Ravi Vij1, Amitabha Mazumder2, Mark Klinger3, Denise O'Dea2, Jacob Paasch1, Thomas Martin4, Li Weng3, Jeesun Park2, Mark Fiala1, Malek Faham3, Jeffrey Wolf5. 1. Division of Oncology, Washington University School of Medicine, St. Louis, MO. 2. Department of Medicine, New York University Langone Medical Center, New York, NY. 3. Sequenta, Inc, South San Francisco, CA. 4. Division of Hematology/Oncology, University of California San Francisco, San Francisco, CA. 5. Division of Hematology/Oncology, University of California San Francisco, San Francisco, CA. Electronic address: wolfj@medicine.ucsf.edu.
Abstract
INTRODUCTION: The evaluation of myeloma cells in multiple myeloma (MM) patients has generally been limited to the assessment of bone marrow involvement because of the sensitivity limitations of traditional minimal-residual-disease-detection methods. MATERIALS AND METHODS: We developed a sequencing-based method to identify myeloma cells in bone marrow (BM) and peripheral blood (PB) samples, based on their unique immunoglobulin gene rearrangements, that can detect cancer clones at levels well below 1 in 1 million leukocytes (0.0001%). In this multisite study, we used this sequencing method to determine the fraction of patients with myeloma cells in their PB at diagnosis and posttreatment time points. RESULTS: Using this sequencing approach, we detected myeloma cells in the PB in the vast majority of MM patients (44/46, 96%). We demonstrated a clear correlation (R(2) = 0.57) between myeloma clone levels in paired BM and PB samples, and noted that PB clone levels were approximately 100-fold lower than levels in BM samples. The sequencing assay demonstrated a clear sensitivity advantage in the BM compartment and at least equivalent sensitivity in the PB compared with that of monoclonal-protein results. CONCLUSION: This study highlights the promise of a blood-based, sequencing minimal-residual-disease assay that can be used to measure MM disease burden at different time points and various disease stages.
INTRODUCTION: The evaluation of myeloma cells in multiple myeloma (MM) patients has generally been limited to the assessment of bone marrow involvement because of the sensitivity limitations of traditional minimal-residual-disease-detection methods. MATERIALS AND METHODS: We developed a sequencing-based method to identify myeloma cells in bone marrow (BM) and peripheral blood (PB) samples, based on their unique immunoglobulin gene rearrangements, that can detect cancer clones at levels well below 1 in 1 million leukocytes (0.0001%). In this multisite study, we used this sequencing method to determine the fraction of patients with myeloma cells in their PB at diagnosis and posttreatment time points. RESULTS: Using this sequencing approach, we detected myeloma cells in the PB in the vast majority of MMpatients (44/46, 96%). We demonstrated a clear correlation (R(2) = 0.57) between myeloma clone levels in paired BM and PB samples, and noted that PB clone levels were approximately 100-fold lower than levels in BM samples. The sequencing assay demonstrated a clear sensitivity advantage in the BM compartment and at least equivalent sensitivity in the PB compared with that of monoclonal-protein results. CONCLUSION: This study highlights the promise of a blood-based, sequencing minimal-residual-disease assay that can be used to measure MM disease burden at different time points and various disease stages.
Authors: S Ferrero; M Ladetto; D Drandi; F Cavallo; E Genuardi; M Urbano; S Caltagirone; M Grasso; F Rossini; T Guglielmelli; C Cangialosi; A M Liberati; V Callea; T Carovita; C Crippa; L De Rosa; F Pisani; A P Falcone; P Pregno; S Oliva; C Terragna; P Musto; R Passera; M Boccadoro; A Palumbo Journal: Leukemia Date: 2014-07-16 Impact factor: 11.528
Authors: Yasuhiro Oki; Sattva S Neelapu; Michelle Fanale; Larry W Kwak; Luis Fayad; Maria A Rodriguez; Michael Wallace; Mark Klinger; Victoria Carlton; Katherine Kong; Malek Faham; Anas Younes Journal: Br J Haematol Date: 2015-03-29 Impact factor: 6.998
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Authors: Joyce W Kamande; Maria A M Lindell; Małgorzata A Witek; Peter M Voorhees; Steven A Soper Journal: Integr Biol (Camb) Date: 2018-02-19 Impact factor: 2.192