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Multiple myeloma gammopathies

Monitoring tumour burden and therapeutic response through analysis of circulating tumour DNA and extracellular RNA in multiple myeloma patients

Abstract

Monitoring tumour burden and therapeutic response through analyses of circulating cell-free tumour DNA (ctDNA) and extracellular RNA (exRNA) in multiple myeloma (MM) patients were performed in a Phase Ib trial of 24 relapsed/refractory patients receiving oral azacitidine in combination with lenalidomide and dexamethasone. Mutational characterisation of paired BM and PL samples at study entry identified that patients with a higher number of mutations or a higher mutational fractional abundance in PL had significantly shorter overall survival (OS) (p = 0.005 and p = 0.018, respectively). A decrease in ctDNA levels at day 5 of cycle 1 of treatment (C1D5) correlated with superior progression-free survival (PFS) (p = 0.017). Evaluation of exRNA transcripts of candidate biomarkers indicated that high CRBN levels coupled with low levels of SPARC at baseline were associated with shorter OS (p = 0.000003). IKZF1 fold-change <0.05 at C1D5 was associated with shorter PFS (p = 0.0051) and OS (p = 0.0001). Furthermore, patients with high baseline CRBN coupled with low fold-change at C1D5 were at the highest risk of progression (p = 0.0001). In conclusion, this exploratory analysis has provided the first demonstration in MM of ctDNA for predicting disease outcome and of the utility of exRNA as a biomarker of therapeutic response.

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References

  1. 1.

    Rasche L, Chavan SS, Stephens OW, Patel PH, Tytarenko R, Ashby C, et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun. 2017;8:268.

    CAS  Article  Google Scholar 

  2. 2.

    Mithraprabhu S, Sirdesai S, Chen M, Khong T, Spencer A. Circulating tumour DNA analysis for tumour genome characterisation and monitoring disease burden in extramedullary multiple myeloma. Int J Mol Sci. 2018;19:1858. https://doi.org/10.3390/ijms19071858.

    Article  Google Scholar 

  3. 3.

    Mithraprabhu S, Khong T, Ramachandran M, Chow A, Klarica D, Mai L, et al. Circulating tumour DNA analysis demonstrates spatial mutational heterogeneity that coincides with disease relapse in myeloma. Leukemia. 2017;31:1695–705.

    CAS  Article  Google Scholar 

  4. 4.

    Oberle A, Brandt A, Voigtlaender M, Thiele B, Radloff J, Schulenkorf A, et al. Monitoring multiple myeloma by next-generation sequencing of V(D)J rearrangements from circulating myeloma cells and cell-free myeloma DNA. Haematologica. 2017;102:1105–11.

    CAS  Article  Google Scholar 

  5. 5.

    Rustad EH, Coward E, Skytoen ER, Misund K, Holien T, Standal T, et al. Monitoring multiple myeloma by quantification of recurrent mutations in serum. Haematologica. 2017;102:1266–72.

    CAS  Article  Google Scholar 

  6. 6.

    Kis O, Kaedbey R, Chow S, Danesh A, Dowar M, Li T, et al. Circulating tumour DNA sequence analysis as an alternative to multiple myeloma bone marrow aspirates. Nat Commun. 2017;8:15086.

    Article  Google Scholar 

  7. 7.

    Barzon L, Boscaro M, Pacenti M, Taccaliti A, Palu G. Evaluation of circulating thyroid-specific transcripts as markers of thyroid cancer relapse. Int J Cancer. 2004;110:914–20.

    CAS  Article  Google Scholar 

  8. 8.

    Chen XQ, Bonnefoi H, Pelte MF, Lyautey J, Lederrey C, Movarekhi S, et al. Telomerase RNA as a detection marker in the serum of breast cancer patients. Clin Cancer Res. 2000;6:3823–6.

    CAS  PubMed  Google Scholar 

  9. 9.

    Deligezer U, Yaman F, Darendeliler E, Dizdar Y, Holdenrieder S, Kovancilar M, et al. Post-treatment circulating plasma BMP6 mRNA and H3K27 methylation levels discriminate metastatic prostate cancer from localized disease. Clin Chim Acta. 2010;411:1452–6.

    CAS  Article  Google Scholar 

  10. 10.

    Garcia JM, Pena C, Garcia V, Dominguez G, Munoz C, Silva J, et al. Prognostic value of LISCH7 mRNA in plasma and tumor of colon cancer patients. Clin Cancer Res. 2007;13:6351–8.

    CAS  Article  Google Scholar 

  11. 11.

    Garcia V, Garcia JM, Pena C, Silva J, Dominguez G, Lorenzo Y, et al. Free circulating mRNA in plasma from breast cancer patients and clinical outcome. Cancer Lett. 2008;263:312–20.

    CAS  Article  Google Scholar 

  12. 12.

    Garcia V, Garcia JM, Silva J, Martin P, Pena C, Dominguez G, et al. Extracellular tumor-related mRNA in plasma of lymphoma patients and survival implications. PLoS ONE. 2009;4:e8173.

    Article  Google Scholar 

  13. 13.

    Joosse SA, Muller V, Steinbach B, Pantel K, Schwarzenbach H. Circulating cell-free cancer-testis MAGE-A RNA, BORIS RNA, let-7b and miR-202 in the blood of patients with breast cancer and benign breast diseases. Br J Cancer. 2014;111:909–17.

    CAS  Article  Google Scholar 

  14. 14.

    Kang Y, Zhang J, Sun P, Shang J. Circulating cell-free human telomerase reverse transcriptase mRNA in plasma and its potential diagnostic and prognostic value for gastric cancer. Int J Clin Oncol. 2013;18:478–86.

    CAS  Article  Google Scholar 

  15. 15.

    Lo KW, Lo YM, Leung SF, Tsang YS, Chan LY, Johnson PJ, et al. Analysis of cell-free Epstein-Barr virus associated RNA in the plasma of patients with nasopharyngeal carcinoma. Clin Chem. 1999;45(8 Pt 1):1292–4.

    CAS  PubMed  Google Scholar 

  16. 16.

    March-Villalba JA, Martinez-Jabaloyas JM, Herrero MJ, Santamaria J, Alino SF, Dasi F. Cell-free circulating plasma hTERT mRNA is a useful marker for prostate cancer diagnosis and is associated with poor prognosis tumor characteristics. PLoS ONE. 2012;7:e43470.

    CAS  Article  Google Scholar 

  17. 17.

    Miura N, Maeda Y, Kanbe T, Yazama H, Takeda Y, Sato R, et al. Serum human telomerase reverse transcriptase messenger RNA as a novel tumor marker for hepatocellular carcinoma. Clin Cancer Res. 2005;11:3205–9.

    CAS  Article  Google Scholar 

  18. 18.

    Silva JM, Dominguez G, Silva J, Garcia JM, Sanchez A, Rodriguez O, et al. Detection of epithelial messenger RNA in the plasma of breast cancer patients is associated with poor prognosis tumor characteristics. Clin Cancer Res. 2001;7:2821–5.

    CAS  PubMed  Google Scholar 

  19. 19.

    Silva JM, Rodriguez R, Garcia JM, Munoz C, Silva J, Dominguez G, et al. Detection of epithelial tumour RNA in the plasma of colon cancer patients is associated with advanced stages and circulating tumour cells. Gut. 2002;50:530–4.

    CAS  Article  Google Scholar 

  20. 20.

    Sueoka E, Sueoka N, Iwanaga K, Sato A, Suga K, Hayashi S, et al. Detection of plasma hnRNP B1 mRNA, a new cancer biomarker, in lung cancer patients by quantitative real-time polymerase chain reaction. Lung Cancer. 2005;48:77–83.

    Article  Google Scholar 

  21. 21.

    Wong SC, Lo SF, Cheung MT, Ng KO, Tse CW, Lai BS, et al. Quantification of plasma beta-catenin mRNA in colorectal cancer and adenoma patients. Clin Cancer Res. 2004;10:1613–7.

    CAS  Article  Google Scholar 

  22. 22.

    Xu W, Zhou H, Qian H, Bu X, Chen D, Gu H, et al. Combination of circulating CXCR4 and Bmi-1 mRNA in plasma: A potential novel tumor marker for gastric cancer. Mol Med Rep. 2009;2:765–71.

    CAS  Article  Google Scholar 

  23. 23.

    Zhou D, Tang W, Liu X, An HX, Zhang Y. Clinical verification of plasma messenger RNA as novel noninvasive biomarker identified through bioinformatics analysis for lung cancer. Oncotarget. 2017;8:43978–89.

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Kalff A, Khong T, Mithraprabhu S, Bergin K, Reynolds J, Bowen KM, et al. Oral azacitidine (CC-486) in combination with lenalidomide and dexamethasone in advanced, lenalidomide-refractory multiple myeloma (ROAR study). Leuk Lymphoma. 2019. (in press).

  25. 25.

    Cluzeau T, Robert G, Mounier N, Karsenti JM, Dufies M, Puissant A, et al. BCL2L10 is a predictive factor for resistance to azacitidine in MDS and AML patients. Oncotarget. 2012;3:490–501.

    Article  Google Scholar 

  26. 26.

    Kaiser MF, Johnson DC, Wu P, Walker BA, Brioli A, Mirabella F, et al. Global methylation analysis identifies prognostically important epigenetically inactivated tumor suppressor genes in multiple myeloma. Blood. 2013;122:219–26.

    CAS  Article  Google Scholar 

  27. 27.

    Kronke J, Udeshi ND, Narla A, Grauman P, Hurst SN, McConkey M, et al. Lenalidomide causes selective degradation of IKZF1 and IKZF3 in multiple myeloma cells. Science. 2014;343:301–5.

    Article  Google Scholar 

  28. 28.

    Locatelli SL, Papait R, Careddu G, Koschorke A, Stirparo GG, Balzarotti M, et al. Upregulation of cereblon expression by the DNA methyltransferase inhibitor azacytidine strongly enhances lenalidomide cytotoxicity in germinal center B-cell-like (GCB) and activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL). Blood. 2014;124:2253.

    Google Scholar 

  29. 29.

    Lopez-Girona A, Mendy D, Ito T, Miller K, Gandhi AK, Kang J, et al. Cereblon is a direct protein target for immunomodulatory and antiproliferative activities of lenalidomide and pomalidomide. Leukemia. 2012;26:2326–35.

    CAS  Article  Google Scholar 

  30. 30.

    Eichner R, Heider M, Fernandez-Saiz V, van Bebber F, Garz AK, Lemeer S, et al. Immunomodulatory drugs disrupt the cereblon-CD147-MCT1 axis to exert antitumor activity and teratogenicity. Nat Med. 2016;22:735–43.

    CAS  Article  Google Scholar 

  31. 31.

    Kronke J, Kuchenbauer F, Kull M, Teleanu V, Bullinger L, Bunjes D, et al. IKZF1 expression is a prognostic marker in newly diagnosed standard-risk multiple myeloma treated with lenalidomide and intensive chemotherapy: a study of the German Myeloma Study Group (DSMM). Leukemia. 2017;31:1363–7.

    CAS  Article  Google Scholar 

  32. 32.

    An J, Ponthier CM, Sack R, Seebacher J, Stadler MB, Donovan KA, et al. pSILAC mass spectrometry reveals ZFP91 as IMiD-dependent substrate of the CRL4(CRBN) ubiquitin ligase. Nat Commun. 2017;8:15398.

    CAS  Article  Google Scholar 

  33. 33.

    Ishwaran H, Kogalur UB, Gorodeski EZ, Minn AJ, Lauer MS. High-dimensional variable selection for survival data. J Am Stat Assoc. 2010;105:205–17.

    CAS  Article  Google Scholar 

  34. 34.

    Walker BA, Boyle EM, Wardell CP, Murison A, Begum DB, Dahir NM, et al. Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma. J Clin Oncol. 2015;33:3911.

    CAS  Article  Google Scholar 

  35. 35.

    Broyl A, Kuiper R, van Duin M, van der Holt B, el Jarari L, Bertsch U, et al. High cereblon expression is associated with better survival in patients with newly diagnosed multiple myeloma treated with thalidomide maintenance. Blood. 2013;121:624–7.

    CAS  Article  Google Scholar 

  36. 36.

    Heintel D, Rocci A, Ludwig H, Bolomsky A, Caltagirone S, Schreder M, et al. High expression of cereblon (CRBN) is associated with improved clinical response in patients with multiple myeloma treated with lenalidomide and dexamethasone. Br J Haematol. 2013;161:695–700.

    CAS  Article  Google Scholar 

  37. 37.

    Schuster SR, Kortuem KM, Zhu YX, Braggio E, Shi CX, Bruins LA, et al. The clinical significance of cereblon expression in multiple myeloma. Leuk Res. 2014;38:23–8.

    CAS  Article  Google Scholar 

  38. 38.

    Kronke J, Knop S, Langer C. Prognostic impact of Ikaros expression in lenalidomide-treated multiple myeloma. Oncotarget. 2017;8:106163–4.

    Article  Google Scholar 

  39. 39.

    Sehgal K, Das R, Zhang L, Verma R, Deng Y, Kocoglu M, et al. Clinical and pharmacodynamic analysis of pomalidomide dosing strategies in myeloma: impact of immune activation and cereblon targets. Blood. 2015;125:4042–51.

    CAS  Article  Google Scholar 

  40. 40.

    Zhu YX, Braggio E, Shi CX, Kortuem KM, Bruins LA, Schmidt JE, et al. Identification of cereblon-binding proteins and relationship with response and survival after IMiDs in multiple myeloma. Blood. 2014;124:536–45.

    CAS  Article  Google Scholar 

  41. 41.

    Alcazar O, Achberger S, Aldrich W, Hu Z, Negrotto S, Saunthararajah Y, et al. Epigenetic regulation by decitabine of melanoma differentiation in vitro and in vivo. Int J Cancer. 2012;131:18–29.

    CAS  Article  Google Scholar 

  42. 42.

    Lopez-Girona A, Heintel D, Zhang LH, Mendy D, Gaidarova S, Brady H, et al. Lenalidomide downregulates the cell survival factor, interferon regulatory factor-4, providing a potential mechanistic link for predicting response. Br J Haematol. 2011;154:325–36.

    CAS  Article  Google Scholar 

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Acknowledgements

We thank the staff and patients of Malignant Haematology & Stem Cell Transplantation, Alfred Hospital for the invaluable contribution towards sample collection.

Funding

Dr. Mithraprabhu was supported by a fellowship from the James and Elsie Borrowman Estate.

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SM and AS had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. SM and AS were involved in the study concept and design. SM, RM, TK, AK, KB, JH, IS, KB, MR, KW, BKLW, JR and AS contributed to acquisition, analysis and interpretation of data. SM, RM and AS drafted the manuscript. Critical revision of the manuscript was performed by all authors. Statistical analyses were performed by SM, RM and JR. Administrative, technical and/or material support were provided by TK, AK, KB, JH, IS, KB, MR, BKLW, KC and AS. The study was supervised by SM, TK, AK and AS.

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Correspondence to Andrew Spencer.

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Mithraprabhu, S., Morley, R., Khong, T. et al. Monitoring tumour burden and therapeutic response through analysis of circulating tumour DNA and extracellular RNA in multiple myeloma patients. Leukemia 33, 2022–2033 (2019). https://doi.org/10.1038/s41375-019-0469-x

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