Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression

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.