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Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma

Abstract

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies.

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Figure 1: Inhibition of EGFR-driven glucose metabolism induces minimal cell death but primes GBM cells for apoptosis.
Figure 2: Cytoplasmic p53 links EGFR to intrinsic apoptosis.
Figure 3: Bcl-xL prevents GBM cell death by binding to and sequestering cytoplasmic p53.
Figure 4: Synthetic lethality with combined targeting of EGFR and p53.
Figure 5: Modulation of glucose metabolism primes GBM for p53-mediated cell death.
Figure 6: Combined targeting of EGFR-driven glucose uptake and p53 suppresses tumor growth in vivo.

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References

  1. Brennan, C.W. et al. The somatic genomic landscape of glioblastoma. Cell 155, 462–477 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Vivanco, I. et al. Differential sensitivity of glioma- versus lung cancer-specific EGFR mutations to EGFR kinase inhibitors. Cancer Discov. 2, 458–471 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Cloughesy, T.F., Cavenee, W.K. & Mischel, P.S. Glioblastoma: from molecular pathology to targeted treatment. Annu. Rev. Pathol. 9, 1–25 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. Lee, E.Q. et al. Phase I/II study of sorafenib in combination with temsirolimus for recurrent glioblastoma or gliosarcoma: North American Brain Tumor Consortium study 05-02. Neuro-oncol. 14, 1511–1518 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wen, P.Y. et al. Phase I/II study of erlotinib and temsirolimus for patients with recurrent malignant gliomas: North American Brain Tumor Consortium trial 04-02. Neuro-oncol. 16, 567–578 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lee, M.J. et al. Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks. Cell 149, 780–794 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Vander Heiden, M.G. et al. Growth factors can influence cell growth and survival through effects on glucose metabolism. Mol. Cell. Biol. 21, 5899–5912 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Altman, B.J. & Rathmell, J.C. Metabolic stress in autophagy and cell death pathways. Cold Spring Harb. Perspect. Biol. 4, a008763 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Verhaak, R.G.W. et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17, 98–110 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Babic, I. et al. EGFR mutation-induced alternative splicing of Max contributes to growth of glycolytic tumors in brain cancer. Cell Metab. 17, 1000–1008 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Lee, J. et al. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell 9, 391–403 (2006).

    Article  CAS  PubMed  Google Scholar 

  12. Nathanson, D.A. et al. Targeted therapy resistance mediated by dynamic regulation of extrachromosomal mutant EGFR DNA. Science 343, 72–76 (2014).

    Article  CAS  PubMed  Google Scholar 

  13. Masui, K. et al. mTOR complex 2 controls glycolytic metabolism in glioblastoma through FoxO acetylation and upregulation of c-Myc. Cell Metab. 18, 726–739 (2013).

    Article  CAS  PubMed  Google Scholar 

  14. Haq, R. et al. Oncogenic BRAF regulates oxidative metabolism via PGC1α and MITF. Cancer Cell 23, 302–315 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zhao, Y. et al. Glucose metabolism attenuates p53 and Puma-dependent cell death upon growth factor deprivation. J. Biol. Chem. 283, 36344–36353 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Deng, J. et al. BH3 profiling identifies three distinct classes of apoptotic blocks to predict response to ABT-737 and conventional chemotherapeutic agents. Cancer Cell 12, 171–185 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. Montero, J. et al. Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy. Cell 160, 977–989 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kruse, J.P. & Gu, W. Modes of p53 regulation. Cell 137, 609–622 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Maddocks, O.D. & Vousden, K.H. Metabolic regulation by p53. J. Mol. Med. (Berl.) 89, 237–245 (2011).

    Article  CAS  Google Scholar 

  20. Jiang, D. et al. Analysis of p53 transactivation domain mutants reveals Acad11 as a metabolic target important for p53 pro-survival function. Cell Rep. 10, 1096–1109 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Chipuk, J.E. et al. Direct activation of Bax by p53 mediates mitochondrial membrane permeabilization and apoptosis. Science 303, 1010–1014 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Mihara, M. et al. p53 has a direct apoptogenic role at the mitochondria. Mol. Cell 11, 577–590 (2003).

    Article  CAS  PubMed  Google Scholar 

  23. Liu, J.C. et al. High mitochondrial priming sensitizes hESCs to DNA-damage-induced apoptosis. Cell Stem Cell 13, 483–491 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Strom, E. et al. Small-molecule inhibitor of p53 binding to mitochondria protects mice from gamma radiation. Nat. Chem. Biol. 2, 474–479 (2006).

    Article  CAS  PubMed  Google Scholar 

  25. Tasdemir, E. et al. Regulation of autophagy by cytoplasmic p53. Nat. Cell Biol. 10, 676–687 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Green, D.R. & Kroemer, G. Cytoplasmic functions of the tumour suppressor p53. Nature 458, 1127–1130 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Chipuk, J.E., Bouchier-Hayes, L., Kuwana, T., Newmeyer, D.D. & Green, D.R. PUMA couples the nuclear and cytoplasmic proapoptotic function of p53. Science 309, 1732–1735 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Lessene, G. et al. Structure-guided design of a selective BCL-X(L) inhibitor. Nat. Chem. Biol. 9, 390–397 (2013).

    Article  CAS  PubMed  Google Scholar 

  29. The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455, 1061–1068 (2008).

  30. Zhang, Y., Xiong, Y. & Yarbrough, W.G. ARF promotes MDM2 degradation and stabilizes p53: ARF-INK4a locus deletion impairs both the Rb and p53 tumor suppression pathways. Cell 92, 725–734 (1998).

    Article  CAS  PubMed  Google Scholar 

  31. Pomerantz, J. et al. The Ink4a tumor suppressor gene product, p19Arf, interacts with MDM2 and neutralizes MDM2′s inhibition of p53. Cell 92, 713–723 (1998).

    Article  CAS  PubMed  Google Scholar 

  32. Tovar, C. et al. Small-molecule MDM2 antagonists reveal aberrant p53 signaling in cancer: implications for therapy. Proc. Natl. Acad. Sci. USA 103, 1888–1893 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lehár, J. et al. Synergistic drug combinations tend to improve therapeutically relevant selectivity. Nat. Biotechnol. 27, 659–666 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Vaseva, A.V., Marchenko, N.D. & Moll, U.M. The transcription-independent mitochondrial p53 program is a major contributor to nutlin-induced apoptosis in tumor cells. Cell Cycle 8, 1711–1719 (2009).

    Article  CAS  PubMed  Google Scholar 

  35. Chipuk, J.E., Maurer, U., Green, D.R. & Schuler, M. Pharmacologic activation of p53 elicits Bax-dependent apoptosis in the absence of transcription. Cancer Cell 4, 371–381 (2003).

    Article  CAS  PubMed  Google Scholar 

  36. DeBerardinis, R.J., Lum, J.J., Hatzivassiliou, G. & Thompson, C.B. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 7, 11–20 (2008).

    Article  CAS  PubMed  Google Scholar 

  37. Ding, Q. et al. Discovery of RG7388, a potent and selective p53-MDM2 inhibitor in clinical development. J. Med. Chem. 56, 5979–5983 (2013).

    Article  CAS  PubMed  Google Scholar 

  38. Tannous, B.A. Gaussia luciferase reporter assay for monitoring biological processes in culture and in vivo. Nat. Protoc. 4, 582–591 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Qu, L. et al. Endoplasmic reticulum stress induces p53 cytoplasmic localization and prevents p53-dependent apoptosis by a pathway involving glycogen synthase kinase-3β. Genes Dev. 18, 261–277 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Han, M.-K. et al. SIRT1 regulates apoptosis and Nanog expression in mouse embryonic stem cells by controlling p53 subcellular localization. Cell Stem Cell 2, 241–251 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Yang, W.H. et al. Modification of p53 with O-linked N-acetylglucosamine regulates p53 activity and stability. Nat. Cell Biol. 8, 1074–1083 (2006).

    Article  CAS  PubMed  Google Scholar 

  42. Leu, J.I.J., Dumont, P., Hafey, M., Murphy, M.E. & George, D.L. Mitochondrial p53 activates Bak and causes disruption of a Bak–Mcl1 complex. Nat. Cell Biol. 6, 443–450 (2004).

    Article  CAS  PubMed  Google Scholar 

  43. Follis, A.V. et al. PUMA binding induces partial unfolding within BCL-xL to disrupt p53 binding and promote apoptosis. Nat. Chem. Biol. 9, 163–168 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Reardon, D.A., Wen, P.Y. & Mellinghoff, I.K. Targeted molecular therapies against epidermal growth factor receptor: past experiences and challenges. Neuro. Oncol. 16 (Suppl. 8), viii7–vii13 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Wei, W. et al. Single-cell phosphoproteomics resolves adaptive signaling dynamics and informs targeted combination therapy in glioblastoma. Cancer Cell 29, 563–573 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Clark, P.M., Ebiana, V.A., Gosa, L., Cloughesy, T.F. & Nathanson, D.A. Harnessing preclinical molecular imaging to inform advances in personalized cancer medicine. J. Nucl. Med. 58, 689–696 (2017).

    Article  CAS  PubMed  Google Scholar 

  47. Spence, A.M. et al. 18F-FDG PET of gliomas at delayed intervals: improved distinction between tumor and normal gray matter. J. Nucl. Med. 45, 1653–1659 (2004).

    PubMed  Google Scholar 

  48. Nathanson, D. et al. Co-targeting of convergent nucleotide biosynthetic pathways for leukemia eradication. J. Exp. Med. 211, 473–486 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Takanaga, H. & Frommer, W.B. Facilitative plasma membrane transporters function during ER transit. FASEB J. 24, 2849–2858 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Cheng, E.H. et al. BCL-2, BCL-X(L) sequester BH3 domain-only molecules preventing BAX- and BAK-mediated mitochondrial apoptosis. Mol. Cell 8, 705–711 (2001).

    Article  CAS  PubMed  Google Scholar 

  51. Dai, H., Marbach, P., Lemaire, M., Hayes, M. & Elmquist, W.F. Distribution of STI-571 to the brain is limited by P-glycoprotein-mediated efflux. J. Pharmacol. Exp. Ther. 304, 1085–1092 (2003).

    Article  CAS  PubMed  Google Scholar 

  52. Magi, A. et al. EXCAVATOR: detecting copy number variants from whole-exome sequencing data. Genome Biol. 14, R120 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank H. Herschman, M. Teitell, and T. Graeber for their critical review of the manuscript. This work was funded by National Institutes of Health (NIH)/National Cancer Institute (NCI) R01 CA 213133 (D.A.N.), NIH/NCI UCLA SPORE in Brain Cancer P50 CA 211015 (D.A.N., T.F.C., S.J.B., H.I.K., and W.H.Y.), Nanosystems Biology Cancer Center U54 CA 199090 (D.A.N., T.F.C., and J.T.L.), a Jonsson Comprehensive Cancer Center Foundation/Seed Grant (D.A.N.), the Uncle Kory Foundation (D.A.N. and T.F.C.), the B Hasso Family Foundation (D.A.N. and T.F.C.), the Spiegelman Family Foundation in Memory of Barry Spiegelman (D.A.N. and T.F.C.), the Art of the Brain (T.F.C.), the Ziering Family Foundation (T.F.C. and P.S.M.), the National Brain Tumor Society (T.F.C. and P.S.M.), and the Ben And Catherine Ivy Foundation (T.F.C. and P.S.M.). A.L. and V.W.D. were supported by the Ludwig Institute for Cancer Research and NIH grant R01 CA 205967. H.I.K. was supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation and NIH grant NS 052563. W.X.M. was supported by National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) DGE-114087. We thank L. Abrey, J. Garcia, G. Nichols, S. Middleton, and L. Chen (all at Roche Pharmaceuticals) for their medical and scientific advice regarding idasanutlin; G. Coppola (UCLA) and Y. Qin (UCLA) for assistance in analyzing exome-sequencing data; K. Faull (UCLA) for help with mass spectrometry; L. Baufeld (UCLA) for technical assistance; J. Heath (Caltech) and M. Phelps (UCLA) for helpful discussions; and W. Fromer (Stanford), S. Korsmeyer (Dana-Farber Cancer Institute), R. Agami (The Netherlands Cancer Institute), and G. Lahav (Harvard) for reagents.

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W.X.M., T.F.C., and D.A.N. conceived the study. W.X.M., L.G., V.W.D., L.T., J.E.T., B.H., W.B.G., N.A.B., M.D.H., J.T.L., W.H.Y., P.N.R., A.L., and D.A.N. designed and/or conducted the experiments and analyzed data. B.H., H.I.K., S.J.B., P.S.M., P.M.C. and A.L. provided reagents, cell lines, and critical input. W.X.M. and D.A.N. wrote the original manuscript. All authors read and edited the manuscript.

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Correspondence to David A Nathanson.

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B.H. is an employee of Roche. T.F.C. has received consulting fees from Roche.

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Mai, W., Gosa, L., Daniels, V. et al. Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma. Nat Med 23, 1342–1351 (2017). https://doi.org/10.1038/nm.4418

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