Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression
| Autor: | C B T Moore, Mohammad E. Khamseh, Maryam Honardoost, Nazanin Hosseinkhan, Kevin Blighe |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Oncology medicine.medical_specialty Differential expression analysis endocrine system diseases Endocrinology Diabetes and Metabolism Thyroid Gland 030209 endocrinology & metabolism Biology Papillary thyroid cancer Thyroid carcinoma Transcriptome 03 medical and health sciences 0302 clinical medicine Endocrinology Internal medicine microRNA Biomarkers Tumor medicine Humans Thyroid Neoplasms Neoplasm Metastasis Aged Cell Proliferation Neoplasm Staging Gene Expression Profiling Middle Aged medicine.disease Hierarchical clustering Gene Expression Regulation Neoplastic Thyroid Cancer Papillary Tumor progression Case-Control Studies 030220 oncology & carcinogenesis Potential biomarkers Disease Progression Female |
| Zdroj: | Journal of Endocrinological Investigation. 43:911-923 |
| ISSN: | 1720-8386 |
| DOI: | 10.1007/s40618-019-01175-7 |
| Popis: | Identification of stage-specific prognostic/predictive biomarkers in papillary thyroid carcinoma (PTC) could lead to its more efficient clinical management. The main objective of this study was to characterize the stage-specific deregulation in genes and miRNA expression in PTC to identify potential prognostic biomarkers. 495 RNASeq and 499 miRNASeq PTC samples (stage I–IV) as well as, respectively, 56 and 57 normal samples were retrieved from The Cancer Genome Atlas (TCGA). Differential expression analysis was performed using DESeq 2 to identify deregulation of genes and miRNAs between sequential stages. To identify the minority of patients who progress to higher stages, we performed clustering analysis on stage I RNASeq data. An independent PTC RNASeq data set (BioProject accession PRJEB11591) was also used for the validation of the results. LTF and PLA2R1 were identified as two promising biomarkers down-regulated in a subgroup of stage I (both in TCGA and in the validation data set) and in the majority of stage IV of PTC (in TCGA data set). hsa-miR-205, hsa-miR-509-2, hsa-miR-514-1 and hsa-miR-514-2 were also detected as up-regulated miRNAs in both PTC patients with stage I and stage III. Hierarchical clustering of stage I samples showed substantial heterogeneity in the expression pattern of PTC indicating the necessity of categorizing stage I patients based on the expressional alterations of specific biomarkers. Stage I PTC patients showed large amount of expressional heterogeneity. Therefore, risk stratification based on the expressional alterations of candidate biomarkers could be an important step toward personalized management of these patients. |
| Databáze: | OpenAIRE |
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