 9 microsatellite loci for detecting MSI status in CRC cases. This approach possesses 100% sensitivity and specificity, and performed robustly in samples with low tumor purity. BioMed Central 2020-05-28 /pmc/articles/PMC7257555/ /pubmed/32466784 http://dx.doi.org/10.1186/s12967-020-02373-1 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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
Zheng, Kai
Wan, Hua
Zhang, Jie
Shan, Guangyu
Chai, Ningning
Li, Dongdong
Fang, Nan
Liu, Lina
Zhang, Jingbo
Du, Rong
Wu, Qixi
Li, Xichuan
Zhang, Chunze
A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title_full A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title_fullStr A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title_full_unstemmed A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title_short A novel NGS-based microsatellite instability (MSI) status classifier with 9 loci for colorectal cancer patients
title_sort novel ngs-based microsatellite instability (msi) status classifier with 9 loci for colorectal cancer patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257555/
https://www.ncbi.nlm.nih.gov/pubmed/32466784
http://dx.doi.org/10.1186/s12967-020-02373-1
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