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Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome

Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for p...

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Autores principales: Hu, Zixin, Liu, Zhening, Zheng, Jiabin, Peng, Yanmei, Lu, Xingyu, Li, Jia, Tan, Kexin, Cui, Huijuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981642/
https://www.ncbi.nlm.nih.gov/pubmed/36873930
http://dx.doi.org/10.3389/fgene.2023.1061002
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author Hu, Zixin
Liu, Zhening
Zheng, Jiabin
Peng, Yanmei
Lu, Xingyu
Li, Jia
Tan, Kexin
Cui, Huijuan
author_facet Hu, Zixin
Liu, Zhening
Zheng, Jiabin
Peng, Yanmei
Lu, Xingyu
Li, Jia
Tan, Kexin
Cui, Huijuan
author_sort Hu, Zixin
collection PubMed
description Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA–LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.
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spelling pubmed-99816422023-03-04 Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome Hu, Zixin Liu, Zhening Zheng, Jiabin Peng, Yanmei Lu, Xingyu Li, Jia Tan, Kexin Cui, Huijuan Front Genet Genetics Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA–LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC. Frontiers Media S.A. 2023-02-17 /pmc/articles/PMC9981642/ /pubmed/36873930 http://dx.doi.org/10.3389/fgene.2023.1061002 Text en Copyright © 2023 Hu, Liu, Zheng, Peng, Lu, Li, Tan and Cui. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Hu, Zixin
Liu, Zhening
Zheng, Jiabin
Peng, Yanmei
Lu, Xingyu
Li, Jia
Tan, Kexin
Cui, Huijuan
Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title_full Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title_fullStr Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title_full_unstemmed Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title_short Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome
title_sort microsatellite instability-related prognostic risk score (msi-prs) defines a subset of lung squamous cell carcinoma (lusc) patients with genomic instability and poor clinical outcome
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981642/
https://www.ncbi.nlm.nih.gov/pubmed/36873930
http://dx.doi.org/10.3389/fgene.2023.1061002
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