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.

p53-NEIL1 co-abnormalities induce genomic instability and promote synthetic lethality with Chk1 inhibition in multiple myeloma having concomitant 17p13(del) and 1q21(gain)

Oncogene volume 41, pages 2106–2121 (2022)Cite this article

Subjects

Abstract

Recurrent cytogenetic abnormalities are the main hallmark of multiple myeloma (MM) and patients having 2 or more high-risk prognostic events are associated with extremely poor outcome. 17p13(del) and 1q21(gain) are critical and independent high-risk cytogenetic markers, however, the biological significance underlying the poor outcome in MM patients having co-occurrence of both these chromosomal aberrations has never been interrogated. Herein, we identified that patients harbouring concomitant 17p13(del) with 1q21(gain) demonstrated the worst prognosis as compared to patients with single- (either 17p13(del) or 1q21(gain)) and with no chromosomal events (WT for both chromosomal loci); and they are highly enriched for genomic instability (GI) signature. We discovered that the GI feature in the patients with concomitant 17p13(del)-1q21(gain) was recapitulating the biological properties of myeloma cells with co-existing p53-deficiency and NEIL1 mRNA-hyper-editing (associated with chromosome 17p and 1q, respectively) that have inherent DNA damage response (DDR) and persistent activation of Chk1 pathway. Importantly, this became a vulnerable point for therapeutic targeting whereby the cells with this co-abnormalities demonstrated hyper-sensitivity to siRNA- and pharmacological-mediated-Chk1 inhibition, as observed at both the in vitro and in vivo levels. Mechanistically, this was attributable to the synthetic lethal relationship between p53-NEIL1-Chk1 abnormalities. The Chk1 inhibitor (AZD7762) tested showed good synergism with standard-of-care myeloma drugs, velcade and melphalan, thus further reinforcing the translational potential of this therapeutic approach. In summary, combination of NEIL1-p53 abnormalities with an ensuing Chk1 activation could serve as an Achilles heel and predispose MM cells with co-existing 1q21(gain) and 17p13(del) to therapeutic vulnerability for Chk1 inhibition.

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

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

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

Fig. 1: DDR is clinically relevant and MM cells are vulnerable to CHK1 inhibition.
Fig. 2: NEIL1-hyper editing enhanced DSBs and is synthetically lethal with Chk1 inhibition.
Fig. 3: MM cells lacking functional p53 are more sensitive to Chk1 inhibition.
Fig. 4: Combination of NEIL1-hyperediting and p53-deficiency heightened DSBs and increased vulnerability to Chk1 inhibition.
Fig. 5: 17p13(del) and 1q21(gain) co-abnormalities were associated with genomic instability.
Fig. 6: Therapeutic implications of DDR abnormalities in MM.
Fig. 7: Schematic diagram demonstrating the plausible synthetic lethality model in MM.

References

  1. Fonseca R, Bergsagel PL, Drach J, Shaughnessy J, Gutierrez N, Stewart AK, et al. International myeloma working group molecular classification of multiple myeloma: Spotlight review. Leukemia 2009;23:2210–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bolli N, Biancon G, Moarii M, Gimondi S, Li Y, de Philippis C, et al. Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups. Leukemia 2018;32:2604–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Walker BA, Mavrommatis K, Wardell CP, Ashby TC, Bauer M, Davies F, et al. A high-risk, double-Hit, group of newly diagnosed myeloma identified by genomic analysis. Leukemia 2019;33:159–70.

    Article  CAS  PubMed  Google Scholar 

  4. Shah V, Sherborne AL, Walker BA, Johnson DC, Boyle EM, Ellis S, et al. Prediction of outcome in newly diagnosed myeloma: a meta-analysis of the molecular profiles of 1905 trial patients. Leukemia 2018;32:102–10.

    Article  CAS  PubMed  Google Scholar 

  5. Boyd KD, Ross FM, Chiecchio L, Dagrada GP, Konn ZJ, Tapper WJ, et al. A novel prognostic model in myeloma based on co-segregating adverse FISH lesions and the ISS: Analysis of patients treated in the MRC Myeloma IX trial. Leukemia 2012;26:349–55.

    Article  CAS  PubMed  Google Scholar 

  6. Hao S, Lu X, Gong Z, Bassett RL, Hu S, Konoplev SN, et al. The survival impact of CKS1B gains or amplification is dependent on the background karyotype and TP53 deletion status in patients with myeloma. Mod Pathol. 2021;34:327–35.

    Article  CAS  PubMed  Google Scholar 

  7. Schmidt TM, Fonseca R, Usmani SZ. Chromosome 1q21 abnormalities in multiple myeloma. Blood Cancer J. 2021;11:83.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Stewart AK, Rajkumar SV, Dimopoulos MA, Masszi T, Spicka I, Oriol A, et al. Carfilzomib, lenalidomide, and dexamethasone for relapsed multiple myeloma. N. Engl J Med. 2015;372:142–52.

    Article  PubMed  Google Scholar 

  9. Jakubowiak AJ, Siegel DS, Martin T, Wang M, Vij R, Lonial S, et al. Treatment outcomes in patients with relapsed and refractory multiple myeloma and high-risk cytogenetics receiving single-agent carfilzomib in the PX-171-003-A1 study. Leukemia 2013;27:2351–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Avet-Loiseau H, Leleu X, Roussel M, Moreau P, Guerin-Charbonnel C, Caillot D, et al. Bortezomib plus dexamethasone induction improves outcome of patients with t(4;14) myeloma but not outcome of patients with del(17p). J Clin Oncol: Off J Am Soc Clin Oncol. 2010;28:4630–4.

    Article  CAS  Google Scholar 

  11. Dimopoulos MA, Kastritis E, Christoulas D, Migkou M, Gavriatopoulou M, Gkotzamanidou M, et al. Treatment of patients with relapsed/refractory multiple myeloma with lenalidomide and dexamethasone with or without bortezomib: prospective evaluation of the impact of cytogenetic abnormalities and of previous therapies. Leukemia 2010;24:1769–78.

    Article  CAS  PubMed  Google Scholar 

  12. Chang H, Trieu Y, Qi X, Jiang NN, Xu W, Reece D. Impact of cytogenetics in patients with relapsed or refractory multiple myeloma treated with bortezomib: Adverse effect of 1q21 gains. Leuk Res. 2011;35:95–8.

    Article  CAS  PubMed  Google Scholar 

  13. Sonneveld P, Broijl A. Treatment of relapsed and refractory multiple myeloma. Haematologica 2016;101:396.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Neri P, Bahlis NJ. Genomic instability in multiple myeloma: Mechanisms and therapeutic implications. Expert Opin Biol Ther. 2013;13:S69–S82.

    Article  CAS  PubMed  Google Scholar 

  15. Agnelli L, Tassone P, Neri A. Molecular profiling of multiple myeloma: From gene expression analysis to next-generation sequencing. Expert Opin Biol Ther. 2013;13:S55–68. Suppl 1

    Article  CAS  PubMed  Google Scholar 

  16. Kumar SK. Targeted management strategies in multiple myeloma. Cancer J. 2019;25:59–64.

    Article  CAS  PubMed  Google Scholar 

  17. Chapman MA, Lawrence MS, Keats JJ, Cibulskis K, Sougnez C, Schinzel AC, et al. Initial genome sequencing and analysis of multiple myeloma. Nature 2011;471:467–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Herrero AB, Gutiérrez NC. Targeting ongoing DNA damage in multiple myeloma: Effects of DNA damage response inhibitors on plasma cell survival. Front Oncol. 2017;7:98.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Herrero AB, San Miguel J, Gutierrez NC. Deregulation of DNA double-strand break repair in multiple myeloma: Implications for genome stability. PloS One. 2015;10:e0121581.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Shammas MA, Shmookler Reis RJ, Koley H, Batchu RB, Li C, Munshi NC. Dysfunctional homologous recombination mediates genomic instability and progression in myeloma. Blood 2009;113:2290–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Yang CG, Garcia K, He C. Damage detection and base flipping in direct DNA alkylation repair. Chembiochem: Eur J Chem Biol. 2009;10:417–23.

    Article  CAS  Google Scholar 

  22. Hayden PJ, Tewari P, Morris DW, Staines A, Crowley D, Nieters A, et al. Variation in DNA repair genes XRCC3, XRCC4, XRCC5 and susceptibility to myeloma. Hum Mol Genet. 2007;16:3117–27.

    Article  CAS  PubMed  Google Scholar 

  23. Sousa MM, Zub KA, Aas PA, Hanssen-Bauer A, Demirovic A, Sarno A, et al. An inverse switch in DNA base excision and strand break repair contributes to melphalan resistance in multiple myeloma cells. PloS One. 2013;8:e55493.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Teoh PJ, An O, Chung TH, Chooi JY, Toh SHM, Fan S, et al. Aberrant hyperediting of the myeloma transcriptome by ADAR1 confers oncogenicity and is a marker of poor prognosis. Blood 2018;132:1304–17.

    Article  CAS  PubMed  Google Scholar 

  25. Gkotzamanidou M, Terpos E, Bamia C, Munshi NC, Dimopoulos MA, Souliotis VL. DNA repair of myeloma plasma cells correlates with clinical outcome: The effect of the nonhomologous end-joining inhibitor SCR7. Blood 2016;128:1214.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Cottini F, Hideshima T, Suzuki R, Tai Y-T, Bianchini G, Richardson PG, et al. Synthetic lethal approaches exploiting DNA damage in aggressive myeloma. Cancer Discov. 2015;5:972.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Janz S, Zhan F, Sun F, Cheng Y, Pisano M, Yang Y, et al. Germline Risk Contribution to Genomic Instability in Multiple Myeloma. Front Genet. 2019;10:424.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Gu C, Wang W, Tang X, Xu T, Zhang Y, Guo M, et al. CHEK1 and circCHEK1_246aa evoke chromosomal instability and induce bone lesion formation in multiple myeloma. Mol Cancer. 2021;20:84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Herrero AB, Rojas EA, Misiewicz-Krzeminska I, Krzeminski P, Gutiérrez NC. Molecular mechanisms of p53 deregulation in cancer: An overview in multiple myeloma. Int J Mol Sci. 2016;17:2003.

    Article  PubMed Central  Google Scholar 

  30. Bieging KT, Mello SS, Attardi LD. Unravelling mechanisms of p53-mediated tumour suppression. Nat Rev Cancer. 2014;14:359–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Eischen CM. Genome Stability Requires p53. Cold Spring Harb Perspect Med. 2016;6:a026096.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Teoh PJ, Chung TH, Sebastian S, Choo SN, Yan J, Ng SB, et al. p53 haploinsufficiency and functional abnormalities in multiple myeloma. Leukemia 2014;14:102.

    Google Scholar 

  33. Kawasumi M, Bradner JE, Tolliday N, Thibodeau R, Sloan H, Brummond KM, et al. Identification of ATR–Chk1 pathway inhibitors that selectively target p53-deficient cells without directly suppressing ATR catalytic activity. Cancer Res. 2014;74:7534.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Teoh PJ, Chung T-H, Chng PYZ, Toh SHM, Chng WJ. IL6R-STAT3-ADAR1 (P150) interplay promotes oncogenicity in multiple myeloma with 1q21 amplification. Haematologica. 2020;105:1391–404.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Lazzari E, Mondala PK, Santos ND, Miller AC, Pineda G, Jiang Q, et al. Alu-dependent RNA editing of GLI1 promotes malignant regeneration in multiple myeloma. Nat Commun. 2017;8:1922.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Teoh PJ, Koh MY, Chng WJ. ADARs, RNA editing and more in hematological malignancies. Leukemia 2021;35:346–59.

    Article  CAS  PubMed  Google Scholar 

  37. Rundle S, Bradbury A, Drew Y, Curtin NJ. Targeting the ATR-CHK1 axis in cancer therapy. Cancers (Basel). 2017;9:41.

    Article  Google Scholar 

  38. Qiu Z, Oleinick NL, Zhang J. ATR/CHK1 inhibitors and cancer therapy. Radiother Oncol. 2018;126:450–64.

    Article  CAS  PubMed  Google Scholar 

  39. Zabludoff SD, Deng C, Grondine MR, Sheehy AM, Ashwell S, Caleb BL, et al. AZD7762, a novel checkpoint kinase inhibitor, drives checkpoint abrogation and potentiates DNA-targeted therapies. Mol Cancer Therapeutics. 2008;7:2955–66.

    Article  CAS  Google Scholar 

  40. Landau HJ, McNeely SC, Nair JS, Comenzo RL, Asai T, Friedman H, et al. The checkpoint kinase inhibitor AZD7762 potentiates chemotherapy-induced apoptosis of p53-mutated multiple myeloma cells. Mol Cancer Therapeutics. 2012;11:1781–8.

    Article  CAS  Google Scholar 

  41. Tembhare P, Yuan C, Korde N, Maric I, Landgren O. Antigenic drift in relapsed extramedullary multiple myeloma: Plasma cells without CD38 expression. Leuk Lymphoma. 2012;53:721–4.

    Article  PubMed  Google Scholar 

  42. Ma Z, Yao G, Zhou B, Fan Y, Gao S, Feng X. The Chk1 inhibitor AZD7762 sensitises p53 mutant breast cancer cells to radiation in vitro and in vivo. Mol Med Rep. 2012;6:897–903.

    Article  CAS  PubMed  Google Scholar 

  43. Muller FL, Colla S, Aquilanti E, Manzo VE, Genovese G, Lee J, et al. Passenger deletions generate therapeutic vulnerabilities in cancer. Nature 2012;488:337–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Chung T-H, Mulligan G, Fonseca R, Chng WJ. A novel measure of chromosome instability can account for prognostic difference in multiple myeloma. PloS One. 2013;8:e66361.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chibon F, Lagarde P, Salas S, Perot G, Brouste V, Tirode F, et al. Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity. Nat Med. 2010;16:781–7.

    Article  CAS  PubMed  Google Scholar 

  46. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet. 2006;38:1043–8.

    Article  CAS  PubMed  Google Scholar 

  47. Chin SF, Teschendorff AE, Marioni JC, Wang Y, Barbosa-Morais NL, Thorne NP, et al. High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer. Genome Biol. 2007;8:R215.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Gourzones-Dmitriev C, Kassambara A, Sahota S, Rème T, Moreaux J, Bourquard P, et al. DNA repair pathways in human multiple myeloma: Role in oncogenesis and potential targets for treatment. Cell Cycle. 2013;12:2760–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ray A, Ravillah D, Das DS, Song Y, Nordström E, Gullbo J, et al. A novel alkylating agent Melflufen induces irreversible DNA damage and cytotoxicity in multiple myeloma cells. Br J Haematol. 2016;174:397–409.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Neri P, Ren L, Gratton K, Stebner E, Johnson J, Klimowicz A, et al. Bortezomib-induced “BRCAness” sensitizes multiple myeloma cells to PARP inhibitors. Blood 2011;118:6368–79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Chng WJ, Huang GF, Chung TH, Ng SB, Gonzalez-Paz N, Troska-Price T, et al. Clinical and biological implications of MYC activation: a common difference between MGUS and newly diagnosed multiple myeloma. Leukemia 2011;25:1026–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was funded by Tier 2 grant provided by the Ministry of Education of Singapore (MOE2019-T2-1-083) and NMRC OF-YIRG grant (NMRC/OFYIRG/032/2017-00). We would like to thank Pamela Chng for helping out with tissue culture and functional assays, Y.F. Goh, J.Q. Thng and W.N. Fam for helping with the processing and isolation of normal CD138 + plasma cells from healthy volunteers’ samples and M.Y. Koh for assisting in lentivirus work.

Author information

Authors and Affiliations

  1. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Phaik Ju Teoh, Anand D. Jeyasekharan & Wee Joo Chng

  2. Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore

    Phaik Ju Teoh, Omer An, Tae-Hoon Chung, Michal M. Hoppe, Sabrina H. M. Toh, Melissa J. Fullwood, Anand D. Jeyasekharan, Leilei Chen, Henry Yang & Wee Joo Chng

  3. Institute of Molecular and Cell Biology (IMCB), Agency for Science. Technology and Research (A-Star), Singapore, Singapore

    Thamil Vaiyapuri, Anandhkumar Raju & Vinay Tergaonkar

  4. Department of Orthopaedic Surgery, National University Hospital, Singapore, Singapore

    Wilson Wang & Ming Chun Chan

  5. Department of Orthopaedic Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Wilson Wang & Ming Chun Chan

  6. National University Cancer Institute, Singapore, Singapore

    Anand D. Jeyasekharan & Wee Joo Chng

  7. Department of Haematology-Oncology, National University Cancer Institute of Singapore, National University Health System, Singapore, Singapore

    Anand D. Jeyasekharan & Wee Joo Chng

Authors
  1. Phaik Ju Teoh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omer An
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tae-Hoon Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thamil Vaiyapuri
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Anandhkumar Raju
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michal M. Hoppe
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sabrina H. M. Toh
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Wilson Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ming Chun Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Melissa J. Fullwood
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Anand D. Jeyasekharan
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Vinay Tergaonkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Leilei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Henry Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Wee Joo Chng
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

PJT designed the study and performed all the wet experiments, analysed and interpreted data, and was entirely involved in the manuscript preparation, from drafting, editing to final submission. OA, THC, and HY were involved in bioinformatics analyses of MM datasets. TSV, AR, and VT contributed to the in vivo mouse work. MMH and ADJ performed IF on patient TMA, imaging, and data analysis. SHMT helped with the wet experiments and processing of primary patient samples. WW and MCC were the clinicians who performed hip surgeries on the healthy volunteers and harvested the bone marrow samples for CD138 + isolation. LC and MJF provided experimental advice, contributed vital reagents, and proofread the manuscript. WJC conceptualised the study, provided study direction, proofread and finalized the paper.

Corresponding author

Correspondence to Phaik Ju Teoh.

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

Verify currency and authenticity via CrossMark

Cite this article

Teoh, P.J., An, O., Chung, TH. et al. p53-NEIL1 co-abnormalities induce genomic instability and promote synthetic lethality with Chk1 inhibition in multiple myeloma having concomitant 17p13(del) and 1q21(gain). Oncogene 41, 2106–2121 (2022). https://doi.org/10.1038/s41388-022-02227-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41388-022-02227-8

Search

Advanced search

Quick links