Background: Papillary thyroid carcinoma (PTC) is a subtype of thyroid cancer with increasing incidence over time.
Objective: This study aimed to build a risk score (RS) system for PTC patients.
Methods: PTC microRNA (miRNA) and messenger RNA (mRNA) expression data were extracted from The Cancer Genome Atlas (TCGA) database. The 491 PTC samples were randomly divided into training and validation sets. Using the limma software package, differentially expressed mRNAs (DEGs) and miRNAs (DEMs) between the tumor and control groups were screened. In order to construct an RS system, a survival package was used to select independent miRNAs related to prognosis. Enrichment analysis was performed, and a miRNA-mRNA co-expression network was constructed. High-throughput sequencing was also used to verify the prognostic miRNAs in exosomes.
Results: We found 1363 DEGs and 171 DEMs between the tumor and control groups. After identifying 26 DEMs significantly related to prognosis, 6 independent prognosis-associated miRNAs were selected to build an RS system. The areas under the curves of the overall survival rates of the training, validation, and entire sets were 0.847, 0.772, and 0.819, respectively. By conducting pathway analysis using the miRNA-mRNA co-expression network, one overlapping factor and five overlapping pathways were obtained. In addition, high-throughput sequencing revealed that the hsa-miR-129-2, hsa-miR-548j, hsa-miR-6734, and hsa-miR-889 expression levels in TCGA tumor tissues and exosomes were consistent, and those of hsa-miR-129-2 and hsa-miR- 889 between patients and controls were significantly different in exosomes.
Conclusion: The six-miRNA RS system in exosomes may comprise independent signatures for predicting PTC patient prognosis.
Keywords: co-expression network; differential expression analysis; enrichment analysis; exosomes; papillary thyroid carcinoma; risk score system.
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