Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma
| Autor: | Guinv Hu, Jinzhong Wu, Qinyan Shen, Liting Lv, Liyu Cao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Oncology medicine.medical_specialty lcsh:QH426-470 methylation-driven genes Biology medicine.disease_cause Thyroid carcinoma 03 medical and health sciences 0302 clinical medicine prognostic indicators Internal medicine Genetics medicine KEGG Thyroid cancer Gene Genetics (clinical) Survival analysis Original Research Methylation TCGA medicine.disease thyroid carcinoma lcsh:Genetics 030104 developmental biology 030220 oncology & carcinogenesis DNA methylation biomarker Molecular Medicine Carcinogenesis |
| Zdroj: | Frontiers in Genetics, Vol 11 (2020) Frontiers in Genetics |
| ISSN: | 1664-8021 |
| DOI: | 10.3389/fgene.2020.00294 |
| Popis: | Background Aberrant DNA methylation plays an crucial role in tumorigenesis through regulating gene expression. Nevertheless, the exact role of methylation in the carcinogenesis of thyroid cancer and its association with prognosis remains unclear. The purpose of this study is to explore the DNA methylation-driven genes in thyroid cancer by integrative bioinformatics analysis. Methods The transcriptome profiling data and DNA methylation data of thyroid cancer were downloaded from The Cancer Genome Atlas (TCGA) database. The methylmix R package was used to screen DNA methylation-driven genes in thyroid cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted to annotate the function of methylation-driven genes. Univariate Cox regression analyses was performed to distinguish prognosis-related methylation-driven genes. Multivariate Cox regression analyses was utilized to build a prognostic multi-gene signature. A survival analysis was carried out to determine the individual prognostic significance of this multi-gene signature. Results A total of 51 methylation-driven genes were identified. The functional analysis indicated that these genes were significantly enriched in diverse biological processes (BP) and pathways related to the malignancy processes. Four of these genes (RDH5, TREM1, BIRC7, and SLC26A7) were selected to construct the risk evaluation model. Patients in the low-risk group had an conspicuously better overall survival (OS) than those in high-risk group (p < 0.001). The area under the receiver operating characteristic (ROC) curve for this model was 0.836, suggesting a good specificity and sensitivity. Subsequent survival analysis revealed that this four-gene signature served as an independent indicator for the prognosis of thyroid cancer. Moreover, the prognostic signature was well validated in a external thyroid cancer cohort. Conclusion We identified methylation-driven genes in thyroid cancer with independent prognostic value, which may offer new insight into molecular mechanisms of thyroid cancer and provide new possibility for individualized treatment of thyroid cancer patients. |
| Databáze: | OpenAIRE |
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