Predicting Panel of Metabolism and Immune-Related Genes for the Prognosis of Human Ovarian Cancer.
Predicting Panel of Metabolism and Immune-Related Genes for the Prognosis of Human Ovarian Cancer.
复制标题
预测人类卵巢癌预后的代谢和免疫相关基因组
DOI：
10.3389/fcell.2021.690542
复制
发表时间：
2021
影响因子：
5.5
通讯作者：
Xu G
中科院分区：
文献类型：
--
作者：
Zhang L;Sun W;Ren W;Zhang J;Xu G
目的卵巢癌是一种高致死率、预后较差的妇科肿瘤。基因组畸变的鉴定可以预测OC患者的临床预后，并可能最终在未来制定新的治疗策略。本研究的目的是建立与OC代谢和免疫过程相关的综合共表达基因网络。方法对TCGA OC数据集和GSE26193数据集进行转录组分析。从TCGA、GTEX、Oncomine、Kaplan-Meier Plotter、cBioPortal、TIMER、ESTIMATE、CIBERSORT等数据库分析代谢相关基因的mRNA表达水平、枢纽基因组改变、患者生存状态和肿瘤细胞免疫微环境。我们利用qRT-PCR和免疫组织化学进一步验证了这些中枢基因在OC细胞系和组织中的mRNA和蛋白表达水平。结果LASSO-Cox回归分析揭示了7个不同表达的代谢相关基因，包括GFPT2、DGKD、ACACB、ACSM3、IDO1、TPMT和PGP。Cox回归风险模型可作为预测OC患者总体临床生存的独立指标。OC组织中GFPT2、DGKD、ACACB、ACSM3表达下调，IDO1、TPMT、PGP表达上调。此外，DGKD和IDO1与人体免疫系统有显著相关性。结论不同表达的代谢相关基因是预测卵巢癌预后的风险模型。已确定的中枢基因与OC预后相关，可能在影响人体代谢和免疫系统方面发挥重要作用。
Objective Ovarian cancer (OC) is a high deadly gynecologic cancer with a poor prognosis. The identification of genomic aberrations could predict the clinical prognosis of OC patients and may eventually develop new therapeutic strategies in the future. The purpose of this study is to create comprehensive co-expressed gene networks correlated with metabolism and the immune process of OC. Methods The transcriptome profiles of TCGA OC datasets and GSE26193 datasets were analyzed. The mRNA expression level, hub genomic alteration, patient’s survival status, and tumor cell immune microenvironment of metabolism-related genes were analyzed from TCGA, GTEX, Oncomine, Kaplan-Meier Plotter, cBioPortal, TIMER, ESTIMATE, and CIBERSORT databases. We further validated the mRNA and protein expression levels of these hub genes in OC cell lines and tissues using qRT-PCR and immunohistochemistry. Results The LASSO-Cox regression analyses unveiled seven differently expressed metabolism-related genes, including GFPT2, DGKD, ACACB, ACSM3, IDO1, TPMT, and PGP. The Cox regression risk model could be served as an independent marker to predict the overall clinical survival of OC patients. The expression of GFPT2, DGKD, ACACB, and ACSM3 were downregulated in OC tissues, while IDO1, TPMT, and PGP were upregulated in OC tissues than in control. Moreover, DGKD and IDO1 were significantly associated with the human immune system. Conclusion The differently expressed metabolism-related genes were identified to be a risk model in the prediction of the prognosis of OC. The identified hub genes related to OC prognosis may play important roles in influencing both human metabolism and the immune system.
登录
查看更多内容
DOI：
10.1158/1078-0432.ccr-11-2762
发表时间：
2012-02-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Gonzalez-Angulo AM;Iwamoto T;Liu S;Chen H;Do KA;Hortobagyi GN;Mills GB;Meric-Bernstam F;Symmans WF;Pusztai L
通讯作者：
Pusztai L
影响因子：
1.7
作者：
Khadirnaikar, Seema;Kumar, Pranjal;Shukla, Sudhanshu Kumar
通讯作者：
Shukla, Sudhanshu Kumar
DOI：
10.1073/pnas.0604104103
发表时间：
2006-10-17
影响因子：
11.1
作者：
Crotty, Tracy;Cai, Jinjin;Topham, Matthew K.
通讯作者：
Topham, Matthew K.
影响因子：
13.8
作者：
KANOH, H;YAMADA, K;SAKANE, F
通讯作者：
SAKANE, F
卵巢癌和免疫系统。
影响因子：
1.2
作者：
Baert T;Vergote I;Coosemans A
通讯作者：
Coosemans A