Literature DB >> 29759152

Minimal Residual Disease Detection by Flow Cytometry in Multiple Myeloma: Why and How?

Mikhail Roshal1.   

Abstract

The outlook for myeloma patients has steadily improved with the introduction of newer drug combinations in recent years. Unlike older therapies that largely achieved only modest levels of neoplastic clone reduction, the newer drug combinations have led to deeper suppression of myeloma clones in most patients. Frequently the neoplastic clones become undetectable with traditional disease evaluation approaches. Recent studies using ultrasensitive disease monitoring have demonstrated that patients with disease undetectable by traditional techniques show wide heterogeneity in disease levels varying by several orders of magnitude. Moreover, measurement of the depth of disease suppression even at very low level has emerged as the most powerful prognostication tool in myeloma. Minimal (or measurable) residual disease (MRD) evaluation has also been proposed as a relevant tool in assessment of drug efficacy and in selection of further therapeutic options. In the face of the robust MRD measurement utility data, it has become critical to develop widely applicable disease monitoring techniques that can be applied to more patients in a variety of clinical setting. Both DNA-based and flow cytometry-based approaches have been successfully developed for this purpose achieving sensitivity approaching 1 neoplastic cell in a million. This review article focuses on the theoretical and practical aspects and challenges of deep MRD monitoring in myeloma by flow cytometry. Challenges of flow cytometric disease monitoring in the era of antigen-directed therapy are also discussed.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  flow cytometry; minimal residual disease; myeloma

Mesh:

Year:  2018        PMID: 29759152     DOI: 10.1053/j.seminhematol.2018.02.011

Source DB:  PubMed          Journal:  Semin Hematol        ISSN: 0037-1963            Impact factor:   3.851


  6 in total

Review 1.  Monitoring minimal residual disease in the bone marrow using next generation sequencing.

Authors:  Even H Rustad; Eileen M Boyle
Journal:  Best Pract Res Clin Haematol       Date:  2020-01-17       Impact factor: 3.020

2.  CytoML for cross-platform cytometry data sharing.

Authors:  Greg Finak; Wenxin Jiang; Raphael Gottardo
Journal:  Cytometry A       Date:  2018-12       Impact factor: 4.355

3.  Minimal Residual Disease Negativity Does Not Overcome Poor Prognosis in High-Risk Multiple Myeloma: A Single-Center Retrospective Study.

Authors:  Chutima Kunacheewa; Hans C Lee; Krina Patel; Sheeba Thomas; Behrang Amini; Samer Srour; Qaiser Bashir; Yago Nieto; Muzzaffar H Qazilbash; Donna M Weber; Lei Feng; Robert Z Orlowski; Pei Lin; Elisabet E Manasanch
Journal:  Clin Lymphoma Myeloma Leuk       Date:  2020-01-15

4.  Baseline identification of clonal V(D)J sequences for DNA-based minimal residual disease detection in multiple myeloma.

Authors:  Even H Rustad; Malin Hultcrantz; Venkata D Yellapantula; Theresia Akhlaghi; Caleb Ho; Maria E Arcila; Mikhail Roshal; Akshar Patel; Denise Chen; Sean M Devlin; Austin Jacobsen; Ying Huang; Jeffrey E Miller; Elli Papaemmanuil; Ola Landgren
Journal:  PLoS One       Date:  2019-03-22       Impact factor: 3.240

5.  Combination of flow cytometry and functional imaging for monitoring of residual disease in myeloma.

Authors:  L Rasche; D Alapat; M Kumar; G Gershner; J McDonald; C P Wardell; R Samant; R Van Hemert; J Epstein; A F Williams; S Thanendrarajan; C Schinke; M Bauer; C Ashby; R G Tytarenko; F van Rhee; B A Walker; M Zangari; B Barlogie; F E Davies; G J Morgan; N Weinhold
Journal:  Leukemia       Date:  2018-12-20       Impact factor: 11.528

Review 6.  Minimal Residual Disease Assessment Within the Bone Marrow of Multiple Myeloma: A Review of Caveats, Clinical Significance and Future Perspectives.

Authors:  Alessandra Romano; Giuseppe Alberto Palumbo; Nunziatina Laura Parrinello; Concetta Conticello; Marina Martello; Carolina Terragna
Journal:  Front Oncol       Date:  2019-08-20       Impact factor: 6.244

  6 in total

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