Objective To construct a risk model for predicting the prognosis of papillary thyroid carcinoma (PTC) patients based on the expression of microRNAs (miRNA).
Methods The original microRNAs sequencing data and corresponding clinical data of PTC patients were downloaded from the official website of TCGA database. The aberrant expression of microRNAs in PTC was screened by edgeR package in R 3.6.0 software. Univariate and multivariate Cox regression analyses as well as the Lasso regression analysis were utilized to screen out the microRNAs which were related to the prognosis of patients. Then, the risk score equation was established by multivariate Cox regression analysis and the risk prognosis model was constructed. The receiver operating characteristic (ROC) curve was utilized to evaluate the sensitivity and specificity of the model.
Results Compared with normal tissues, 75 microRNAs (|log foldchange|≥2, FDR < 0.05) were dysregulated in PTC tissues. Multivariate Cox regression analysis revealed eight microRNAs (hsa-mir-6730, hsa-mir-4709, hsa-mir-196a-2, hsa-mir-146b, hsa-mir-6860, hsa-mir-509-3, hsa-mir-513c, hsa-mir-515-1) which could be used to construct risk model for predicting the prognosis of patients. The model had good sensitivity and specificity (AUC > 0.8).
Conclusion A risk prediction model based on the expression of microRNAs has been successfully constructed, and the model could effectively predict the prognosis of thyroid cancer patients.
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