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Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma

Introduction: Oral squamous cell carcinoma (OSCC), which accounts for a high proportion of oral cancers, is characterized by high aggressiveness and rising incidence. Lysine acetylation is associated with cancer pathogenesis. Lysine acetylation-related genes (LARGs) are therapeutic targets and poten...

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Autores principales: Deng, Shi-Zhou, Wu, Xuechen, Tang, Jiezhang, Dai, Lin, Cheng, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495994/
https://www.ncbi.nlm.nih.gov/pubmed/37705968
http://dx.doi.org/10.3389/fmolb.2023.1185832
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author Deng, Shi-Zhou
Wu, Xuechen
Tang, Jiezhang
Dai, Lin
Cheng, Bo
author_facet Deng, Shi-Zhou
Wu, Xuechen
Tang, Jiezhang
Dai, Lin
Cheng, Bo
author_sort Deng, Shi-Zhou
collection PubMed
description Introduction: Oral squamous cell carcinoma (OSCC), which accounts for a high proportion of oral cancers, is characterized by high aggressiveness and rising incidence. Lysine acetylation is associated with cancer pathogenesis. Lysine acetylation-related genes (LARGs) are therapeutic targets and potential prognostic indicators in various tumors, including oral squamous cell carcinoma. However, systematic bioinformatics analysis of the Lysine acetylation-related genes in Oral squamous cell carcinoma is still unexplored. Methods: We analyzed the expression of 33 Lysine acetylation-related genes in oral squamous cell carcinoma and the effects of their somatic mutations on oral squamous cell carcinoma prognosis. Consistent clustering analysis identified two lysine acetylation patterns and the differences between the two patterns were further evaluated. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to develop a lysine acetylation-related prognostic model using TCGA oral squamous cell carcinoma datasets, which was then validated using gene expression omnibus (GEO) dataset GSE41613. Results: Patients with lower risk scores had better prognoses, in both the overall cohort and within the subgroups These patients also had “hot” immune microenvironments and were more sensitive to immunotherapy. Disscussion: Our findings offer a new model for classifying oral squamous cell carcinoma and determining its prognosis and offer novel insights into oral squamous cell carcinoma diagnosis and treatment.
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spelling pubmed-104959942023-09-13 Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma Deng, Shi-Zhou Wu, Xuechen Tang, Jiezhang Dai, Lin Cheng, Bo Front Mol Biosci Molecular Biosciences Introduction: Oral squamous cell carcinoma (OSCC), which accounts for a high proportion of oral cancers, is characterized by high aggressiveness and rising incidence. Lysine acetylation is associated with cancer pathogenesis. Lysine acetylation-related genes (LARGs) are therapeutic targets and potential prognostic indicators in various tumors, including oral squamous cell carcinoma. However, systematic bioinformatics analysis of the Lysine acetylation-related genes in Oral squamous cell carcinoma is still unexplored. Methods: We analyzed the expression of 33 Lysine acetylation-related genes in oral squamous cell carcinoma and the effects of their somatic mutations on oral squamous cell carcinoma prognosis. Consistent clustering analysis identified two lysine acetylation patterns and the differences between the two patterns were further evaluated. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to develop a lysine acetylation-related prognostic model using TCGA oral squamous cell carcinoma datasets, which was then validated using gene expression omnibus (GEO) dataset GSE41613. Results: Patients with lower risk scores had better prognoses, in both the overall cohort and within the subgroups These patients also had “hot” immune microenvironments and were more sensitive to immunotherapy. Disscussion: Our findings offer a new model for classifying oral squamous cell carcinoma and determining its prognosis and offer novel insights into oral squamous cell carcinoma diagnosis and treatment. Frontiers Media S.A. 2023-08-29 /pmc/articles/PMC10495994/ /pubmed/37705968 http://dx.doi.org/10.3389/fmolb.2023.1185832 Text en Copyright © 2023 Deng, Wu, Tang, Dai and Cheng. 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 Molecular Biosciences
Deng, Shi-Zhou
Wu, Xuechen
Tang, Jiezhang
Dai, Lin
Cheng, Bo
Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title_full Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title_fullStr Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title_full_unstemmed Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title_short Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
title_sort integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495994/
https://www.ncbi.nlm.nih.gov/pubmed/37705968
http://dx.doi.org/10.3389/fmolb.2023.1185832
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