Effect of circFOXM1/miR-218-5p on the proliferation, apoptosis and migration of glioma cells.

This study aimed to explore the influence of circFOXM1/miR-218-5p molecular axis in the proliferation, apoptosis and migration of glioma cells. The levels of circFOXM1 and miR-218-5p in glioma and adjacent tissues were tested by qRT-PCR. Cultured human glioma U251 cells were randomly split into groups: si-NC, si-circFOXM1, miR-NC, miR-218-5p, si-circFOXM1+anti-miR-NC, si-circFOXM1+anti-miR-218-5p. MTT method, plate clone formation, flow cytometry and Transwell experiments were utilized for detecting the proliferation, clone formation, apoptosis and migration of glioma cells. Dual-luciferase reporter experiment authenticated the targeted relation of circFOXM1 and miR-218-5p. Western blot tested the levels of E-cadherin and N-cadherin. CircFOXM1 was upregulated while miR-218-5p was low expressed in glioma tissues versus normal tissues. After circFOXM1 silence or miR-218-5p overexpression, miR-218-5p level was increased, and cell apoptosis rate and E-cadherin expression were enhancive, whereas cell proliferation, cell clone formation and migration abilities, and N-cadherin level were reduced. CircFOXM1 could affect miR-218-5 level by negative regulation. Furthermore, miR-218-5p silence could reverse the stimulative influence of si-circFOXM1 on apoptosis rate, and E-cadherin level, and the repressive effect on cell viability, cell number of colony formation and migration, and N-cadherin expression. Inhibition of circFOXM1 expression could block the proliferation, clone formation, and migration and induce apoptosis of glioma cells by upregulating miR-218-5p.

Comprehensive analysis of prognosis of patients with GBM based on 4 m6A-related lncRNAs and immune cell infiltration.

Objective: To investigate the immune cell infiltration status in glioblastoma multiforme (GBM) and construct a novel prognostic risk model that can predict patients' prognosis. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain RNA-sequence information and relevant clinical data. We performed Pearson correlation, univariate Cox regression to screen m6A-related prognostic lncRNA. GMB patients' samples were separated into different clusters through the ConsensusClusterPlus package. The risk score model was established through LASSO regression analysis. Besides, KEGG pathway enrichment analysis was implemented. CIBERSORT algorithm was used to analyze the difference of 22 types of immune cell infiltration in different cluster of GBM patient. Cox regression analyses were used to verify the independence of the model and correlation analysis was performed to demonstrate the link between our model and clinical characteristics of GBM patients. Experiments were used to validate the differential expression of the model lncRNA in patients with different prognosis. Results: 17 lncRNA related to prognosis were screened from 1021 m6A-related lncRNAs. Further, four m6A-related lncRNAs that were significantly correlated with GBM prognosis were selected to establish our prognostic risk model, which had excellent accuracy and can independently predict the prognosis of GBM patients. The infiltration fractions of T regulatory cells, T cells CD4 memory activated and neutrophils were positively associated with risk score, which suggested a significant relationship between the model and tumor immune microenvironment. Conclusion: The m6A-related RNA risk model offered potential for identifying biomarkers of therapy and predicting prognosis of GBM patients.

The prognostic value of inflammation markers in postoperative gliomas with or without adjuvant treatments.

ABSTRACT: Recent studies have shown that some inflammatory markers are associated with the prognosis of solid tumors. This study aims to evaluate the prognosis of glioma patients with or without adjuvant treatment using the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR).All patients who were diagnosed with gliomas at the first and second affiliated hospital of Guangxi Medical University between 2011 and 2020 were included in this study. The optimal cutoff value of SII, NLR, and PLR was determined by X-tile software program. We stratified patients into several groups and evaluated the progression-free survival (PFS) and overall survival (OS) of SII, NLR, and PLR during the period of pre-surgical, con-chemoradiotherapy, and post-treatments. Multivariate Cox regression analyses were performed to detect the relationships between OS, PFS, and prognostic variables.A total of 67 gliomas patients were enrolled in the study. The cutoff values of SII, NLR, and PLR were 781.5 × 109/L, 2.9 × 109/L, and 123.2 × 109/L, respectively. Patients who are pre-SII < 781.5 × 109/L had better PFS (P = .027), but no difference in OS. In addition, patients who had low pre-NLR (<2.9 × 109/L) meant better OS and PFS. PLR after adjuvant treatments (post-PLR) was significantly higher than pre-PLR (P = .035). Multivariate analyses revealed that pre-SII, pre-NLR were independent prognostic factors for OS (pre-SII: HR 1.002, 95% CI: 1.000-1.005, P = .030 and pre-PLR: HR 0.983, 95% CI: 0.973-0.994, P = .001), while pre-PLR was an independent factor for PFS (HR 0.989, 95% CI: 0.979-1.000, P = .041).High pre-SII or high pre-NLR could be prognostic markers to identify glioma patients who had a poor prognosis.