Annals of Laboratory Medicine

Korean Society for Laboratory Medicine (대한진단검사의학회)
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Clinical Implications of Circulating Tumor DNA in Multiple Myeloma and Its Precursor Diseases

  • Sung-Soo Park (Department of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea) ;
  • Na Yung Kim (Department of Medical Sciences, Graduate School of The Catholic University of Korea) ;
  • Ji-Young Lim (Department of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea) ;
  • Jung Yeon Lee (Department of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea) ;
  • Sujin Yun (Department of Medical Sciences, Graduate School of The Catholic University of Korea) ;
  • Yeun-Jun Chung (Department of Medical Sciences, Graduate School of The Catholic University of Korea) ;
  • Seung-Hyun Jung (Department of Medical Sciences, Graduate School of The Catholic University of Korea) ;
  • Chang-Ki Min (Department of Hematology, Seoul St. Mary's Hematology Hospital, College of Medicine, The Catholic University of Korea)
  • Received : 2024.08.11
  • Accepted : 2025.01.15
  • Published : 2025.05.01
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Abstract

Background: Genetic alterations play a pivotal role in multiple myeloma (MM) development and therapeutic resistance. Traditionally, the genetic profiling of MM requires invasive bone marrow (BM) procedures; however, these procedures are associated with patient discomfort and cannot fully capture the spatial and temporal heterogeneity of the disease. Therefore, we investigated the clinical implications of liquid biopsy using targeted deep sequencing. Methods: We analyzed the genetic profiles of circulating tumor DNA (ctDNA) by targeted deep sequencing from 102 patients, including those with monoclonal gammopathy of undetermined significance (MGUS, N=7), smoldering MM (N=6), and symptomatic MM (N=89). Results: The number of ctDNA mutations increased with disease progression from MGUS to MM, with averages of 1.0 mutations in MGUS, 1.8 mutations in smoldering MM, and 1.9 mutations in MM, respectively. Shared mutations between BM and ctDNA were more prevalent in MM (68.9%) than in MGUS (25.0%). RAS/RAF and TP53 mutations were significantly enriched in MM ctDNA. Specific mutations were associated with clinical features in patients with MM: hypercalcemia and TET2 (P=0.006), renal insufficiency and NRAS (P=0.012), paramedullary myeloma and TP53 (P=0.02), and extramedullary myeloma and NRAS (P=0.007). TET2 mutations significantly affected 2-yr progression-free survival (hazard ratio=7.11, P=0.003). Serial ctDNA profiling accurately predicted treatment response in patients with MM. Conclusions: Our findings highlight the potential of liquid biopsy for understanding MM progression and prognosis utilizing a minimally invasive approach, paving the way for its integration into personalized treatment strategies and real-time disease monitoring.

Keywords

Acknowledgement

We appreciate the support from the Basic Medical Science Facilitation Program through the Catholic Medical Center of the Catholic University of Korea funded by the Catholic Education Foundation. The authors wish to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2024.

References

  1. Lohr JG, Stojanov P, Carter SL, Cruz-Gordillo P, Lawrence MS, Auclair D, et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell 2014;25:91–101. https://doi.org/10.1016/j.ccr.2013.12.015
  2. Manier S, Salem KZ, Park J, Landau DA, Getz G, Ghobrial IM. Genomic complexity of multiple myeloma and its clinical implications. Nat Rev Clin Oncol 2017;14:100–13. https://doi.org/10.1038/nrclinonc.2016.122
  3. Landgren O, Kyle RA, Pfeiffer RM, Katzmann JA, Caporaso NE, Hayes RB, et al. Monoclonal gammopathy of undetermined significance (MGUS) consistently precedes multiple myeloma: a prospective study. Blood 2009;113:5412–7. https://doi.org/10.1182/blood-2008-12-194241
  4. Rajkumar SV, Kumar S, Lonial S, Mateos MV. Smoldering multiple myeloma current treatment algorithms. Blood Cancer J 2022;12:129. https://doi.org/10.1038/s41408-022-00719-0
  5. 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. https://doi.org/10.1038/nature09837
  6. Egan JB, Shi CX, Tembe W, Christoforides A, Kurdoglu A, Sinari S, et al. Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood 2012;120:1060–6. https://doi.org/10.1182/blood-2012-01-405977
  7. Boyle EM, Deshpande S, Tytarenko R, Ashby C, Wang Y, Bauer MA, et al. The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma. Nat Commun 2021;12:293. https://doi.org/10.1038/s41467-020-20524-2
  8. 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. https://doi.org/10.1038/s41467-017-00296-y
  9. Heitzer E, Ulz P, Geigl JB. Circulating tumor DNA as a liquid biopsy for cancer. Clin Chem 2015;61:112–23. https://doi.org/10.1373/clinchem.2014.222679
  10. Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, et al. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer 2017;17:223–38. https://doi.org/10.1038/nrc.2017.7
  11. Gerber B, Manzoni M, Spina V, Bruscaggin A, Lionetti M, Fabris S, et al. Circulating tumor DNA as a liquid biopsy in plasma cell dyscrasias. Haematologica 2018;103:e245–8. https://doi.org/10.3324/haematol.2017.184358
  12. 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. https://doi.org/10.1038/ncomms15086
  13. Guo G, Raje NS, Seifer C, Kloeber J, Isenhart R, Ha G, et al. Genomic discovery and clonal tracking in multiple myeloma by cell-free DNA sequencing. Leukemia 2018;32:1838–41. https://doi.org/10.1038/s41375-018-0115-z
  14. Waldschmidt JM, Yee AJ, Vijaykumar T, Pinto RA, Frede J, Anand P, et al. Cell-free DNA for the detection of emerging treatment failure in relapsed/refractory multiple myeloma. Leukemia 2022;36:1078–87. https://doi.org/10.1038/s41375-021-01492-y
  15. Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos MV, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol 2014;15:e538–48. https://doi.org/10.1016/S1470-2045(14)70442-5
  16. Fernández de Larrea C, Kyle R, Rosiñol L, Paiva B, Engelhardt M, Usmani S, et al. Primary plasma cell leukemia: consensus definition by the International Myeloma Working Group according to peripheral blood plasma cell percentage. Blood Cancer J 2021;11:192. https://doi.org/10.1038/s41408-021-00587-0
  17. Weinstock M and Ghobrial IM. Extramedullary multiple myeloma. Leuk Lymphoma 2013;54:1135–41. https://doi.org/10.3109/10428194.2012.740562
  18. Touzeau C and Moreau P. How I treat extramedullary myeloma. Blood 2016;127:971–6. https://doi.org/10.1182/blood-2015-07-635383
  19. Greipp PR, San Miguel J, Durie BG, Crowley JJ, Barlogie B, Bladé J, et al. International staging system for multiple myeloma. J Clin Oncol 2005; 23:3412–20. https://doi.org/10.1200/JCO.2005.04.242
  20. Palumbo A, Avet-Loiseau H, Oliva S, Lokhorst HM, Goldschmidt H, Rosinol L, et al. Revised international staging system for multiple myeloma: A report from International Myeloma Working Group. J Clin Oncol 2015; 33:2863–9. https://doi.org/10.1200/JCO.2015.61.2267
  21. D'Agostino M, Cairns DA, Lahuerta JJ, Wester R, Bertsch U, Waage A, et al. Second revision of the International Staging System (R2-ISS) for Overall Survival in Multiple Myeloma: A European Myeloma Network (EMN) report within the HARMONY project. J Clin Oncol 2022;40:3406–18. https://doi.org/10.1200/JCO.21.02614
  22. Kim Y, Park SS, Min CK, Lee GD, Son J, Jo SJ, et al. KRAS, NRAS, and BRAF mutations in plasma cell myeloma at a single Korean institute. Blood Res 2020;55:159–68. https://doi.org/10.5045/br.2020.2020137
  23. Walker BA, Mavrommatis K, Wardell CP, Ashby TC, Bauer M, Davies FE, et al. Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood 2018;132:587–97. https://doi.org/10.1182/blood-2018-03-840132
  24. Manzoni M, Pompa A, Fabris S, Pelizzoni F, Ciceri G, Seia M, et al. Limits and applications of genomic analysis of circulating tumor DNA as a liquid biopsy in asymptomatic forms of multiple myeloma. Hemasphere 2020;4:e402. https://doi.org/10.1097/HS9.0000000000000402
  25. Mithraprabhu S, Reynolds J, Turner R, Quach H, Horvath N, Kerridge I, et al. Circulating tumour DNA analysis predicts relapse and improves risk stratification in primary refractory multiple myeloma. Blood Cancer J 2023;13:25. https://doi.org/10.1038/s41408-023-00796-9
  26. 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;33:3911–20. https://doi.org/10.1200/JCO.2014.59.1503
  27. Barbieri CE, Baca SC, Lawrence MS, Demichelis F, Blattner M, Theurillat JP, et al. Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat Genet 2012;44:685–9. https://doi.org/10.1038/ng.2279
  28. Zhao W, Zhang W, Ma H, Yang M. NIPA2 regulates osteoblast function by modulating mitophagy in type 2 diabetes osteoporosis. Sci Rep 2020;10:3078. https://doi.org/10.1038/s41598-020-59743-4
  29. Beider K, Rosenberg E, Dimenshtein-Voevoda V, Sirovsky Y, Vladimirsky J, Magen H, et al. Blocking of Transient Receptor Potential vanilloid 1 (TRPV1) promotes terminal mitophagy in multiple myeloma, disturbing calcium homeostasis and targeting ubiquitin pathway and bortezomibinduced unfolded protein response. J Hematol Oncol 2020;13:158. https://doi.org/10.1186/s13045-020-00993-0
  30. Lv T and Zhang H. Mitophagy-related gene signature for predicting the prognosis of multiple myeloma. Heliyon 2024;10:e24520. https://doi.org/10.1016/j.heliyon.2024.e24520
  31. de Haart SJ, Willems SM, Mutis T, Koudijs MJ, van Blokland MT, Lokhorst HM, et al. Comparison of intramedullary myeloma and corresponding extramedullary soft tissue plasmacytomas using genetic mutational panel analyses. Blood Cancer J 2016;6:e426. https://doi.org/10.1038/bcj.2016.35
  32. Merz M, Merz AMA, Wang J, Wei L, Hu Q, Hutson N, et al. Deciphering spatial genomic heterogeneity at a single cell resolution in multiple myeloma. Nat Commun 2022;13:807. https://doi.org/10.1038/s41467-022-28266-z
  33. Xiong W, Wu X, Starnes S, Johnson SK, Haessler J, Wang S, et al. An analysis of the clinical and biologic significance of TP53 loss and the identification of potential novel transcriptional targets of TP53 in multiple myeloma. Blood 2008;112:4235–46. https://doi.org/10.1182/blood-2007-10-119123
  34. 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. https://doi.org/10.1038/leu.2016.366
  35. Deshpande S, Tytarenko RG, Wang Y, Boyle EM, Ashby C, Schinke CD, et al. Monitoring treatment response and disease progression in myeloma with circulating cell-free DNA. Eur J Haematol 2021;106:230–40. https://doi.org/10.1111/ejh.13541
  36. Mithraprabhu S, Hocking J, Ramachandran M, Choi K, Klarica D, Khong T, et al. DNA-repair gene mutations are highly prevalent in circulating tumour DNA from multiple myeloma patients. Cancers (Basel) 2019;11. https://doi.org/10.3390/cancers11070917
  37. 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. https://doi.org/10.1038/s41375-018-0196-8
  38. Li S, Zhang E, Cai Z. Liquid biopsy by analysis of circulating myeloma cells and cell-free nucleic acids: a novel noninvasive approach of disease evaluation in multiple myeloma. Biomark Res 2023;11:27. https://doi.org/10.1186/s40364-023-00469-6