| Literature DB >> 36010867 |
James Wood1, Salah Abdelrazig2, Sergey Evseev2, Catherine Ortori2, Marcos Castellanos-Uribe3, Sean T May3, David A Barrett2, Mohammed Diksin1, Sajib Chakraborty4, Dong-Hyun Kim2, Richard G Grundy1, Ruman Rahman1.
Abstract
Poor outcomes associated with diffuse high-grade gliomas occur in both adults and children, despite substantial progress made in the molecular characterisation of the disease. Targeting the metabolic requirements of cancer cells represents an alternative therapeutic strategy to overcome the redundancy associated with cell signalling. Cholesterol is an integral component of cell membranes and is required by cancer cells to maintain growth and may also drive transformation. Here, we show that removal of exogenous cholesterol in the form of lipoproteins from culture medium was detrimental to the growth of two paediatric diffuse glioma cell lines, KNS42 and SF188, in association with S-phase elongation and a transcriptomic program, indicating dysregulated cholesterol homeostasis. Interrogation of metabolic perturbations under lipoprotein-deficient conditions revealed a reduced abundance of taurine-related metabolites and cholesterol ester species. Pharmacological reduction in intracellular cholesterol via decreased uptake and increased export was simulated using the liver X receptor agonist LXR-623, which reduced cellular viability in both adult and paediatric models of diffuse glioma, although the mechanism appeared to be cholesterol-independent in the latter. These results provide proof-of-principle for further assessment of liver X receptor agonists in paediatric diffuse glioma to complement the currently approved therapeutic regimens and expand the options available to clinicians to treat this highly debilitating disease.Entities:
Keywords: LXR agonists; cholesterol; diffuse glioma; lipoprotein; metabolism
Year: 2022 PMID: 36010867 PMCID: PMC9405833 DOI: 10.3390/cancers14163873
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.575
Figure 1Altered growth characteristics of adult and paediatric diffuse glioma cells under lipoprotein-deplete conditions. U373 (adult GBM), KNS42 and SF188 (both paediatric diffuse glioma) cells were grown under lipoprotein -replete (black) or -deplete (grey) conditions in monolayer (A–C) or spheroid (D–F) format, respectively, over a 7- or 14-day period, respectively. (D–F) Brightfield images are representative of 14-day old spheroids in lipoprotein-replete (left) or -deplete (right) conditions. Black bars depict 300 μm in scaled length. (G–I) Flow cytometric cell cycle analysis following U373, KNS42 and SF188 monolayer culture, respectively, under lipoprotein -replete (black) or -deplete (grey) conditions for 72 h. Results are the mean ± SEM (A–F) or SD (G–I) for n ≥ 3 independent replicates (n = 6 spheroid replicates). Statistical evaluation of differences between lipoprotein -replete or -deplete conditions was conducted using t-tests: ns = not significant * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.00001.
Figure 2Cholesterol metabolism-related transcriptomic signatures induced by lipoprotein starvation. (A) Hierarchical clustering analysis of U373, KNS42, and SF188 diffuse glioma cells cultured under lipoprotein-replete (grey bar) or -deplete (black bar) conditions. Venn diagram (right) indicates the number of differentially expressed genes under lipoprotein-deplete conditions shared across the three diffuse glioma cell lines. (B) Heatmap representation of cholesterol metabolism-related gene expression for each of the three diffuse glioma cell lines cultured under lipoprotein-deplete conditions. Colour scale represents log2 fold change gene intensity values. Results are the mean of n = 3 independent replicates. Statistical evaluation of differences between lipoprotein -replete or -deplete between the two culture conditions was performed by implementing a Bayesian linear model using the R package limma and correcting for multiple comparisons: * p < 0.05. (C) Kaplan–Meier curve representing the overall survival outcome between CA9-High and CA9-Low groups based upon TCGA adult GBM data.
Gene ontology analysis of differentially expressed genes in U373, KNS42 and SF188 diffuse glioma cells starved of lipoproteins.
| GO.ID | Term | Annotated | Significant | Expected | classicFisher | Weight01KS | Genes |
|---|---|---|---|---|---|---|---|
|
| |||||||
| GO:0071456 | Cellular response to hypoxia | 98 | 5 | 0.53 | 1.70 × 104 | 8.80 × 104 | |
| GO:0032376 | Positive regulation of cholesterol transport | 11 | 2 | 0.06 | 1.52 × 103 | 2.69 × 102 | |
| GO:0030823 | Regulation of cGMP metabolic process | 12 | 2 | 0.06 | 1.82 × 103 | 3.50 × 102 | |
| GO:0030199 | Collagen fibril organisation | 15 | 3 | 0.08 | 6.40 × 105 | 4.81 × 102 | |
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| |||||||
| GO:0060337 | Type 1 interferon signalling pathway | 52 | 16 | 0.99 | 8.00 × 10−16 | 2.10 × 109 | |
| GO:0051607 | Defence response to virus | 107 | 17 | 2.05 | 1.30 × 10−11 | 2.00 × 105 | |
| GO:0006695 | Cholesterol biosynthetic process | 42 | 15 | 0.8 | 5.10 × 10−16 | 8.00 × 103 | |
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| GO:0060337 | Type 1 interferon signalling pathway | 55 | 20 | 3.08 | 4.90× 10−12 | 1.30 × 109 | |
| GO:0045540 | Regulation of cholesterol biosynthetic process | 27 | 14 | 1.51 | 2.50 × 10−11 | 1.10 × 107 | |
| GO:0051607 | Defence response to virus | 111 | 28 | 6.22 | 7.30 × 10−12 | 1.80 × 106 | |
| GO:0006695 | Cholesterol biosynthetic process | 41 | 20 | 2.3 | 5.40× 10−15 | 2.80 × 103 | |
| GO:0016126 | Sterol biosynthetic process | 43 | 21 | 2.41 | 1.10 × 10−15 | 3.10 × 102 | |
Statistical evaluation of gene ontology (GO) categories based of the number of significant-to-expected observations using either Fisher’s exact test (Fis) or Kolmogorov–Smirnov test (KS). Classic and weight01 algorithms were utilised which either do or do not, take into account the structure of the GO hierarchy, respectively. Genes in bold were downregulated under lipoprotein-deplete conditions.
Figure 3Lipoprotein starvation-induced perturbation of central metabolic pathways. Identified intermediates within glycolysis (A), TCA cycle and linked amino acid pathways (B), methionine cycle and transulphuration pathway (C), proline metabolism (D), choline pathway (E), and nucleotide metabolism (F) are depicted in black, with unidentified intermediates in red. (A–E) Heatmaps represent peak intensity fold changes between lipoprotein-replete and -deplete conditions in U373 (left box), KNS42 (middle box), and SF188 (right box) cells. Colour scales indicating the fold change range are specific to each panel. (F) Log2-fold peak intensity changes in nucleotide metabolism intermediates in U373 (red), KNS42 (blue), and SF188 (green) cells. Results are the mean of n = 6 independent replicates.
Figure 4Lipid and cholesterol alterations under lipoprotein-deplete conditions. (A–C) Number of each lipid species significantly altered between lipoprotein-replete and -deplete conditions in U373, KNS42, and SF188 diffuse glioma cells, respectively. Colours represent different categories of log2-fold peak intensity changes, with dark red and dark green representing fold changes of 1.5 and 0.67, respectively. (D,E) Measurement of the total and free cholesterol concentrations in diffuse glioma cells under lipoprotein-replete (black) and -deplete (grey) conditions. (F) The change in concentration of cholesterol ester in each cell line upon lipoprotein starvation was calculated from the concentrations of total and free cholesterol. Results are the mean ± SD of n = 6 independent replicates. Statistical evaluation of differences between the two culture conditions was conducted using t-tests: ns = not significant * p < 0.05; ** p < 0.01; **** p < 0.00001. Abbreviations: LPC: lysophosphatidylcholine; PC: phosphatidylcholine; PE: phosphatidylethanolamine; PG: phosphatidylglycerol; PI: phosphatidyl-inositol; PS: phosphatidylserine; Cer: ceramide; SM: sphingomyelin; DG: diacylglycerol; TG: triacyl-glycerol. (P−) and (O−) represent alkenyl-acylphospholipids (plasmologens) and alkyl-acylphospho-lipids, respectively.
Figure 5Therapeutic efficacy of the LXR agonist LXR-623 in diffuse cells. (A–C) Treatment of U373, KNS42, and SF188 cells with 7.5, 15, and 30 µM LXR-623 for 72 h, respectively. (D–F) Dose-response curves to determine IC50 (half maximal inhibitory concentration) values of LXR-623 in U373, KNS42, and SF188 cells. (G–I) Flow cytometric cell cycle analysis following treatment with LXR-623 for 72 h at respective IC50 concentrations and at higher concentrations deemed to result in 25% cellular viability. Results are the mean ± SEM (A–F) or SD (G–I) for n ≥ 3 independent replicates. Statistical evaluation of differences between the two culture conditions was conducted using t-tests: ns = not significant * p < 0.05; ** p < 0.01; *** p < 0.001.
Figure 6Dependence of LXR-623 on cholesterol export for therapeutic efficacy. (A–C) Cellular viability of U373, KNS42 and SF188 glioma cells, respectively, treated with LXR-623 for 72 h in the presence of different concentrations of water-soluble cholesterol (MβCD-Cho). Results are the mean ± SEM for n = 3 independent replicates. Statistical evaluation of was conducted using ANOVA: ns = not significant * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.00001.
Figure 7Transcriptomic networks induced by LXR-623 treatment. (A) Interconnected network of ER stress- and cell cycle-related genes in LXR-623-treated U373 cells. (B,C) Networks of downregulated genes associated with cell cycle regulation in LXR-623-treated KNS42 and SF188 cells, respectively.