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Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors

BACKGROUND: Parathyroid tumors are common endocrine neoplasias associated with primary hyperparathyroidism. Although numerous studies have studied the subject, the predictive value of gene biomarkers nevertheless remains low. METHODS: In this study, we performed genomic analysis of abnormal DNA meth...

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Detalles Bibliográficos
Autores principales: Li, Qing, Li, Yonghao, Sun, Ximei, Zhang, Xinlei, Zhang, Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308548/
https://www.ncbi.nlm.nih.gov/pubmed/35879975
http://dx.doi.org/10.1155/2022/4995196
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author Li, Qing
Li, Yonghao
Sun, Ximei
Zhang, Xinlei
Zhang, Mei
author_facet Li, Qing
Li, Yonghao
Sun, Ximei
Zhang, Xinlei
Zhang, Mei
author_sort Li, Qing
collection PubMed
description BACKGROUND: Parathyroid tumors are common endocrine neoplasias associated with primary hyperparathyroidism. Although numerous studies have studied the subject, the predictive value of gene biomarkers nevertheless remains low. METHODS: In this study, we performed genomic analysis of abnormal DNA methylation in parathyroid tumors. After data preprocessing, differentially methylated genes were extracted from patients with parathyroid tumors by using t-tests. RESULTS: After refinement of the basic differential methylation, 28241 unique CpGs (634 genes) were identified to be methylated. The methylated genes were primarily involved in 7 GO terms, and the top 3 terms were associated with cyst morphogenesis, ion transport, and GTPase signal. Following pathway enrichment analyses, a total of 10 significant pathways were enriched; notably, the top 3 pathways were cholinergic synapses, glutamatergic synapses, and oxytocin signaling pathways. Based on PPIN and ego-net analysis, 67 ego genes were found which could completely separate the diseased group from the normal group. The 10 most prominent genes included POLA1, FAM155 B, AMMECR1, THOC2, CCND1, CLDN11, IDS, TST, RBPJ, and GNA11. SVM analysis confirmed that this grouping approach was precise. CONCLUSIONS: This research provides useful data to further explore novel genes and pathways as therapeutic targets for parathyroid tumors.
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spelling pubmed-93085482022-07-24 Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors Li, Qing Li, Yonghao Sun, Ximei Zhang, Xinlei Zhang, Mei Int J Endocrinol Research Article BACKGROUND: Parathyroid tumors are common endocrine neoplasias associated with primary hyperparathyroidism. Although numerous studies have studied the subject, the predictive value of gene biomarkers nevertheless remains low. METHODS: In this study, we performed genomic analysis of abnormal DNA methylation in parathyroid tumors. After data preprocessing, differentially methylated genes were extracted from patients with parathyroid tumors by using t-tests. RESULTS: After refinement of the basic differential methylation, 28241 unique CpGs (634 genes) were identified to be methylated. The methylated genes were primarily involved in 7 GO terms, and the top 3 terms were associated with cyst morphogenesis, ion transport, and GTPase signal. Following pathway enrichment analyses, a total of 10 significant pathways were enriched; notably, the top 3 pathways were cholinergic synapses, glutamatergic synapses, and oxytocin signaling pathways. Based on PPIN and ego-net analysis, 67 ego genes were found which could completely separate the diseased group from the normal group. The 10 most prominent genes included POLA1, FAM155 B, AMMECR1, THOC2, CCND1, CLDN11, IDS, TST, RBPJ, and GNA11. SVM analysis confirmed that this grouping approach was precise. CONCLUSIONS: This research provides useful data to further explore novel genes and pathways as therapeutic targets for parathyroid tumors. Hindawi 2022-07-16 /pmc/articles/PMC9308548/ /pubmed/35879975 http://dx.doi.org/10.1155/2022/4995196 Text en Copyright © 2022 Qing Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Qing
Li, Yonghao
Sun, Ximei
Zhang, Xinlei
Zhang, Mei
Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title_full Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title_fullStr Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title_full_unstemmed Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title_short Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors
title_sort genomic analysis of abnormal dnam methylation in parathyroid tumors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308548/
https://www.ncbi.nlm.nih.gov/pubmed/35879975
http://dx.doi.org/10.1155/2022/4995196
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