Construction of a ceRNA network in glioma and analysis of its clinical significance.

BACKGROUND: Glioma is the most common central nervous system tumor with a poor survival rate and prognosis. Previous studies have found that long non-coding RNA (lncRNA) and competitive endogenous RNA (ceRNA) play important roles in regulating various tumor mechanisms. We obtained RNA-Seq data of glioma and normal brain tissue samples from TCGA and GTEx databases and extracted the lncRNA and mRNA expression data. Further, we analyzed these data using weighted gene co-expression network analysis and differential expression analysis, respectively. Differential expression analysis was also carried out on the mRNA data from the GEO database. Further, we predicted the interactions between lncRNA, miRNA, and targeted mRNA. Using the CGGA data to perform univariate and multivariate Cox regression analysis on mRNA. RESULTS: We constructed a Cox proportional hazard regression model containing four mRNAs and performed immune infiltration analysis. Moreover, we also constructed a ceRNA network including 21 lncRNAs, two miRNAs, and four mRNAs, and identified seven lncRNAs related to survival that have not been previously studied in gliomas. Through the gene set enrichment analysis, we found four lncRNAs that may have a significant role in tumors and should be explored further in the context of gliomas. CONCLUSIONS: In short, we identified four lncRNAs with research value for gliomas, constructed a ceRNA network in gliomas, and developed a prognostic prediction model. Our research enhances our understanding of the molecular mechanisms underlying gliomas, providing new insights for developing targeted therapies and efficiently evaluating the prognosis of gliomas.

Comprehensive analysis of ceRNA network related to lincRNA in glioblastoma and prediction of clinical prognosis.

BACKGROUND: Long intergenic non-coding RNAs (lincRNAs) are capable of regulating several tumours, while competitive endogenous RNA (ceRNA) networks are of great significance in revealing the biological mechanism of tumours. Here, we aimed to study the ceRNA network of lincRNA in glioblastoma (GBM). METHODS: We obtained GBM and normal brain tissue samples from TCGA, GTEx, and GEO databases, and performed weighted gene co-expression network analysis and differential expression analysis on all lincRNA and mRNA data. Subsequently, we predicted the interaction between lincRNAs, miRNAs, and target mRNAs. Univariate and multivariate Cox regression analyses were performed on the mRNAs using CGGA data, and a Cox proportional hazards regression model was constructed. The ceRNA network was further screened by the DEmiRNA and mRNA of Cox model. RESULTS: A prognostic prediction model was constructed for patients with GBM. We assembled a ceRNA network consisting of 18 lincRNAs, 6 miRNAs, and 8 mRNAs. Gene Set Enrichment Analysis was carried out on four lincRNAs with obvious differential expressions and relatively few studies in GBM. CONCLUSION: We identified four lincRNAs that have research value for GBM and obtained the ceRNA network. Our research is expected to facilitate in-depth understanding and study of the molecular mechanism of GBM, and provide new insights into targeted therapy and prognosis of the tumour.

BCAT1 alleviates early brain injury by inhibiting ferroptosis through PI3K/AKT/mTOR/GPX4 pathway after subarachnoid hemorrhage.

Regulation of the redox system by branched-chain amino acid transferase 1 (BCAT1) is of great significance in the occurrence and development of diseases, but the relationship between BCAT1 and subarachnoid hemorrhage (SAH) is still unknown. Ferroptosis, featured by iron-dependent lipid peroxidation accompanied by the depletion of glutathione peroxidase 4 (GPX4), has been implicated in the pathological process of early brain injury after subarachnoid hemorrhage. This study established SAH model by endovascular perforation and adding oxyhemoglobin (Hb) to HT22 cells and delved into the mechanism of BCAT1 in SAH-induced ferroptotic neuronal cell death. It was found that SAH-induced neuronal ferroptosis could be inhibited by BCAT1 overexpression (OE) in rats and HT22 cells, and BCAT1 OE alleviated neurological deficits and cognitive dysfunction in rats after SAH. In addition, the effect of BCAT1 could be reversed by the Ly294002, a specific inhibitor of the PI3K pathway. In summary, our present study indicated that BCAT1 OE alleviated early brain injury EBI after SAH by inhibiting neuron ferroptosis via activation of PI3K/AKT/mTOR pathway and the elevation of GPX4. These results suggested that BCAT1 was a promising therapeutic target for subarachnoid hemorrhage.

[Antitumor effect of baicalin on rat brain glioma].

OBJECTIVE: To investigate the therapeutic mechanism of baicalin on rat brain glioma. METHODS: Deep brain glioma models were established by injection of glioma cell line C6 cells into the brain of Wistar rats. The rats at 7 days after modeling were randomly divided into tumor control group (0.9% NaCl solution 30 mg×kg(-1)×d(-1) gavage)and experimental groups. The experimental rats was divided into 3 groups: low dose group (50 mg×kg(-1)×d(-1)), middle dose group (100 mg×kg(-1)×d(-1)) and high dose group (200 mg×kg(-1)×d(-1)), given the baicalin by gavage. Pathological and electron microscopic changes were observed. The expressions of p53 and Bcl-2 were determined by immunohistochemistry, and the changes of MRI, the average survival time and body weight of the rats in each group after treatments were analyzed. RESULTS: Compared with the control group, the tumor diameter and volume of high dose group rats before sacrifice were significantly reduced (P < 0.01), and the survival time was significantly prolonged (P < 0.01). Immunohistochemistry revealed strong positive expression rate of mutant p53 (84.47 ± 3.74)% and moderately positive rate (47.28 ± 2.38)% in the control group, significantly higher than that in the negative group (12.91 ± 1.07)% (P < 0.01). The positive rate of mutant p53 of the high dose group was (46.42 ± 2.19)%, significantly lower than that of the control group (84.47 ± 3.74)% (P < 0.01). The expression rate of Bcl-2 in the control group was strongly positive (86.51 ± 4.17)% and moderate positive (48.19 ± 2.11)%, significantly higher than that of the negative group (10.36 ± 1.43)% (P < 0.01). Electron microscopy revealed that baicalin caused damages of the cell nuclei and organelles in the gliomas. CONCLUSIONS: Baicalin has significant inhibitory effect on glioma in vivo, and its mechanism may be related to cell apoptosis induced by down-regulated expression of mutant p53, but not related with Bcl-2 expression.

Constructing a signature based on the SIRT family to help the prognosis and treatment sensitivity in glioma patients.

Enzymes of the silent information regulator (SIRT) family exert crucial roles in basic cellular physiological processes including apoptosis, metabolism, ageing, and cell cycle progression. They critically contribute to promoting or inhibiting cancers such as glioma. In the present study, a new gene signature of this family was identified for use in risk assessment and stratification of glioma patients. To this end, the transcriptome and relevant clinical records of patients diagnosed with glioma were obtained from the Cancer Genomic Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LASSO regression and multivariate Cox analyses were used to establish the signature. Using Kaplan-Meier analyses, overall survival (OS) was assessed and compared between a training and an external test datasets which showed lower OS in patients with high risk of glioma compared to those with low risk. Further, ROC curve analyses indicated that the SIRT-based signature had the desired accuracy and universality for evaluating the prognosis of glioma patients. Using univariate and multivariate Cox regression analyses, the SIRT-based signature was confirmed as an independent prognostic factor applicable to subjects in the TCGA and CGGA databases. We also developed an OS nomogram including gender, age, risk score, pathological grade, and IDH status for clinical decision-making purposes. ssGSEA analysis showed a higher score for various immune subgroups (e.g., CD8+ T cells, DC, and TIL) in samples from high-risk patients, compared to those of low-risk ones. qPCR and western blotting confirmed the dysregulated expression of SIRTs in gliomas. Taken together, we developed a new signature on the basis of five SIRT family genes, which can help accurately predict OS of glioma patients. In addition, the findings of the present study suggest that this characteristic is associated with differences in immune status and infiltration levels of various immune cells in the tumor microenvironment.

Four common polymorphisms in microRNAs and the risk of adult glioma in a Chinese case-control study.

Emerging evidence has shown that microRNAs (miRNAs) participate in human carcinogenesis as tumor suppressors or oncogenes. It has been suggested that four common single nucleotide polymorphisms (SNPs; miR-146aG > C, 149C > T, 196a2C > T, and 499A > G) are associated with susceptibility to numerous malignancies. However, published results are inconsistent and inclusive. To further investigate the role of these loci, we examined the association of the miRNA polymorphisms with the risk of gliomas in a Han population in northeastern China. Both miR-146aG > C and 196a2C > T showed allelic differences between glioma patients and healthy controls in the studied population, with an OR of 1.30 (P = 0.0006) and an odds ratio (OR) of 1.25 (P = 0.003), respectively. Logistic regression analysis also revealed that the 146aG > C and 196a2C > T wild-type homozygous carriers had an increased glioma risk compared to the variant carriers. Besides, in pairwise comparisons two SNP combinations were associated with the risk of glioma. Among others, carriers of both homozygous risk genotypes, i.e., 146aGG and 196a2CC were associated with a nearly 4-fold increased risk of glioma (OR = 3.77, P = 1.3 × 10(-4)). Overall, glioma risk increased with increasing numbers of risk variant alleles. These results suggest that the miR-146aG > C and 196a2C > T might influence the risk of developing glioma in a northeastern Han Chinese population.

Genetic polymorphisms in the DNA repair gene XRCC1 and susceptibility to glioma in a Han population in northeastern China: a case-control study.

BACKGROUND: Several single nucleotide polymorphisms (SNPs) in the X-ray cross-complementing group 1 (XRCC1) gene have been shown to influence DNA repair and to modify cancer susceptibility. To investigate the role of these loci further, we examined the association of three XRCC1 polymorphisms with the risk of gliomas in a Han population in northeastern China. METHODS: Using a PCR-RFLP method, XRCC1 Arg194Trp, Arg280His and Arg399Gln were genotyped in 624 glioma patients and 580 healthy controls. RESULTS: Significant differences in the distribution of the Arg399Gln allele were detected between glioma patients and healthy controls by a logistic regression analysis (OR=1.35, 95%CI 1.17-1.68, P=0.001). Our data also revealed that the Arg399Gln variant (allele A) carriers had an increased glioma risk compared to the wild-type (allele G) homozygous carriers (OR=1.40, 95%CI 1.12-1.76, P=0.003). CONCLUSIONS: These results suggest that the XRCC1 Arg399Gln might influence the risk of developing glioma in a Han population in northeastern Chinese.

[Copper complexing capacities of seawater in surface microlayer in Jiaozhou Bay].

Copper complexing capacities (CC) and conditional stability constants (K) of seawater surface microlayer (SML) and subsurface layer (SSL) in Jiaozhou Bay were determined by the anodic stripping voltammetry (ASV) technique in 2004. The distribution regularity and the relationship with COD, DOC, TN, TP of Jiaozhou Bay were discussed systematically. The results are as following: The copper complexing capacities show the enrichment phenomenon of SML in Jiaozhou Bay. The average copper complexing capacities of SML and SSL are 3.85 x 10(-7) mol x L(-1), 2.45 x 10(-7) mol x L(-1) respectively, and the average enrichment factor of SML is 1.56. The average conditional stability constants (lgK) of SML and SSL are the same 7.21. K(SML) is lower than K(SSL) in March and September, but K(SML) is higher than K(SSL) in June and December. The copper complexing capacities in Jiaozhou Bay become lower by one turn of northeast, northwest, south, center, entrance and the other turn of September, June, December, March. Meanwhile the obviously positive relationship between copper complexing capacities and COD, DOC of SML and SSL is found, comparing to the negative relationship between copper complexing capacities and TN, TP.