Dataset Information

Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in Glioma.

ABSTRACT: Background: Epithelial-mesenchymal transition (EMT) is regulated by induction factors, transcription factor families and an array of signaling pathways genes, and has been implicated in the invasion and progression of gliomas. Methods: We obtained the Clinicopathological data sets from Chinese Glioma Genome Atlas (CGGA). The "limma" package was used to analyze the expression of EMT-related genes in gliomas with different pathological characteristics. We used the "ConsensusClusterPlus" package to divide gliomas into two groups to study their correlation with glioma malignancy. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to select seven prognosis-associated genes to build the risk signature, and the coefficients obtained from the LASSO algorithm were used to calculate the risk score which we applied to determine the prognostic value of the risk signature. Univariate and multivariate Cox regression analyses were used to determine whether the risk signature is an independent prognostic indicator. Results: We analyzed the differentially expressed 22 common epithelial-mesenchymal transition-associated genes in 508 gliomas graded by different clinicopathological features. Two glioma subgroups (EM1/2) were identified by consistent clustering of the proteins, of which the EM1 subgroup had a better prognosis than the EM2 subgroup, and the EM2 group was associated with cancer migration and proliferation. Significant enrichment analysis revealed that EMT-related transcriptional regulators and signaling pathways genes were highly related to glioma malignancies. Seven EMT-related genes were used to derive risk scores, which served as independent prognostic markers and prediction factors for the clinicopathological features of glioma. And we found the overall survival (OS) was significantly different between the low- and high-risk groups, the ROC curve indicated that the risk score can predict survival rates for glioma patients. Conclusion: EMT-related induction factors, transcriptional regulators and signaling pathways genes are important players in the malignant progression of glioma and may help in decision making regarding the choice of prognosis assessment and provide us clues to understand EMT epigenetic modification in glioma.

SUBMITTER: Tao C

PROVIDER: S-EPMC7047417 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in Glioma.

Tao Chuming C Huang Kai K Shi Jin J Hu Qing Q Li Kuangxun K Zhu Xingen X

Frontiers in oncology 20200221

<b>Background:</b> Epithelial-mesenchymal transition (EMT) is regulated by induction factors, transcription factor families and an array of signaling pathways genes, and has been implicated in the invasion and progression of gliomas. <b>Methods:</b> We obtained the Clinicopathological data sets from Chinese Glioma Genome Atlas (CGGA). The "limma" package was used to analyze the expression of EMT-related genes in gliomas with different pathological characteristics. We used the "ConsensusClusterPl ...[more]

PMID: 32154177

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Project description:BackgroundTo observe the effects of triptolide (TP) on the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) of glioma cells, and to explore the possible mechanisms of phenotypic changes in EMT.MethodsThe U87 and U251 glioma cell lines were treated TP. The Cell Counting Kit-8 (CCK-8) method was used to detect the half-maximal inhibitory concentration (IC50) of TP in these two cell lines and the inhibition of cell proliferation at the IC50 concentration. The wound-healing experiment and Transwell invasion assay were used to detect the cells' migration and invasion abilities, respectively. Using western blot protocol, the expression levels of the EMT markers were analyzed, and the levels of the autophagy markers were also detected. The pEGFP-C2-LC3B plasmid was transfected into glioma cells, and the effect of TP on autophagy was detected by immunofluorescence. A subcutaneous tumor model in nude mice was established to observe the effect of TP on cell proliferation in vivo, and immunohistochemistry (IHC) was used to detect the expression levels of EMT markers in mouse tumor tissues.ResultsTP significantly inhibited the proliferation of U87 and U251 cells in a dose- and time-dependent manner. TP had a significant inhibitory effect on the migration and invasion of U87 and U251 cells. Western blot showed that TP reversed the process of EMT in glioma cells, which was evidenced by the upregulated expression of the epithelial marker E-cadherin, and the downregulated expression of the mesenchymal markers N-cadherin, Vimentin, ZEB1, Snail, and Slug. TP increased autophagy in glioma cells, increased the LC3B II/I ratio, and upregulated Beclin-1 and Atg-7 expression. Immunofluorescence showed that the number of autophagosomes increased significantly after TP was applied to cells. In the nude mouse subcutaneous tumor model, experiments revealed an inhibitory effect of TP on glioma cell proliferation in vivo. IHC confirmed that the expression of E-cadherin was upregulated in mouse tumor tissues, while the expression levels of N-Cadherin and Vimentin were downregulated.ConclusionsTP can inhibit glioma cell proliferation, migration, and invasion, and reverse EMT progression. The possible mechanism of EMT reversal in glioma cells is that TP induces autophagy.

Project description:ObjectiveGlioma has the highest incidence among the different tumor types within the nervous system, accounting for about 40% of them. Malignant glioma has a high invasion and metastasis rate, which leads to the poor prognosis of patients. By targeting specific genes, microRNAs serve as key regulators in the epithelial-mesenchymal transformation (EMT) process, which could provide new insights into the treatment of glioblastomas (GBM). The detailed molecular role that miR-623 plays in GBM still remains unclear.Materials and methodsThe level of miR-623 in GBM cells was evaluated by RT-PCR. The function of miR-623 overexpression on GBM cell proliferation, migration, and invasion was assessed by MTS, Transwell analysis, and colony formation assay. In addition, a mouse subcutaneous xenograft model was used to study in vivo effects. The binding between miR-623 and TRIM44 was verified by a dual-luciferase reporter assay and the regulatory function of miR-623 on EMT markers was evaluated using Western blot.ResultsThe expression of miR-623 was repressed in the GBM cancer cell lines. MiR-623 overexpression or TRIM44 knockdown attenuated the proliferation, migration, and invasion of GBM cell lines. TRIM44 could facilitate the reverse suppression of EMT and miR-623 in GBM progression. MiR-623 was found to inhibit TRIM44 expression by directly binding to its 3'UTR. In addition, systemic delivery of miR-623 mimic reduced tumor growth and inhibited TRIM44 protein expression in tumor-bearing nude mice. Furthermore, our findings indicated that miR-623 overexpression or TRIM44 down-regulation impeded the proliferation and migratory ability of LN229 and U251MG glioma cells, and miR-623 attenuates TRIM44-induced EMT by directly targeting the 3'UTR of TRIM44, which could serve as preliminary research to identify potential therapeutic targets for future treatment of GBM.ConclusionOverall, microRNA-623 inhibits epithelial-mesenchymal transition to attenuate glioma proliferation by targeting TRIM44.

Project description:ObjectiveThis study aimed to design a weighted co-expression network and a breast cancer (BC) prognosis evaluation system using a specific whole-genome expression profile combined with epithelial-mesenchymal transition (EMT)-related genes; thus, providing the basis and reference for assessing the prognosis risk of spreading of metastatic breast cancer (MBC) to the bone.MethodsFour gene expression datasets of a large number of samples from GEO were downloaded and combined with the dbEMT database to screen out EMT differentially expressed genes (DEGs). Using the GSE20685 dataset as a training set, we designed a weighted co-expression network for EMT DEGs, and the hub genes most relevant to metastasis were selected. We chose eight hub genes to build prognostic assessment models to estimate the 3-, 5-, and 10-year survival rates. We evaluated the models' independent predictive abilities using univariable and multivariable Cox regression analyses. Two GEO datasets related to bone metastases from BC were downloaded and used to perform differential genetic analysis. We used CIBERSORT to distinguish 22 immune cell types based on tumor transcripts.ResultsDifferential expression analysis showed a total of 304 DEGs, which were mainly related to proteoglycans in cancer, and the PI3K/Akt and the TGF-β signaling pathways, as well as mesenchyme development, focal adhesion, and cytokine binding functionally. The 50 hub genes were selected, and a survival-related linear risk assessment model consisting of eight genes (FERMT2, ITGA5, ITGB1, MCAM, CEMIP, HGF, TGFBR1, F2RL2) was constructed. The survival rate of patients in the high-risk group (HRG) was substantially lower than that of the low-risk group (LRG), and the 3-, 5-, and 10-year AUCs were 0.68, 0.687, and 0.672, respectively. In addition, we explored the DEGs of BC bone metastasis, and BMP2, BMPR2, and GREM1 were differentially expressed in both data sets. In GSE20685, memory B cells, resting memory T cell CD4 cells, T regulatory cells (Tregs), γδ T cells, monocytes, M0 macrophages, M2 macrophages, resting dendritic cells (DCs), resting mast cells, and neutrophils exhibited substantially different distribution between HRG and LRG. In GSE45255, there was a considerable difference in abundance of activated NK cells, monocytes, M0 macrophages, M2 macrophages, resting DCs, and neutrophils in HRG and LRG.ConclusionsBased on the weighted co-expression network for breast-cancer-metastasis-related DEGs, we screened hub genes to explore a prognostic model and the immune infiltration patterns of MBC. The results of this study provided a factual basis to bioinformatically explore the molecular mechanisms of the spread of MBC to the bone and the possibility of predicting the survival of patients.

Project description:BackgroundGliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression.MethodsWe downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers.ResultsWe identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells.ConclusionsIn summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Dataset Information

Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in Glioma.

Publications

Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in Glioma.

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