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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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Endocrinology |
| Online Access: | http://dx.doi.org/10.1155/2022/4995196 |
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| author | Qing Li Yonghao Li Ximei Sun Xinlei Zhang Mei Zhang |
| author_facet | Qing Li Yonghao Li Ximei Sun Xinlei Zhang Mei Zhang |
| author_sort | Qing Li |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-c88b64cdf49b4d0f868ccd4d05645ae8 |
| institution | Kabale University |
| issn | 1687-8345 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Endocrinology |
| spelling | doaj-art-c88b64cdf49b4d0f868ccd4d05645ae82025-02-03T01:32:27ZengWileyInternational Journal of Endocrinology1687-83452022-01-01202210.1155/2022/4995196Genomic Analysis of Abnormal DNAM Methylation in Parathyroid TumorsQing Li0Yonghao Li1Ximei Sun2Xinlei Zhang3Mei Zhang4Department of General SurgeryDepartment of General SurgeryDepartment of General SurgeryDepartment of General SurgeryDepartment of General SurgeryBackground. 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.http://dx.doi.org/10.1155/2022/4995196 |
| spellingShingle | Qing Li Yonghao Li Ximei Sun Xinlei Zhang Mei Zhang Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors International Journal of Endocrinology |
| 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 |
| url | http://dx.doi.org/10.1155/2022/4995196 |
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