Suppr超能文献

基于三个代谢相关基因的多中心验证的食管癌亚型分型模型

A Multi-Center Validated Subtyping Model of Esophageal Cancer Based on Three Metabolism-Related Genes.

作者信息

Liu Yu, Wang Liyu, Fang Lingling, Liu Hengchang, Tian He, Zheng Yujia, Fan Tao, Li Chunxiang, He Jie

机构信息

Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Front Oncol. 2021 Oct 25;11:772145. doi: 10.3389/fonc.2021.772145. eCollection 2021.

Abstract

Metabolic reprogramming is a hallmark of malignancy. Understanding the characteristics of metabolic reprogramming in esophageal squamous cell carcinoma (ESCC) helps uncover novel targets for cancer progression. In this study, 880 metabolism-related genes were identified from microarray data and then filtered to divide patients into two subgroups using consensus clustering, which exhibits significantly different overall survival. After a differential analysis between two subtypes, 3 genes were screened out to construct a two subtypes decision model on the training cohort (GSE53624), defined as high-risk and low-risk subtypes. These risk models were then verified in two public databases (GSE53622 and TCGA-ESCC), an independent cohort of 49 ESCC patients by RT-qPCR and an external cohort of 95 ESCC patients by immunohistochemistry analysis (IHC). Furthermore, the immune cell infiltration of regulatory T cells (Tregs) and plasma cells showed a significant difference between the high and low-risk subtypes in the IHC experiment with 119 ESCC patients. In conclusion, our study indicated that three metabolism-related prognostic genes could stratify patients into subgroups and were associated with immune infiltration, clinical features and clinical outcomes.

摘要

代谢重编程是恶性肿瘤的一个标志。了解食管鳞状细胞癌(ESCC)中代谢重编程的特征有助于发现癌症进展的新靶点。在本研究中,从微阵列数据中鉴定出880个与代谢相关的基因,然后通过一致性聚类进行筛选,将患者分为两个亚组,这两个亚组的总生存期存在显著差异。在对两个亚型进行差异分析后,筛选出3个基因,在训练队列(GSE53624)上构建了一个双亚型决策模型,定义为高风险和低风险亚型。然后在两个公共数据库(GSE53622和TCGA-ESCC)、一个由49例ESCC患者组成的独立队列通过RT-qPCR以及一个由95例ESCC患者组成的外部队列通过免疫组织化学分析(IHC)对这些风险模型进行验证。此外,在对119例ESCC患者进行的IHC实验中,调节性T细胞(Tregs)和浆细胞的免疫细胞浸润在高风险和低风险亚型之间存在显著差异。总之,我们的研究表明,三个与代谢相关的预后基因可将患者分层为亚组,并与免疫浸润、临床特征和临床结局相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5a9/8573269/07c289daf0c8/fonc-11-772145-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验