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A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples
BACKGROUND: Microsatellite instability (MSI) is a key biomarker for cancer immunotherapy and prognosis. Integration of MSI testing into a next-generation-sequencing (NGS) panel could save tissue sample, reduce turn-around time and cost, and provide MSI status and comprehensive genomic profiling in s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228480/ https://www.ncbi.nlm.nih.gov/pubmed/37022939 http://dx.doi.org/10.1097/CM9.0000000000002216 |
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author | Zhang, Zili Wan, Hua Xu, Bing He, Hongyang Shan, Guangyu Zhang, Jingbo Wu, Qixi Li, Tong |
author_facet | Zhang, Zili Wan, Hua Xu, Bing He, Hongyang Shan, Guangyu Zhang, Jingbo Wu, Qixi Li, Tong |
author_sort | Zhang, Zili |
collection | PubMed |
description | BACKGROUND: Microsatellite instability (MSI) is a key biomarker for cancer immunotherapy and prognosis. Integration of MSI testing into a next-generation-sequencing (NGS) panel could save tissue sample, reduce turn-around time and cost, and provide MSI status and comprehensive genomic profiling in single test. We aimed to develop an MSI calling model to detect MSI status along with the NGS panel-based profiling test using tumor-only samples. METHODS: From January 2019 to December 2020, a total of 174 colorectal cancer (CRC) patients were enrolled, including 31 MSI-high (MSI-H) and 143 microsatellite stability (MSS) cases. Among them, 56 paired tumor and normal samples (10 MSI-H and 46 MSS) were used for modeling, and another 118 tumor-only samples were used for validation. MSI polymerase chain reaction (MSI-PCR) was performed as the gold standard. A baseline was built for the selected microsatellite loci using the NGS data of 56 normal blood samples. An MSI detection model was constructed by analyzing the NGS data of tissue samples. The performance of the model was compared with the results of MSI-PCR. RESULTS: We first intersected the target genomic regions of the NGS panels used in this study to select common microsatellite loci. A total of 42 loci including 23 mononucleotide repeat sites and 19 longer repeat sites were candidates for modeling. As mononucleotide repeat sites are more sensitive and specific for detecting MSI status than sites with longer length motif and the mononucleotide repeat sites performed even better than the total sites, a model containing 23 mononucleotide repeat sites was constructed and named Colorectal Cancer Microsatellite Instability test (CRC-MSI). The model achieved 100% sensitivity and 100% specificity when compared with MSI-PCR in both training and validation sets. Furthermore, the CRC-MSI model was robust with the tumor content as low as 6%. In addition, 8 out of 10 MSI-H samples showed alternations in the four mismatch repair genes (MLH1, MSH2, MSH6, and PMS2). CONCLUSION: MSI status can be accurately determined along the targeted NGS panels using only tumor samples. The performance of mononucleotide repeat sites surpasses loci with longer repeat motif in MSI calling. |
format | Online Article Text |
id | pubmed-10228480 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-102284802023-05-31 A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples Zhang, Zili Wan, Hua Xu, Bing He, Hongyang Shan, Guangyu Zhang, Jingbo Wu, Qixi Li, Tong Chin Med J (Engl) Original Articles BACKGROUND: Microsatellite instability (MSI) is a key biomarker for cancer immunotherapy and prognosis. Integration of MSI testing into a next-generation-sequencing (NGS) panel could save tissue sample, reduce turn-around time and cost, and provide MSI status and comprehensive genomic profiling in single test. We aimed to develop an MSI calling model to detect MSI status along with the NGS panel-based profiling test using tumor-only samples. METHODS: From January 2019 to December 2020, a total of 174 colorectal cancer (CRC) patients were enrolled, including 31 MSI-high (MSI-H) and 143 microsatellite stability (MSS) cases. Among them, 56 paired tumor and normal samples (10 MSI-H and 46 MSS) were used for modeling, and another 118 tumor-only samples were used for validation. MSI polymerase chain reaction (MSI-PCR) was performed as the gold standard. A baseline was built for the selected microsatellite loci using the NGS data of 56 normal blood samples. An MSI detection model was constructed by analyzing the NGS data of tissue samples. The performance of the model was compared with the results of MSI-PCR. RESULTS: We first intersected the target genomic regions of the NGS panels used in this study to select common microsatellite loci. A total of 42 loci including 23 mononucleotide repeat sites and 19 longer repeat sites were candidates for modeling. As mononucleotide repeat sites are more sensitive and specific for detecting MSI status than sites with longer length motif and the mononucleotide repeat sites performed even better than the total sites, a model containing 23 mononucleotide repeat sites was constructed and named Colorectal Cancer Microsatellite Instability test (CRC-MSI). The model achieved 100% sensitivity and 100% specificity when compared with MSI-PCR in both training and validation sets. Furthermore, the CRC-MSI model was robust with the tumor content as low as 6%. In addition, 8 out of 10 MSI-H samples showed alternations in the four mismatch repair genes (MLH1, MSH2, MSH6, and PMS2). CONCLUSION: MSI status can be accurately determined along the targeted NGS panels using only tumor samples. The performance of mononucleotide repeat sites surpasses loci with longer repeat motif in MSI calling. Lippincott Williams & Wilkins 2023-05-05 2023-04-06 /pmc/articles/PMC10228480/ /pubmed/37022939 http://dx.doi.org/10.1097/CM9.0000000000002216 Text en Copyright © 2023 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
spellingShingle | Original Articles Zhang, Zili Wan, Hua Xu, Bing He, Hongyang Shan, Guangyu Zhang, Jingbo Wu, Qixi Li, Tong A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title | A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title_full | A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title_fullStr | A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title_full_unstemmed | A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title_short | A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
title_sort | robust microsatellite instability detection model for unpaired colorectal cancer tissue samples |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228480/ https://www.ncbi.nlm.nih.gov/pubmed/37022939 http://dx.doi.org/10.1097/CM9.0000000000002216 |
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