GBM Cells Exhibit Susceptibility to Metformin Treatment According to TLR4 Pathway Activation and Metabolic and Antioxidant Status

Abstract

Glioblastoma (GBM) is an aggressive brain cancer associated with poor overall survival. The metabolic status and tumor microenvironment of GBM cells have been targeted to improve therapeutic strategies. TLR4 is an important innate immune receptor capable of recognizing pathogens and danger-associated molecules. We have previously demonstrated the presence of TLR4 in GBM tumors and the decreased viability of the GBM tumor cell line after lipopolysaccharide (LPS) (TLR4 agonist) stimulation. In the present study, metformin (MET) treatment, used in combination with temozolomide (TMZ) in two GBM cell lines (U87MG and A172) and stimulated with LPS was analyzed. MET is a drug widely used for the treatment of diabetes and has been repurposed for cancer treatment owing to its anti-proliferative and anti-inflammatory actions. The aim of the study was to investigate MET and LPS treatment in two GBM cell lines with different metabolic statuses. MET treatment led to mitochondrial respiration blunting and oxidative stress with superoxide production in both cell lines, more markedly in U87MG cells. Decreased cell viability after MET + TMZ and MET + LPS + TMZ treatment was observed in both cell lines. U87MG cells exhibited apoptosis after MET + LPS + TMZ treatment, promoting increased ER stress, unfolded protein response, and BLC2 downregulation. LPS stimulation of U87MG cells led to upregulation of SOD2 and genes related to the TLR4 signaling pathway, including IL1B and CXCL8. A172 cells attained upregulated antioxidant gene expression, particularly SOD1, TXN and PRDX1-5, while MET treatment led to cell-cycle arrest. In silico analysis of the TCGA-GBM-RNASeq dataset indicated that the glycolytic plurimetabolic (GPM)-GBM subtype had a transcriptomic profile which overlapped with U87MG cells, suggesting GBM cases exhibiting this metabolic background with an activated inflammatory TLR4 pathway may respond to MET treatment. For cases with upregulated CXCL8, coding for IL8 (a pro-angiogenic factor), combination treatment with an IL8 inhibitor may improve tumor growth control. The A172 cell line corresponded to the mitochondrial (MTC)-GBM subtype, where MET plus an antioxidant inhibitor, such as anti-SOD1, may be indicated as a combinatory therapy.

Keywords: A172; GBM; LPS; Metformin; U87MG; antioxidant; apoptosis; cell cycle arrest.

Figure 1

The schematic presentation of the experimental design.

Figure 2

Cell viability and death assays for A172 and U87MG treatment with LPS, MET, and TMZ. (A) Heatmap presenting expression values for the genes related to glycolysis, TCA cycle and oxidative phosphorylation normalized by z−score. A score value for the expression of genes attributed as a marker for glycolytic plurimetabolic (GPM) and mitochondrial (MTC) GBM subtypes according to Garofano’s (2021) classification [32]. Upregulated genes are presented in red and downregulated genes in blue. Graph bars representing the viability plotted for the single and combined treatments for LPS, MET, and TMZ in U87MG; (B) and A172 (D) after 48 h of treatment (**) p < 0.01, (***) p < 0.001 by one−way ANOVA post hoc Tukey test. Cellular death was analyzed by flow cytometry 48 h after treatments for U87MG; (C) and A172; and (E), and the results for initial apoptosis are presented. The graphs represent the percentage of the population in initial apoptosis through the positivity for annexin and PI negative in bars for each treatment condition. (*) p < 0.05, (**) p < 0.01, (***) p < 0.001 by two−way ANOVA post hoc Tukey test.

Figure 3

Transcriptome analysis for U87MG and A172 at 24 h after LPS and MET single and combined treatments compared to non−treated cells. A heatmap for the expression values after each treatment is presented and Pearson’s correlation analysis for clusterization of the different groups showed six different clusters for U87MG (A) and four clusters for A172 (C). The top two gene ontology enrichment pathways identified in each cluster are shown in bars with the −log adj p for U87MG (B) and A172 (D).

Figure 4

Mitochondrial stress. (A) The superoxide production in mitochondria after LPS, MET, and TMZ single and combined treatments for U87MG and A172. Graph bars represent the percentage of positive cells for MitoSOX. (*) p < 0.0001, One−wayANOVA post hoc Tukey test; (B) heatmap presenting the expression levels of antioxidant-related genes in U87MG and A172 cells. Presenting score values for the pathway for both cells (**) p < 0.01, and (***) p < 0.001, Limma t-test; (C) values for logCPM for SOD1 and SOD2 represented by the graph bars for U87MG and A172 after LPS, MET and LPS + MET treatment (*) p < 0.05, (**) p < 0.01, and p < 0.001, Limma t-test; (D) mitochondrial respiration by Seahorse, following the mitochondrial stress analysis. The oxygen consumption rate (OCR) curves along the time interval up to 60 min are presented according to applied drugs; and (E) histograms of basal respiration calculated by OCR before oligomycin incubation; ATP production evaluated by oligomycin−OCR subtracted from baseline cellular rate and maximal mitochondria respiration calculated as the value after CCCP−OCR subtracted from the value after rotenone- and antimycin A−OCR for U87MG and A172 in non-treated and MET treated. (*) p < 0.0001, one−way ANOVA followed by Tukey test. Red (parental-PAR), blue (MET treated) for U87MG and lilac (PAR), green (MET treated) for A172.

Figure 5

Cell cycle analysis and expression of genes related to chromosome segregation. (A) Cell cycle analysis for U87MG and A172 after MET and TMZ single and combined treatments. The bars represent each treatment condition. (*) p < 0.0001, two−way ANOVA post hoc Tukey test. G0/G1 phase (bottom bar), S phase (medium bar), G2/M phase (top bar); and (B) heatmap of chromosome segregation-related gene expressions after LPS and MET single and combined treatments in U87MG and A172 cells relative to non-treated controls. (*) p < 0.05, (**) p < 0.01, and (***) p < 0.001, Limma t-test for MET in comparison to PAR.

Figure 6

ER stress, pro- and anti-apoptotic and TLR4 pathway related gene expressions. (A) Heatmap for expression values of genes related to ER stress, pro−apoptotic, anti−apoptotic and TLR4 pathway in U87MG cells and A172 cells after LPS and MET single and combined treatments, (*) p < 0.05, (**) p < 0.01, and (***) p < 0.001, Limma t-test for LPS + MET combined and MET single treatment compared to non−treated cells; and (B) Western blot results for BCL2 of U87MG and A172 parental, DMSO, LPS, TMZ, MET single treated cells. β-actin was used for protein loading control.

Figure 7

In silico validation of antioxidant and TLR4 pathway-related gene expressions in TCGA GBM-RNASeq dataset. (A) Heatmap of antioxidant and TLR4 pathway-related gene expressions normalized by z−score in 34 GPM and 43 MTC GBM subtypes according to Garofano’s classification. The gene signatures for each case were calculated, and a score value was designated and normalized by z−score. (*) p < 0.05, (**) p < 0.01 (***), p < 0.001 (Mann−Whitney test); (B) in MTC, Spearman’s correlation analysis showed strong correlation between the expression of SOD1 and other antioxidant genes. The size of the circles is proportional to the p values, and positive (green) and negative (pink) correlations are presented according to the rho values in the bar scale at right. (C) RPKM values of SOD2 and CXCL8 for GPM− and MTC−GBM subtypes, graph bar presenting the mean values. Each circle represents a GBM case. (**) p < 0.01 (***), p < 0.001 (Mann−Whitney test); (D) in GPM, longer OS was presented by GBM cases with higher SOD2/CXCL8 ratio in a Kaplan−Meier graph, p = 0.002 by log rank test (four cases were censored).