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• W4281391089 abstract "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).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.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.The novel EMT signature and nomogram are useful and convenient for personalized management for thyroid cancer." @default.
• W4281391089 created "2022-05-25" @default.
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• W4281391089 date "2022-05-24" @default.
• W4281391089 modified "2023-10-16" @default.
• W4281391089 title "A novel prognostic model for papillary thyroid cancer based on epithelial–mesenchymal transition‐related genes" @default.
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• W4281391089 doi "https://doi.org/10.1002/cam4.4836" @default.
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