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. 2023 Feb 8;24(4):3378.
doi: 10.3390/ijms24043378.

Targeting Glutaminolysis Shows Efficacy in Both Prednisolone-Sensitive and in Metabolically Rewired Prednisolone-Resistant B-Cell Childhood Acute Lymphoblastic Leukaemia Cells

Yordan Sbirkov  1   2 , Bozhidar Vergov  1 , Vasil Dzharov  2 , Tino Schenk  3   4 , Kevin Petrie  5 , Victoria Sarafian  1   2
Affiliations

Targeting Glutaminolysis Shows Efficacy in Both Prednisolone-Sensitive and in Metabolically Rewired Prednisolone-Resistant B-Cell Childhood Acute Lymphoblastic Leukaemia Cells

Yordan Sbirkov et al. Int J Mol Sci. .

Abstract

The prognosis for patients with relapsed childhood acute lymphoblastic leukaemia (cALL) remains poor. The main reason for treatment failure is drug resistance, most commonly to glucocorticoids (GCs). The molecular differences between prednisolone-sensitive and -resistant lymphoblasts are not well-studied, thereby precluding the development of novel and targeted therapies. Therefore, the aim of this work was to elucidate at least some aspects of the molecular differences between matched pairs of GC-sensitive and -resistant cell lines. To address this, we carried out an integrated transcriptomic and metabolomic analysis, which revealed that lack of response to prednisolone may be underpinned by alterations in oxidative phosphorylation, glycolysis, amino acid, pyruvate and nucleotide biosynthesis, as well as activation of mTORC1 and MYC signalling, which are also known to control cell metabolism. In an attempt to explore the potential therapeutic effect of inhibiting one of the hits from our analysis, we targeted the glutamine-glutamate-α-ketoglutarate axis by three different strategies, all of which impaired mitochondrial respiration and ATP production and induced apoptosis. Thereby, we report that prednisolone resistance may be accompanied by considerable rewiring of transcriptional and biosynthesis programs. Among other druggable targets that were identified in this study, inhibition of glutamine metabolism presents a potential therapeutic approach in GC-sensitive, but more importantly, in GC-resistant cALL cells. Lastly, these findings may be clinically relevant in the context of relapse-in publicly available datasets, we found gene expression patterns suggesting that in vivo drug resistance is characterised by similar metabolic dysregulation to what we found in our in vitro model.

Keywords: EGCG (epigallocatechin gallate); V-9302; childhood ALL; glucocorticoids; glutamine; glutaminolysis; metabolism; metabolomics; prednisolone; resistance.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Gene expression and metabolite analyses of prednisolone-resistant cells suggest dysregulated metabolism. (A) Gene ontology analysis of upregulated genes in Sup-PR showing overrepresentation of transcripts in several clusters, as annotated, and the statistical significance of the enrichment terms. (B) GSEA of differentially expressed genes in Sup-PR cells demonstrating enhanced oxidative phosphorylation and the list of up- (in red) and downregulated (in blue) genes involved in this process (NES—normalised enrichment score, FDR—false discovery rate). (C) Heatmap based on log2 fold change, as annotated, of metabolites that are up- or downregulated (in blue and red, respectively) in Sup-PR compared to Sup-B15 cells. (D) Metabolite pathway analysis presenting the involvement of the metabolites from (C) in biosynthetic pathways, as annotated, showing the statistical significance of the enrichment and the impact they have on the relative pathway.
Figure 2
Figure 2
Integrated transcriptomic and metabolomic analysis reveals alterations in the number of biosynthesis pathways. (A) Network analysis of differentially expressed genes and metabolites in Sup-PR compared to Sup-B15 cells and statistical data for six of the top ten enriched KEGG pathways. The genes highlighted in blue colour (circles) and metabolites (squares) on the diagram are from the selected pathways. (B) A more detailed view of genes and metabolites involved in glutamine metabolism (in red circles)—GLUD1, l-Glutamine and oxoglutaric acid.
Figure 3
Figure 3
Targeting glutamine metabolism induces apoptosis in cALL cell lines. The percentage of live and annexin-positive cells, and representative flow cytometry plots, of Sup-B15 and Sup-PR cells grown for 72 h in a medium without Gln (top panel), or treated with IC50 concentrations of the Gln transporter inhibitor V-9302 (middle panel) and with the glutamate dehydrogenease inhibitor EGCG (bottom panel). Error bars represent the mean with SD from biological duplicates. *—p < 0.05, **—p < 0.005, ***—p < 0.0005, Student’s t-test.
Figure 4
Figure 4
Inhibition of glutaminolysis impairs mitochondrial function. (A) Seahorse analysis of mitochondrial function showing oxygen consumption rates (OCR) in a Seahorse mito stress test (left hand side), and the relevant quantification (right hand side) of basal and maximal respiration and ATP production, as annotated in cells grown in a medium without glutamine (top panel), or treated with V-9302 (middle panel) or EGCG (bottom panel) for 72 h. Error bars represent the mean with SD from biological duplicates. **—p < 0.005, ***—p < 0.005 Student’s t-test. (B) Metabolite analysis of Sup-PR and Sup-B15 cells treated with EGCG compared to control untreated samples of the two cell lines, showing a heatmap of the up- and downregulated metabolites after treatment for 16 h (left hand side), as well as pathway analysis (right hand side) and a list of the top enrichment terms from a MSEA (bottom).
Figure 5
Figure 5
Gene expression analysis of metadata of matched patient samples at diagnosis and relapse. (A) GO analysis of upregulated genes in patient samples from meta-analysis [10] showing a metabolism-enriched cluster of nodes from upregulated genes in relapsed cALL patients and selected enrichment terms. (B) GO analysis of 142 upregulated genes found in both the meta-analysis and Sup-PR cells showing enrichment for metabolic processes, as annotated. (C) Integrated analysis of all up- and downregulated genes in relapse patients [10] and all dysregulated metabolites in Sup-PR cells. The genes (circles) and metabolites (squares) from the top 5 enriched KEGG terms are highlighted in red.
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References

    1. Malczewska M., Kosmider K., Bednarz K., Ostapinska K., Lejman M., Zawitkowska J. Recent Advances in Treatment Options for Childhood Acute Lymphoblastic Leukemia. Cancers. 2022;14:2021. doi: 10.3390/cancers14082021. - DOI - PMC - PubMed
    1. Gu Z., Churchman M.L., Roberts K.G., Moore I., Zhou X., Nakitandwe J., Hagiwara K., Pelletier S., Gingras S., Berns H., et al. PAX5-driven subtypes of B-progenitor acute lymphoblastic leukemia. Nat. Genet. 2019;51:296–307. doi: 10.1038/s41588-018-0315-5. - DOI - PMC - PubMed
    1. Bhojwani D., Pui C.H. Relapsed childhood acute lymphoblastic leukaemia. Lancet Oncol. 2013;14:e205–e217. doi: 10.1016/S1470-2045(12)70580-6. - DOI - PubMed
    1. Goto H. Childhood relapsed acute lymphoblastic leukemia: Biology and recent treatment progress. Pediatr. Int. 2015;57:1059–1066. doi: 10.1111/ped.12837. - DOI - PubMed
    1. Sbirkov Y., Burnusuzov H., Sarafian V. Metabolic reprogramming in childhood acute lymphoblastic leukemia. Pediatr. Blood Cancer. 2020;67:e28255. doi: 10.1002/pbc.28255. - DOI - PubMed

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