Extracellular Glutathione Peroxidase GPx3 and Its Role in Cancer

Chang, Caroline; Worley, Beth L.; Phaëton, Rébécca; Hempel, Nadine

doi:10.3390/cancers12082197

Cited by 152 publications

(120 citation statements)

References 139 publications

(286 reference statements)

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“…Proteomic analysis revealed significantly increased levels of neutrophil gelatinase-associated lipocalin (LCN2), superoxide dismutase (SOD2), glutathione peroxidase 3 (GPX3), S100-A12, and synaptosomal-associated protein 23 (SNAP23) [ 43 ]. Those proteins are related to mitochondrial metabolism, cancer genesis modulation, and phagocytosis; thus, EVs may play a role in CF progression by modulating various pathophysiological mechanisms [ 44 , 45 , 46 ].…”

Section: Balf-evs Modulate Inflammation In Pulmonary Diseasesmentioning

confidence: 99%

EVs from BALF—Mediators of Inflammation and Potential Biomarkers in Lung Diseases

Zaręba

Szymański

Homoncik

et al. 2021

IJMS

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Extracellular vesicles (EVs) have been identified as key messengers of intracellular communication in health and disease, including the lung. EVs that can be found in bronchoalveolar lavage fluid (BALF) are released by multiple cells of the airways including bronchial epithelial cells, endothelial cells, alveolar macrophages, and other immune cells, and they have been shown to mediate proinflammatory signals in many inflammatory lung diseases. They transfer complex molecular cargo, including proteins, cytokines, lipids, and nucleic acids such as microRNA, between structural cells such as pulmonary epithelial cells and innate immune cells such as alveolar macrophages, shaping mutually their functions and affecting the alveolar microenvironment homeostasis. Here, we discuss this distinct molecular cargo of BALF-EVs in the context of inducing and propagating inflammatory responses in particular acute and chronic lung disorders. We present different identified cellular interactions in the inflammatory lung via EVs and their role in lung pathogenesis. We also summarize the latest studies on the potential use of BALF-EVs as diagnostic and prognostic biomarkers of lung diseases, especially of lung cancer.

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Section: Balf-evs Modulate Inflammation In Pulmonary Diseasesmentioning

confidence: 99%

EVs from BALF—Mediators of Inflammation and Potential Biomarkers in Lung Diseases

Zaręba

Szymański

Homoncik

et al. 2021

IJMS

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“…GPX3 has dual properties in tumors, acting as a tumor suppressor in some tumors and as a tumor promoter in others. 26 In colorectal cancer, tumor cells with low GPX3 expression were more sensitive to chemotherapy drugs, such as oxaliplatin and cisplatin. 27 ENPP2 can encode a secreted glycoprotein autotaxin, which converts lysophosphatidylcholine into lysophosphatidic acid, and the autotaxin–LPA axis is essential for cell survival, migration, proliferation, and differentiation in many cancers.…”

Section: Discussionmentioning

confidence: 99%

Identification of Metabolic-Associated Genes for the Prediction of Colon and Rectal Adenocarcinoma

Cui¹,

Han²,

Zhang³

et al. 2021

OTT

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Background and Aim: Uncontrolled proliferation is the most prominent biological feature of tumors. In order to rapidly proliferate, tumor cells regulate their metabolic behavior by controlling the expression of metabolism-related genes (MRGs) to maximize the utilization of available nutrients. In this study, we aimed to construct prognosis models for colorectal adenocarcinoma (COAD) and rectum adenocarcinoma (READ) using MRGs to predict the prognoses of patients. Methods: We first acquired the gene expression profiles of COAD and READ from the TCGA database, and then utilized univariate Cox analysis, Lasso regression, and multivariable Cox analysis to identify the MRGs for risk models. Results: Eight genes (CPT1C, PLCB2, PLA2G2D, GAMT, ENPP2, PIP4K2B, GPX3, and GSR) in the colon cancer risk model and six genes (TDO2, PKLR, GAMT, EARS2, ACO1, and WAS) in the rectal cancer risk model were identified successfully. Multivariate Cox analysis indicated that these two models could accurately and independently predict overall survival (OS) for patients with COAD or READ. Furthermore, functional enrichment analysis was used to identify the metabolism pathway of MRGs in the risk models and analyzed these genes comprehensively. Then, we verified the prognosis model in independent COAD cohorts (GSE17538) and detected the correlations of the protein expression levels of GSR and ENPP2 with prognosis for COAD or READ. Conclusion:In this study, 14 MRGs were identified as potential prognostic biomarkers and therapeutic targets for colorectal cancer.

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“…GPX3, the only extracellular GPX of the family of oxidoreductases, can catalyze the detoxi cation of lipid hydroperoxides by reduced glutathione. GPX3 has dual properties in tumors, acting as a tumor suppressor in some tumors and as a tumor promoter in others 23 . In colorectal cancer, tumor cells with low GPX3 expression were more sensitive to chemotherapy drugs, such as oxaliplatin and cisplatin 24 .…”

Section: Discussionmentioning

confidence: 99%

Survival-associated Metabolic Genes in Colon and Rectal Cancers

Cui

Han²,

He³

et al. 2020

Preprint

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Background Uncontrolled proliferation is the most prominent biological feature of tumors. To rapidly proliferate and maximize the use of available nutrients, tumor cells regulate their metabolic behavior and the expression of metabolism-related genes (MRGs). In this study, we aimed to construct prognosis models for colon and rectal cancers, using MRGs to indicate the prognoses of patients. MethodsWe first acquired the gene expression profiles of colon and rectal cancers from the TCGA and GEO database, and utilized univariate Cox analysis, lasso regression, and multivariable cox analysis to identify MRGs for risk models. Then GSEA and KEGG functional enrichment analysis were utilized to identify the metabolism pathway of MRGs in the risk models and analyzed these genes comprehensively using GSCALite.ResultsEight genes (CPT1C, PLCB2, PLA2G2D, GAMT, ENPP2, PIP4K2B, GPX3, and GSR) in the colon cancer risk model and six genes (TDO2, PKLR, GAMT, EARS2, ACO1, and WAS) in the rectal cancer risk model were identified successfully. Multivariate Cox analysis indicated that the models predicted overall survival accurately and independently for patients with colon or rectal cancer. Furthermore, we identified the metabolism pathway of MRGs in the risk models and analyzed these genes comprehensively. Then, we verified the prognosis model in independent colon cancer cohorts (GSE17538) and detected the correlations of the protein expression levels of GSR and ENPP2 with prognosis for colon or rectal cancer. ConclusionsOur findings demonstrated that 14 MRGs are potential prognostic biomarkers and therapeutic targets of colorectal cancer.

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Extracellular Glutathione Peroxidase GPx3 and Its Role in Cancer

Cited by 152 publications

References 139 publications

EVs from BALF—Mediators of Inflammation and Potential Biomarkers in Lung Diseases

EVs from BALF—Mediators of Inflammation and Potential Biomarkers in Lung Diseases

Identification of Metabolic-Associated Genes for the Prediction of Colon and Rectal Adenocarcinoma

Survival-associated Metabolic Genes in Colon and Rectal Cancers

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