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Cystine transporter regulation of pentose phosphate pathway dependency and disulfide stress exposes a targetable metabolic vulnerability in cancer

Abstract

SLC7A11-mediated cystine uptake is critical for maintaining redox balance and cell survival. Here we show that this comes at a significant cost for cancer cells with high levels of SLC7A11. Actively importing cystine is potentially toxic due to its low solubility, forcing cancer cells with high levels of SLC7A11 (SLC7A11high) to constitutively reduce cystine to the more soluble cysteine. This presents a significant drain on the cellular NADPH pool and renders such cells dependent on the pentose phosphate pathway. Limiting glucose supply to SLC7A11high cancer cells results in marked accumulation of intracellular cystine, redox system collapse and rapid cell death, which can be rescued by treatments that prevent disulfide accumulation. We further show that inhibitors of glucose transporters selectively kill SLC7A11high cancer cells and suppress SLC7A11high tumour growth. Our results identify a coupling between SLC7A11-associated cystine metabolism and the pentose phosphate pathway, and uncover an accompanying metabolic vulnerability for therapeutic targeting in SLC7A11high cancers.

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Fig. 1: SLC7A11 promotes the PPP flux.
Fig. 2: The crosstalk between SLC7A11 and the PPP in regulating glucose-limitation-induced cell death and their co-expression in human cancers.
Fig. 3: SLC7A11-mediated cystine uptake and subsequent cystine reduction to cysteine promote disulfide stress, deplete NADPH and cause redox system collapse under glucose deprivation.
Fig. 4: Preventing disulfide but not ROS accumulation rescues redox defects and cell death in SLC7A11-overexpressing cells under glucose starvation.
Fig. 5: Aberrant expression of SLC7A11 sensitizes cancer cells to GLUT inhibition.
Fig. 6: SLC7A11high tumours are sensitive to GLUT inhibitor.

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Data availability

Source Data for Figs. 16 and Extended Data Figs. 17 are provided with the paper. The 33 cancer-type data were derived from the TCGA Research Network: http://cancergenome.nih.gov/. The RNA-seq data from PDXs have been deposited in dbGAP under accession number phs001980.v1.p1. All data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank R. DePinho for critical reading and insightful comments. This research has been supported by the Andrew Sabin Family Fellow Award and Bridge Fund from The University of Texas MD Anderson Cancer Center, Career Enhancement Award from University of Texas Specialized Program of Research Excellence in Lung Cancer National Institutes of Health/National Cancer Institute 5P50CA070907, KC180131 from Department of Defense Kidney Cancer Research Program (to B.G.), grants from the National Institutes of Health (R01CA181196 to B.G. and R01CA188652 to C.M.M.). B.G. is an Andrew Sabin Family Fellow. Y.Z. and P.K. were Scholars at the Center for Cancer Epigenetics at The University of Texas MD Anderson Cancer Center. P.K. is also supported by the CPRIT Research Training Grant (RP170067) and Dr. John J. Kopchick Research Award from The MD Anderson UTHealth Graduate School of Biomedical Sciences. E.W.L. is supported by National Institutes of Health grant T32EB009380. PDX generation and annotation were supported by the University of Texas MD Anderson Cancer Center Moon Shots Program, Specialized Program of Research Excellence grant CA070907 and University of Texas PDX Development and Trial Center grant U54CA224065. This research was also supported by the National Institutes of Health Cancer Center Support Grant P30CA016672 to The University of Texas MD Anderson Cancer Center.

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Authors and Affiliations

Authors

Contributions

X.L. and Y.Z. performed most of the experiments with assistance from P.K., G.L, L.Z. and H.L. K.O. conducted most metabolomic and isotope-tracing analyses except 3-[2H]glucose-tracing analyses. E.W.L. performed 3-[2H]glucose tracing analyses under the direction of C.M.M. J.S. conducted bioinformatics analysis under the direction of W.L. X.Z. and B.F. provided PDXs. J.Z. processed tumour and tissue samples. M.J.Y. performed histopathological analysis. K.O. and M.V.P. provided KL-11743 and designed and interpreted pharmacokinetic analysis. B.G. conceived and supervised the study and wrote most of the manuscript. All authors commented on the manuscript.

Corresponding author

Correspondence to Boyi Gan.

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K.O. and M.V.P. are full-time employees of Kadmon Corporation. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 The effect of SLC7A11 overexpression on glutamate, TCA cycle and glycolysis metabolites, and the expression levels of PPP enzymes.

a, Western blotting showing Myc-tagged SLC7A11 expression in 786-O cells. The experiment was repeated five times, independently, with similar results. b, Bar graph showing relative fold changes of glutamate and TCA cycle metabolites in EV and SLC7A11-overexpressing 786-O cells. n=3 independent experiments. c, Western blotting showing indicated protein levels in EV and SLC7A11-overexpressing 786-O cells. The experiment was repeated twice, independently, with similar results. d, Bar graph showing relative fold changes of glycolysis metabolites in EV and SLC7A11-overexpressing 786-O cells. n=3 independent experiments. e,f, Bar graph showing the fold changes of PPP and PPP-derived intermediates induced by SLC7A11 overexpression in RCC4 or ACHN cells. n=3 independent experiments. g, Simplified schematic of glycolysis and the PPP, showing 13C labeling patterns resulting from 1,2-13C2 glucose. Red fills indicate 13C atoms. h, Glucose consumption rates in EV and SLC7A11-overexpressing 786-O cells. n=5 independent experiments. i, Simplified schematic showing the sequential transfer of deuterium labels at position 3 of glucose to NADPH and then newly synthesized palmitic acid. Red circles indicate positional deuterium labels. j, Newly synthesized deuterium labelled palmitate in EV and SLC7A11-overexpressing 786-O cells. n=3 independent experiments. In (j), data are plotted as mean ±95% confidence interval (CI). Other error bars are mean ± s.d. All p values were calculated using two-tailed unpaired Student’s t-test. Detailed statistical tests are described in the Methods. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 1. Numeral data are provided in Statistics Source Data Extended Data Fig. 1.

Source data

Extended Data Fig. 2 G6PD knockdown sensitizes cancer cells to glucose limitation and SLC7A11 expression correlates with PPP gene expression in human cancers.

a, c, G6PD protein levels in control shRNA (shCtrl) and G6PD knockdown (shG6PD) UMRC6 (a) and A498 cells (c). The experiments were repeated twice, independently, with similar results. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 2. b, d, Cell death analysed by PI staining in indicated cells cultured in 25 or 1 mM glucose for 24 hours. Error bars are mean± s.d., n=3 independent experiments, p values were calculated using two-tailed unpaired Student’s t-test. e, Compared to other glucose metabolism genes, PPP genes show significant positive correlations with SLC7A11 in LUAD(n=514), BLCA(n=407), HNSC(n=520), CHOL(n=36), ESCA(n=184), LUSC(n=502), and LIHC(n=371). f, Scatter plots showing the correlations between SLC7A11 and 4 PPP genes (G6PD, PGD, TALDO1, and TKT) in KIRC(n=533), LUAD(n=514), and LUSC(n=502), respectively. g, Scatter plots showing the correlations between SLC7A11 and SLC2A1 in KIRP(n=290).h, Kaplan–Meier plots of KIRP patients stratified by SLC7A11 and SLC2A1 expression levels, respectively (left 2 panels); Kaplan–Meier plots of KIRP patients stratified by unsupervised clustering on SLC7A11 and SLC2A1 expression (right 2 panels). Group 1 has lower SLC7A11 and SLC2A1 expression, while Group 2 has higher SLC7A11 and SLC2A1 expression. Detailed statistical tests of b, d and f-h are described in the Methods. Error bars are mean ± s.d, all bar graphs have 3 independent repeats. Numeral data are provided in Statistics Source Data Extended Data Fig. 2.

Source data

Extended Data Fig. 3 High expression of SLC7A11 promote disulfide stress, deplete NADPH and causes redox system collapse under glucose deprivation.

a, Simplified schematic of how SLC7A11 can be linked to NADPH and the PPP. b, c, Measurement of intracellular GSSG (b) and GSH (c) concentrations in EV and SLC7A11-overexpressing 786-O cells cultured with (+Glc) or without glucose (-Glc). d, Diagrams illustrating the structures of γ-glutamylcysteine, γ-glutamyl-cystine, GSH, and glutathionyl-cysteine. Glu: glutamate; Gly: glycine; Cys: cysteine. e, f, The relative levels of intracellular γ-glutamyl-cystine (e) and glutathionyl-cysteine (f) in EV and SLC7A11-overexpressing 786-O cells cultured with (+Glc) or without glucose (-Glc). g, Representative phase-contrast images of indicated cells cultured with or without glucose.h, Western blotting analysis of SLC7A11 protein levels in the control (sgCtrl) and SLC7A11 knockout (sgSLC-1/2) UMRC6 cells. i-l, Measurement of intracellular GSSG (i) and GSH (j) concentrations and the relative levels of intracellular γ-glutamyl-cystine (k) and glutathionyl-cysteine (l) in control (sgCtrl) and SLC7A11 knockout (sgSLC-1/2) UMRC6 cells cultured with (+Glc) or without glucose (-Glc). m, Representative phase-contrast images of indicated cells cultured with (+Glc) or without glucose (-Glc). n, o, Cystine uptake levels in EV and SLC7A11- overexpressing 786-O cells (n) or UMRC6 cells (o) upon treatment with 1 mM sulfasalazine (SAS). p-u, Cell death with or without representative phase-contrast images (p, s), NADP+/NADPH ratios (q, t), and ROS levels (r, u) of EV and SLC7A11- overexpressing 786-O or UMRC6 cells cultured in glucose-containing or glucose free medium with or without treatment of 1 mM SAS. Error bars are mean ± s.d, all bar graphs have 3 independent repeats. All scale bars=100 μm. The experiment (g, h, m, p) was repeated twice, independently, with similar results. All p values were calculated using two-tailed unpaired Student’s t-test. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 3. Numeral data are provided in Statistics Source Data Extended Data Fig. 3.

Source data

Extended Data Fig. 4 Cystine deprivation or 2DG reverses redox defects and prevents cell death upon glucose starvation.

a-d, Measurement of intracellular GSSG (a) and GSH (b) concentrations, and the relative levels of intracellular γ-glutamyl-cystine (c) and glutathionyl-cysteine (d) in UMRC6 cells cultured with normal (+Glc), glucose free (-Glc), glucose/cystine-double free (-Glc-Cystine), or cystine free (-Cystine) medium. e, f, Measurement of NADP+/NADPH ratios (e), and ROS levels (f) in EV and SLC7A11-overexpressing 786-O cells cultured with indicated medium. g-i, Representative phase-contrast images and cell death of indicated cells cultured with indicated medium. j, k, Diagrams illustrating the structure (j) and metabolism (k) of glucose and 2DG. l-n, The relative levels of intracellular 2-deoxyglucose-6-phosphate (l), 2-deoxy-6-phosphogluconolactone (m) and 2-deoxy-6-phosphogluconate (n) in UMRC6 cells cultured in glucose-containing or glucose free medium with or without treatment of 2 mM 2DG. o-r, Measurement of intracellular GSSG (o) and GSH (p) concentrations, and the relative levels of intracellular γ-glutamyl-cystine (q) and glutathionyl-cysteine (r) in UMRC6 cells cultured in glucose-containing or glucose free medium with or without treatment of 2 mM 2DG. s, Representative phase-contrast images of UMRC6 cells cultured in glucose-containing or glucose free medium with or without treatment of 2 mM 2DG.t-w, Measurement of NADP+/NADPH ratios (t), ROS levels (u), cell death (v) and the representative phase-contrast images (w) of EV and SLC7A11-overexpressing 786-O cells cultured in glucose-containing or glucose-free medium with or without treatment of 2 mM 2DG. The experiments (g, h, i, s, w) were repeated twice, independently, with similar results. All error bars are mean± s.d., n=3 independent experiments. All scale bars=100 μm. All p values were calculated using two-tailed unpaired Student’s t-test. Numeral data are provided in Statistics Source Data Extended Data Fig. 4.

Source data

Extended Data Fig. 5 Preventing disulfide but not ROS accumulation rescues redox defects and cell death in SLC7A11-overexpressing cells under glucose starvation.

a, b, Measurement of cell death of UMRC6 or 786-O cells cultured in glucose-containing, glucose-free medium or cystine-free medium with or without treatment of 100 μM DFO or 10 μM Ferrostatin-1. c–h, Measurement intracellular levels of cysteine (c), the relative levels of intracellular γ-glutamyl-cystine (d), glutathionyl-cysteine (e), NAC-cysteine (f), GSSG/GSH ratio (g) and ROS levels (h) of UMRC6 cells cultured in glucose-containing or glucose-free medium with or without treatment of 2 mM NAC. i, The solubility of different amino acids. j–o, Measurement intracellular levels of cysteine (j), the relative levels of intracellular γ-glutamyl-cystine (k), glutathionyl-cysteine (l), GSSG/GSH ratio (m), ROS levels (n) and Cysteine-penicillamine (o) of UMRC6 cells cultured in glucose-containing or glucose-free medium with or without treatment of 2 mM D-Penicillamine or L-Penicillamine. p–t, Measurement intracellular levels of cysteine (p), the relative levels of intracellular γ-glutamyl-cystine (q), glutathionyl-cysteine (r), GSSG/GSH ratio (s) and ROS levels (t) of UMRC6 cells cultured in glucose-containing or glucose-free medium with or without treatment of TCEP. u-y, Measurement intracellular levels of cysteine (u), the relative levels of intracellular γ-glutamyl-cystine (v), glutathionyl-cysteine (w), GSSG/GSH ratio (x) and ROS levels (y) of UMRC6 cells cultured in glucose-containing or glucose-free medium with or without treatment of 1 mM 2ME. Except i, all other error bars are mean± s.d., n=3 independent experiments. All p values were calculated using two-tailed unpaired Student’s t-test. Detailed statistical tests are described in the Methods. Numeral data are provided in Statistics Source Data Extended Data Fig. 5.

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Extended Data Fig. 6 Cancer cells with high SLC7A11 expression are sensitive to GLUT inhibition.

a, Cell death of EV and SLC7A11- overexpressing 786-O cells treated with 0.125-0.5 mM 6-AN. b, Cell death of EV and SLC7A11- overexpressing 786-O cells treated with 0.1 mM epiandrosterone (EA). c, Quantification of NADP+/NADPH ratios in EV and SLC7A11- overexpressing 786-O cells treated with normal (+Glc), glucose free (-Glc) medium, or normal medium containing 0.1 mM EA. d, Quantification of NADP+/NADPH ratios in UMRC6 cells treated with normal (+Glc), glucose free (-Glc), glucose/cystine double free medium (-Glc-Cystine), or normal medium containing 0.1 mM EA. e, SLC7A11 protein levels in control (sgCtrl) and SLC7A11 knockout (sgSLC7A11) NCI-H226 cells were measured by western blotting. The experiment was repeated twice, independently, with similar results. f, Measurement of GSSG/GSH ratios in EV and SLC7A11-overexpressing 786-O cells treated with KL-11743, BAY-876 or cultured in glucose free medium. g, Western blotting analysis of indicated proteins in ACHN cells with SLC7A11 and/or G6PD overexpression. The experiment was repeated twice, independently, with similar results. All error bars are mean± s.d., n=3 independent experiments. All p values were calculated using two-tailed unpaired Student’s t-test. Detailed statistical tests are described in the Methods. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 6. Numeral data are provided in Statistics Source Data Extended Data Fig. 6.

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Extended Data Fig. 7 SLC7A11-high tumors are sensitive to GLUT inhibitor.

a, Plasma levels of GLUT inhibitor KL-11743 were measured in mice at different time points after intraperitoneal injection. Error bars are mean ± s.d, n=4 independent repeats. b, End-point weights of NCI-H226 xenograft tumors with indicated genotypes treated with KL-11743 or vehicle. Error bars are mean ± s.d., n=9 independent repeats. c, End-point weights of ACHN xenograft tumors with indicated genotypes treated with BAY-876, KL-11743, or vehicle. Error bars are mean ± s.d., n=8 independent repeats. d-h, End-point weights of PDX xenograft tumors with indicated genotypes treated with KL-11743 or vehicle. . Error bars are mean ± s.d., n=6 (d: KL-11743, f-h) or7 (d: vehicle, e) independent repeats. i, Representative hematoxylin and eosin staining of major organs from mice treated with vehicle or GLUT inhibitors. The experiment was repeated twice, independently, with similar results. Scale bars=50 μm. j-p, Mice weights of indicated cell line-xenografts or PDXs at different time points treated with KL-11743 or vehicle. Error bars are mean ± s.d., n=6 (l: KL-11743, n-p), 7 (l: vehicle, m), 8 (k) or 9 (j) independent repeats. All p values were calculated using two-tailed unpaired Student’s t-test. Detailed statistical tests are described in the Methods. Numeral data are provided in Statistics Source Data Extended Data Fig. 7.

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Extended Data Fig. 8 The working model depicting how SLC7A11 regulates pentose phosphate pathway dependency and glucose-deprivation-induced cell death.

See discussion for detailed description. PPP: pentose phosphate pathway; GLUT: glucose transporter.

Extended Data Fig. 9 An example for the gating strategy of Flow Cytometry.

Initial cell population gating (FSC-Area VS FSC-Height) was adopted to make sure only single cells were used for analysis.

Supplementary information

Reporting Summary

Supplementary Information

Supplementary Table 1: glucose metabolism related genes. Supplementary Table 2: summary of various approaches on rescuing redox defects and cell death in SLC7A11-high cancer cells under glucose starvation. Supplementary Table 3: oligos and shRNA sequences. Supplementary Table 4: information on human research participants (age, gender, genotypic information, diagnosis and treatment categories) of PDXs in this study.

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Liu, X., Olszewski, K., Zhang, Y. et al. Cystine transporter regulation of pentose phosphate pathway dependency and disulfide stress exposes a targetable metabolic vulnerability in cancer. Nat Cell Biol 22, 476–486 (2020). https://doi.org/10.1038/s41556-020-0496-x

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