A novel prognostic model for papillary thyroid cancer based on epithelial–mesenchymal transition‐related genes. (24th May 2022)

• Record Type: Journal Article
• Authors: Liu, Rui; Cao, Zhen; Pan, Meng; Wu, Mengwei; Li, Xiaobin; Yuan, Hongwei; Liu, Ziwen
• Is Part Of: Cancer medicine. Volume 11:Number 23(2022)
• Page Start: 4703
• Page End: 4720
• Publication Date: 2022-05-24
• Subjects: bioinformatics -- epithelial–mesenchymal transition -- nomogram -- papillary thyroid cancer -- predictive model -- recurrence -- The Cancer Genome Atlas; 616.994005
• DOI: 10.1002/cam4.4836
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Background: The frequent incidence of postsurgical recurrence issues in papillary thyroid cancer (PTC) patients is a primary concern considering the low cancer‐related mortality. Previous studies have demonstrated that epithelial–mesenchymal transition (EMT) activation is closely related to PTC progression and invasion. In this study, we aimed to develop a novel EMT signature and ancillary nomogram to improve personalized prediction of progression‐free interval (PFI). Methods: First, we carried out a differential analysis of PTC samples and pairwise normal thyroid samples to explore the differentially expressed genes (DEGs). The intersection of the DEGs with EMT‐related genes (ERGs) were identified as differentially expressed EMT‐related genes (DE‐ERGs). We determined PFI‐related DE‐ERGs by Cox regression analysis and then established a novel gene classifier by LASSO regression analysis. We validated the signature in external datasets and in multiple cell lines. Further, we used uni‐ and multivariate analyses to identify independent prognostic characters. Results: We identified 244 prognosis‐related DE‐ERGs. The 244 DE‐ERGs were associated with several pivotal oncogenic processes. We also constructed a novel 10‐gene signature and relevant prognostic model for recurrence prediction of PTC. The 10‐gene signature had a C‐index of 0.723 and the relevant nomogram had a C‐index of 0.776. The efficacy of the signature and nomogram was satisfying and closely correlated with relevant clinical parameters. Furthermore, the signature also had a unique potential in differentiating anaplastic thyroid cancer (ATC) samples. Conclusions: The novel EMT signature and nomogram are useful and convenient for personalized management for thyroid cancer. Abstract : We e identified a 10‐EMTgene signature and constructed a prognostic nomogram with relevant clinical parameters involved. The novel 10‐gene classifier and the nomogram could provide a novel and reliable tool for prognosis prediction with PTC, therefore help decision making for the purpose of individualized surveillance.