A Comprehensive Analysis of the Glutathione Peroxidase 8 (GPX8) in Human Cancer.
A Comprehensive Analysis of the Glutathione Peroxidase 8 (GPX8) in Human Cancer.
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DOI：
10.3389/fonc.2022.812811
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发表时间：
2022
影响因子：
4.7
通讯作者：
Tian X
中科院分区：
文献类型：
--
作者：
Ren Z;He Y;Yang Q;Guo J;Huang H;Li B;Wang D;Yang Z;Tian X
目前，癌症仍然是世界范围内的主要公共卫生问题。一些研究已经报道GPX 8可能与胃癌和乳腺癌的不良预后相关。然而，GPX 8在泛癌症中的预后潜力仍不清楚。在这项工作中，我们的目的是探索GPX 8在人类癌症中的预后和免疫学作用，并确认GBM中的致癌价值。采用TCGA、CPTAC和GEO数据库进行生存分析。基于TCGA的RNAseq和Methylation 450数据，使用R语言和软件包“ggplot 2”分析肿瘤中GPX 8启动子区域的DNA甲基化。在cBioPortal中研究了来自TCGA癌症的GPX 8的遗传改变。采用R软件包“GSVA”和“ssGSEA”评价GPX 8表达与免疫浸润的相关性。KEGG网站用于途径分析。通过STRING网站和GEPIA预测GPX 8结合蛋白。使用R软件包“ggplot 2”和“clusterprofile”来分析和可视化GO和KEGG分析。在合适的条件下培养正常人星形胶质细胞系和三种GBM细胞系。通过Lipofectamine 3000将shRNA转移到细胞中。采用qRT-PCR和WB检测GPX 8的表达。采用创伤愈合实验和transwell实验检测细胞的侵袭转移能力。收集GBM患者的肿瘤组织和癌旁组织。WB法检测GPX 8蛋白的表达。GPX 8是多种癌症的有价值的诊断生物标志物，包括GBM/LGG（多形性胶质母细胞瘤/脑低级别胶质瘤）、KIRC（肾透明细胞癌）、KIRP（肾乳头状细胞癌）和STAD（胃腺癌）。此外，我们观察到GPX 8的表达与几种肿瘤（如GBM/LGG）启动子区域DNA甲基化降低之间存在相关性。我们的结果表明GPX 8表达与免疫浸润呈正相关。此外，富集分析表明，抗氧化活性主要参与GPX 8的功能机制。特别地，我们首先证实了GPX 8在GBM细胞中的上调，并观察到通过敲低GPX 8对迁移和侵袭表型的抑制。进一步证实GPX 8在GBM肿瘤组织中的表达高于癌旁组织。我们的研究表明GPX 8表达与临床预后、DNA甲基化和免疫浸润相关。此外，我们首次证实GPX 8在GBM细胞中高度表达，并有助于迁移和侵袭。这些结果提供了一种预测性生物标志物，并全面了解了GPX 8在多种肿瘤类型，特别是GBM中的表达。
Nowadays, cancer is still a leading public health problem all over the world. Several studies have reported the GPX8 could be correlated with the poor prognostic of Gastric Cancer and Breast Cancer. However, the prognostic potential of GPX8 in pan-cancer remains unclear. In this work, we aimed to explore the prognostic and immunological role of GPX8 in human cancer and confirm the oncogenic value in GBM. The data of TCGA, CPTAC and GEO databases were adopted for the survival analysis. Based on the RNAseq and Methylation450 data of TCGA, the R language and package “ggplot2” were used to analyze the DNA methylation at the region of the promoter of GPX8 in tumors. The genetic alteration of GPX8 from TCGA cancers was investigated in cBioPortal. The R package “GSVA” and “ssGSEA” were employed to evaluate the correlation of GPX8 expression with the immune infiltration. The KEGG website was used for pathway analysis. The STRING website and GEPIA were performed to predict GPX8-binding proteins. The R package “ggplot2” and “clusterprofile” were used to analyze and visualize the GO and KEGG analysis. A normal human astrocyte cell line and three GBM cell lines were cultured under suitable conditions. The shRNA was transferred to cells by Lipofectamine 3000. The qRT-PCR and WB were adopted to detect the expression of GPX8. The wound-healing assay and transwell assay were taken to analyze the invasive and metastatic abilities. The tumor tissues and paracancerous ones were collected from patients with GBM. WB assay was employed to analyze the expression of GPX8 protein. GPX8 was a valuable diagnostic biomarker in multiple cancers, including GBM/LGG (glioblastoma multiforme/Brain lower grade glioma), KIRC (kidney renal clear cell carcinoma), KIRP (kidney renal papillary cell carcinoma) and STAD (stomach adenocarcinoma). Moreover, we observed a correlation between the expression of GPX8 and the reduced DNA methylation at the promoter region in several tumors, such as GBM/LGG. Our results indicated a positive correlation between the GPX8 expression and immune infiltration. In addition, the enrichment analysis demonstrated that antioxidant activity was mainly involved in the functional mechanism of GPX8. In particular, we first confirmed the up-regulated of GPX8 in GBM cells and observed the suppression of migrative and invasive phenotypes by knockdown of GPX8. Furthermore, we confirmed the expression of GPX8 was higher in GBM tumor tissues than paracancerous ones. Our study showed a correlation of GPX8 expression with clinical prognosis, DNA methylation and immune infiltrates. Furthermore, we first confirmed GPX8 was highly expressed in GBM cells and contributed to migration and invasion. These results provided a predictive biomarker and an inclusive understanding of the GPX8 expression in multiple tumors types, especially in GBM.
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影响因子：
11.2
作者：
Miao L;Liu Q;Lin CM;Luo C;Wang Y;Liu L;Yin W;Hu S;Kim WY;Huang L
通讯作者：
Huang L
影响因子：
16.6
作者：
Hamarsheh S;Groß O;Brummer T;Zeiser R
通讯作者：
Zeiser R
影响因子：
16.2
作者：
Feng, Rui-Mei;Zong, Yi-Nan;Xu, Rui-Hua
通讯作者：
Xu, Rui-Hua
影响因子：
32.4
作者：
Fielding, Ceri A.;Jones, Gareth W.;McLoughlin, Rachel M.;McLeod, Louise;Hammond, Victoria J.;Uceda, Javier;Williams, Anwen S.;Lambie, Mark;Foster, Thomas L.;Liao, Chia-Te;Rice, Christopher M.;Greenhill, Claire J.;Colmont, Chantal S.;Hams, Emily;Coles, Barbara;Kift-Morgan, Ann;Newton, Zarabeth;Craig, Katherine J.;Williams, John D.;Williams, Geraint T.;Davies, Simon J.;Humphreys, Ian R.;O'Donnell, Valerie B.;Taylor, Philip R.;Jenkins, Brendan J.;Topley, Nicholas;Jones, Simon A.
通讯作者：
Jones, Simon A.
影响因子：
--
作者：
Jiao Y;Wang Y;Guo S;Wang G
通讯作者：
Wang G