Prognostic lncRNA, miRNA, and mRNA Signatures in Papillary Thyroid Carcinoma - Wang, Kun; Xu, Jing; Zhao, Lu; Liu, Shiyang; Liu, Chenguang; Zhang, Lin (Frontiers in Genetics, 2020)
The current focus in the treatment of papillary thyroid carcinoma is tumor progression. The aim of this study was to build RNAs-based classifiers and develop a comprehensive model to provide progression-free interval risk prediction for papillary thyroid carcinoma. The RNAseq data, miRNAseq data and clinical information of papillary thyroid carcinoma were downloaded from The Cancer Genome Atlas database. Based on the differently expressed RNA, the LASSO Cox regression model was utilized to build the RNAs-based classifiers for progression-free interval of the patients with papillary thyroid carcinoma. A 6-mRNAs-based classifier, a 5-lncRNAs-based classifier and a 4-miRNAs-based classifier were constructed to predict the progression-free interval. Patients with high risk based on the constructed RNAs-based classifiers had worse prognosis in Kaplan-Meier curve analysis with log-rank test. The areas under the curves of the first, third, and fifth year in the training and testing set were 0.83, 0.82, 0.82 and 0.67, 0.72, 0.73 for the 6-mRNAs-based classifier respectively; 0.75, 0.84, 0.85 and 0.71, 0.67, 0.71 for the 5-lncRNAs-based classifier respectively; 0.70, 0.77, 0.79 and 0.74, 0.67, 0.66 for the 4-miRNAs-based classifier respectively. The prediction capability of the three RNAs-based classifiers was superior to the TNM stage system. Furthermore, a nomogram based on the verified independent prognostic factors was established for the prognostic prediction. The C-index and calibration plots indicated good predictive accuracy of the nomogram. In summary, the 6-mRNAs-based classifier and 5-lncRNAs-based classifier constructed in this study were independent prognostic factors for papillary thyroid carcinoma.