Construction of a Signature Model to Predict the Radioactive Iodine Response of Papillary Thyroid Cancer

Abstract

Papillary thyroid cancer (PTC) accounts for about 90% of thyroid cancer. There are approximately 20%–30% of PTC patients showing disease persistence/recurrence and resistance to radioactive iodine (RAI) treatment. For these PTC patients with RAI refractoriness, the prognosis is poor. In this study, we aimed to establish a comprehensive prognostic model covering multiple signatures to increase the predictive accuracy for progression-free survival (PFS) of PTC patients with RAI treatment. The expression profiles of mRNAs and miRNAs as well as the clinical information of PTC patients were extracted from TCGA and GEO databases. A series of bioinformatics methods were successfully applied to filtrate a two-RNA model (IPCEF1 and hsa-mir-486-5p) associated with the prognosis of RAI-therapy. Finally, the RNA-based risk score was calculated based on the Cox coefficient of the individual RNA, which achieved good performances by the time-dependent receiver operating characteristic (tROC) curve and PFS analyses. Furthermore, the predictive power of the nomogram, integrated with the risk score and clinical parameters (age at diagnosis and tumor stage), was assessed by tROC curves. Collectively, our study demonstrated high precision in predicting the RAI response of PTC patients.

Predictive Factors of Radioactive Iodine Therapy Refractoriness in Patients with Differentiated Thyroid Carcinoma

“…Liu et al 21 conducted a retrospective study on 404 patients and demonstrated that primary tumor diameter > 18.5 mm significantly increases the risk of RAIR-DTC. Additionally, Liu et al 29 reported that patients with advanced tumor stage had a higher RAIR rate. In a study conducted by Lee et al, 30 which was in line with a previous report by Tavares et al, 31 NIS expression was inversely correlated with tumor size, this finding implies that NIS depletion occurs as a tumor progresses and that NIS downregulation is likely mediated by molecular mechanisms occurring in the late stages.…”

“…Another study conducted by Liu et al 29 included ribonucleic acid biomarkers (IPCEF1 and hsa-mir-486–5p) in a prognosis prediction model to predict the progression-free survival of PTC patients with RAI therapy.…”