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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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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. |
format | Online Article Text |
id | pubmed-9308548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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