Hypoxia-induced GBE1 expression promotes tumor progression through metabolic reprogramming in lung adenocarcinoma

Li, Lifeng; Li, Yang; Fan, Zhirui; Xue, Wenhua; Shen, Zhibo; Yuan, Yanggang; Sun, Xiangdong; Wang, Dan; Lian, Jingyao; Wang, Liping; Zhao, Jie; Zhang, Yi

doi:10.1038/s41392-020-0152-8

Cited by 62 publications

(55 citation statements)

References 53 publications

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“…In various cancers, the expression of GPI is induced by c-Myc, and HIF-1 is overexpressed at the same time ( 43 , 44 ). HIF-1 can induce GBE1 upregulation, which would decrease CCL5 and CXCL10 secretion, hindering the recruitment of CD8+ T lymphocytes ( 45 , 46 ). GPI can also induce the protein expression of matrix metalloproteinase-3 and thereby promote the invasiveness of tumors ( 47 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Liang

Liu

et al. 2021

Front. Oncol.

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BackgroundCD8+ T cells are one of the central effector cells in the immune microenvironment. CD8+ T cells play a vital role in the development and progression of lung adenocarcinoma (LUAD). This study aimed to explore the key genes related to CD8+ T-cell infiltration in LUAD and to develop a novel prognosis model based on these genes.MethodsWith the use of the LUAD dataset from The Cancer Genome Atlas (TCGA), the differentially expressed genes (DEGs) were analyzed, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Combined with the CIBERSORT algorithm, the gene module in WGCNA, which was the most significantly correlated with CD8+ T cells, was selected for the subsequent analyses. Key genes were then identified by co-expression network analysis, protein–protein interactions network analysis, and least absolute shrinkage and selection operator (Lasso)-penalized Cox regression analysis. A risk assessment model was built based on these key genes and then validated by the dataset from the Gene Expression Omnibus (GEO) database and multiple fluorescence in situ hybridization experiments of a tissue microarray.ResultsFive key genes (MZT2A, ALG3, ATIC, GPI, and GAPDH) related to prognosis and CD8+ T-cell infiltration were identified, and a risk assessment model was established based on them. We found that the risk score could well predict the prognosis of LUAD, and the risk score was negatively related to CD8+ T-cell infiltration and correlated with the advanced tumor stage. The results of the GEO database and tissue microarray were consistent with those of TCGA. Furthermore, the risk score was higher significantly in tumor tissues than in adjacent lung tissues and was correlated with the advanced tumor stage.ConclusionsThis study may provide a novel risk assessment model for prognosis prediction and a new perspective to explore the mechanism of tumor immune microenvironment related to CD8+ T-cell infiltration in LUAD.

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Section: Discussionmentioning

confidence: 99%

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Liang

Liu

et al. 2021

Front. Oncol.

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“…TFRC promotes the proliferation and metastasis of cancer cells by up-regulating the expression of AXIN2 to accelerate the progress of epithelial ovarian cancer (41). Transforming growth factor (TGFA) stimulates cell growth and proliferation, and its overexpression is associated with the survival rate of patients with many tumors (42 NFKB1 [ 7] XRCC6 [ 7] PGK1 [ 6] ENO1 [ 5] PFKP [ 5] TEK [ 5] SPP1 [ 4] TFRC [ 4] ADM [ 2] GAPDH [ 2] STC1 [ 2] DDIT3 [ 1] FGF3 [ 1] PLAUR [ 1] TGFA [ 1] EPAS1 [10] NFKB1 [ 7] XRCC6 [ 7] PGK1 [ 6] ENO1 [ 5] PFKP [ 5] TEK [ 5] SPP1 [ 4] TFRC [ 4] ADM [ 2] GAPDH [ 2] STC1 [ 2] DDIT3 [ 1] FGF3 [ 1] PLAUR [ 1] TGFA [ 1] * P < 0.001 NFKB1 [10] TEK [ 8] PFKP [ 5] STC1 [ 5] EPAS1 [ 4] PLAUR [ 4] TFRC [ 4] SPP1 [ 3] GAPDH [ 2] PGK1 [ 2]…”

Section: A B C Dmentioning

confidence: 99%

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

Huang¹,

Wang²,

Zhang³

et al. 2021

Transl Lung Cancer Res

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Background: The mechanisms of hypoxia or immune microenvironment in cancer have been studiedrespectively, but the role of hypoxia immune microenvironment in non-small cell lung cancer (NSCLC) still needs further exploration.Methods: By applying the K-means algorithm, 1,121 patients with NSCLC were divided into three categories. We evaluated the constructed signature in order to link it with the prognosis, which was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression analysis.Results: A total of three clusters were obtained by clustering five Gene Expression Omnibus (GEO) data sets. Gene Set Variation Analysis (GSVA) and immune infiltration analysis were performed to explore the biological behavior. Cluster one presented an activated state of oncogenic pathways, and compared with the other two clusters, the median risk score was the highest, which was the reason for its poor survival. Cluster three showed that the immune pathway was active and the median risk score was the lowest, so the survival was the best. However, cluster two presented a state in which both immune and matrix pathways were activate. This was manifested as mutual antagonism, and its risk score was in the middle. Its survival was in the middle.Conclusions: This work revealed the role of hypoxia related genes (HRGs) modification in tumor microenvironment, which was conducive to our comprehensive analysis of the prognosis of NSCLC, and provided direction and guidance for clinical immunotherapy.

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“…2.11 Transwell and wound-healing assays Transwell (8.0 µm pore size, Corning, USA) and wound-healing assays were used to detect the migration of tumor cells, which has been described detailedly in a previous paper [19].…”

Section: Cell Counting Kit-8 (Cck-8) and Colony Formation Assaysmentioning

confidence: 99%

m6A Demethylase FTO Promotes Tumor Progression via Regulation of Lipid Metabolism in Esophageal Cancer

Duan

Yang

Wang

et al. 2021

Preprint

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BackgroundEpitranscriptomics studies have contributed greatly to the development of research on human cancers. In recent years, N6-methyladenosine (m6A), an RNA modification on the N-6 position of adenosine, has been found to play a potential role in epigenetic regulation. Therefore, we aimed to evaluate the regulation of cancer progression properties by m6A. ResultsWe found that m6A demethylase fat mass and obesity-associated protein (FTO) was highly expressed in esophageal cancer (EC) stem-like cells, and that its level was also substantially increased in EC tissues, which was closely correlated with a poor prognosis in EC patients. FTO knockdown significantly inhibited the proliferation, invasion, stemness, and tumorigenicity of EC cells, whereas FTO overexpression promoted these characteristics. Furthermore, integrated transcriptome and meRIP-seq analyses revealed that HSD17B11 may be a target gene regulated by FTO. Moreover, FTO promoted the formation of lipid droplets in EC cells by enhancing HSD17B11 expression. Furthermore, depleting YTHDF1 increased the protein level of HSD17B11. ConclusionsThese data indicate that FTO may rely on the reading protein YTHDF1 to affect the translation pathway of the HSD17B11 gene to regulate the formation of lipid droplets in EC cells, thereby promoting the development of EC. The understanding of the role of epitranscriptomics in the development of EC will lay a theoretical foundation for seeking new anticancer therapies.

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Hypoxia-induced GBE1 expression promotes tumor progression through metabolic reprogramming in lung adenocarcinoma

Cited by 62 publications

References 53 publications

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

m6A Demethylase FTO Promotes Tumor Progression via Regulation of Lipid Metabolism in Esophageal Cancer

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