Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

ACUTE MYELOID LEUKEMIA

Targeting cell cycle and apoptosis to overcome chemotherapy resistance in acute myeloid leukemia

Abstract

Chemotherapy-resistant acute myeloid leukemia (AML), frequently driven by clonal evolution, has a dismal prognosis. A genome-wide CRISPR knockout screen investigating resistance to doxorubicin and cytarabine (Dox/AraC) in human AML cell lines identified gene knockouts involving AraC metabolism and genes that regulate cell cycle arrest (cyclin dependent kinase inhibitor 2A (CDKN2A), checkpoint kinase 2 (CHEK2) and TP53) as contributing to resistance. In human AML cohorts, reduced expression of CDKN2A conferred inferior overall survival and CDKN2A downregulation occurred at relapse in paired diagnosis-relapse samples, validating its clinical relevance. Therapeutically targeting the G1S cell cycle restriction point (with CDK4/6 inhibitor, palbociclib and KAT6A inhibitor, WM-1119, to upregulate CDKN2A) synergized with chemotherapy. Additionally, direct promotion of apoptosis with venetoclax, showed substantial synergy with chemotherapy, overcoming resistance mediated by impaired cell cycle arrest. Altogether, we identify defective cell cycle arrest as a clinically relevant contributor to chemoresistance and identify rationally designed therapeutic combinations that enhance response in AML, potentially circumventing chemoresistance.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Brunello genome-wide CRISPR knockout screen investigating chemoresistance in AML cell lines.
Fig. 2: DCK inactivation diminishes cytotoxicity of combination chemotherapy in AML cells.
Fig. 3: CDKN2A and CHEK2 inactivation confer chemoresistance in OCI-AML3 cell lines.
Fig. 4: CDKN2A is a clinically relevant mediator of poor prognosis in human AML.
Fig. 5: Therapeutic targeting of G1S cell cycle restriction point with palbociclib potentiates apoptotic responses to chemotherapy.
Fig. 6: Promotion of apoptosis with venetoclax synergizes with chemotherapy in AML cell lines harboring defects in cell cycle arrest.

Similar content being viewed by others

Data availability

The RNA sequencing dataset generated and analyzed during the current study is available in the Gene Expression Omnibus repository (GSE205802).

References

  1. Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374:2209–21.

    Article  CAS  Google Scholar 

  2. Matthews J, Bishop J, Young G, Juneja S, Lowenthal R, Garson O, et al. Patterns of failure with increasing intensification of induction chemotherapy for acute myeloid leukaemia. Br J Haematol. 2001;113:727–36.

    Article  CAS  Google Scholar 

  3. Ganzel C, Sun Z, Cripe LD, Fernandez HF, Douer D, Rowe JM, et al. Very poor long‐term survival in past and more recent studies for relapsed AML patients: the ECOG‐ACRIN experience. Am J Hematol. 2018;93:1074–81.

    Article  Google Scholar 

  4. Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012;481:506.

    Article  CAS  Google Scholar 

  5. Rapaport F, Neelamraju Y, Baslan T, Hassane D, Gruszczynska A, Robert de Massy M, et al. Genomic and evolutionary portraits of disease relapse in acute myeloid leukemia. Leukemia. 2021;35:2688–92.

    Article  Google Scholar 

  6. Jongen-Lavrencic M, Grob T, Hanekamp D, Kavelaars FG, al Hinai A, Zeilemaker A, et al. Molecular minimal residual disease in acute myeloid leukemia. N Engl J Med. 2018;378:1189–99.

    Article  CAS  Google Scholar 

  7. Bell CC, Fennell KA, Chan Y-C, Rambow F, Yeung MM, Vassiliadis D, et al. Targeting enhancer switching overcomes non-genetic drug resistance in acute myeloid leukaemia. Nat Commun. 2019;10:2723.

    Article  Google Scholar 

  8. Sanjana NE, Shalem O, Zhang F. Improved vectors and genome-wide libraries for CRISPR screening. Nat Methods. 2014;11:783–4.

    Article  CAS  Google Scholar 

  9. Heckl D, Kowalczyk MS, Yudovich D, Belizaire R, Puram RV, McConkey ME, et al. Generation of mouse models of myeloid malignancy with combinatorial genetic lesions using CRISPR-Cas9 genome editing. Nat Biotechnol. 2014;32:941–6.

    Article  CAS  Google Scholar 

  10. Doench JG, Fusi N, Sullender M, Hegde M, Vaimberg EW, Donovan KF, et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat Biotechnol. 2016;34:184–91.

    Article  CAS  Google Scholar 

  11. Luo B, Cheung HW, Subramanian A, Sharifnia T, Okamoto M, Yang X, et al. Highly parallel identification of essential genes in cancer cells. Proc Natl Acad Sci USA. 2008;105:20380–5.

    Article  CAS  Google Scholar 

  12. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.

    Article  CAS  Google Scholar 

  13. Merolla F, Pentimalli F, Pacelli R, Vecchio G, Fusco A, Grieco M, et al. Involvement of H4 (D10S170) protein in ATM-dependent response to DNA damage. Oncogene. 2007;26:6167.

    Article  CAS  Google Scholar 

  14. Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49:D605–D12.

    Article  CAS  Google Scholar 

  15. Quelle DE, Zindy F, Ashmun RA, Sherr CJ. Alternative reading frames of the INK4a tumor suppressor gene encode two unrelated proteins capable of inducing cell cycle arrest. Cell. 1995;83:993–1000.

    Article  CAS  Google Scholar 

  16. Kim MY, Yu K-R, Kenderian SS, Ruella M, Chen S, Shin T-H, et al. Genetic inactivation of CD33 in hematopoietic stem cells to enable CAR T cell immunotherapy for acute myeloid leukemia. Cell. 2018;173:1439–53 e19.

    Article  CAS  Google Scholar 

  17. Zhao R, Choi BY, Lee M-H, Bode AM, Dong Z. Implications of genetic and epigenetic alterations of CDKN2A (p16INK4a) in cancer. EBioMedicine. 2016;8:30–9.

    Article  Google Scholar 

  18. Verhaak RG, Wouters BJ, Erpelinck CA, Abbas S, Beverloo HB, Lugthart S, et al. Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling. Haematologica. 2009;94:131–4.

    Article  Google Scholar 

  19. Metzeler KH, Hummel M, Bloomfield CD, Spiekermann K, Braess J, Sauerland M-C, et al. An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia. Blood. 2008;112:4193–201.

    Article  CAS  Google Scholar 

  20. Kharas MG, Lengner CJ, Al-Shahrour F, Bullinger L, Ball B, Zaidi S, et al. Musashi-2 regulates normal hematopoiesis and promotes aggressive myeloid leukemia. Nat Med. 2010;16:903–8.

    Article  CAS  Google Scholar 

  21. Li S, Garrett-Bakelman FE, Chung SS, Sanders MA, Hricik T, Rapaport F, et al. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 2016;22:792.

    Article  CAS  Google Scholar 

  22. Cocciardi S, Dolnik A, Kapp-Schwoerer S, Rücker FG, Lux S, Blätte TJ, et al. Clonal evolution patterns in acute myeloid leukemia with NPM1 mutation. Nat Commun. 2019;10:1–11.

    Article  CAS  Google Scholar 

  23. Bolouri H, Farrar JE, Triche T, Ries RE, Lim EL, Alonzo TA, et al. The molecular landscape of pediatric acute myeloid leukemia reveals recurrent structural alterations and age-specific mutational interactions. Nat Med. 2018;24:103–12.

    Article  CAS  Google Scholar 

  24. Baell JB, Leaver DJ, Hermans SJ, Kelly GL, Brennan MS, Downer NL, et al. Inhibitors of histone acetyltransferases KAT6A/B induce senescence and arrest tumour growth. Nature. 2018;560:253–7.

    Article  CAS  Google Scholar 

  25. DiNardo CD, Jonas BA, Pullarkat V, Thirman MJ, Garcia JS, Wei AH, et al. Azacitidine and venetoclax in previously untreated acute myeloid leukemia. N Engl J Med. 2020;383:617–29.

    Article  CAS  Google Scholar 

  26. Wei AH, Montesinos P, Ivanov V, DiNardo CD, Novak J, Laribi K, et al. Venetoclax plus LDAC for newly diagnosed AML ineligible for intensive chemotherapy: a phase 3 randomized placebo-controlled trial. Blood. 2020;135:2137–45.

    Article  CAS  Google Scholar 

  27. Lachowiez CA, Atluri H, DiNardo CD. Advancing the standard: venetoclax combined with intensive induction and consolidation therapy for acute myeloid leukemia. Ther Adv Hematol. 2022;13:20406207221093964.

  28. Kurata M, Rathe SK, Bailey NJ, Aumann NK, Jones JM, Veldhuijzen GW, et al. Using genome-wide CRISPR library screening with library resistant DCK to find new sources of Ara-C drug resistance in AML. Sci Rep. 2016;6:36199.

  29. Gruber E, Franich RL, Shortt J, Johnstone RW, Kats LM. Distinct and overlapping mechanisms of resistance to azacytidine and guadecitabine in acute myeloid leukemia. Leukemia. 2020;34:3388–92.

    Article  Google Scholar 

  30. Lamba JK. Genetic factors influencing cytarabine therapy. Pharmacogenomics 2009;10:1657–74.

    Article  CAS  Google Scholar 

  31. Veuger MJ, Honders MW, Willemze R, Barge RM. Deoxycytidine kinase expression and activity in patients with resistant versus sensitive acute myeloid leukemia. Eur J Haematol. 2002;69:171–8.

    Article  CAS  Google Scholar 

  32. Löwenberg B, Pabst T, Vellenga E, van Putten W, Schouten HC, Graux C, et al. Cytarabine dose for acute myeloid leukemia. N Engl J Med. 2011;364:1027–36.

    Article  Google Scholar 

  33. Lancet JE, Uy GL, Cortes JE, Newell LF, Lin TL, Ritchie EK, et al. CPX-351 (cytarabine and daunorubicin) liposome for injection versus conventional cytarabine plus daunorubicin in older patients with newly diagnosed secondary acute myeloid leukemia. J Clin Oncol. 2018;36:2684.

    Article  CAS  Google Scholar 

  34. Herold N, Rudd SG, Ljungblad L, Sanjiv K, Myrberg IH, Paulin CB, et al. Targeting SAMHD1 with the Vpx protein to improve cytarabine therapy for hematological malignancies. Nat Med. 2017;23:256.

    Article  CAS  Google Scholar 

  35. Schneider C, Oellerich T, Baldauf H-M, Schwarz S-M, Thomas D, Flick R, et al. SAMHD1 is a biomarker for cytarabine response and a therapeutic target in acute myeloid leukemia. Nat Med. 2017;23:250.

    Article  Google Scholar 

  36. Rücker FG, Schlenk RF, Bullinger L, Kayser S, Teleanu V, Kett H, et al. TP53 alterations in acute myeloid leukemia with complex karyotype correlate with specific copy number alterations, monosomal karyotype, and dismal outcome. Blood. 2012;119:2114–21.

    Article  Google Scholar 

  37. Grob T, Al Hinai AS, Sanders MA, Kavelaars FG, Rijken M, Gradowska PL, et al. Molecular characterization of mutant TP53 acute myeloid leukemia and high-risk myelodysplastic syndrome. Blood. 2022;139:2347–54.

    Article  CAS  Google Scholar 

  38. Craddock CF, Houlton AE, Quek LS, Ferguson P, Gbandi E, Roberts C, et al. Outcome of azacitidine therapy in acute myeloid leukemia is not improved by concurrent vorinostat therapy but is predicted by a diagnostic molecular signature. Clin Cancer Res. 2017;23:6430–40.

    Article  CAS  Google Scholar 

  39. Nangalia J, Massie CE, Baxter EJ, Nice FL, Gundem G, Wedge DC, et al. Somatic CALR mutations in myeloproliferative neoplasms with nonmutated JAK2. N Engl J Med. 2013;369:2391–405.

    Article  CAS  Google Scholar 

  40. Coombs CC, Zehir A, Devlin SM, Kishtagari A, Syed A, Jonsson P, et al. Therapy-related clonal hematopoiesis in patients with non-hematologic cancers is common and associated with adverse clinical outcomes. Cell Stem Cell. 2017;21:374–82.

    Article  CAS  Google Scholar 

  41. Bolton KL, Ptashkin RN, Gao T, Braunstein L, Devlin SM, Kelly D, et al. Cancer therapy shapes the fitness landscape of clonal hematopoiesis. Nat Genet. 2020;52:1219–26.

    Article  CAS  Google Scholar 

  42. Garg M, Nagata Y, Kanojia D, Mayakonda A, Yoshida K, Haridas Keloth S, et al. Profiling of somatic mutations in acute myeloid leukemia with FLT3-ITD at diagnosis and relapse. Blood. 2015;126:2491–501.

    Article  CAS  Google Scholar 

  43. Aleem E, Arceci RJ Targeting cell cycle regulators in hematologic malignancies. Front Cell Dev Biol. 2015;3:16.

  44. Yan F, Li J, Milosevic J, Petroni R, Liu S, Shi Z, et al. KAT6A and ENL form an epigenetic transcriptional control module to drive critical leukemogenic gene-expression programs. Cancer Discov. 2022;12:792–811.

    Article  CAS  Google Scholar 

  45. MacPherson, L, Anokye J, Yeung, MM, Lam EY, Chan Y-C, Weng C-F, et al. HBO1 is required for the maintenance of leukaemia stem cells. Nature. 2020;577:266–70.

  46. Finn RS, Martin M, Rugo HS, Jones S, Im S-A, Gelmon K, et al. Palbociclib and letrozole in advanced breast cancer. N Engl J Med. 2016;375:1925–36.

    Article  CAS  Google Scholar 

  47. Turner NC, Slamon DJ, Ro J, Bondarenko I, Im S-A, Masuda N, et al. Overall survival with palbociclib and fulvestrant in advanced breast cancer. N Engl J Med. 2018;379:1926–36.

    Article  CAS  Google Scholar 

  48. Placke T, Faber K, Nonami A, Putwain SL, Salih HR, Heidel FH, et al. Requirement for CDK6 in MLL-rearranged acute myeloid leukemia. Blood. 2014;124:13–23.

    Article  CAS  Google Scholar 

  49. Van der Linden M, Willekes M, van Roon E, Seslija L, Schneider P, Pieters R, et al. MLL fusion-driven activation of CDK6 potentiates proliferation in MLL-rearranged infant ALL. Cell Cycle. 2014;13:834–44.

    Article  Google Scholar 

  50. Uras IZ, Walter GJ, Scheicher R, Bellutti F, Prchal-Murphy M, Tigan AS, et al. Palbociclib treatment of FLT3-ITD+ AML cells uncovers a kinase-dependent transcriptional regulation of FLT3 and PIM1 by CDK6. Blood. 2016;127:2890–902.

    Article  CAS  Google Scholar 

  51. Wang L, Wang J, Blaser BW, Duchemin A-M, Kusewitt DF, Liu T, et al. Pharmacologic inhibition of CDK4/6: mechanistic evidence for selective activity or acquired resistance in acute myeloid leukemia. Blood. 2007;110:2075–83.

    Article  CAS  Google Scholar 

  52. Martinez-Soria N, McKenzie L, Draper J, Ptasinska A, Issa H, Potluri S, et al. The oncogenic transcription factor RUNX1/ETO corrupts cell cycle regulation to drive leukemic transformation. Cancer Cell. 2018;34:626–42.

    Article  CAS  Google Scholar 

  53. Salvador-Barbero B, Álvarez-Fernández M, Zapatero-Solana E, El Bakkali A, del Camino Menéndez M, López-Casas PP, et al. CDK4/6 inhibitors impair recovery from cytotoxic chemotherapy in pancreatic adenocarcinoma. Cancer Cell. 2020;37:340–53.

    Article  CAS  Google Scholar 

  54. Ishikawa F, Yoshida S, Saito Y, Hijikata A, Kitamura H, Tanaka S, et al. Chemotherapy-resistant human AML stem cells home to and engraft within the bone-marrow endosteal region. Nat Biotechnol. 2007;25:1315–21.

    Article  CAS  Google Scholar 

  55. Duy C, Li M, Teater M, Meydan C, Garrett-Bakelman FE, Lee TC, et al. Chemotherapy induces senescence-like resilient cells capable of initiating AML recurrence. Cancer Discov. 2021;11:1542–61.

    Article  CAS  Google Scholar 

  56. DiNardo C, Tiong I, Quaglieri A, MacRaild S, Loghavi S, Brown F, et al. Molecular patterns of response and treatment failure after frontline venetoclax combinations in older patients with AML. Blood. 2020;135:791–803.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The work was funded through grants from the National Health and Medical Research Council (NHMRC), Australia (Postgraduate Scholarship to VYL, Fellowship to MJB and Fellowship to SWL), CSL Centenary Fellowship (SWL) and the Gordon and Jessie Gilmour Leukaemia Research Fund (SWL). The authors thank and acknowledge Marco Herold (Walter and Eliza Hall Institute, Melbourne, Australia) for provision of critical reagents and expert technical advice and Peter Adams and Xue Lei (Sanford Burnham Prebys, California, United States of America (USA)) for analysis of RNA sequencing data (shown in Supplementary Fig. 12) and helpful discussions. We further thank Geoffrey Hill (Fred Hutch Cancer Center, Washington, USA), Richard D’Andrea (University of South Australia, Adelaide, Australia), Jason Powell (University of South Australia) and Francine Garrett-Bakelman (University of Virginia, Virginia, USA) for helpful discussions. The authors thank all the members of the Translational Leukaemia Research laboratory, QIMR Berghofer Medical Research Institute (Brisbane, Australia) for helpful discussions and technical assistance and the QIMR Berghofer core facilities (including the animal facility, flow cytometry and sequencing laboratory) for technical assistance.

Author information

Authors and Affiliations

Authors

Contributions

VYL, SJ, MJB and SWL conceived and designed the work. VYL, JS, WG, RH, YJ, LC, CB, EC, PTS, SJ and MJB acquired data and interpreted results. JB, FH, JJ and YZ designed and performed experiments to supply critical reagents. ST, JB and LB provided intellectual input and/or critical reagents and interpreted results. VYL, MJB and SWL wrote the manuscript. All authors revised the manuscript and approved the final version.

Corresponding authors

Correspondence to Megan J. Bywater or Steven W. Lane.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ling, V.Y., Straube, J., Godfrey, W. et al. Targeting cell cycle and apoptosis to overcome chemotherapy resistance in acute myeloid leukemia. Leukemia 37, 143–153 (2023). https://doi.org/10.1038/s41375-022-01755-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-022-01755-2

This article is cited by

Search

Quick links