Wu Mengwei, Li Shuo, Han Jiashu, Liu Rui, Yuan Hongwei, Xu Xiequn, Li Xiaobin, Liu Ziwen
Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
MD Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Front Cell Dev Biol. 2021 Jan 21;8:606327. doi: 10.3389/fcell.2020.606327. eCollection 2020.
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. 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. Six hub DE-mRNAs, namely, , and , 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. 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.
准确评估甲状腺乳头状癌(PTC)患者术后病情进展风险至关重要。通过ceRNA机制探索由差异表达的环状RNA(circRNA)调控的关键差异表达mRNA(DE-mRNA),有助于建立一种新型评估工具。基于差异表达的RNA和相关性分析建立ceRNA网络。鉴定ceRNA网络中与PTC无进展生存期(PFI)相关的DE-mRNA,以构建预后ceRNA调控子网。应用最小绝对收缩和选择算子(LASSO)-Cox回归来鉴定关键DE-mRNA,并建立预测PTC患者PFI的新型DE-mRNA特征。鉴定出6个关键DE-mRNA,即 、 和 ,它们与PTC的PFI最显著相关,并提出了一种预后DE-mRNA特征。建立了一个包含DE-mRNA特征和临床参数的列线图,以改善术后PTC患者的病情进展风险评估,该列线图优于美国甲状腺协会风险分层系统以及远处转移、患者年龄、切除完整性、局部侵犯和肿瘤大小(MACIS)评分的美国癌症联合委员会分期系统。基于circRNA相关的ceRNA机制,建立了DE-mRNA特征和预后列线图,这可能会改善术后PTC患者的病情进展风险评估。