Comprehensive Transcriptomic Analysis of Papillary Thyroid Cancer: Potential Biomarkers Associated With Tumor Progression Publisher Pubmed



Hosseinkhan N¹ ; Honardoost M¹ ; Blighe K² ; Moore CBT² ; Khamseh ME¹
Source: Journal of Endocrinological Investigation Published:2020

Abstract

Purpose: 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. Methods: 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. 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. Conclusion: 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. © 2020, Italian Society of Endocrinology (SIE).