Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm
| Autor: | Guolie Zhang, Fangfang Liu, Wei Lin, Xiaoli Liu, Zhi-Wei Chen, Haifeng Lin, Hai-Jian Tu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Oncology
Aging medicine.medical_specialty ALDOC Dishevelled Proteins Protein tyrosine phosphatase Biology PTPRC Epigenesis Genetic Cell Movement Internal medicine Fructose-Bisphosphate Aldolase medicine Humans Thyroid Neoplasms Gene Thyroid cancer Survival rate Cell Proliferation chemistry.chemical_classification Proportional hazards model Cell Biology Methylation DNA Methylation TCGA medicine.disease Prognosis Dishevelled Gene Expression Regulation Neoplastic DVL1 chemistry biology.protein Leukocyte Common Antigens RNA Long Noncoding C14orf62 Algorithms Research Paper |
| Zdroj: | Aging (Albany NY) |
| ISSN: | 1945-4589 |
| Popis: | Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment. |
| Databáze: | OpenAIRE |
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