Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

Deng, Teng; Gong, Yizhen; Wang, Xiangkun; Liao, Xiwen; Huang, Ketuan; Zhu, Guangzhi; Chen, Hainan; Guo, Fang-Zhou; Mo, Ligen; Li, Le‐Qun

doi:10.12659/msm.913602

Cited by 18 publications

(19 citation statements)

References 60 publications

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“…However, correlation between EZR gene expression in breast cancer and its correlation with patients’ survival is not fully understood. In recent years, with the development of cancer databases, more and more studies have been published in the aspects of deep data mining in the database through bioinformatics analysis . In the present work, we investigated the EZR gene expression in breast cancer, function enrichment and correlation with the prognosis through bioinformatics analysis and immunohistochemistry assay in order to provide a greater understanding of the EZR gene in breast cancer.…”

Section: Introductionmentioning

confidence: 99%

High expression of EZR (ezrin) gene is correlated with the poor overall survival of breast cancer patients

Zhang

Zhang²,

Rongge

et al. 2019

Thoracic Cancer

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Background To evaluate the EZR (ezrin) gene expression in breast cancer and correlation with the prognosis through bioinformatics analysis and immunohistochemistry assay. Methods EZR gene expression in breast cancer and corresponding normal breast tissue was compared in the TCGA database. Protein‐protein interaction (PPI) network relevant EZR was established through the STRING database. The correlation between EZR expression and prognosis of breast cancer was analyzed by the log‐rank analysis from the TCGA. Ezrin protein (coded by EZR) expression was also examined by immunohistochemistry assay in 120 breast cancer patients. Results EZR expression level in tumor tissue was significantly upregulated compared to that of normal breast tissue of breast cancer patients (P < 0.05). In the PPI analysis, there were 51 nodes and 455 edges in the network. The top 10 hub genes of the network were identified. High expression of EZR mRNA was correlated with poor overall survival (OS) of the breast cancer patients (HR = 1.40, P = 0.038). However, the disease‐free survival (DFS) of breast cancer patients did not correlate with the EZR mRNA level (HR = 0.86, P = 0.44). The ezrin protein expression was positive with uniform brown‐yellow granules in the cell membrane, cavity surface and cytoplasm of the breast cancer cells. Of the included 120 cancer samples, 98 cases were positive for ezrin expression and 22 were negative. No correlation was found between ezrin expression site and patients’ clinicopathological features. Conclusion EZR is upregulated in breast cancer and can be used as potential biomarker for overall survival.

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Section: Introductionmentioning

confidence: 99%

High expression of EZR (ezrin) gene is correlated with the poor overall survival of breast cancer patients

Zhang

Zhang²,

Rongge

et al. 2019

Thoracic Cancer

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“…Interestingly, Canty and Kadler found the relationship between collagen molecules and ECM. Similarly, Deng et al also found that the ECM‐receptor interaction pathway had a strong association with COL1A1, COL1A2, COL3A1, and so on. In addition, COL5A2 and COL3A1 collagen‐related genes have been identified that they participated in the remodeling of ECM .…”

Section: Discussionmentioning

confidence: 85%

“…And it has been proven that the expression level of COL1A2 in primary medulloblastoma was significantly elevated, higher than other medulloblastomas . COL3A1, encoding collagen type III alpha 1 chain, with high expression level was associated with glioma grades and it significantly increased in malignant glioma . Kuivaniemi and Tromp also have proven that COL3A1 gene participated in the progression of glioma.…”

Section: Discussionmentioning

confidence: 96%

Identification of genes related to low‐grade glioma progression and prognosis based on integrated transcriptome analysis

Jiang

Guo

et al. 2019

J of Cellular Biochemistry

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Glioma is one of the most common types of human brain tumor, with high mortality in high-grade gliomas (HGG). Low-grade gliomas (LGG) can progress into HGG, leading to poor prognosis. However, it is unclear what factors affect the progression of LGG to HGG. This study aims to explore the function of the crosstalk genes on the progression and prognosis of LGG using bioinformatics analysis. Integrated transcriptome analysis was used to screen differentially expressed genes (DEGs). Then, gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the association between DEGs and gene functions and pathways by ClusterProfiler package and ClueGO plug-in. Protein-protein interaction (PPI) network analysis was applied to explore the connection between genes and biological processes. Subsequently, the gene clusters were analyzed using the Centiscape and molecular complex detection (MCODE) plug-in in Cytoscape software, where the crosstalk genes were identified for further study. Ultimately, the UALCAN website and Gene Expression Profiling Interactive Analysis (GEPIA) website were performed to visualize the expression levels and survival curves of genes, respectively. There were 74DEGs identified in glioma, including 55 upregulated genes and 19 downregulated genes, which mainly were enriched in extracellular matrix (ECM)receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and so on. Then, six crosstalk genes were selected, including COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 genes. Overall survival (OS) analysis of crosstalk genes was conducted on the GEPIA website. High expression levels of crosstalk genes were closely related to the low survival rate of patients withLGG. The overexpressed crosstalk genes, such as COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 may participate in the progression and poor prognosis of LGG through the ECM-receptor interaction pathway. K E Y W O R D S bioinformatics, crosstalk genes, glioma, prognosis, progression Yongcan Guo and Hualin Tao contributed equally to this study.Glioma is the most common primary tumor of the central nervous system, 1 diagnosed based on pathological grade and molecular subtype. And gliomas are classified into grades I to IV by World Health Organization (WHO), including low-grade (WHO grades I-II) and high-grade (WHO grades III-IV) gliomas. 2 High-grade gliomas (HGG) have a high mortality rate and low five-year survival rate with less than 10%. 3 The effect of radiotherapy and chemotherapy is not obvious for HGG, leading to the median survival time of 14 to 17 months, 4 less than the low-grade glioma (LGG), of which the average survival time is approximately 10 years. By contrast, in case the LGG progress into HGG, the mortality rate will increase. 5 Therefore, it is necessary to explore the factors that have an influence on the progression of LGG to HGG, aiming at slowing down the progression and extending survival time of patients with LGG. In recent years, most ...

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“…However, the exact pathogenesis of glioma is still unclear [16,17]. In recent years, with the development of molecular biology technology, more and more evidence has shown that the occurrence and prognosis of glioma is related to the different expressed oncogenes and tumor suppressor genes [18][19][20].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics Analysis of the Expression of ATP binding cassette subfamily C member 3 (ABCC3) in Human Glioma

Sun

Zhang

2020

Open Medicine

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AbstractObjectiveTo investigate the expression of the ABCC3 gene in human glioma and its correlation with the patient’s prognosis.MethodsThe cancer genome atlas (TCGA) database was used to analyze the differential expression of the ABCC3 gene in human glioma. The STRING database was used to construct the protein-protein interaction (PPI) network of the ABCC3 gene coding protein. The co-expression genes relevant to the ABCC3 gene were analyzed by the Pearson correlation test. A log-rank test was used to analyze the difference of overall survival (OS) and disease-free survival (DFS) between the high and low ABCC3 gene expression groups.ResultsThe expression level of the ABCC3 gene in glioma tissues was lower than that of corresponding normal brain tissues. The PPI network contains 51 nodes with the average node degree of 13.3 and the local clustering coefficient of 0.72 which indicated that the PPI enrichment was significant (p<0.001). Ten hub genes (ABCC3,NR1I2,NR1H4,-CYP7A1,SLC10A1,CYP3A4,UGT1A1,UGT1A8,UGT1A6 and ALB) were identified by the cytoscape software. The KEGG analysis was enriched in drug metabolism - cytochrome P450 and PPAR signaling pathway. CFI gene expression level was positive correlated with the ABCC3 expression level (r=0.71, p<0.05). And the CNRIP1 gene expressed was negative correlated with ABCC3 expression (r=-0.43, p<0.05). The overall survival (HR=2.8, P<0.05) and disease-free survival rates (HR=2.0, P<0.05) of patients with ABCC3 low expression glioma were significantly higher than those of patients with high expression of ABCC3. Conclusion The expression level of the ABCC3 gene in glioma was decreased compared to normal brain tissue. The overall survival and disease-free survival of in the ABCC3 low-expression group was significant decreased.

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Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma

Cited by 18 publications

References 60 publications

High expression of EZR (ezrin) gene is correlated with the poor overall survival of breast cancer patients

High expression of EZR (ezrin) gene is correlated with the poor overall survival of breast cancer patients

Identification of genes related to low‐grade glioma progression and prognosis based on integrated transcriptome analysis

Bioinformatics Analysis of the Expression of ATP binding cassette subfamily C member 3 (ABCC3) in Human Glioma

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