Background: Accurate risk assessment of post-surgical progression in papillary thyroid carcinoma (PTC) patients is critical. Exploring key differentially expressed mRNAs (DE-mRNAs) regulated by differentially expressed circular RNAs (circRNAs) via the ceRNA mechanism could help establish a novel assessment tool.

Methods: ceRNA network was established based on differentially expressed RNAs and correlation analysis. DE-mRNAs within the ceRNA network associated with progression-free interval (PFI) of PTC were identified to construct a prognostic ceRNA regulatory subnetwork. least absolute shrinkage and selection operator (LASSO)–Cox regression was applied to identify hub DE-mRNAs and establish a novel DE-mRNA signature in predicting PFI of PTC.

Results: Six hub DE-mRNAs, namely, CLCNKB, FXBO27, FXYD6, RIMS2, SPC24, and CDKN2A, were identified to be most significantly related to the PFI of PTC, and a prognostic DE-mRNA signature was proposed. A nomogram incorporating the DE-mRNA signature and clinical parameters was established to improve the progression risk assessment in post-surgical PTC, which was superior to the American Thyroid Association risk stratification system and distant Metastasis, patient Age, Completeness of resection, local Invasion, and tumor Size (MACIS) score American Joint Committee on Cancer staging system.

Conclusions: Based on the circRNA-associated ceRNA RNA mechanism, a DE-mRNA signature and prognostic nomogram was established, which may improve the progression risk assessment in post-surgical PTC.

背景：甲状腺乳头状癌（PTC）患者手术后进展的准确风险评估至关重要。探索通过ceRNA机制由差异表达的环状RNA（circRNA）调控的关键差异表达的mRNA（DE-mRNA）可以帮助建立一种新颖的评估工具。

方法：基于差异表达的RNA和相关分析建立了ceRNA网络。在ceRNA网络中与PTC的无进展间隔（PFI）相关的DE-mRNA被鉴定出来，以构建预后的ceRNA调节子网络。最小绝对收缩和选择算子（LASSO）-Cox回归用于确定中心DE-mRNA，并建立新的DE-mRNA签名预测PTC的PFI。

结果： 六个中枢DE-mRNA，即 CLCNKB，FXBO27，FXYD6，RIMS2，SPC24和 CDKN2A被确定与PTC的PFI最为相关，并提出了预后的DE-mRNA签名。建立了包含DE-mRNA签名和临床参数的诺模图以改善手术后PTC的进展风险评估，其优于美国甲状腺协会风险分层系统和远处转移，患者年龄，切除的完整性，局部浸润，和肿瘤大小（MACIS）评分美国癌症分期系统联合委员会。

结论： 基于circRNA相关的ceRNA RNA机制，建立了DE-mRNA签名和预后诺模图，可以改善PTC术后的进展风险评估。