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基于 4 个 mRNA 的风险模型预测经典型甲状腺乳头状癌患者的预后。

Prognostic prediction of patients having classical papillary thyroid carcinoma with a 4 mRNA-based risk model.

机构信息

Department of Otolaryngology-Head and Neck Surgery, Minda Hospital of Hubei Minzu University, Enshi, Hubei, China.

出版信息

Medicine (Baltimore). 2024 Jun 7;103(23):e38472. doi: 10.1097/MD.0000000000038472.

Abstract

The dysregulation of protein-coding genes involved in various biological functions is closely associated with the progression of thyroid cancer. This study aimed to investigate the effects of dysregulated gene expressions on the prognosis of classical papillary thyroid carcinoma (cPTC). Using expression profiling datasets from the Cancer Genome Atlas (TCGA) database, we performed differential expression analysis to identify differentially expressed genes (DEGs). Cox regression and Kaplan-Meier analysis were used to identify DEGs, which were used to construct a risk model to predict the prognosis of cPTC patients. Functional enrichment analysis unveiled the potential significance of co-expressed protein-encoding genes in tumors. We identified 4 DEGs (SALL3, PPBP, MYH1, and SYNDIG1), which were used to construct a risk model to predict the prognosis of cPTC patients. These 4 genes were independent of clinical parameters and could be functional in cPTC carcinogenesis. Furthermore, PPBP exhibited a strong correlation with poorer overall survival (OS) in the advanced stage of the disease. This study suggests that the 4-gene signature could be an independent prognostic biomarker to improve prognosis prediction in cPTC patients older than 46.

摘要

涉及各种生物功能的蛋白质编码基因的失调与甲状腺癌的进展密切相关。本研究旨在探讨失调基因表达对经典型甲状腺乳头状癌(cPTC)预后的影响。我们使用来自癌症基因组图谱(TCGA)数据库的表达谱数据集进行差异表达分析,以鉴定差异表达基因(DEGs)。Cox 回归和 Kaplan-Meier 分析用于鉴定 DEGs,这些基因用于构建风险模型,以预测 cPTC 患者的预后。功能富集分析揭示了肿瘤中共同表达的蛋白质编码基因的潜在意义。我们鉴定了 4 个 DEGs(SALL3、PPBP、MYH1 和 SYNDIG1),这些基因用于构建风险模型,以预测 cPTC 患者的预后。这些 4 个基因独立于临床参数,可能在 cPTC 癌变中具有功能。此外,PPBP 在疾病晚期与更差的总生存期(OS)具有很强的相关性。这项研究表明,4 基因特征可能是改善 46 岁以上 cPTC 患者预后预测的独立预后生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5408/11155612/50c729ad4216/medi-103-e38472-g001.jpg

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