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. 2023 Oct 6;33(8):626-636.
doi: 10.1093/glycob/cwad051.

Role of the ST6GAL1 sialyltransferase in regulating ovarian cancer cell metabolism

Affiliations

Role of the ST6GAL1 sialyltransferase in regulating ovarian cancer cell metabolism

Robert B Jones et al. Glycobiology. .

Abstract

The ST6GAL1 sialyltransferase, which adds α2-6-linked sialic acids to N-glycosylated proteins, is upregulated in many malignancies including ovarian cancer. Through its activity in sialylating select surface receptors, ST6GAL1 modulates intracellular signaling to regulate tumor cell phenotype. ST6GAL1 has previously been shown to act as a survival factor that protects cancer cells from cytotoxic stressors such as hypoxia. In the present study, we investigated a role for ST6GAL1 in tumor cell metabolism. ST6GAL1 was overexpressed (OE) in OV4 ovarian cancer cells, which have low endogenous ST6GAL1, or knocked-down (KD) in ID8 ovarian cancer cells, which have high endogenous ST6GAL1. OV4 and ID8 cells with modulated ST6GAL1 expression were grown under normoxic or hypoxic conditions, and metabolism was assessed using Seahorse technology. Results showed that cells with high ST6GAL1 expression maintained a higher rate of oxidative metabolism than control cells following treatment with the hypoxia mimetic, desferrioxamine (DFO). This enrichment was not due to an increase in mitochondrial number. Glycolytic metabolism was also increased in OV4 and ID8 cells with high ST6GAL1 expression, and these cells displayed greater activity of the glycolytic enzymes, hexokinase and phosphofructokinase. Metabolism maps were generated from the combined Seahorse data, which suggested that ST6GAL1 functions to enhance the overall metabolism of tumor cells. Finally, we determined that OV4 and ID8 cells with high ST6GAL1 expression were more invasive under conditions of hypoxia. Collectively, these results highlight the importance of sialylation in regulating the metabolic phenotype of ovarian cancer cells.

Keywords: ST6GAL1; cancer stem cells; hypoxia; metabolism; sialic acid.

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Figures

Fig. 1
Fig. 1
ST6GAL1 overexpression protects OV4 ovarian cancer cells from a reduction in oxidative metabolism due to hypoxic stress. (A) OV4 cells were stably transduced with a lentivirus encoding ST6GAL1 and overexpression (OE) was confirmed by immunoblotting. Control cells were generated by stable transduction of an empty vector (EV). (B) Increases in cell surface α2–6 sialic acids were confirmed by SNA staining followed by flow cytometry. (C) Representative mitochondrial stress test profile for OV4 cells treated with DFO, or left untreated (UT). (D) Basal respiration rate, (E) ATP production, (F) maximal respiration rate, and (G) proton leak levels for cells treated with or without DFO. Graphs depict means and S.E.M. from three independent experiments. *P < 0.05.
Fig. 2
Fig. 2
ST6GAL1 activity enhances basal respiration in hypoxic ID8 cells. ID8 cells were stably transduced with ST6GAL1 targeting shRNA, and ST6GAL1 knockdown (KD) was confirmed by immunoblotting. Control ID8 cells were generated by stable transduction of an empty vector (EV). (B) A decrease in surface α2–6 sialylation was confirmed by SNA staining. (C) Representative mitochondrial stress test for ID8 cell models treated with or without DFO. (D) Basal respiration rate, (E) ATP production, (F) maximal respiration rate, and (G) proton leak levels for cells treated with or without DFO. Graphs depict mean and S.E.M. from three independent experiments. *P < 0.05.
Fig. 3
Fig. 3
ST6GAL1 activity does not alter mitochondrial number. Representative images of OV4 and ID8 cells stained with the Cytopainter Green mitochondrial dye. (B–C) Mean fluorescent intensity of OV4 (B) or ID8 (C) cells treated with or without DFO and then stained with Cytopainter Green. (D–E) caspase Glo apoptosis assays conducted on OV4 (D) and ID8 (E) cells treated with DFO. Graphs depict mean and S.E.M. from at three independent experiments. *P < 0.05.
Fig. 4
Fig. 4
ST6GAL1 activity contributes to increased glycolytic metabolism in hypoxic OV4 cells. Representative glycolytic stress test profile in OV4 cells treated with and without DFO. (B) Glycolytic rate, (C) glycolytic capacity, (D) glycolytic reserve, and (E) non-glycolytic acidification rate of cells treated with and without DFO. Graphs depict mean and S.E.M. from three independent experiments. *P < 0.05.
Fig. 5
Fig. 5
ST6GAL1 activity contributes to increased glycolytic metabolism in ID8 cells under normoxia. Representative glycolytic stress test profile for ID8 cells treated with and without DFO. (B) Glycolytic rate, (C) glycolytic capacity, (D) glycolytic reserve, and (E) non-glycolytic acidification rate of cells treated with and without DFO. Graphs depict mean and S.E.M. from three independent experiments. *P < 0.05.
Fig. 6
Fig. 6
Metabolic maps of OV4 and ID8 cells. Representative metabolic maps of OV4 (A) and ID8 (B) cells treated with or without DFO.
Fig. 7
Fig. 7
ST6GAL1 promotes increased activity of key glycolytic enzymes. OV4 (A) and ID8 (B) cells were cultured under normoxic conditions, or in a hypoxia chamber (0.5 percent O2) for 48 h. The activity of hexokinase (HK) and phosphofructokinase (PFK) was subsequently quantified. Graphs depict mean and S.E.M. from at least three independent experiments. *P < 0.05.
Fig. 8
Fig. 8
ST6GAL1 enhances the invasiveness of hypoxic cells. OV4 (A) and ID8 (B) cells were treated with or without DFO and then evaluated for invasion using a 3D spheroid invasion assay. The formation of invadopodia was quantified by Image J. Graphs depict mean and S.E.M. from three independent experiments. *P < 0.05.

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References

    1. Aasheim HC, Aas-Eng DA, Deggerdal A, Blomhoff HK, Funderud S, Smeland EB. Cell-specific expression of human beta-galactoside alpha 2,6-sialyltransferase transcripts differing in the 5′ untranslated region. Eur J Biochem. 1993:213(1):467–475. - PubMed
    1. Ahmed N, Escalona R, Leung D, Chan E, Kannourakis G. Tumour microenvironment and metabolic plasticity in cancer and cancer stem cells: perspectives on metabolic and immune regulatory signatures in chemoresistant ovarian cancer stem cells. Semin Cancer Biol. 2018:53:265–281. - PubMed
    1. Anderson AS, Roberts PC, Frisard MI, Hulver MW, Schmelz EM. Ovarian tumor-initiating cells display a flexible metabolism. Exp Cell Res. 2014:328(1):44–57. - PMC - PubMed
    1. Bellis SL, Reis CA, Varki A, Kannagi R, Stanley P. Glycosylation changes in cancer. In: Varki A, Cummings RD, Esko JD, Stanley P, Hart GW, Aebi M, Kinoshita T, Mohnen D, Packer NH, Prestegard JH, et al., editors. Essentials of glycobiology, Chapter 47. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press; 2022. pp. 631–644
    1. Berens EB, Holy JM, Riegel AT, Wellstein A. A cancer cell spheroid assay to assess invasion in a 3D setting. J Vis Exp. 2015:105(105):53409. - PMC - PubMed