基于六个代谢相关基因的胃腺癌预后预测模型

A prediction model for prognosis of gastric adenocarcinoma based on six metabolism-related genes.

作者信息

Zhao Jingyu, Liu Yu, Cui Qianwen, He Rongli, Zhao Jia-Rong, Lu Li, Wang Hong-Qiang, Dai Haiming, Wang Hongzhi, Yang Wulin

机构信息

Institutes of Physical Science and Information Technology, Anhui University, Hefei, 230601, China.

Anhui Province Key Laboratory of Physics and Technology, Institute of Health & Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.

出版信息

Biochem Biophys Rep. 2023 Feb 18;34:101440. doi: 10.1016/j.bbrep.2023.101440. eCollection 2023 Jul.

DOI:10.1016/j.bbrep.2023.101440

PMID:36852096

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9957706/

Abstract

BACKGROUND

The study of tumor metabolism is of great value to elucidate the mechanism of tumorigenesis and predict the prognosis of patients. However, the prognostic role of metabolism-related genes (MRGs) in gastric adenocarcinoma (GAD) remains poorly understood.

METHODS

We downloaded the gene chip dataset GSE79973 (n = 20) of GAD from the Gene Expression Omnibus (GEO) database to compare differentially expressed genes (DEGs) between normal and tumor tissues. We then extracted MRGs from these DEGs and systematically investigated the prognostic value of these differential MRGs for predicting patients' overall survival by univariable and multivariable Cox regression analysis. Six metabolic genes (ACOX3, APOE, DIO2, HSD17B4, NUAK1, and WHSC1L1) were identified as prognosis-associated hub genes, which were used to build a prognostic model in the training dataset GSE15459 (n = 200), and then validated in the dataset GSE62254 (n = 300).

RESULTS

Patients were divided into high-risk and low-risk subgroups based on the model's risk score, and it was found that patients in the high-risk subgroup had shorter overall survival than those in the low-risk subgroup, both in the training and testing datasets. In addition, for the training and testing cohorts, the area under the ROC curve of the prognostic model for one-year survival prediction was 0.723 and 0.667, respectively, indicating that the model has good predictive performance. Furthermore, we established a nomogram based on tumor stage and risk score to effectively predict the overall survival (OS) of GAD patients. The expression of 6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further confirmed that their expression influenced OS in GAD patients.

CONCLUSION

Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy.

摘要

背景

肿瘤代谢研究对于阐明肿瘤发生机制及预测患者预后具有重要价值。然而，代谢相关基因（MRGs）在胃腺癌（GAD）中的预后作用仍知之甚少。

方法

我们从基因表达综合数据库（GEO）下载了GAD的基因芯片数据集GSE79973（n = 20），以比较正常组织和肿瘤组织之间的差异表达基因（DEGs）。然后，我们从这些DEGs中提取MRGs，并通过单变量和多变量Cox回归分析系统地研究这些差异MRGs对预测患者总生存期的预后价值。六个代谢基因（ACOX3、APOE、DIO2、HSD17B4、NUAK1和WHSC1L1）被鉴定为与预后相关的枢纽基因，用于在训练数据集GSE15459（n = 200）中构建预后模型，然后在数据集GSE62254（n = 300）中进行验证。

结果

根据模型的风险评分将患者分为高风险和低风险亚组，发现在训练和测试数据集中，高风险亚组患者的总生存期均短于低风险亚组患者。此外，对于训练和测试队列，用于预测一年生存期的预后模型的ROC曲线下面积分别为0.723和0.667，表明该模型具有良好的预测性能。此外，我们基于肿瘤分期和风险评分建立了列线图，以有效预测GAD患者的总生存期（OS）。通过免疫组织化学（IHC）证实了6个MRGs在蛋白水平的表达。Kaplan-Meier生存分析进一步证实它们的表达影响GAD患者的OS。