Measurable Residual Disease Assessment in Multiple Myeloma: How Deep Is Enough?
Abstract
:1. Introduction
2. Methods for BM MRD Detection
2.1. Flow Cytometry-Based MRD
2.2. Molecular-Based MRD
2.3. Imaging Techniques-Based MRD
3. Future of MRD Testing: Beyond BM Assessment
4. Clinical Relevance of MRD Evaluation in MM
4.1. MRD Improve Definition of Response
4.2. MRD Is a Relevant Prognostic Factor
5. MRD as a Surrogate Endpoint in Clinical Trials
6. Open Questions That MRD Can Help Answer in the Clinical Setting
6.1. Can MRD Redefine the Use of ASCT?
6.2. Can MRD Guide Maintenance Therapy?
6.3. Can MRD Be Used to Decide Treatment Discontinuation?
6.4. Can MRD Be Used to Intensify Treatment?
7. MRD in the Context of New Therapies
8. Sustained MRD Negative Response: Role of the Immune System
9. Ideal Threshold for MRD: How Deep Should We Go?
10. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Facon, T.; Kumar, S.; Plesner, T.; Orlowski, R.Z.; Moreau, P.; Bahlis, N.; Basu, S.; Nahi, H.; Hulin, C.; Quach, H.; et al. Daratumumab plus Lenalidomide and Dexamethasone for Untreated Myeloma. N. Engl. J. Med. 2019, 380, 2104–2115. [Google Scholar] [CrossRef] [PubMed]
- Spencer, A.; Lentzsch, S.; Weisel, K.; Avet-Loiseau, H.; Mark, T.M.; Spicka, I.; Masszi, T.; Lauri, B.; Levin, M.-D.; Bosi, A.; et al. Daratumumab plus bortezomib and dexamethasone versus bortezomib and dexamethasone in relapsed or refractory multiple myeloma: Updated analysis of CASTOR. Haematologica 2018, 103, 2079–2087. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mateos, M.-V.; Cavo, M.; Blade, J.; Dimopoulos, M.A.; Suzuki, K.; Jakubowiak, A.; Knop, S.; Doyen, C.; Lucio, P.; Nagy, Z.; et al. Overall survival with daratumumab, bortezomib, melphalan, and prednisone in newly diagnosed multiple myeloma (ALCYONE): A randomised, open-label, phase 3 trial. Lancet 2020, 395, 132–141. [Google Scholar] [CrossRef]
- Voorhees, P.M.; Kaufman, J.L.; Laubach, J.; Sborov, D.W.; Reeves, B.; Rodriguez, C.; Chari, A.; Silbermann, R.; Costa, L.J.; Anderson, L.D.; et al. Daratumumab, lenalidomide, bortezomib, and dexamethasone for transplant-eligible newly diagnosed multiple myeloma: The GRIFFIN trial. Blood 2020, 136, 936–945. [Google Scholar] [CrossRef]
- Moreau, P.; Attal, M.; Hulin, C.; Arnulf, B.; Belhadj, K.; Benboubker, L.; Béné, M.C.; Broijl, A.; Caillon, H.; Caillot, D.; et al. Bortezomib, thalidomide, and dexamethasone with or without daratumumab before and after autologous stem-cell transplantation for newly diagnosed multiple myeloma (CASSIOPEIA): A randomised, open-label, phase 3 study. Lancet 2019, 394, 29–38. [Google Scholar] [CrossRef]
- Gay, F.; Larocca, A.; Wijermans, P.; Cavallo, F.; Rossi, D.; Schaafsma, R.; Genuardi, M.; Romano, A.; Liberati, A.M.; Siniscalchi, A.; et al. Complete response correlates with long-term progression-free and overall survival in elderly myeloma treated with novel agents: Analysis of 1175 patients. Blood 2011, 117, 3025–3031. [Google Scholar] [CrossRef]
- Lahuerta, J.J.; Mateos, M.V.; Martínez-López, J.; Rosiñol, L.; Sureda, A.; de la Rubia, J.; García-Laraña, J.; Martínez-Martínez, R.; Hernández-García, M.T.; Carrera, D.; et al. Influence of pre- and post-transplantation responses on outcome of patients with multiple myeloma: Sequential improvement of response and achievement of complete response are associated with longer survival. J. Clin. Oncol. 2008, 26, 5775–5782. [Google Scholar] [CrossRef]
- García-Ortiz, A.; Rodríguez-García, Y.; Encinas, J.; Maroto-Martín, E.; Castellano, E.; Teixidó, J.; Martínez-López, J. The Role of Tumor Microenvironment in Multiple Myeloma Development and Progression. Cancers 2021, 13, 217. [Google Scholar] [CrossRef]
- Lopes, R.; Caetano, J.; Ferreira, B.; Barahona, F.; Carneiro, E.A.; João, C. The Immune Microenvironment in Multiple Myeloma: Friend or Foe? Cancers 2021, 13, 625. [Google Scholar] [CrossRef]
- Ho, M.; Goh, C.Y.; Patel, A.; Staunton, S.; O’Connor, R.; Godeau, M.; Bianchi, G. Role of the Bone Marrow Milieu in Multiple Myeloma Progression and Therapeutic Resistance. Clin. Lymphoma. Myeloma Leuk. 2020, 20, e752–e768. [Google Scholar] [CrossRef]
- Kumar, S.; Paiva, B.; Anderson, K.C.; Durie, B.; Landgren, O.; Moreau, P.; Munshi, N.; Lonial, S.; Bladé, J.; Mateos, M.-V.V.; et al. International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. Lancet Oncol. 2016, 17, e328–e346. [Google Scholar] [CrossRef]
- San Miguel, J.F.; Almeida, J.; Mateo, G.; Bladé, J.; López-Berges, C.; Caballero, D.; Hernández, J.; Moro, M.J.; Fernández-Calvo, J.; Díaz-Mediavilla, J.; et al. Immunophenotypic evaluation of the plasma cell compartment in multiple myeloma: A tool for comparing the efficacy of different treatment strategies and predicting outcome. Blood 2002, 99, 1853–1856. [Google Scholar] [CrossRef]
- Paiva, B.; Vidriales, M.B.; Cerveró, J.; Mateo, G.; Pérez, J.J.; Montalbán, M.A.; Sureda, A.; Montejano, L.; Gutiérrez, N.C.; De Coca, A.G.; et al. Multiparameter flow cytometric remission is the most relevant prognostic factor for multiple myeloma patients who undergo autologous stem cell transplantation. Blood 2008, 112, 4017–4023. [Google Scholar] [CrossRef] [Green Version]
- Rawstron, A.C.; Davies, F.E.; DasGupta, R.; Ashcroft, A.J.; Patmore, R.; Drayson, M.T.; Owen, R.G.; Jack, A.S.; Child, J.A.; Morgan, G.J. Flow cytometric disease monitoring in multiple myeloma: The relationship between normal and neoplastic plasma cells predicts outcome after transplantation. Blood 2002, 100, 3095–3100. [Google Scholar] [CrossRef] [Green Version]
- Avet-Loiseau, H.; Corre, J.; Lauwers-Cances, V.; Chretien, M.-L.; Robillard, N.; Leleu, X.; Hulin, C.; Gentil, C.; Arnulf, B.; Belhadj, K.; et al. Evaluation of Minimal Residual Disease (MRD) By Next Generation Sequencing (NGS) Is Highly Predictive of Progression Free Survival in the IFM/DFCI 2009 Trial. Blood 2015, 126, 191. [Google Scholar] [CrossRef]
- Flores-Montero, J.; Sanoja-Flores, L.; Paiva, B.; Puig, N.; García-Sánchez, O.; Böttcher, S.; van der Velden, V.H.J.; Pérez-Morán, J.-J.; Vidriales, M.-B.; García-Sanz, R.; et al. Next Generation Flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma. Leukemia 2017, 31, 2094–2103. [Google Scholar] [CrossRef] [Green Version]
- Stetler-Stevenson, M.; Paiva, B.; Stoolman, L.; Lin, P.; Jorgensen, J.L.; Orfao, A.; Van Dongen, J.; Rawstron, A.C. Consensus guidelines for myeloma minimal residual disease sample staining and data acquisition. Cytom. Part B-Clin. Cytom. 2016, 90, 26–30. [Google Scholar] [CrossRef]
- Costa, E.S.; Pedreira, C.E.; Barrena, S.; Lecrevisse, Q.; Flores, J.; Quijano, S.; Almeida, J.; del Carmen García-Macias, M.; Bottcher, S.; Van Dongen, J.J.M.M.; et al. Automated pattern-guided principal component analysis vs expert-based immunophenotypic classification of B-cell chronic lymphoproliferative disorders: A step forward in the standardization of clinical immunophenotyping. Leukemia 2010, 24, 1927–1933. [Google Scholar] [CrossRef] [Green Version]
- Roshal, M.; Flores-Montero, J.A.; Gao, Q.; Koeber, M.; Wardrope, J.; Durie, B.G.M.; Dogan, A.; Orfao, A.; Landgren, O. MRD detection in multiple myeloma: Comparison between MSKCC 10-color single-tube and EuroFlow 8-color 2-tube methods. Blood Adv. 2017, 1, 728–732. [Google Scholar] [CrossRef] [Green Version]
- Bene, M.C.; Robillard, N.; Moreau, P.; Wuilleme, S. Comparison of the Performance of Surface Alone or Surface Plus Cytoplasmic Approaches for the Assessment of Minimal Residual Disease in Multiparameter Flow Cytometry in Multiple Myeloma. Blood 2019, 134, 1799. [Google Scholar] [CrossRef]
- Dold, S.M.; Riebl, V.; Wider, D.; Follo, M.; Pantic, M.; Ihorst, G.; Duyster, J.; Zeiser, R.; Wäsch, R.; Engelhardt, M. Validated single-tube multiparameter flow cytometry approach for the assessment of minimal residual disease in multiple myeloma. Haematologica 2020, 105, e523. [Google Scholar] [CrossRef] [Green Version]
- Van Dongen, J.J.M.; Lhermitte, L.; Böttcher, S.; Almeida, J.; van der Velden, V.H.J.; Flores-Montero, J.; Rawstron, A.; Asnafi, V.; Lécrevisse, Q.; Lucio, P.; et al. EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia 2012, 26, 1908–1975. [Google Scholar] [CrossRef] [Green Version]
- Paíno, T.; Paiva, B.; Sayagués, J.M.; Mota, I.; Carvalheiro, T.; Corchete, L.A.; Aires-Mejía, I.; Pérez, J.J.; Sanchez, M.L.; Barcena, P.; et al. Phenotypic identification of subclones in multiple myeloma with different chemoresistant, cytogenetic and clonogenic potential. Leukemia 2015, 29, 1186–1194. [Google Scholar] [CrossRef] [Green Version]
- Zannetti, B.A.; Faini, A.C.; Massari, E.; Geuna, M.; Maffini, E.; Poletti, G.; Cerchione, C.; Martinelli, G.; Malavasi, F.; Lanza, F. Novel Insights in Anti-CD38 Therapy Based on CD38-Receptor Expression and Function: The Multiple Myeloma Model. Cells 2020, 9, 2666. [Google Scholar] [CrossRef]
- Costa, L.J.; Derman, B.A.; Bal, S.; Sidana, S.; Chhabra, S.; Silbermann, R.; Ye, J.C.; Cook, G.; Cornell, R.F.; Holstein, S.A.; et al. International harmonization in performing and reporting minimal residual disease assessment in multiple myeloma trials. Leukemia 2021, 35, 18–30. [Google Scholar] [CrossRef]
- Paiva, B.; Puig, N.; Cedena, M.T.; Rosiñol, L.; Cordón, L.; Vidriales, M.B.; Burgos, L.; Flores-Montero, J.; Sanoja-Flores, L.; Lopez-Anglada, L.; et al. Measurable residual disease by next-generation flow cytometry in multiple myeloma. J. Clin. Oncol. 2020, 38, 784–792. [Google Scholar] [CrossRef]
- Oliva, S.; Hofste Op Bruinink, D.; Rihova, L.; D’agostino, M.; Pantani, L.; Capra, A.; Van Der Holt, B.; Troia, R.; Petrucci, M.T.; Villanova, T.; et al. Minimal residual disease assessment by multiparameter flow cytometry in transplant-eligible myeloma in the EMN02/HOVON 95 MM trial. Blood Cancer J. 2021, 11, 106. [Google Scholar] [CrossRef]
- Rawstron, A.C.; Gregory, W.M.; De Tute, R.M.; Davies, F.E.; Bell, S.E.; Drayson, M.T.; Cook, G.; Jackson, G.H.; Morgan, G.J.; Child, J.A.; et al. Minimal residual disease in myeloma by flow cytometry: Independent prediction of survival benefit per log reduction. Blood 2015, 125, 1932–1935. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gay, F.; Musto, P.; Rota-Scalabrini, D.; Bertamini, L.; Belotti, A.; Galli, M.; Offidani, M.; Zamagni, E.; Ledda, A.; Grasso, M.; et al. Carfilzomib with cyclophosphamide and dexamethasone or lenalidomide and dexamethasone plus autologous transplantation or carfilzomib plus lenalidomide and dexamethasone, followed by maintenance with carfilzomib plus lenalidomide or lenalidomide alone for patients with newly diagnosed multiple myeloma (FORTE): A randomised, open-label, phase 2 trial. Lancet Oncol. 2021, 22, 1705–1720. [Google Scholar] [CrossRef]
- Jasielec, J.K.; Kubicki, T.; Raje, N.; Vij, R.; Reece, D.; Berdeja, J.; Derman, B.A.; Rosenbaum, C.A.; Richardson, P.; Gurbuxani, S.; et al. Carfilzomib, lenalidomide, and dexamethasone plus transplant in newly diagnosed multiple myeloma. Blood 2020, 136, 2513–2523. [Google Scholar] [CrossRef] [PubMed]
- Avet-Loiseau, H.A. Minimal Residual Disease by Next-Generation Sequencing: Pros and Cons. Am. Soc. Clin. Oncol. Educ. Book. 2016, 36, e425–e430. [Google Scholar] [CrossRef]
- Udd, K.A.; Spektor, T.M.; Berenson, J.R. Monitoring multiple myeloma. Clin. Adv. Hematol. Oncol. 2017, 15, 951–961. [Google Scholar]
- Gozzetti, A.; Nieto, Y.; Ramanathan, M.; Terragna, C.; Romano, A.; Palumbo, G.A.; Parrinello, N.L.; Conticello, C.; Martello, M.; Terragna, C. Minimal Residual Disease Assessment Within the Bone Marrow of Multiple Myeloma: A Review of Caveats, Clinical Significance and Future Perspectives. Front. Oncol. 2019, 9, 699. [Google Scholar] [CrossRef]
- Martinez-Lopez, J.; Blade, J.; Mateos, M.-V.; Grande, C.; Alegre, A.; García-Laraña, J.; Sureda, A.; de la Rubia, J.; Conde, E.; Martinez, R.; et al. Long-term prognostic significance of response in multiple myeloma after stem cell transplantation. Blood 2011, 118, 529–534. [Google Scholar] [CrossRef]
- Pulsipher, M.A.; Carlson, C.; Langholz, B.; Wall, D.A.; Schultz, K.R.; Bunin, N.; Kirsch, I.; Gastier-Foster, J.M.; Borowitz, M.; Desmarais, C.; et al. IgH-V(D)J NGS-MRD measurement pre- and early post-allotransplant defines very low- and very high-risk ALL patients. Blood 2015, 125, 3501–3508. [Google Scholar] [CrossRef] [Green Version]
- Pott, C.; Hoster, E.; Delfau-Larue, M.-H.; Beldjord, K.; Böttcher, S.; Asnafi, V.; Plonquet, A.; Siebert, R.; Callet-Bauchu, E.; Andersen, N.; et al. Molecular remission is an independent predictor of clinical outcome in patients with mantle cell lymphoma after combined immunochemotherapy: A European MCL intergroup study. Blood 2010, 115, 3215–3223. [Google Scholar] [CrossRef]
- Bai, Y.; Orfao, A.; Chim, C.S. Molecular detection of minimal residual disease in multiple myeloma. Br. J. Haematol. 2018, 181, 11–26. [Google Scholar] [CrossRef] [Green Version]
- Martinez-Lopez, J.; Lahuerta, J.J.; Pepin, F.; González, M.; Barrio, S.; Ayala, R.; Puig, N.; Montalban, M.A.; Paiva, B.; Weng, L.; et al. Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood 2014, 123, 3073–3079. [Google Scholar] [CrossRef]
- Perrot, A.; Lauwers-Cances, V.; Corre, J.; Robillard, N.; Hulin, C.; Chretien, M.L.; Dejoie, T.; Maheo, S.; Stoppa, A.M.; Pegourie, B.; et al. Minimal residual disease negativity using deep sequencing is a major prognostic factor in multiple myeloma. Blood 2018, 132, 2456–2464. [Google Scholar] [CrossRef] [Green Version]
- Takamatsu, H.; Takezako, N.; Zheng, J.; Moorhead, M.; Carlton, V.E.H.; Kong, K.A.; Murata, R.; Ito, S.; Miyamoto, T.; Yokoyama, K.; et al. Prognostic value of sequencing-based minimal residual disease detection in patients with multiple myeloma who underwent autologous stem-cell transplantation. Ann. Oncol. 2017, 28, 2503–2510. [Google Scholar] [CrossRef]
- Mateos, M.-V.; Dimopoulos, M.A.; Cavo, M.; Suzuki, K.; Jakubowiak, A.; Knop, S.; Doyen, C.; Lucio, P.; Nagy, Z.; Kaplan, P.; et al. Daratumumab plus Bortezomib, Melphalan, and Prednisone for Untreated Myeloma. N. Engl. J. Med. 2018, 378, 518–528. [Google Scholar] [CrossRef]
- Dimopoulos, M.A.; Oriol, A.; Nahi, H.; San-Miguel, J.; Bahlis, N.J.; Usmani, S.Z.; Rabin, N.; Orlowski, R.Z.; Komarnicki, M.; Suzuki, K.; et al. Daratumumab, Lenalidomide, and Dexamethasone for Multiple Myeloma. N. Engl. J. Med. 2016, 375, 1319–1331. [Google Scholar] [CrossRef] [Green Version]
- Landgren, O.; Rustad, E.H. Meeting report: Advances in minimal residual disease testing in multiple myeloma 2018. Adv. Cell Gene Ther. 2019, 2, e26. [Google Scholar] [CrossRef] [Green Version]
- Takamatsu, H. Comparison of minimal residual disease detection by multiparameter flow cytometry, ASO-qPCR, droplet digital PCR, and deep sequencing in patients with multiple myeloma who underwent autologous stem cell transplantation. J. Clin. Med. 2017, 6, 91. [Google Scholar] [CrossRef] [Green Version]
- Ladetto, M.; Brüggemann, M.; Monitillo, L.; Ferrero, S.; Pepin, F.; Drandi, D.; Barbero, D.; Palumbo, A.; Passera, R.; Boccadoro, M.; et al. Next-generation sequencing and real-time quantitative PCR for minimal residual disease detection in B-cell disorders. Leukemia 2014, 28, 1299–1307. [Google Scholar] [CrossRef]
- Paiva, B.; Puig, N.; García-Sanz, R.; San Miguel, J.F. Is this the time to introduce minimal residual disease in multiple myeloma clinical practice? Clin. Cancer Res. 2015, 21, 2001–2008. [Google Scholar] [CrossRef] [Green Version]
- Biran, N.; Ely, S.; Chari, A. Controversies in the Assessment of Minimal Residual Disease in Multiple Myeloma: Clinical Significance of Minimal Residual Disease Negativity Using Highly Sensitive Techniques. Curr. Hematol. Malig. Rep. 2014, 9, 368–378. [Google Scholar] [CrossRef]
- Gargis, A.S.; Kalman, L.; Berry, M.W.; Bick, D.P.; Dimmock, D.P.; Hambuch, T.; Lu, F.; Lyon, E.; Voelkerding, K.V.; Zehnbauer, B.A.; et al. Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat. Biotechnol. 2012, 30, 1033–1036. [Google Scholar] [CrossRef]
- Brüggemann, M.; Kotrová, M.; Knecht, H.; Bartram, J.; Boudjogrha, M.; Bystry, V.; Fazio, G.; Froňková, E.; Giraud, M.; Grioni, A.; et al. Standardized next-generation sequencing of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in acute lymphoblastic leukaemia; a EuroClonality-NGS validation study. Leukemia 2019, 33, 2241–2253. [Google Scholar] [CrossRef] [Green Version]
- Oliva, S.; Genuardi, E.; Belotti, A.; Frascione, P.M.M.; Galli, M.; Capra, A.; Offidani, M.; Vozella, F.; Zambello, R.; Auclair, D.; et al. Multiparameter flow cytometry (MFC) and next generation sequencing (NGS) for minimal residual disease (MRD) evaluation: Results of the FORTE trial in newly diagnosed multiple myeloma (MM). J. Clin. Oncol. 2020, 38, 8533. [Google Scholar] [CrossRef]
- Martinez-Lopez, J.; Sanchez-Vega, B.; Barrio, S.; Cuenca, I.; Ruiz-Heredia, Y.; Alonso, R.; Rapado, I.; Marin, C.; Cedena, M.-T.; Paiva, B.; et al. Analytical and clinical validation of a novel in-house deep-sequencing method for minimal residual disease monitoring in a phase II trial for multiple myeloma. Leukemia 2017, 31, 1446–1449. [Google Scholar] [CrossRef] [PubMed]
- Avet-Loiseau, H.; Bene, M.C.; Wuilleme, S.; Corre, J.; Attal, M.; Arnulf, B.; Garderet, L.; Macro, M.; Stoppa, A.-M.; Delforge, M.; et al. Concordance of Post-consolidation Minimal Residual Disease Rates by Multiparametric Flow Cytometry and Next-generation Sequencing in CASSIOPEIA. Clin. Lymphoma Myeloma Leuk. 2019, 19, e3–e4. [Google Scholar] [CrossRef]
- Lee, N.; Moon, S.Y.; Lee, J.-H.; Park, H.-K.; Kong, S.-Y.; Bang, S.-M.; Lee, J.H.; Yoon, S.-S.; Lee, D.S. Discrepancies between the percentage of plasma cells in bone marrow aspiration and BM biopsy: Impact on the revised IMWG diagnostic criteria of multiple myeloma. Blood Cancer J. 2017, 7, e530. [Google Scholar] [CrossRef] [PubMed]
- Rasche, L.; Chavan, S.S.; Stephens, O.W.; Patel, P.H.; Tytarenko, R.; Ashby, C.; Bauer, M.; Stein, C.; Deshpande, S.; Wardell, C.; et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat. Commun. 2017, 8, 268. [Google Scholar] [CrossRef]
- Hillengass, J.; Landgren, O. Challenges and opportunities of novel imaging techniques in monoclonal plasma cell disorders: Imaging “early myeloma”. Leuk. Lymphoma 2013, 54, 1355–1363. [Google Scholar] [CrossRef]
- Lu, Y.-Y.; Chen, J.-H.; Lin, W.-Y.; Liang, J.-A.; Wang, H.-Y.; Tsai, S.-C.; Kao, C.-H. FDG PET or PET/CT for detecting intramedullary and extramedullary lesions in multiple Myeloma: A systematic review and meta-analysis. Clin. Nucl. Med. 2012, 37, 833–837. [Google Scholar] [CrossRef]
- Hillengass, J.; Usmani, S.; Rajkumar, S.V.; Durie, B.G.M.; Mateos, M.-V.; Lonial, S.; Joao, C.; Anderson, K.C.; García-Sanz, R.; Riva, E.; et al. International myeloma working group consensus recommendations on imaging in monoclonal plasma cell disorders. Lancet Oncol. 2019, 20, e302–e312. [Google Scholar] [CrossRef]
- Cavo, M.; Terpos, E.; Nanni, C.; Moreau, P.; Lentzsch, S.; Zweegman, S.; Hillengass, J.; Engelhardt, M.; Usmani, S.Z.; Vesole, D.H.; et al. Role of 18F-FDG PET/CT in the diagnosis and management of multiple myeloma and other plasma cell disorders: A consensus statement by the International Myeloma Working Group. Lancet Oncol. 2017, 18, e206–e217. [Google Scholar] [CrossRef]
- Moreau, P. PET-CT in MM: A new definition of CR. Blood 2011, 118, 5984–5985. [Google Scholar] [CrossRef] [Green Version]
- Bladé, J.; Fernández de Larrea, C.; Rosiñol, L.; Cibeira, M.T.; Jiménez, R.; Powles, R. Soft-tissue plasmacytomas in multiple myeloma: Incidence, mechanisms of extramedullary spread, and treatment approach. J. Clin. Oncol. 2011, 29, 3805–3812. [Google Scholar] [CrossRef]
- Zamagni, E.; Nanni, C.; Patriarca, F.; Englaro, E.; Castellucci, P.; Geatti, O.; Tosi, P.; Tacchetti, P.; Cangini, D.; Perrone, G.; et al. A prospective comparison of 18F-fluorodeoxyglucose positron emission tomography-computed tomography, magnetic resonance imaging and whole-body planar radiographs in the assessment of bone disease in newly diagnosed multiple myeloma. Haematologica 2007, 92, 50–55. [Google Scholar] [CrossRef]
- Moreau, P.; Attal, M.; Caillot, D.; Macro, M.; Karlin, L.; Garderet, L.; Facon, T.; Benboubker, L.; Escoffre-Barbe, M.; Stoppa, A.-M.; et al. Prospective Evaluation of Magnetic Resonance Imaging and [(18)F]Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography at Diagnosis and Before Maintenance Therapy in Symptomatic Patients With Multiple Myeloma Included in the IFM/DFCI 2009 Trial: Results of the IMAJEM Study. J. Clin. Oncol. 2017, 35, 2911–2918. [Google Scholar] [CrossRef]
- Zamagni, E.; Nanni, C.; Mancuso, K.; Tacchetti, P.; Pezzi, A.; Pantani, L.; Zannetti, B.; Rambaldi, I.; Brioli, A.; Rocchi, S.; et al. PET/CT Improves the Definition of Complete Response and Allows to Detect Otherwise Unidentifiable Skeletal Progression in Multiple Myeloma. Clin. Cancer Res. 2015, 21, 4384–4390. [Google Scholar] [CrossRef] [Green Version]
- Zamagni, E.; Cavo, M. The role of imaging techniques in the management of multiple myeloma. Br. J. Haematol. 2012, 159, 499–513. [Google Scholar] [CrossRef]
- Sachpekidis, C.; Mosebach, J.; Freitag, M.T.; Wilhelm, T.; Mai, E.K.; Goldschmidt, H.; Haberkorn, U.; Schlemmer, H.-P.; Delorme, S.; Dimitrakopoulou-Strauss, A. Application of (18)F-FDG PET and diffusion weighted imaging (DWI) in multiple myeloma: Comparison of functional imaging modalities. Am. J. Nucl. Med. Mol. Imaging 2015, 5, 479–492. [Google Scholar]
- Pawlyn, C.; Fowkes, L.; Otero, S.; Jones, J.R.; Boyd, K.D.; Davies, F.E.; Morgan, G.J.; Collins, D.J.; Sharma, B.; Riddell, A.; et al. Whole-body diffusion-weighted MRI: A new gold standard for assessing disease burden in patients with multiple myeloma? Leukemia 2016, 30, 1446–1448. [Google Scholar] [CrossRef] [Green Version]
- Morales-Lozano, M.I.; Viering, O.; Samnick, S.; Rodriguez-Otero, P.; Buck, A.K.; Marcos-Jubilar, M.; Rasche, L.; Prieto, E.; Kortüm, K.M.; San-Miguel, J.; et al. 18F-FDG and 11C-Methionine PET/CT in Newly Diagnosed Multiple Myeloma Patients: Comparison of Volume-Based PET Biomarkers. Cancers 2020, 12, 1042. [Google Scholar] [CrossRef] [Green Version]
- Rasche, L.; Angtuaco, E.; McDonald, J.E.; Buros, A.; Stein, C.; Pawlyn, C.; Thanendrarajan, S.; Schinke, C.; Samant, R.; Yaccoby, S.; et al. Low expression of hexokinase-2 is associated with false-negative FDG-positron emission tomography in multiple myeloma. Blood 2017, 130, 30–34. [Google Scholar] [CrossRef] [Green Version]
- Pandit-Taskar, N. Functional Imaging Methods for Assessment of Minimal Residual Disease in Multiple Myeloma: Current Status and Novel ImmunoPET Based Methods. Semin. Hematol. 2018, 55, 22–32. [Google Scholar] [CrossRef]
- Ulaner, G.A.; Sobol, N.B.; O’Donoghue, J.A.; Kirov, A.S.; Riedl, C.C.; Min, R.; Smith, E.; Carter, L.M.; Lyashchenko, S.K.; Lewis, J.S.; et al. CD38-targeted Immuno-PET of Multiple Myeloma: From Xenograft Models to First-in-Human Imaging. Radiology 2020, 295, 606–615. [Google Scholar] [CrossRef]
- Moreau, P.; Zweegman, S.; Perrot, A.; Hulin, C.; Caillot, D.; Facon, T.; Leleu, X.; Belhadj, K.; Karlin, L.; Benboubker, L.; et al. Evaluation of the Prognostic Value of Positron Emission Tomography-Computed Tomography (PET-CT) at Diagnosis and Follow-up in Transplant-Eligible Newly Diagnosed Multiple Myeloma (TE NDMM) Patients Treated in the Phase 3 Cassiopeia Study: Results of the Cassiopet Companion Study. Blood 2019, 134, 692. [Google Scholar] [CrossRef]
- Rasche, L.; Alapat, D.; Kumar, M.; Gershner, G.; McDonald, J.; Wardell, C.P.; Samant, R.; Van Hemert, R.; Epstein, J.; Williams, A.F.; et al. Combination of flow cytometry and functional imaging for monitoring of residual disease in myeloma. Leukemia 2019, 33, 1713–1722. [Google Scholar] [CrossRef]
- Zamagni, E.; Patriarca, F.; Nanni, C.; Zannetti, B.; Englaro, E.; Pezzi, A.; Tacchetti, P.; Buttignol, S.; Perrone, G.; Brioli, A.; et al. Prognostic relevance of 18-F FDG PET/CT in newly diagnosed multiple myeloma patients treated with up-front autologous transplantation. Blood 2011, 118, 5989–5995. [Google Scholar] [CrossRef] [Green Version]
- John, L.; Poos, A.; Tirier, S.M.; Mallm, J.-P.; Prokoph, N.; Brobeil, A.; Lutz, R.; Schumacher, S.; Steiger, S.; Bauer, K.; et al. The Spatial Heterogeneity in Newly Diagnosed Multiple Myeloma Patients—From Sub-Clonal Architecture to the Immune Microenvironment. Blood 2021, 138, 729. [Google Scholar] [CrossRef]
- Thiele, J.-A.; Pitule, P.; Hicks, J.; Kuhn, P. Single-Cell Analysis of Circulating Tumor Cells. Methods Mol. Biol. 2019, 1908, 243–264. [Google Scholar] [CrossRef]
- Mishima, Y.; Paiva, B.; Shi, J.; Park, J.; Manier, S.; Takagi, S.; Massoud, M.; Perilla-Glen, A.; Aljawai, Y.; Huynh, D.; et al. The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma. Cell Rep. 2017, 19, 218–224. [Google Scholar] [CrossRef] [Green Version]
- Lohr, J.G.; Kim, S.; Gould, J.; Knoechel, B.; Drier, Y.; Cotton, M.J.; Gray, D.; Birrer, N.; Wong, B.; Ha, G.; et al. Genetic interrogation of circulating multiple myeloma cells at single-cell resolution. Sci. Transl. Med. 2016, 8, 363ra147. [Google Scholar] [CrossRef] [Green Version]
- Manier, S.; Park, J.; Capelletti, M.; Bustoros, M.; Freeman, S.S.; Ha, G.; Rhoades, J.; Liu, C.J.; Huynh, D.; Reed, S.C.; et al. Whole-exome sequencing of cell-free DNA and circulating tumor cells in multiple myeloma. Nat. Commun. 2018, 9, 1691. [Google Scholar] [CrossRef]
- Rawstron, A.C.; Owen, R.G.; Davies, F.E.; Johnson, R.J.; Jones, R.A.; Richards, S.J.; Evans, P.A.; Child, J.A.; Smith, G.M.; Jack, A.S.; et al. Circulating plasma cells in multiple myeloma: Characterization and correlation with disease stage. Br. J. Haematol. 1997, 97, 46–55. [Google Scholar] [CrossRef] [Green Version]
- Nowakowski, G.S.; Witzig, T.E.; Dingli, D.; Tracz, M.J.; Gertz, M.A.; Lacy, M.Q.; Lust, J.A.; Dispenzieri, A.; Greipp, P.R.; Kyle, R.A.; et al. Circulating plasma cells detected by flow cytometry as a predictor of survival in 302 patients with newly diagnosed multiple myeloma. Blood 2005, 106, 2276–2279. [Google Scholar] [CrossRef] [Green Version]
- Gonsalves, W.I.; Rajkumar, S.V.; Gupta, V.; Morice, W.G.; Timm, M.M.; Singh, P.P.; Dispenzieri, A.; Buadi, F.K.; Lacy, M.Q.; Kapoor, P.; et al. Quantification of clonal circulating plasma cells in newly diagnosed multiple myeloma: Implications for redefining high-risk myeloma. Leukemia 2014, 28, 2060–2065. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gonsalves, W.I.; Morice, W.G.; Rajkumar, V.; Gupta, V.; Timm, M.M.; Dispenzieri, A.; Buadi, F.K.; Lacy, M.Q.; Singh, P.P.; Kapoor, P.; et al. Quantification of clonal circulating plasma cells in relapsed multiple myeloma. Br. J. Haematol. 2014, 167, 500–505. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chakraborty, R.; Muchtar, E.; Kumar, S.K.; Jevremovic, D.; Buadi, F.K.; Dingli, D.; Dispenzieri, A.; Hayman, S.R.; Hogan, W.J.; Kapoor, P.; et al. Risk stratification in myeloma by detection of circulating plasma cells prior to autologous stem cell transplantation in the novel agent era. Blood Cancer J. 2016, 6, e512. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kumar, S.; Rajkumar, S.V.; Kyle, R.A.; Lacy, M.Q.; Dispenzieri, A.; Fonseca, R.; Lust, J.A.; Gertz, M.A.; Greipp, P.R.; Witzig, T.E. Prognostic value of circulating plasma cells in monoclonal gammopathy of undetermined significance. J. Clin. Oncol. 2005, 23, 5668–5674. [Google Scholar] [CrossRef] [PubMed]
- Gonsalves, W.I.; Rajkumar, S.V.; Dispenzieri, A.; Dingli, D.; Timm, M.M.; Morice, W.G.; Lacy, M.Q.; Buadi, F.K.; Go, R.S.; Leung, N.; et al. Quantification of circulating clonal plasma cells via multiparametric flow cytometry identifies patients with smoldering multiple myeloma at high risk of progression. Leukemia 2017, 31, 130–135. [Google Scholar] [CrossRef] [Green Version]
- Gonsalves, W.I.; Jevremovic, D.; Nandakumar, B.; Dispenzieri, A.; Buadi, F.K.; Dingli, D.; Lacy, M.Q.; Hayman, S.R.; Kapoor, P.; Leung, N.; et al. Enhancing the R-ISS classification of newly diagnosed multiple myeloma by quantifying circulating clonal plasma cells. Am. J. Hematol. 2020, 95, 310–315. [Google Scholar] [CrossRef]
- Han, W.; Jin, Y.; Xu, M.; Zhao, S.-S.; Shi, Q.; Qu, X.; Zhang, R.; Li, J.; Wu, Y.; Chen, L. Prognostic value of circulating clonal plasma cells in newly diagnosed multiple myeloma. Hematology 2021, 26, 510–517. [Google Scholar] [CrossRef]
- Sanoja-Flores, L.; Flores-Montero, J.; Garcés, J.J.; Paiva, B.; Puig, N.; García-Mateo, A.; García-Sánchez, O.; Corral-Mateos, A.; Burgos, L.; Blanco, E.; et al. Next generation flow for minimally-invasive blood characterization of MGUS and multiple myeloma at diagnosis based on circulating tumor plasma cells (CTPC). Blood Cancer J. 2018, 8, 117. [Google Scholar] [CrossRef] [Green Version]
- Terpos, E.; Kostopoulos, I.V.; Papanota, A.-M.; Papadimitriou, K.; Malandrakis, P.; Micheli, P.; Ntanasis-Stathopoulos, I.; Fotiou, D.; Metousis, A.; Kanellias, N.; et al. Next Generation Flow Cytometry Provides a Standardized, Highly Sensitive and Informative Method for the Analysis of Circulating Plasma Cells in Newly Diagnosed Multiple Myeloma: A Single Center Study in 182 Patients. Blood 2019, 134, 4338. [Google Scholar] [CrossRef]
- Sanoja-Flores, L.; Flores-Montero, J.; Puig, N.; Contreras-Sanfeliciano, T.; Pontes, R.; Corral-Mateos, A.; García-Sánchez, O.; Díez-Campelo, M.; Pessoa de Magalhães, R.J.; García-Martín, L.; et al. Blood monitoring of circulating tumor plasma cells by next generation flow in multiple myeloma after therapy. Blood 2019, 134, 2218–2222. [Google Scholar] [CrossRef] [Green Version]
- Paiva, B.; Paino, T.; Sayagues, J.-M.M.; Garayoa, M.; San-Segundo, L.; Martín, M.; Mota, I.; Sanchez, M.-L.L.; Bárcena, P.; Aires-Mejia, I.; et al. Detailed characterization of multiple myeloma circulating tumor cells shows unique phenotypic, cytogenetic, functional, and circadian distribution profile. Blood 2013, 122, 3591–3598. [Google Scholar] [CrossRef] [Green Version]
- Mazzotti, C.; Buisson, L.; Maheo, S.; Perrot, A.; Chretien, M.-L.; Leleu, X.; Hulin, C.; Manier, S.; Hébraud, B.; Roussel, M.; et al. Myeloma MRD by deep sequencing from circulating tumor DNA does not correlate with results obtained in the bone marrow. Blood Adv. 2018, 2, 2811–2813. [Google Scholar] [CrossRef] [Green Version]
- Huhn, S.; Weinhold, N.; Nickel, J.; Pritsch, M.; Hielscher, T.; Hummel, M.; Bertsch, U.; Huegle-Doerr, B.; Vogel, M.; Angermund, R.; et al. Circulating tumor cells as a biomarker for response to therapy in multiple myeloma patients treated within the GMMG-MM5 trial. Bone Marrow Transplant. 2017, 52, 1194–1198. [Google Scholar] [CrossRef]
- Garcés, J.-J.; Bretones, G.; Burgos, L.; Valdes-Mas, R.; Puig, N.; Cedena, M.-T.; Alignani, D.; Rodriguez, I.; Puente, D.Á.; Álvarez, M.-G.; et al. Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma. Leukemia 2020, 34, 3007–3018. [Google Scholar] [CrossRef]
- Mathai, R.A.; Vidya, R.V.S.; Reddy, B.S.; Thomas, L.; Udupa, K.; Kolesar, J.; Rao, M. Potential Utility of Liquid Biopsy as a Diagnostic and Prognostic Tool for the Assessment of Solid Tumors: Implications in the Precision Oncology. J. Clin. Med. 2019, 8, 373. [Google Scholar] [CrossRef] [Green Version]
- Biancon, G.; Gimondi, S.; Vendramin, A.; Carniti, C.; Corradini, P. Noninvasive Molecular Monitoring in Multiple Myeloma Patients Using Cell-Free Tumor DNA: A Pilot Study. J. Mol. Diagn. 2018, 20, 859–870. [Google Scholar] [CrossRef] [Green Version]
- Kis, O.; Kaedbey, R.; Chow, S.; Danesh, A.; Dowar, M.; Li, T.; Li, Z.; Liu, J.; Mansour, M.; Masih-Khan, E.; et al. Circulating tumour DNA sequence analysis as an alternative to multiple myeloma bone marrow aspirates. Nat. Commun. 2017, 8, 15086. [Google Scholar] [CrossRef]
- Oberle, A.; Brandt, A.; Voigtlaender, M.; Thiele, B.; Radloff, J.; Schulenkorf, A.; Alawi, M.; Akyüz, N.; März, M.; Ford, C.T.; 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, 1105–1111. [Google Scholar] [CrossRef]
- Vrabel, D.; Sedlarikova, L.; Besse, L.; Rihova, L.; Bezdekova, R.; Almasi, M.; Kubaczkova, V.; Brožová, L.; Jarkovsky, J.; Plonkova, H.; et al. Dynamics of tumor-specific cfDNA in response to therapy in multiple myeloma patients. Eur. J. Haematol. 2020, 104, 190–197. [Google Scholar] [CrossRef]
- Arnault Carneiro, E.; Barahona, F.; Pestana, C.; João, C. Is Circulating DNA and Tumor Cells in Myeloma the Way Forward? Hemato 2022, 3, 63–81. [Google Scholar] [CrossRef]
- Thoren, K.L. Mass spectrometry methods for detecting monoclonal immunoglobulins in multiple myeloma minimal residual disease. Semin. Hematol. 2018, 55, 41–43. [Google Scholar] [CrossRef]
- Mills, J.R.; Barnidge, D.R.; Dispenzieri, A.; Murray, D.L. High sensitivity blood-based M-protein detection in sCR patients with multiple myeloma. Blood Cancer J. 2017, 7, e590. [Google Scholar] [CrossRef]
- Bergen, H.R., 3rd; Dasari, S.; Dispenzieri, A.; Mills, J.R.; Ramirez-Alvarado, M.; Tschumper, R.C.; Jelinek, D.F.; Barnidge, D.R.; Murray, D.L. Clonotypic Light Chain Peptides Identified for Monitoring Minimal Residual Disease in Multiple Myeloma without Bone Marrow Aspiration. Clin. Chem. 2016, 62, 243–251. [Google Scholar] [CrossRef] [Green Version]
- Barnidge, D.R.; Tschumper, R.C.; Theis, J.D.; Snyder, M.R.; Jelinek, D.F.; Katzmann, J.A.; Dispenzieri, A.; Murray, D.L. Monitoring M-proteins in patients with multiple myeloma using heavy-chain variable region clonotypic peptides and LC-MS/MS. J. Proteome Res. 2014, 13, 1905–1910. [Google Scholar] [CrossRef]
- North, S.J.; Barnidge, D.R.; Brusseau, S.; Patel, R.I.; Haselton, M.; Du Chateau, B.K.; Wallis, G.L.F.; Harding, S.; Sakrikar, D.J.; Ashby, J.C. QIP-MS: A specific, sensitive, accurate, and quantitative alternative to electrophoresis that can identify endogenous m-proteins and distinguish them from therapeutic monoclonal antibodies in patients being treated for multiple myeloma. Clin. Chim. Acta 2019, 493, S433. [Google Scholar] [CrossRef]
- Dispenzieri, A.; Krishnan, A.Y.; Arendt, B.; Dasari, S.; Efebera, Y.A.; Geller, N.; Giralt, S.; Hahn, T.; Kohlhagen, M.C.; Landau, H.J.; et al. MASS-FIX versus standard methods to predict for PFS and OS among multiple myeloma patients participating on the STAMINA trial. J. Clin. Oncol. 2021, 39, 8009. [Google Scholar] [CrossRef]
- Puig, N.; Paiva, B.; Contreras, T.; Cedena, M.T.; Rosiñol, L.; Martínez, J.; Oriol, A.; Blanchard, M.J.; Rios, R.; Iñigo, M.B.; et al. Analysis of minimal residual disease in bone marrow by NGF and in peripheral blood by mass spectrometry in newly diagnosed multiple myeloma patients enrolled in the GEM2012MENOS65 clinical trial. J. Clin. Oncol. 2021, 39, 8010. [Google Scholar] [CrossRef]
- Jiménez Ubieto, A.; Martinez Lopez, J.; Rosinol, L.; Paiva, B.; Cedena, M.T.; Puig, N.; Calasanz, M.J.; Gonzalez Medina, J.; Martin-Ramos, M.L.; Fernandez, R.A.; et al. Absence of Contribution to a Differential Outcome of the Stringent Complete Response IMWG Category Respect to the Conventional CR in Multiple Myeloma. A Validation Analysis Based on the Pethema/GEM2012MENOS65 Phase III Clinical Trial. Blood 2018, 132, 1943. [Google Scholar] [CrossRef]
- Bal, S.; Weaver, A.; Cornell, R.F.; Costa, L.J. Challenges and opportunities in the assessment of measurable residual disease in multiple myeloma. Br. J. Haematol. 2019, 186, 807–819. [Google Scholar] [CrossRef] [PubMed]
- Kapoor, P.; Kumar, S.K.; Dispenzieri, A.; Lacy, M.Q.; Buadi, F.; Dingli, D.; Russell, S.J.; Hayman, S.R.; Witzig, T.E.; Lust, J.A.; et al. Importance of achieving stringent complete response after autologous stem-cell transplantation in multiple myeloma. J. Clin. Oncol. 2013, 31, 4529–4535. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lopez-Anglada, L.; Cueto-Felgueroso, C.; Rosiñol, L.; Oriol, A.; Teruel, A.I.; Lopez de la Guia, A.; Bengoechea, E.; Palomera, L.; de Arriba, F.; Hernandez, J.M.; et al. Prognostic utility of serum free light chain ratios and heavy-light chain ratios in multiple myeloma in three PETHEMA/GEM phase III clinical trials. PLoS ONE 2018, 13, e0203392. [Google Scholar] [CrossRef] [Green Version]
- Paiva, B.; Gutiérrez, N.C.; Rosiñol, L.; Vídriales, M.-B.; Montalbán, M.-Á.; Martínez-López, J.; Mateos, M.-V.; Cibeira, M.-T.; Cordón, L.; Oriol, A.; et al. High-risk cytogenetics and persistent minimal residual disease by multiparameter flow cytometry predict unsustained complete response after autologous stem cell transplantation in multiple myeloma. Blood 2012, 119, 687–691. [Google Scholar] [CrossRef]
- Lahuerta, J.-J.J.; Paiva, B.; Vidriales, M.-B.B.; Cordón, L.; Cedena, M.-T.T.; Puig, N.; Martinez-Lopez, J.; Rosiñol, L.; Gutierrez, N.C.; Martín-Ramos, M.-L.L.; et al. Depth of response in multiple myeloma: A pooled analysis of three PETHEMA/GEM clinical trials. J. Clin. Oncol. 2017, 35, 2900–2910. [Google Scholar] [CrossRef] [Green Version]
- Munshi, N.C.; Avet-Loiseau, H.; Rawstron, A.C.; Owen, R.G.; Child, J.A.; Thakurta, A.; Sherrington, P.; Samur, M.K.; Georgieva, A.; Anderson, K.C.; et al. Association of minimal residual disease with superior survival outcomes in patients with multiple myeloma: A meta-analysis. JAMA Oncol. 2017, 3, 28–35. [Google Scholar] [CrossRef]
- Landgren, O.; Devlin, S.; Boulad, M.; Mailankody, S. Role of MRD status in relation to clinical outcomes in newly diagnosed multiple myeloma patients: A meta-analysis. Bone Marrow Transplant. 2016, 51, 1565–1568. [Google Scholar] [CrossRef] [Green Version]
- Goicoechea, I.; Puig, N.; Cedena, M.-T.; Burgos, L.; Cordón, L.; Vidriales, M.-B.; Flores-Montero, J.; Gutierrez, N.C.; Calasanz, M.-J.; Ramos, M.-L.M.; et al. Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard- and high-risk myeloma. Blood 2021, 137, 49–60. [Google Scholar] [CrossRef]
- Paiva, B.; Cedena, M.T.; Puig, N.; Arana, P.; Vidriales, M.B.; Cordon, L.; Flores-Montero, J.; Gutierrez, N.C.; Martín-Ramos, M.L.; Martinez-Lopez, J.; et al. Minimal residual disease monitoring and immune profiling in multiple myeloma in elderly patients. Blood 2016, 127, 3165–3174. [Google Scholar] [CrossRef]
- Munshi, N.C.; Avet-Loiseau, H.; Anderson, K.C.; Neri, P.; Paiva, B.; Samur, M.; Dimopoulos, M.; Kulakova, M.; Lam, A.; Hashim, M.; et al. A large meta-analysis establishes the role of MRD negativity in long-term survival outcomes in patients with multiple myeloma. Blood Adv. 2020, 4, 5988–5999. [Google Scholar] [CrossRef]
- Li, H.; Li, F.; Zhou, X.; Mei, J.; Song, P.; An, Z.; Zhao, Q.; Guo, X.; Wang, X.; Zhai, Y. Achieving minimal residual disease-negative by multiparameter flow cytometry may ameliorate a poor prognosis in MM patients with high-risk cytogenetics: A retrospective single-center analysis. Ann. Hematol. 2019, 98, 1185–1195. [Google Scholar] [CrossRef]
- Dimopoulos, M.A.A.; Moreau, P.; Terpos, E.; Mateos, M.V.V.; Zweegman, S.; Cook, G.; Delforge, M.; Hájek, R.; Schjesvold, F.; Cavo, M.; et al. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2021, 32, 309–322. [Google Scholar] [CrossRef]
- Rawstron, A.C.; Child, J.A.; De Tute, R.M.; Davies, F.E.; Gregory, W.M.; Bell, S.E.; Szubert, A.J.; Navarro-Coy, N.; Drayson, M.T.; Feyler, S.; et al. Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: Impact on outcome in the Medical Research Council Myeloma IX study. J. Clin. Oncol. 2013, 31, 2540–2547. [Google Scholar] [CrossRef]
- Roussel, M.; Lauwers-Cances, V.; Robillard, N.; Hulin, C.; Leleu, X.; Benboubker, L.; Marit, G.; Moreau, P.; Pegourie, B.; Caillot, D.; et al. Front-line transplantation program with lenalidomide, bortezomib, and dexamethasone combination as induction and consolidation followed by lenalidomide maintenance in patients with multiple myeloma: A phase II study by the Intergroupe Francophone du Myélome. J. Clin. Oncol. 2014, 32, 2712–2717. [Google Scholar] [CrossRef]
- Palumbo, A.; Cavallo, F.; Gay, F.; Di Raimondo, F.; Ben Yehuda, D.; Petrucci, M.T.; Pezzatti, S.; Caravita, T.; Cerrato, C.; Ribakovsky, E.; et al. Autologous transplantation and maintenance therapy in multiple myeloma. N. Engl. J. Med. 2014, 371, 895–905. [Google Scholar] [CrossRef]
- Gay, F.; Oliva, S.; Petrucci, M.T.; Conticello, C.; Catalano, L.; Corradini, P.; Siniscalchi, A.; Magarotto, V.; Pour, L.; Carella, A.; et al. Chemotherapy plus lenalidomide versus autologous transplantation, followed by lenalidomide plus prednisone versus lenalidomide maintenance, in patients with multiple myeloma: A randomised, multicentre, phase 3 trial. Lancet Oncol. 2015, 16, 1617–1629. [Google Scholar] [CrossRef]
- Cavo, M.; Gay, F.; Beksac, M.; Pantani, L.; Petrucci, M.T.; Dimopoulos, M.A.; Dozza, L.; van der Holt, B.; Zweegman, S.; Oliva, S.; et al. Autologous haematopoietic stem-cell transplantation versus bortezomib-melphalan-prednisone, with or without bortezomib-lenalidomide-dexamethasone consolidation therapy, and lenalidomide maintenance for newly diagnosed multiple myeloma (EMN02/HO95): A multicentre, randomised, open-label, phase 3 study. Lancet Haematol. 2020, 7, e456–e468. [Google Scholar] [CrossRef]
- Hahn, T.E.; Wallace, P.K.; Fraser, R.; Fei, M.; Tario, J.D.; Howard, A.; Zhang, Y.; Blackwell, B.; Brunstein, C.G.; Efebera, Y.A.; et al. Minimal Residual Disease (MRD) Assessment before and after Autologous Hematopoietic Cell Transplantation (AutoHCT) and Maintenance for Multiple Myeloma (MM): Results of the Prognostic Immunophenotyping for Myeloma Response (PRIMeR) Study. Biol. Blood Marrow Transplant. 2019, 25, S4–S6. [Google Scholar] [CrossRef]
- San-Miguel, J.; Avet-Loiseau, H.; Paiva, B.; Kumar, S.; Dimopoulos, M.A.; Facon, T.; Mateos, M.-V.; Touzeau, C.; Jakubowiak, A.; Usmani, S.Z.; et al. Sustained minimal residual disease negativity in newly diagnosed multiple myeloma and the impact of daratumumab in MAIA and ALCYONE. Blood 2022, 139, 492–501. [Google Scholar] [CrossRef]
- Jiménez-Ubieto, A.; Paiva, B.; Puig, N.; Cedena, M.-T.; Martínez-López, J.; Oriol, A.; Blanchard, M.-J.; Ríos, R.; Martin, J.; Martínez, R.; et al. Validation of the International Myeloma Working Group standard response criteria in the PETHEMA/GEM2012MENOS65 study: Are these times of change? Blood 2021, 138, 1901–1905. [Google Scholar] [CrossRef]
- Kumar, S.K.; Callander, N.S.; Adekola, K.; Anderson, L.; Baljevic, M.; Campagnaro, E.; Castillo, J.J.; Chandler, J.C.; Costello, C.; Efebera, Y.; et al. Multiple Myeloma, Version 3.2021, NCCN Clinical Practice Guidelines in Oncology. J. Natl. Compr. Cancer Netw. 2020, 18, 1685–1717. [Google Scholar] [CrossRef]
- Landgren, O.; Iskander, K. Modern multiple myeloma therapy: Deep, sustained treatment response and good clinical outcomes. J. Intern. Med. 2017, 281, 365–382. [Google Scholar] [CrossRef]
- Landgren, O.; Hultcrantz, M.; Diamond, B.; Lesokhin, A.M.; Mailankody, S.; Hassoun, H.; Tan, C.; Shah, U.A.; Lu, S.X.; Salcedo, M.; et al. Safety and Effectiveness of Weekly Carfilzomib, Lenalidomide, Dexamethasone, and Daratumumab Combination Therapy for Patients With Newly Diagnosed Multiple Myeloma: The MANHATTAN Nonrandomized Clinical Trial. JAMA Oncol. 2021, 7, 862–868. [Google Scholar] [CrossRef] [PubMed]
- Holstein, S.A.; Al-Kadhimi, Z.; Costa, L.J.; Hahn, T.; Hari, P.; Hillengass, J.; Jacob, A.; Munshi, N.C.; Oliva, S.; Pasquini, M.C.; et al. Summary of the Third Annual Blood and Marrow Transplant Clinical Trials Network Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling. Biol. Blood Marrow Transplant. 2020, 26, e7–e15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- FDA Guidance for Industry. Hematologic Malignancies: Regulatory Considerations for Use of Minimal Residual Disease in Development of Drug and Biological Products for Treatment. Available online: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/U (accessed on 25 February 2022).
- EMA Guideline on the use of Minimal Residual Disease as a Clinical Endpoint in Multiple Myeloma Studies. Available online: https://www.ema.europa.eu/en/documents/scienti_cguideline/%0Adraft-guideline-use-minimal-residual-disease-clinical-endpoint-multiplemyeloma-%0Astudies_en.pdf%0A (accessed on 25 February 2022).
- Attal, M.; Lauwers-Cances, V.; Hulin, C.; Leleu, X.; Caillot, D.; Escoffre, M.; Arnulf, B.; Macro, M.; Belhadj, K.; Garderet, L.; et al. Lenalidomide, Bortezomib, and Dexamethasone with Transplantation for Myeloma. N. Engl. J. Med. 2017, 376, 1311–1320. [Google Scholar] [CrossRef] [PubMed]
- Costa, L.J.; Chhabra, S.; Medvedova, E.; Dholaria, B.R.; Schmidt, T.M.; Godby, K.N.; Silbermann, R.; Dhakal, B.; Bal, S.; Giri, S.; et al. Daratumumab, Carfilzomib, Lenalidomide, and Dexamethasone With Minimal Residual Disease Response-Adapted Therapy in Newly Diagnosed Multiple Myeloma. J. Clin. Oncol. 2021, JCO2101935. [Google Scholar] [CrossRef]
- Gambella, M.; Omedé, P.; Spada, S.; Muccio, V.E.; Gilestro, M.; Saraci, E.; Grammatico, S.; Larocca, A.; Conticello, C.; Bernardini, A.; et al. Minimal residual disease by flow cytometry and allelic-specific oligonucleotide real-time quantitative polymerase chain reaction in patients with myeloma receiving lenalidomide maintenance: A pooled analysis. Cancer 2019, 125, 750–760. [Google Scholar] [CrossRef]
- Oliva, S.; Gambella, M.; Larocca, A.; Spada, S.; Marzanati, E.; Mantoan, B.; Grammatico, S.; Conticello, C.; Gamberi, B.; Offidani, M.; et al. Prognostic Impact of Minimal Residual Disease By ASO-RQ-PCR in Multiple Myeloma: A Pooled Analysis of 2 Phase III Studies in Patients Treated with Lenalidomide after Front-Line Therapy. Blood 2016, 128, 4409. [Google Scholar] [CrossRef]
- Jackson, G.H.; Davies, F.E.; Pawlyn, C.; Cairns, D.A.; Striha, A.; Collett, C.; Hockaday, A.; Jones, J.R.; Kishore, B.; Garg, M.; et al. Lenalidomide maintenance versus observation for patients with newly diagnosed multiple myeloma (Myeloma XI): A multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2019, 20, 57–73. [Google Scholar] [CrossRef] [Green Version]
- Alonso, R.; Cedena, M.-T.; Wong, S.; Shah, N.; Ríos-Tamayo, R.; Moraleda, J.M.; López-Jiménez, J.; García, C.; Bahri, N.; Valeri, A.; et al. Prolonged lenalidomide maintenance therapy improves the depth of response in multiple myeloma. Blood Adv. 2020, 4, 2163–2171. [Google Scholar] [CrossRef]
- Amsler, I.G.; Jeker, B.; Mansouri Taleghani, B.; Bacher, U.; Betticher, D.; Egger, T.; Zander, T.; Luethi, J.-M.; Novak, U.; Pabst, T. Prolonged survival with increasing duration of lenalidomide maintenance after autologous transplant for multiple myeloma. Leuk. Lymphoma 2019, 60, 511–514. [Google Scholar] [CrossRef]
- Mian, I.; Milton, D.R.; Shah, N.; Nieto, Y.; Popat, U.R.; Kebriaei, P.; Parmar, S.; Oran, B.; Shah, J.J.; Manasanch, E.E.; et al. Prolonged survival with a longer duration of maintenance lenalidomide after autologous hematopoietic stem cell transplantation for multiple myeloma. Cancer 2016, 122, 3831–3837. [Google Scholar] [CrossRef] [Green Version]
- Gu, J.; Liu, J.; Chen, M.; Huang, B.; Li, J. Longitudinal Flow Cytometry Identified “Minimal Residual Disease” (MRD) Evolution Patterns for Predicting the Prognosis of Patients with Transplant-Eligible Multiple Myeloma. Biol. Blood Marrow Transplant. 2018, 24, 2568–2574. [Google Scholar] [CrossRef] [Green Version]
- Ferrero, S.; Ladetto, M.; Drandi, D.; Cavallo, F.; Genuardi, E.; Urbano, M.; Caltagirone, S.; Grasso, M.; Rossini, F.; Guglielmelli, T.; et al. Long-term results of the GIMEMA VEL-03-096 trial in MM patients receiving VTD consolidation after ASCT: MRD kinetics’ impact on survival. Leukemia 2015, 29, 689–695. [Google Scholar] [CrossRef]
- Oliva, S.; Gambella, M.; Gilestro, M.; Muccio, V.E.; Gay, F.; Drandi, D.; Ferrero, S.; Passera, R.; Pautasso, C.; Bernardini, A.; et al. Minimal residual disease after transplantation or lenalidomide-based consolidation in myeloma patients: A prospective analysis. Oncotarget 2017, 8, 5924–5935. [Google Scholar] [CrossRef] [Green Version]
- Mina, R.; Belotti, A.; Petrucci, M.T.; Zambello, R.; Capra, A.; Di Lullo, G.; Ronconi, S.; Pescosta, N.; Grasso, M.; Monaco, F.; et al. Bortezomib-dexamethasone as maintenance therapy or early retreatment at biochemical relapse versus observation in relapsed/refractory multiple myeloma patients: A randomized phase II study. Blood Cancer J. 2020, 10, 58. [Google Scholar] [CrossRef]
- Mohan, M.; Kendrick, S.; Szabo, A.; Yarlagadda, N.; Atwal, D.; Pandey, Y.; Roy, A.; Parikh, R.; Lopez, J.; Thanendrarajan, S.; et al. Clinical implications of loss of bone marrow minimal residual disease negativity in multiple myeloma. Blood Adv. 2022, 6, 808–817. [Google Scholar] [CrossRef]
- Moreau, P.; Siegel, D.S.; Goldschmidt, H.; Niesvizky, R.; Bringhen, S.; Orlowski, R.Z.; Blaedel, J.; Yang, Z.; Dimopoulos, M.A. Subgroup Analysis of Patients with Biochemical or Symptomatic Relapse at the Time of Enrollment in the Endeavor Study. Blood 2018, 132, 3243. [Google Scholar] [CrossRef]
- Rasmussen, A.-M.; Askeland, F.B.; Schjesvold, F. The Next Step for MRD in Myeloma? Treating MRD Relapse after First Line Treatment in the REMNANT Study. Hemato 2020, 1, 36–48. [Google Scholar] [CrossRef]
- Dimopoulos, M.; Quach, H.; Mateos, M.-V.; Landgren, O.; Leleu, X.; Siegel, D.; Weisel, K.; Yang, H.; Klippel, Z.; Zahlten-Kumeli, A.; et al. Carfilzomib, dexamethasone, and daratumumab versus carfilzomib and dexamethasone for patients with relapsed or refractory multiple myeloma (CANDOR): Results from a randomised, multicentre, open-label, phase 3 study. Lancet 2020, 396, 186–197. [Google Scholar] [CrossRef]
- Palumbo, A.; Chanan-Khan, A.; Weisel, K.; Nooka, A.K.; Masszi, T.; Beksac, M.; Spicka, I.; Hungria, V.; Munder, M.; Mateos, M.V.; et al. Daratumumab, Bortezomib, and Dexamethasone for Multiple Myeloma. N. Engl. J. Med. 2016, 375, 754–766. [Google Scholar] [CrossRef]
- Avet-Loiseau, H.; San-Miguel, J.; Casneuf, T.; Iida, S.; Lonial, S.; Usmani, S.Z.; Spencer, A.; Moreau, P.; Plesner, T.; Weisel, K.; et al. Evaluation of Sustained Minimal Residual Disease Negativity with Daratumumab-Combination Regimens in Relapsed and/or Refractory Multiple Myeloma: Analysis of POLLUX and CASTOR. J. Clin. Med. 2021, 39, 1139–1149. [Google Scholar] [CrossRef]
- Munshi, N.C.; Berdeja, J.G.; Lin, Y.; Kochenderfer, J.; Raje, N.S.; Liedtke, M.; Jagannath, S.; Madduri, D.; Rosenblatt, J.; Maus, M.V.; et al. Early MRD negativity to predict deepening myeloma response in relapsed/refractory multiple myeloma (RRMM) patients treated with bb2121 anti-BCMA CAR T cells. J. Clin. Oncol. 2018, 36, 8024. [Google Scholar] [CrossRef]
- Costa, L.J.; Wong, S.W.; Bermúdez, A.; de la Rubia, J.; Mateos, M.-V.; Ocio, E.M.; Rodríguez-Otero, P.; San-Miguel, J.; Li, S.; Sarmiento, R.; et al. First Clinical Study of the B-Cell Maturation Antigen (BCMA) 2+1 T Cell Engager (TCE) CC-93269 in Patients (Pts) with Relapsed/Refractory Multiple Myeloma (RRMM): Interim Results of a Phase 1 Multicenter Trial. Blood 2019, 134, 143. [Google Scholar] [CrossRef]
- Attal, M.; Richardson, P.G.; Rajkumar, S.V.; San-Miguel, J.; Beksac, M.; Spicka, I.; Leleu, X.; Schjesvold, F.; Moreau, P.; Dimopoulos, M.A.; et al. Isatuximab plus pomalidomide and low-dose dexamethasone versus pomalidomide and low-dose dexamethasone in patients with relapsed and refractory multiple myeloma (ICARIA-MM): A randomised, multicentre, open-label, phase 3 study. Lancet 2019, 394, 2096–2107. [Google Scholar] [CrossRef]
- Bahlis, N.J.; Dimopoulos, M.A.; White, D.J.; Benboubker, L.; Cook, G.; Leiba, M.; Ho, P.J.; Kim, K.; Takezako, N.; Moreau, P.; et al. Daratumumab plus lenalidomide and dexamethasone in relapsed/refractory multiple myeloma: Extended follow-up of POLLUX, a randomized, open-label, phase 3 study. Leukemia 2020, 34, 1875–1884. [Google Scholar] [CrossRef] [Green Version]
- Martin, T.; Usmani, S.Z.; Berdeja, J.G.; Jakubowiak, A.; Agha, M.; Cohen, A.D.; Hari, P.; Avigan, D.; Deol, A.; Htut, M.; et al. Updated Results from CARTITUDE-1: Phase 1b/2Study of Ciltacabtagene Autoleucel, a B-Cell Maturation Antigen-Directed Chimeric Antigen Receptor T Cell Therapy, in Patients With Relapsed/Refractory Multiple Myeloma. Blood 2021, 138, 549. [Google Scholar] [CrossRef]
- Wang, B.-Y.; Zhao, W.-H.; Liu, J.; Chen, Y.-X.; Cao, X.-M.; Yang, Y.; Zhang, Y.-L.; Wang, F.-X.; Zhang, P.-Y.; Lei, B.; et al. Long-Term Follow-up of a Phase 1, First-in-Human Open-Label Study of LCAR-B38M, a Structurally Differentiated Chimeric Antigen Receptor T (CAR-T) Cell Therapy Targeting B-Cell Maturation Antigen (BCMA), in Patients (pts) with Relapsed/Refractory Multiple Myeloma (RRMM). Blood 2019, 134, 579. [Google Scholar] [CrossRef]
- Munshi, N.C.; Anderson, L.D.J.; Shah, N.; Madduri, D.; Berdeja, J.; Lonial, S.; Raje, N.; Lin, Y.; Siegel, D.; Oriol, A.; et al. Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma. N. Engl. J. Med. 2021, 384, 705–716. [Google Scholar] [CrossRef]
- Da Vià, M.C.; Dietrich, O.; Truger, M.; Arampatzi, P.; Duell, J.; Heidemeier, A.; Zhou, X.; Danhof, S.; Kraus, S.; Chatterjee, M.; et al. Homozygous BCMA gene deletion in response to anti-BCMA CAR T cells in a patient with multiple myeloma. Nat. Med. 2021, 27, 616–619. [Google Scholar] [CrossRef]
- Mailankody, S.; Jakubowiak, A.J.; Htut, M.; Costa, L.J.; Lee, K.; Ganguly, S.; Kaufman, J.L.; Siegel, D.S.D.; Bensinger, W.; Cota, M.; et al. Orvacabtagene autoleucel (orva-cel), a B-cell maturation antigen (BCMA)-directed CAR T cell therapy for patients (pts) with relapsed/refractory multiple myeloma (RRMM): Update of the phase 1/2 EVOLVE study (NCT03430011). J. Clin. Oncol. 2020, 38, 8504. [Google Scholar] [CrossRef]
- Mohyuddin, G.R.; Rooney, A.; Balmaceda, N.; Aziz, M.; Sborov, D.W.; McClune, B.; Kumar, S.K. Chimeric antigen receptor T-cell therapy in multiple myeloma: A systematic review and meta-analysis of 950 patients. Blood Adv. 2021, 5, 1097–1101. [Google Scholar] [CrossRef]
- Bravo-Pérez, C.; Sola, M.; Teruel-Montoya, R.; García-Malo, M.D.; Ortuño, F.J.; Vicente, V.; de Arriba, F.; Jerez, A. Minimal Residual Disease in Multiple Myeloma: Something Old, Something New. Cancers 2021, 13, 4332. [Google Scholar] [CrossRef] [PubMed]
- Topp, M.S.; Duell, J.; Zugmaier, G.; Attal, M.; Moreau, P.; Langer, C.; Krönke, J.; Facon, T.; Salnikov, A.V.; Lesley, R.; et al. Anti-B-Cell Maturation Antigen BiTE Molecule AMG 420 Induces Responses in Multiple Myeloma. J. Clin. Oncol. 2020, 38, 775–783. [Google Scholar] [CrossRef] [PubMed]
- Kaufman, J.L.; Baz, R.C.; Harrison, S.J.; Quach, H.; Ho, S.-J.; Vangsted, A.J.; Moreau, P.; Gibbs, S.D.J.; Salem, A.H.; Coppola, S.; et al. Updated analysis of a phase I/II study of venetoclax in combination with daratumumab and dexamethasone, +/- bortezomib, in patients with relapsed/refractory multiple myeloma. J. Clin. Oncol. 2020, 38, 8511. [Google Scholar] [CrossRef]
- Lutz, R.; Mahmoud, A.; Awwad, M.H.S.; Imbusch, C.D.; Boch, T.; Durie, B.G.M.; Weinhold, N.; Raab, M.S.; Müller-Tidow, C.; Haas, S.; et al. The Bone Marrow Microenvironment of Multiple Myeloma Long-Term Survivors at Single Cell Resolution. Blood 2020, 136, 32–33. [Google Scholar] [CrossRef]
- Ho, C.M.; McCarthy, P.L.; Wallace, P.K.; Zhang, Y.; Fora, A.; Mellors, P.; Tario, J.D.; McCarthy, B.L.S.; Chen, G.L.; Holstein, S.A.; et al. Immune signatures associated with improved progression-free and overall survival for myeloma patients treated with AHSCT. Blood Adv. 2017, 1, 1056–1066. [Google Scholar] [CrossRef] [Green Version]
- Bhutani, M.; Foureau, D.; Zhang, Q.; Robinson, M.; Wynn, A.S.; Steuerwald, N.M.; Druhan, L.J.; Guo, F.; Rigby, K.; Turner, M.; et al. Peripheral Immunotype Correlates with Minimal Residual Disease Status and Is Modulated by Immunomodulatory Drugs in Multiple Myeloma. Biol. Blood Marrow Transplant. 2019, 25, 459–465. [Google Scholar] [CrossRef] [Green Version]
- Papadimitriou, K.; Tsakirakis, N.; Malandrakis, P.; Vitsos, P.; Metousis, A.; Orologas-Stavrou, N.; Ntanasis-Stathopoulos, I.; Kanellias, N.; Eleutherakis-Papaiakovou, E.; Pothos, P.; et al. Deep Phenotyping Reveals Distinct Immune Signatures Correlating with Prognostication, Treatment Responses, and MRD Status in Multiple Myeloma. Cancers 2020, 12, 3245. [Google Scholar] [CrossRef]
- Paiva, B.; Vídriales, M.B.; Rosiñol, L.; Martínez-López, J.; Mateos, M.V.; Ocio, E.M.; Montalbán, M.A.; Cordón, L.; Gutiérrez, N.C.; Corchete, L.; et al. A multiparameter flow cytometry immunophenotypic algorithm for the identification of newly diagnosed symptomatic myeloma with an MGUS-like signature and long-term disease control. Leukemia 2013, 27, 2056–2061. [Google Scholar] [CrossRef] [Green Version]
- De Magalhães, R.J.P.; Vidriales, M.B.; Paiva, B.; Fernandez-Gimenez, C.; García-Sanz, R.; Mateos, M.V.; Gutierrez, N.C.; Lecrevisse, Q.; Blanco, J.F.; Hernández, J.; et al. Analysis of the immune system of multiple myeloma patients achieving long-term disease control by multidimensional flow cytometry. Haematologica 2013, 98, 79–86. [Google Scholar] [CrossRef] [Green Version]
- Coffey, D.G.; Maura, F.; Gonzalez-Kozlova, E.; Diaz-Mejia3, J.; Luo, P.; Zhang, Y.; Xu, Y.; Warren, E.H.; Smith, E.L.; Cho, H.J.; et al. Normalization of the Immune Microenvironment during Lenalidomide Maintenance Is Associated with Sustained MRD Negativity in Patients with Multiple Myeloma. Blood 2021, 138, 329. [Google Scholar] [CrossRef]
- Shaughnessy, J.D.J.; Zhan, F.; Burington, B.E.; Huang, Y.; Colla, S.; Hanamura, I.; Stewart, J.P.; Kordsmeier, B.; Randolph, C.; Williams, D.R.; et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood 2007, 109, 2276–2284. [Google Scholar] [CrossRef] [Green Version]
- Zhan, F.; Barlogie, B.; Arzoumanian, V.; Huang, Y.; Williams, D.R.; Hollmig, K.; Pineda-Roman, M.; Tricot, G.; van Rhee, F.; Zangari, M.; et al. Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis. Blood 2007, 109, 1692–1700. [Google Scholar] [CrossRef] [Green Version]
- Schinke, C.; Hoering, A.; Wang, H.; Carlton, V.; Thanandrarajan, S.; Deshpande, S.; Patel, P.; Molnar, G.; Susanibar, S.; Mohan, M.; et al. The prognostic value of the depth of response in multiple myeloma depends on the time of assessment, risk status and molecular subtype. Haematologica 2017, 102, e313–e316. [Google Scholar] [CrossRef] [Green Version]
- Palumbo, A.; Avet-Loiseau, H.; Oliva, S.; Lokhorst, H.M.; Goldschmidt, H.; Rosinol, L.; Richardson, P.; Caltagirone, S.; Lahuerta, J.J.; Facon, T.; et al. Revised international staging system for multiple myeloma: A report from international myeloma working group. J. Clin. Oncol. 2015, 33, 2863–2869. [Google Scholar] [CrossRef]
- Brown, P.A.; Shah, B.; Advani, A.; Aoun, P.; Boyer, M.W.; Burke, P.W.; DeAngelo, D.J.; Dinner, S.; Fathi, A.T.; Gauthier, J.; et al. Acute Lymphoblastic Leukemia, Version 2.2021, NCCN Clinical Practice Guidelines in Oncology. J. Natl. Compr. Canc. Netw. 2021, 19, 1079–1109. [Google Scholar] [CrossRef]
- Hochhaus, A.; Baccarani, M.; Silver, R.T.; Schiffer, C.; Apperley, J.F.; Cervantes, F.; Clark, R.E.; Cortes, J.E.; Deininger, M.W.; Guilhot, F.; et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 2020, 34, 966–984. [Google Scholar] [CrossRef] [Green Version]
- Clinicaltrials.gov. Available online: https://clinicaltrials.gov/ct2/home (accessed on 25 February 2022).
Next Generation Flow (NGF) | Next Generation Sequencing (NGS) | PET/CT | |
---|---|---|---|
Applicability | ~100% | ~90% | ~90% (specifically extramedullary disease) |
Availability | High (≥8 colors needed) | Low (commercial and academic platforms) | Intermediate |
Sample at diagnosis | Not obligatory | Obligatory (identification of dominant clone) | Not obligatory (required for identification of focal lesions or extramedullary disease |
Number of cells required | 10 × 106 cells | 1–3 × 106 cells | NA |
Sample processing | Fresh samples Processing within 24–48 h | Fresh/frozen samples | NA |
Patchy sample | Impact | Impact | No impact |
Whole sample characterization | Yes (global cell characterization) | No | No |
Clonal evaluation | Not possible | Possible (identification of minor clones) | Possible (requires focal lesion biopsy) |
Quantitative method | Yes | Yes | Yes |
Standardization | Yes (EuroFlow Consortium) | Yes (Adaptive Biotechnologies; FDA approved) | No (ongoing) |
Sensitivity | 10−5–10−6 | 10−5–10−6 | High (4 mm) |
Time to results | 3–4 h | 7 days | 2 h |
Complexity | Cytometry skills; automated analysis available | Bioinformatic support | Nuclear medicine support |
Reproducibility | High | High | Moderate |
Title | Phase | Objective | Study Population | Time Point Assessment | Decision | Treatment | Primary Outcome | MRD Method |
---|---|---|---|---|---|---|---|---|
MASTER trial (NCT03224507) | 2 | Decision to begin maintenance | NDMM after Dara-KRd and ASCT | End of consolidation | MRD+ | Maintenance Dara-KRd | MRD negativity rate | NGS (10−5) |
MRD- | Observation (2x MRD-) | |||||||
DART4MM study (NCT03992170) | 2 | Effect of Dara on MRD positive patients | MRD+ patients >VGPR | Maintenance (24 weeks) | MRD+ | Dara (80 weeks) | MRD negativity rate | NGF (10−5) |
MRD- | Stop treatment | |||||||
AURIGA study (NCT03901963) | 3 | Guide maintenance | MRD+ patients after ASCT | Maintenance | MRD+ | Dara-R | MRD negative status | NGS (10−5) |
MRD- | R | |||||||
NCT04140162 | 2 | Guide consolidation after initial therapy | NDMM after Dara-Rd induction | After induction | MRD+ | Consolidation Dara-RVd | MRD negativity rate | NGS (10−5) |
MRD- | Maintenance Dara-R/R | |||||||
DRAMMATIC study (NCT04071457) | 3 | Guide maintenance after initial therapy | NDMM after randomization to Dara-R versus R following ASCT | Maintenance (2 years) (R versus Dara/rHuPH20) | MRD+ | Continue maintenance | OS | NGS (10−5) |
MRD- | Continue versus stopping maintenance | |||||||
REMNANT study (NCT04513639) | 2–3 | Guide early treatment of relapse | NDMM MRD- after VRd and ASCT | After consolidation (MRD assessed every 4 months) | MRD+ | Dara-Kd | MRD negativity rate; PFS; OS | NGF (10−5) |
MRD- | Observation (until PD) | |||||||
MRD2STOP (NCT04108624) | NA | Guide maintenance cessation | Patients at CR after ASCT during maintenance | Maintenance (≥ 1 year) | MRD+ | Continue maintenance | MRD conversion rate; PFS; OS | NGS (exploring 10−7) or NGF and PET/CT |
MRD- | Stop maintenance | |||||||
PERSEUS (NCT03710603) | 3 | Guide maintenance after initial therapy | NDMM after Dara-VRd during maintenance (Dara-R) | Maintenance (2 years) | MRD+ | Dara-R | PFS | NGS (10−5) |
MRD- | R (sustained MRD- 12 months) | |||||||
PREDATOR-MRD (NCT03697655) | 2 | Role of Dara in MRD | RRMM (1–2 prior lines therapy) | Maintenance | MRD+ | Dara | EFS | NGF (10−5) |
MRD- | Observation | |||||||
NCT03490344 | 2 | Effect of Dara on MRD positive patients | Patients in ≤VGPR after induction with/without ASCT | Maintenance (Dara-R) | _ | _ | MRD negativity rate | NGF (10−5) |
NCT04221178 | NA | Guide maintenance cessation | MRD- patients under maintenance | Maintenance (≥ 3 years) | MRD+ | Continue | MRD negativity rate after 1 year | NGF (10−5) |
MRD- | Stop maintenance | |||||||
NCT02659293 | 3 | Guide duration of maintenance | NDMM patients after ASCT | Maintenance (end cycle 6) | MRD+ | KRd (cycle 5–36) | PFS | NGS (10−5) |
MRD- | KRd (cycle 5–8) | |||||||
NCT02389517 | 2 | Effect of Ixa on MRD positive patients | MRD+ patients after ASCT | Maintenance (Ixa-Rd versus R) | _ | _ | MRD negativity rate | NGF (10−5) |
NCT02969837 | 2 | Guide duration of maintenance | NDMM | Maintenance | MRD+ | E-KRd (6 cycles) + E-Rd (until PD) | MRD negativity rate | NGS (10−5) |
MRD- | E-Rd until PD | |||||||
NCT04096066 | 3 | Guide maintenance therapy | NDMM (≥ 65 years) | Maintenance (KRd versus Rd) | MRD+ | KRd | MRD negativity rate; PFS | NGF or NGS (10−5) |
MRD- | Rd (after 2 years) | |||||||
NCT04140162 | 2 | Guide consolidation therapy | NDMM after Dara-Rd induction | After Induction | MRD+ | DRVd consolidation | MRD negativity rate | NGF or NGS (10−5) |
MRD- | Dara-Rd maintenance | |||||||
NCT05091372 | 2 | Effect of Belantamab mafodotin on MRD | NDMM MRD+ patients after ASCT | Maintenance | _ | _ | MRD negativity rate | NGF or NGS (10−5) |
MILESTONE (NCT04991103) | 2 | Guide consolidation/maintenance therapy | NDMM after Dara-VRd | After Induction | MRD+ | Proceed to ASCT and Maintenance | MRD negativity rate | NGS (10−5) |
MRD- | Defer ASCT | |||||||
MIDAS (NCT04934475) | 3 | Guide consolidation therapy | NDMM after Isa-KRd | After Induction | MRD+ | ASCT+Isa-KRd versus ASCT | MRD negativity rate | NGS (10−5) |
MRD- | Isa-KRd versus ASCT+Isa-KRd | |||||||
MASTER-2 (NCT05231629) | 2 | Guide consolidation/maintenance therapy | NDMM after Dara-VRd | After Induction | MRD+ | ASCT+Dara-Tec versus ASCT+Dara-R | Depth of response; sustained MRD negativity | NGS (10−5) |
MRD- | Dara-VRd+Dara-R versus ASCT+Dara-R | |||||||
HEME-20 (NCT05192122) | 1 | Guide maintenance cessation | NDMM MRD- after ASCT | Maintenance (3 years) | MRD+ | Continue maintenance | Sustained MRD negativity | NGS (10−5) |
MRD- | Stop maintenance |
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Caetano, J.; Barahona, F.; Lúcio, P.; João, C. Measurable Residual Disease Assessment in Multiple Myeloma: How Deep Is Enough? Hemato 2022, 3, 385-413. https://doi.org/10.3390/hemato3030027
Caetano J, Barahona F, Lúcio P, João C. Measurable Residual Disease Assessment in Multiple Myeloma: How Deep Is Enough? Hemato. 2022; 3(3):385-413. https://doi.org/10.3390/hemato3030027
Chicago/Turabian StyleCaetano, Joana, Filipa Barahona, Paulo Lúcio, and Cristina João. 2022. "Measurable Residual Disease Assessment in Multiple Myeloma: How Deep Is Enough?" Hemato 3, no. 3: 385-413. https://doi.org/10.3390/hemato3030027
APA StyleCaetano, J., Barahona, F., Lúcio, P., & João, C. (2022). Measurable Residual Disease Assessment in Multiple Myeloma: How Deep Is Enough? Hemato, 3(3), 385-413. https://doi.org/10.3390/hemato3030027