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Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer

Cellular senescence can both inhibit and promote the occurrence of tumors, so how to apply cellular senescence therapy is of great importance. However, it is worth to be analyzed from multiple perspectives by researchers, especially for tumors with a high incidence like papillary thyroid cancer (PTC...

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Autores principales: Wen, Tingting, Guo, Shuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238039/
https://www.ncbi.nlm.nih.gov/pubmed/37266618
http://dx.doi.org/10.1097/MD.0000000000033934
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author Wen, Tingting
Guo, Shuang
author_facet Wen, Tingting
Guo, Shuang
author_sort Wen, Tingting
collection PubMed
description Cellular senescence can both inhibit and promote the occurrence of tumors, so how to apply cellular senescence therapy is of great importance. However, it is worth to be analyzed from multiple perspectives by researchers, especially for tumors with a high incidence like papillary thyroid cancer (PTC). We obtained senescence-related differentially expressed genes (SRGs) from The Cancer Genome Atlas (TCGA) and gene expression omnibus database. Enrichment analysis of SRGs was performed via gene ontology and Kyoto Encyclopedia of Genes and Genomes. Prognostic model was constructed by univariate and multivariate Cox regression analysis. Evaluation of clinical value was analyzed via Receiver operating characteristic curve, Kaplan–Meier curve and Cox regression. Immune infiltrates were investigated through ESTIMATE and single-sample gene set enrichment analysis. Immunohistochemical images were obtained from The Human Protein Atlas. Twenty-seven SRGs from TCGA cohort and gene expression omnibus datasets were found. These genes are mainly concentrated in senescence-related terms and pathways, including “DNA damage response, signal transduction by p53 class mediator,” “signal transduction in response to DNA damage,” “p53 signaling pathway” and “Endocrine resistance.” Based on SRGs, prognostic model was constructed by E2F transcription factor 1, snail family transcriptional repressor 1 and phospholipase A2 receptor 1. PTC patients were divided into a low-risk group and a high-risk group according to the median value (cutoff point = 0.969) of risk score in TCGA cohort. The diagnostic efficiency of this model is good (area under curve = 0.803, 0.809, and 0.877 at 1, 2, and 3 years in TCGA; area under curve = 0.964, 0.813 in GPL570 and GPL96), particularly advanced grade, state and tumor mutation burden, such as Stage III − IV, T3 − 4, H-tumor mutation burden. Furthermore, High-risk group was significantly associated with poor prognosis and more immune infiltration. Our prognostic model has a good diagnostic and prognostic efficacy, and there is a certain clinical application value. In addition, we provide the first new insight into the genesis, diagnosis, prognosis and treatment of PTC based on senescence-related genes.
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spelling pubmed-102380392023-06-03 Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer Wen, Tingting Guo, Shuang Medicine (Baltimore) 5700 Cellular senescence can both inhibit and promote the occurrence of tumors, so how to apply cellular senescence therapy is of great importance. However, it is worth to be analyzed from multiple perspectives by researchers, especially for tumors with a high incidence like papillary thyroid cancer (PTC). We obtained senescence-related differentially expressed genes (SRGs) from The Cancer Genome Atlas (TCGA) and gene expression omnibus database. Enrichment analysis of SRGs was performed via gene ontology and Kyoto Encyclopedia of Genes and Genomes. Prognostic model was constructed by univariate and multivariate Cox regression analysis. Evaluation of clinical value was analyzed via Receiver operating characteristic curve, Kaplan–Meier curve and Cox regression. Immune infiltrates were investigated through ESTIMATE and single-sample gene set enrichment analysis. Immunohistochemical images were obtained from The Human Protein Atlas. Twenty-seven SRGs from TCGA cohort and gene expression omnibus datasets were found. These genes are mainly concentrated in senescence-related terms and pathways, including “DNA damage response, signal transduction by p53 class mediator,” “signal transduction in response to DNA damage,” “p53 signaling pathway” and “Endocrine resistance.” Based on SRGs, prognostic model was constructed by E2F transcription factor 1, snail family transcriptional repressor 1 and phospholipase A2 receptor 1. PTC patients were divided into a low-risk group and a high-risk group according to the median value (cutoff point = 0.969) of risk score in TCGA cohort. The diagnostic efficiency of this model is good (area under curve = 0.803, 0.809, and 0.877 at 1, 2, and 3 years in TCGA; area under curve = 0.964, 0.813 in GPL570 and GPL96), particularly advanced grade, state and tumor mutation burden, such as Stage III − IV, T3 − 4, H-tumor mutation burden. Furthermore, High-risk group was significantly associated with poor prognosis and more immune infiltration. Our prognostic model has a good diagnostic and prognostic efficacy, and there is a certain clinical application value. In addition, we provide the first new insight into the genesis, diagnosis, prognosis and treatment of PTC based on senescence-related genes. Lippincott Williams & Wilkins 2023-06-02 /pmc/articles/PMC10238039/ /pubmed/37266618 http://dx.doi.org/10.1097/MD.0000000000033934 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 5700
Wen, Tingting
Guo, Shuang
Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title_full Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title_fullStr Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title_full_unstemmed Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title_short Bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
title_sort bioinformatics analysis of the prognostic and clinical value of senescence-related gene signature in papillary thyroid cancer
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238039/
https://www.ncbi.nlm.nih.gov/pubmed/37266618
http://dx.doi.org/10.1097/MD.0000000000033934
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