An 8 miRNA-Based Risk Score System for Predicting the Prognosis of Patients With Papillary Thyroid Cancer

• Published in: Technology in cancer research & treatment Vol. 19; p. 1533033820965594
• Main Authors: Yi, Wanwan, Liu, Jin, Qu, Shuping, Fan, Hengwei, Lv, Zhongwei
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 2020; Sage Publications Ltd; SAGE Publishing
• Subjects: Calcium signalling; Gene expression; Genomes; Hedgehog protein; MicroRNAs; miRNA; Original; Papillary thyroid cancer; Prognosis; Risk groups; Signal transduction; Thyroid cancer; stratification analysis; papillary thyroid cancer; risk score system; differential expression analysis; enrichment analysis
• ISSN: 1533-0346; 1533-0338
• DOI: 10.1177/1533033820965594

Background: Dysregulation of microRNAs (miRNAs) in papillary thyroid cancer (PTC) might influence prognosis of PTC. This study is aimed to develop a risk score system for predicting prognosis of PTC. Methods: The miRNA and gene expression profiles of PTC were obtained from The Cancer Genome Atlas database. PTC samples were randomly separated into training set (n = 248) and validation set (n = 248). The differentially expressed miRNAs (DE-miRNAs) in the training set were screened using limma package. The independent prognosis-associated DE-miRNAs were identified for building a risk score system. Risk score of PTC samples in the training set was calculated and samples were divided into high risk group and low risk group. Kaplan-Meier curves and receiver operating characteristic (ROC) curve were used to assess the accuracy of the risk score system in the training set, validation set and entire set. Finally, a miRNA-gene regulatory network was visualized by Cytoscape software, followed by enrichment analysis. Results: Totally, 162 DE-miRNAs between tumor and control groups in the training set were identified. An 8 independent prognosis-associated DE-miRNAs, (including miR-1179, miR-133b, miR-3194, miR-3912, miR-548j, miR-6720, miR-6734, and miR-6843) based risk score system was developed. The area under ROC curve in the training set, validation set and entire set was all above 0.93. A miRNA-gene regulatory network involving the 8 DE-miRNAs were built and functional enrichment analysis suggested the genes in the network were significantly enriched into 13 pathways, including calcium signaling pathway and hedgehog signaling pathway. Conclusion: The risk score system developed this study might be used for predicting the prognosis of PTC. Besides, the 8 miRNAs might affect the prognosis of PTC via hedgehog signaling pathway and calcium signaling pathway.