Inhibition of IRE1 modifies effect of glucose deprivation on the expression of TNF?-related genes in U87 glioma cells

Identification of molecular subtypes and a risk model based on inflammation-related genes in patients with low grade glioma

Lower grade gliomas (LGGs) exhibit invasiveness and heterogeneity as distinguishing features. The outcome of patients with LGG differs greatly. Recently, more and more studies have suggested that infiltrating inflammation cells and inflammation-related genes (IRGs) play an essential role in tumorigenesis, prognosis, and treatment responses. Nevertheless, the role of IRGs in LGG remains unclear. In The Cancer Genome Atlas (TCGA) cohort, we conducted a thorough examination of the predictive significance of IRGs and identified 245 IRGs that correlated with the clinical prognosis of individuals diagnosed with LGG. Based on unsupervised cluster analysis, we identified two inflammation-associated molecular clusters, which presented different tumor immune microenvironments, tumorigenesis scores, and tumor stemness indices. Furthermore, a prognostic risk model including ten prognostic IRGs (ADRB2, CD274, CXCL12, IL12B, NFE2L2, PRF1, SFTPC, TBX21, TNFRSF11B, and TTR) was constructed. The survival analysis indicated that the IRGs risk model independently predicted the prognosis of patients with LGG, which was validated in an independent LGG cohort. Moreover, the risk model significantly correlated with the infiltrative level of immune cells, tumor mutation burden, expression of HLA and immune checkpoint genes, tumorigenesis scores, and tumor stemness indices in LGG. Additionally, we found that our risk model could predict the chemotherapy response of some drugs in patients with LGG. This study may enhance the advancement of personalized therapy and improve outcomes of LGG.

The role of TNF-α induced protein 1 in the activation of pro-apoptotic proteins

It is known that Porphyromonas gingivalis/lipopolysaccharide (P. gingivalis/LPS) induces inflammatory diseases via TNF-α-mediated transcription factors. Our recent data shows that TNFAIP1 (TNF-α induced protein 1) is related to TNF-α. However, little is known regarding how TNFAIP1 is involved in the TNF-α-dependent pathway. We therefore focused on the biological function of TNFAIP1 and examined how TNFAIP1 mediates TNF-α and other genes. We found that TNF-α was upregulated and peaks before the upregulation of apoptotic genes such as Bad, Bcl-x, Caspase 3, Catalase, Claspin, Cytochromic, Ho-1/HMOX1/HSP32, or MCI-1 in our time course with TNFAIP1-treated cells. Our findings here may serve as the foundation for future studies linking regulation of TNFAIP1 and intervention of inflammatory disease.

Glucose deprivation affects the expression of genes encoding cAMP-activated protein kinase and related proteins in U87 glioma cells in ERN1 dependent manner

Objective. The aim of this investigation was to study the expression of genes encoding cAMP-activated protein kinase catalytic and regulatory A subunits (PRKACA and PRKAR1A) and related proteins such as cAMP-dependent protein kinase inhibitors A and G (PKIA and PKIG), catalytic subunit A of protein phosphatase 3 (PPP3CA), A-kinase anchoring protein 12 (AKAP12), and praja ring finger ubiquitin ligase 2 (PJA2) in U87 glioma cells in response to glucose deprivation in both control U87 glioma cells and cells with ERN1 (endoplasmic reticulum to nucleus signaling 1) knockdown, the major pathway of the endoplasmic reticulum stress signaling, for evaluation of possible significance of glucose deprivation in ERN1 dependent regulation of glioma growth.Methods. The expression level of PRKA related genes was studied in control (transfected by vector) and ERN1 knockdown U87 glioma cells under glucose deprivation by real-time quantitative polymerase chain reaction.Results. It was shown that the expression level of PRKACA and PKIA genes was down-regulated in control glioma cells treated by glucose deprivation, but PJA2 gene was up-regulated. At the same time, the expression of four other genes (PRKAR1A, PKIG, AKAP12, and PPP3CA) was resistant to this experimental condition. Furthermore, ERN1 knockdown of glioma cells significantly modified the effect glucose deprivation on the expression almost all studied genes. Thus, treatment of glioma cells with inhibited ERN1 enzymatic activity by glucose deprivation lead to a more significant down-regulation of the expression level of PKIA and to suppression PRKAR1A gene expressions. Moreover, the ERN1 knockdown introduced up-regulation of PKIG and AKAP12 gene expressions in glioma cells treated by glucose deprivation and eliminated the sensitivity of PJA2 gene to this experimental condition.Conclusions. Results of this investigation demonstrated that ERN1 knockdown significantly modified the sensitivity of most studied PRKA related gene expressions to glucose deprivation and that these changes are a result of complex interactions of variable endoplasmic reticulum stress related and unrelated regulatory factors and contributed to the suppression of glioma cell proliferation and their possibly chemoresistance.

Effect of Necrosis on the miRNA-mRNA Regulatory Network in CRT-MG Human Astroglioma Cells

Purpose

Glioblastoma multiforme (GBM) is the most common adult primary intracranial tumor. The remarkable features of GBM include central necrosis. MicroRNAs (miRNAs) have been considered as diagnostic/prognostic biomarkers for many cancers, including glioblastoma. However, the effect of necrosis on the miRNA expression profile and predicted miRNA-mRNA regulatory information remain unclear. The purpose of this study is to examine the effect of necrotic cells on the modulation of miRNA and mRNA expression profiles and miRNA-mRNA network in CRT-MG cells.

Materials and Methods

We used human astroglioma cells, CRT-MG, treated with necrotic CRT-MG cells to examine the effect of necrosis on the modulation of miRNA and mRNA by next-generation sequencing. For preparation of necrotic cells, CRT-MGcellswere frozen and thawed through cycle of liquid nitrogen–water bath. The putative miRNA-mRNA regulatory relationshipwas inferred through target information, using miRDB.

Results

The necrotic cells induced dysregulation of 106 miRNAs and 887 mRNAs. Among them, 11 miRNAs that had a negative correlation value of p < 0.05 by the hypergeometric test were screened, and their target mRNAs were analyzed by Gene Ontology enrichment analysis. Using the Kyoto Encyclopedia of Genes and Genomes database, we also found several necrotic cell treatment-activated pathways that were modulated by relevant gene targets of differentially expressed miRNAs.

Conclusion

Our result demonstrated that dysregulation of miRNA and mRNA expression profiles occurs when GBM cells are exposed to necrotic cells, suggesting that several miRNAs may have the potential to be used as biomarkers for predicting GBM progression and pathogenesis.