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Venetoclax with azacitidine disrupts energy metabolism and targets leukemia stem cells in patients with acute myeloid leukemia

Abstract

Acute myeloid leukemia (AML) is the most common acute leukemia in adults. Leukemia stem cells (LSCs) drive the initiation and perpetuation of AML, are quantifiably associated with worse clinical outcomes, and often persist after conventional chemotherapy resulting in relapse1,2,3,4,5. In this report, we show that treatment of older patients with AML with the B cell lymphoma 2 (BCL-2) inhibitor venetoclax in combination with azacitidine results in deep and durable remissions and is superior to conventional treatments. We hypothesized that these promising clinical results were due to targeting LSCs. Analysis of LSCs from patients undergoing treatment with venetoclax + azacitidine showed disruption of the tricarboxylic acid (TCA) cycle manifested by decreased α-ketoglutarate and increased succinate levels, suggesting inhibition of electron transport chain complex II. In vitro modeling confirmed inhibition of complex II via reduced glutathionylation of succinate dehydrogenase. These metabolic perturbations suppress oxidative phosphorylation (OXPHOS), which efficiently and selectively targets LSCs. Our findings show for the first time that a therapeutic intervention can eradicate LSCs in patients with AML by disrupting the metabolic machinery driving energy metabolism, resulting in promising clinical activity in a patient population with historically poor outcomes.

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Fig. 1: Clinical responses for the 33 patients treated with venetoclax + azacitidine at a single institution.
Fig. 2: Mass cytometry and single-cell transcriptomics at early timepoints show significant decreases in blasts and LSCs.
Fig. 3: Venetoclax + azacitidine reduces oxidative phosphorylation in AML LSCs.
Fig. 4: Venetoclax + azacitidine reduces complex II activity through reduction in SDHA glutathionylation.

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Data availability

Patient-related clinical data not included in the paper were generated as part of a multicenter clinical trial (NCT02203773). A detailed description of the dose escalation portion of the study has been published (Dinardo et al.)1. The dose expansion portion of the study is now complete and the manuscript describing these data is currently in preparation. All DNA and RNA raw and analyzed sequencing data can be found at the GEO database and are available via accession number GSE116481 (single-cell RNA-seq) and accession number GSE116567 (bulk RNA-seq).

References

  1. Bonnet, D. & Dick, J. E. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med. 3, 730–737 (1997).

    Article  CAS  PubMed  Google Scholar 

  2. van Rhenen, A. et al. High stem cell frequency in acute myeloid leukemia at diagnosis predicts high minimal residual disease and poor survival. Clin. Cancer Res. 11, 6520–6527 (2005).

    Article  CAS  PubMed  Google Scholar 

  3. Shlush, L. I. et al. Identification of pre-leukaemic haematopoietic stem cells in acute leukaemia. Nature 506, 328–333 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Lapidot, T. et al. A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 367, 645–648 (1994).

    Article  CAS  PubMed  Google Scholar 

  5. Jordan, C. T., Guzman, M. L. & Noble, M. Cancer stem cells. N. Engl. J. Med. 355, 1253–1261 (2006).

    Article  CAS  PubMed  Google Scholar 

  6. Chao, D. T. & Korsmeyer, S. J. BCL-2 family: regulators of cell death. Annu. Rev. Immunol. 16, 395–419 (1998).

    Article  CAS  PubMed  Google Scholar 

  7. Lagadinou, E. D. BCL-2 inhibition targets oxidative phosphorylation and selectively eradicates quiescent human leukemia stem cells. Cell Stem Cell 12, 329–341 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Konopleva, M. et al. Mechanisms of antileukemic activity of the novel Bcl-2 homology domain-3 mimetic GX15-070 (obatoclax). Cancer Res. 68, 3413–3420 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Konopleva, M. et al. Mechanisms of apoptosis sensitivity and resistance to the BH3 mimetic ABT-737 in acute myeloid leukemia. Cancer Cell 10, 375–388 (2006).

    Article  CAS  PubMed  Google Scholar 

  10. Chan, S. M. et al. Isocitrate dehydrogenase 1 and 2 mutations induce BCL-2 dependence in acute myeloid leukemia. Nat. Med. 21, 178–184 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Souers, A. J. et al. ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets. Nat. Med. 19, 202–208 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. Pan, R. et al. Selective BCL-2 inhibition by ABT-199 causes on-target cell death in acute myeloid leukemia. Cancer Discov. 4, 362–375 (2014).

    Article  CAS  PubMed  Google Scholar 

  13. Konopleva, M. et al. Efficacy and biological correlates of response in a phase II study of venetoclax monotherapy in patients with acute myelogenous leukemia. Cancer Discov. 6, 1106–1117 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. DiNardo, C. D. et al. Safety and preliminary efficacy of venetoclax with decitabine or azacitidine in elderly patients with previously untreated acute myeloid leukaemia: a non-randomised, open-label, phase 1b study. Lancet. Oncol. 19, 216–228 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Ng, S. W. et al. A 17-gene stemness score for rapid determination of risk in acute leukaemia. Nature 540, 433–437 (2016).

    Article  CAS  Google Scholar 

  16. Eppert, K. et al. Stem cell gene expression programs influence clinical outcome in human leukemia. Nat. Med. 17, 1086–1093 (2011).

    Article  CAS  PubMed  Google Scholar 

  17. Pei, S. et al. MPK/FIS1-Mediated mitophagy is required for self-renewal of human AML stem cells. Cell Stem Cell 23, 86–100 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Sarry, J. E. et al. Human acute myelogenous leukemia stem cells are rare and heterogeneous when assayed in NOD/SCID/IL2Rgammac-deficient mice. J. Clin. Invest. 121, 384–395 (2011).

    Article  CAS  PubMed  Google Scholar 

  19. Ho, T. C. et al. Evolution of acute myelogenous leukemia stem cell properties after treatment and progression. Blood 128, 1671–1678 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chen, Y. R., Chen, C. L., Pfeiffer, D. R. & Zweier, J. L. Mitochondrial complex II in the post-ischemic heart: oxidative injury and the role of protein S-glutathionylation. J. Biol. Chem. 282, 32640–32654 (2007).

    Article  CAS  PubMed  Google Scholar 

  21. Yadav, B., Wennerberg, K., Aittokallio, T. & Tang, J. Searching for drug synergy in complex dose–response landscapes using an interaction potency model. Comput. Struct. Biotechnol. J. 13, 504–513 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ianevski, A., He, L., Aittokallio, T. & Tang, J. SynergyFinder: a web application for analyzing drug combination dose–response matrix data. Bioinformatics 33, 2413–2415 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dombret, H. et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with > 30% blasts. Blood 126, 291–299 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ivey, A. et al. Assessment of minimal residual disease in standard-risk AML. N. Engl. J. Med. 374, 422–433 (2016).

    Article  CAS  PubMed  Google Scholar 

  25. Pollyea, D. A., Gutman, J. A., Gore, L., Smith, C. A. & Jordan, C. T. Targeting acute myeloid leukemia stem cells: a review and principles for the development of clinical trials. Haematologica 99, 1277–1284 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Pollyea, D. A. & Jordan, C. T. Therapeutic targeting of acute myeloid leukemia stem cells. Blood 129, 1627–1635 (2017).

    Article  CAS  PubMed  Google Scholar 

  27. Warburg, O. On the origin of cancer cells. Science 123, 309–314 (1956).

    Article  CAS  PubMed  Google Scholar 

  28. Viale, A. et al. Oncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function. Nature 514, 628–632 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lee, K. M. et al. MYC and MCL1 cooperatively promote chemotherapy-resistant breast cancer stem cells via regulation of mitochondrial oxidative phosphorylation. Cell Metab. 26, 633–647.e7 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Sriskanthadevan, S. et al. AML cells have low spare reserve capacity in their respiratory chain that renders them susceptible to oxidative metabolic stress. Blood 125, 2120–2130 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cole, A. et al. Inhibition of the mitochondrial protease ClpP as a therapeutic strategy for human acute myeloid leukemia. Cancer Cell 27, 864–876 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Skrtic, M. et al. Inhibition of mitochondrial translation as a therapeutic strategy for human acute myeloid leukemia. Cancer Cell 20, 674–688 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kurtz, S. E. et al. Molecularly targeted drug combinations demonstrate selective effectiveness for myeloid- and lymphoid-derived hematologic malignancies. Proc. Natl Acad. Sci. USA 114, E7554–E7563 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. Bogenberger, J. M. et al. Ex vivo activity of BCL-2 family inhibitors ABT-199 and ABT-737 combined with 5-azacytidine in myeloid malignancies. Leukemia Lymphoma 56, 226–229 (2015).

    Article  PubMed  Google Scholar 

  35. Bogenberger, J. M. et al. BCL-2 family proteins as 5-azacytidine-sensitizing targets and determinants of response in myeloid malignancies. Leukemia 28, 1657–1665 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Slovak, M. L. et al. Karyotypic analysis predicts outcome of preremission and postremission therapy in adult acute myeloid leukemia: a Southwest Oncology Group/Eastern Cooperative Oncology Group Study. Blood 96, 4075–4083 (2000).

    CAS  PubMed  Google Scholar 

  37. Cheson, B. D. et al. Revised recommendations of the International Working Group for Diagnosis, Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in Acute Myeloid Leukemia. J. Clin. Oncol. 21, 4642–4649 (2003).

    Article  PubMed  Google Scholar 

  38. Pei, S. et al. Rational design of a parthenolide-based drug regimen that selectively eradicates acute myelogenous leukemia stem cells. J. Biol. Chem. 291, 21984–22000 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Amir, E.-A. D. et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 31, 545–552 (2013).

    Article  CAS  PubMed Central  Google Scholar 

  40. Nemkov, T., D’Alessandro, A. & Hansen, K. C. Three-minute method for amino acid analysis by UHPLC and high-resolution quadrupole orbitrap mass spectrometry. Amino Acids 47, 2345–2357 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

In memory of Richard Berger, a warrior in all aspects of life, who bravely confronted every obstacle and brought courage and inspiration to us, his family and all who were privileged enough to know him. Grant support: D.A.P is supported by the University of Colorado Department of Medicine Outstanding Early Career Scholar Program. B.M.S. and C.T.J are supported by a pilot grant provided by the University of Colorado RNA Bioscience Initiative. C.L.J. was supported by the American Cancer Society (25A5072) and the Colorado Clinical and Translational Sciences Institute (AEF CCTSI YR9 CO 2301425). A.D. is supported by the Webb-Waring Early Career award 2017 sponsored by the Boettcher Foundation. C.T.J. is generously supported by the Nancy Carroll Allen Chair in Hematology Research and NIH (grant R01CA200707). We thank J. DeGregori and E. Pietras for their comments on our manuscript.

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Authors

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D.A.P., B.M.S., C.L.J., A.W., M.M., and R.C.-H. designed and performed the research; collected, analyzed, and interpreted the data; performed the statistical analysis; and wrote the manuscript. S.P., A.D., K.A.R., A.E.G., J.R.H., D.A., and D.S. analyzed and interpreted data, performed statistical analysis, and wrote the manuscript. J.A.G., E.P., and C.S. designed the research and wrote the manuscript. C.T.J. designed and directed the research, analyzed and interpreted data, and wrote the manuscript.

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Correspondence to Craig T. Jordan.

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Supplementary Text and Figures

Supplementary Figures 1–9, Supplementary Tables 1, 3, and 6–8 and Supplementary Methods

Reporting Summary

Supplementary Table 2

Institutional control patient characteristics

Supplementary Table 4

True-seq library coverage

Supplementary Table 5

Patient peripheral blood temporal response

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Pollyea, D.A., Stevens, B.M., Jones, C.L. et al. Venetoclax with azacitidine disrupts energy metabolism and targets leukemia stem cells in patients with acute myeloid leukemia. Nat Med 24, 1859–1866 (2018). https://doi.org/10.1038/s41591-018-0233-1

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