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Rees MJ, Kumar S. High-risk multiple myeloma: Redefining genetic, clinical, and functional high-risk disease in the era of molecular medicine and immunotherapy. Am J Hematol 2024; 99:1560-1575. [PMID: 38613829 DOI: 10.1002/ajh.27327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 03/22/2024] [Accepted: 04/02/2024] [Indexed: 04/15/2024]
Abstract
Multiple myeloma (MM) exhibits significant heterogeneity in its presentation, genetics, and treatment response. Despite therapeutic advances, some patients continue to relapse early (ER, <18-months) and rapidly cycle through therapies. Myriad prognostic factors have been identified and incorporated into risk stratification models; however, these produce discordant, often three-tiered outputs that fail to identify many patients destined for ER. Treatment strategies are increasingly focused on disease biology and trials enriched for high-risk (HR)MM, but consensus on the minimum required testing and a succinct, specific, and clinically meaningful definition for HRMM remains elusive. We review the risk-factors, definitions, and future directions for HRMM.
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Affiliation(s)
- Matthew J Rees
- Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shaji Kumar
- Division of Hematology, Mayo Clinic, Rochester, Minnesota, USA
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2
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Ghosh S, Choudhury D, Ghosh D, Mondal M, Singha D, Malakar P. Characterization of polyploidy in cancer: Current status and future perspectives. Int J Biol Macromol 2024; 268:131706. [PMID: 38643921 DOI: 10.1016/j.ijbiomac.2024.131706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 04/23/2024]
Abstract
Various cancers frequently exhibit polyploidy, observed in a condition where a cell possesses more than two sets of chromosomes, which is considered a hallmark of the disease. The state of polyploidy often leads to aneuploidy, where cells possess an abnormal number or structure of chromosomes. Recent studies suggest that oncogenes contribute to aneuploidy. This finding significantly underscores its impact on cancer. Cancer cells exposed to certain chemotherapeutic drugs tend to exhibit an increased incidence of polyploidy. This occurrence is strongly associated with several challenges in cancer treatment, including metastasis, resistance to chemotherapy and the recurrence of malignant tumors. Indeed, it poses a significant hurdle to achieve complete tumor eradication and effective cancer therapy. Recently, there has been a growing interest in the field of polyploidy related to cancer for developing effective anti-cancer therapies. Polyploid cancer cells confer both advantages and disadvantages to tumor pathogenicity. This review delineates the diverse characteristics of polyploid cells, elucidates the pivotal role of polyploidy in cancer, and explores the advantages and disadvantages it imparts to cancer cells, along with the current approaches tried in lab settings to target polyploid cells. Additionally, it considers experimental strategies aimed at addressing the outstanding questions within the realm of polyploidy in relation to cancer.
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Affiliation(s)
- Srijonee Ghosh
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India
| | - Debopriya Choudhury
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India
| | - Dhruba Ghosh
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India
| | - Meghna Mondal
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India
| | - Didhiti Singha
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India
| | - Pushkar Malakar
- Department of Biomedical Science and Technology, School of Biological Sciences, Ramakrishna Mission Vivekananda Educational Research Institute (RKMVERI), Kolkata, India.
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3
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Clarke SE, Fuller KA, Erber WN. Chromosomal defects in multiple myeloma. Blood Rev 2024; 64:101168. [PMID: 38212176 DOI: 10.1016/j.blre.2024.101168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/01/2023] [Accepted: 01/02/2024] [Indexed: 01/13/2024]
Abstract
Multiple myeloma is a plasma cell neoplasm driven by primary (e.g. hyperdiploidy; IGH translocations) and secondary (e.g. 1q21 gains/amplifications; del(17p); MYC translocations) chromosomal events. These are important to detect as they influence prognosis, therapeutic response and disease survival. Currently, cytogenetic testing is most commonly performed by interphase fluorescence in situ hybridisation (FISH) on aspirated bone marrow samples. A number of variations to FISH methodology are available, including prior plasma cell enrichment and incorporation of immunophenotypic plasma cell identification. Other molecular methods are increasingly being utilised to provide a genome-wide view at high resolution (e.g. single nucleotide polymorphism (SNP) microarray analysis) and these can detect abnormalities in most cases. Despite their wide application at diagnostic assessment, both FISH and SNP-array have relatively low sensitivity, limiting their use for identification of prognostically significant low-level sub-clones or for disease monitoring. Next-generation sequencing is increasingly being used to detect mutations and new FISH techniques such as by flow cytometry are in development and may address some of the current test limitations. Here we review the primary and secondary cytogenetic aberrations in myeloma and discuss the range of techniques available for their assessment.
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Affiliation(s)
- Sarah E Clarke
- School of Biomedical Sciences, The University of Western Australia (M504), Crawley, WA 6009, Australia; Department of Haematology, PathWest Laboratory Medicine WA, Fiona Stanley Hospital, Murdoch, WA 6150, Australia.
| | - Kathryn A Fuller
- School of Biomedical Sciences, The University of Western Australia (M504), Crawley, WA 6009, Australia.
| | - Wendy N Erber
- School of Biomedical Sciences, The University of Western Australia (M504), Crawley, WA 6009, Australia; PathWest Laboratory Medicine WA, Royal Perth Hospital, Perth, WA 6000, Australia.
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4
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Giguère A, Raymond-Bouchard I, Collin V, Claveau JS, Hébert J, LeBlanc R. Optical Genome Mapping Reveals the Complex Genetic Landscape of Myeloma. Cancers (Basel) 2023; 15:4687. [PMID: 37835381 PMCID: PMC10571866 DOI: 10.3390/cancers15194687] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/15/2023] [Accepted: 09/17/2023] [Indexed: 10/15/2023] Open
Abstract
Fluorescence in situ hybridization (FISH) on enriched CD138 plasma cells is the standard method for identification of clinically relevant genetic abnormalities in multiple myeloma. However, FISH is a targeted analysis that can be challenging due to the genetic complexity of myeloma. The aim of this study was to evaluate the potential of optical genome mapping (OGM) to detect clinically significant cytogenetic abnormalities in myeloma and to provide larger pangenomic information. OGM and FISH analyses were performed on CD138-purified cells of 20 myeloma patients. OGM successfully detected structural variants (SVs) (IGH and MYC rearrangements), copy number variants (CNVs) (17p/TP53 deletion, 1p deletion and 1q gain/amplification) and aneuploidy (gains of odd-numbered chromosomes, monosomy 13) classically expected with myeloma and led to a 30% increase in prognosis yield at our institution when compared to FISH. Despite challenges in the interpretation of OGM calls for CNV and aneuploidy losses in non-diploid genomes, OGM has the potential to replace FISH as the standard of care analysis in clinical settings and to efficiently change how we identify prognostic and predictive markers for therapies in the future. To our knowledge, this is the first study highlighting the feasibility and clinical utility of OGM in myeloma.
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Affiliation(s)
- Amélie Giguère
- Cytogenetics Laboratory, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada; (I.R.-B.); (V.C.); (J.H.)
| | - Isabelle Raymond-Bouchard
- Cytogenetics Laboratory, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada; (I.R.-B.); (V.C.); (J.H.)
| | - Vanessa Collin
- Cytogenetics Laboratory, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada; (I.R.-B.); (V.C.); (J.H.)
| | - Jean-Sébastien Claveau
- Division of Hematology, Oncology and Transplantation, Department of Medicine, Maisonneuve-Rosemont Hospital, Université de Montréal, Montreal, QC H1T 2M4, Canada; (J.-S.C.); (R.L.)
| | - Josée Hébert
- Cytogenetics Laboratory, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada; (I.R.-B.); (V.C.); (J.H.)
- Division of Hematology, Oncology and Transplantation, Department of Medicine, Maisonneuve-Rosemont Hospital, Université de Montréal, Montreal, QC H1T 2M4, Canada; (J.-S.C.); (R.L.)
| | - Richard LeBlanc
- Division of Hematology, Oncology and Transplantation, Department of Medicine, Maisonneuve-Rosemont Hospital, Université de Montréal, Montreal, QC H1T 2M4, Canada; (J.-S.C.); (R.L.)
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5
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Baughn LB, Jessen E, Sharma N, Tang H, Smadbeck JB, Long MD, Pearce K, Smith M, Dasari S, Sachs Z, Linden MA, Cook J, Keith Stewart A, Chesi M, Mitra A, Leif Bergsagel P, Van Ness B, Kumar SK. Mass Cytometry reveals unique phenotypic patterns associated with subclonal diversity and outcomes in multiple myeloma. Blood Cancer J 2023; 13:84. [PMID: 37217482 PMCID: PMC10203138 DOI: 10.1038/s41408-023-00851-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/26/2023] [Accepted: 05/02/2023] [Indexed: 05/24/2023] Open
Abstract
Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Although it is known that MM tumor cells display extensive intratumoral genetic heterogeneity, an integrated map of the tumor proteomic landscape has not been comprehensively evaluated. We evaluated 49 primary tumor samples from newly diagnosed or relapsed/refractory MM patients by mass cytometry (CyTOF) using 34 antibody targets to characterize the integrated landscape of single-cell cell surface and intracellular signaling proteins. We identified 13 phenotypic meta-clusters across all samples. The abundance of each phenotypic meta-cluster was compared to patient age, sex, treatment response, tumor genetic abnormalities and overall survival. Relative abundance of several of these phenotypic meta-clusters were associated with disease subtypes and clinical behavior. Increased abundance of phenotypic meta-cluster 1, characterized by elevated CD45 and reduced BCL-2 expression, was significantly associated with a favorable treatment response and improved overall survival independent of tumor genetic abnormalities or patient demographic variables. We validated this association using an unrelated gene expression dataset. This study represents the first, large-scale, single-cell protein atlas of primary MM tumors and demonstrates that subclonal protein profiling may be an important determinant of clinical behavior and outcome.
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Affiliation(s)
- Linda B Baughn
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
| | - Erik Jessen
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Neeraj Sharma
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Hongwei Tang
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - James B Smadbeck
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Mark D Long
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Kathryn Pearce
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Matthew Smith
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Surendra Dasari
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Zohar Sachs
- Division of Hematology, Oncology, and Transplantation, Department of Medicine and Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Michael A Linden
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Joselle Cook
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Marta Chesi
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Amit Mitra
- Department of Drug Discovery and Development, Auburn University, Auburn, AL, USA
| | - P Leif Bergsagel
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Brian Van Ness
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Shaji K Kumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
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6
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Locher M, Jukic E, Vogi V, Keller MA, Kröll T, Schwendinger S, Oberhuber K, Verdorfer I, Mühlegger BE, Witsch-Baumgartner M, Nachbaur D, Willenbacher W, Gunsilius E, Wolf D, Zschocke J, Steiner N. Amp(1q) and tetraploidy are commonly acquired chromosomal abnormalities in relapsed multiple myeloma. Eur J Haematol 2023; 110:296-304. [PMID: 36433728 PMCID: PMC10107198 DOI: 10.1111/ejh.13905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 11/14/2022] [Accepted: 11/17/2022] [Indexed: 11/28/2022]
Abstract
Long-term disease control in multiple myeloma (MM) is typically an unmet medical need, and most patients experience multiple relapses. Fluorescence in situ hybridization (FISH) is the standard technique to detect chromosomal abnormalities (CAs), which are important to estimate the prognosis of MM and the allocation of risk adapted therapies. In advanced stages, the importance of CAs needs further investigation. From 148 MM patients, two or more paired samples, at least one of which was collected at relapse, were analyzed by FISH. Using targeted next-generation sequencing, we molecularly investigated samples harboring relapse-associated CAs. Sixty-one percent of the patients showed a change in the cytogenetic profile during the disease course, including 10% who acquired high-risk cytogenetics. Amp(1q) (≥4 copies of 1q21), driven by an additional increase in copy number in patients who already had 3 copies of 1q21, was the most common acquired CA with 16% affected patients. Tetraploidy, found in 10% of the samples collected at the last time-point, was unstable over the course of the disease and was associated with TP53 lesions. Our results indicate that cytogenetic progression is common in relapsed patients. The relatively high frequency of amp(1q) suggests an active role for this CA in disease progression.
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Affiliation(s)
- Maurus Locher
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Emina Jukic
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Verena Vogi
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Markus A Keller
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Teresa Kröll
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Simon Schwendinger
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Klaus Oberhuber
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Irmgard Verdorfer
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Beatrix E Mühlegger
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | | | - David Nachbaur
- Internal Medicine V (Hematology & Oncology), Medical University of Innsbruck, Innsbruck, Austria
| | - Wolfgang Willenbacher
- Internal Medicine V (Hematology & Oncology), Medical University of Innsbruck, Innsbruck, Austria.,syndena GmbH, connect to cure, Innsbruck, Austria
| | - Eberhard Gunsilius
- Internal Medicine V (Hematology & Oncology), Medical University of Innsbruck, Innsbruck, Austria
| | - Dominik Wolf
- Internal Medicine V (Hematology & Oncology), Medical University of Innsbruck, Innsbruck, Austria.,Medical Clinic 3, Oncology, Hematology, Immunoncology and Rheumatology, University Hospital Bonn, Bonn, Germany
| | - Johannes Zschocke
- Institute of Human Genetics, Medical University of Innsbruck, Innsbruck, Austria
| | - Normann Steiner
- Internal Medicine V (Hematology & Oncology), Medical University of Innsbruck, Innsbruck, Austria
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7
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High-risk disease in newly diagnosed multiple myeloma: beyond the R-ISS and IMWG definitions. Blood Cancer J 2022; 12:83. [PMID: 35637223 PMCID: PMC9151761 DOI: 10.1038/s41408-022-00679-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 04/20/2022] [Accepted: 05/09/2022] [Indexed: 12/22/2022] Open
Abstract
Multiple myeloma (MM) is an acquired malignant plasma cell disorder that develops late in life. Although progression free and overall survival has improved across all age, race, and ethnic groups, a subset of patients have suboptimal outcomes and are labeled as having high risk disease. A uniform approach to risk in NDMM remains elusive despite several validated risk stratification systems in clinical use. While we attempt to capture risk at diagnosis, the reality is that many important prognostic characteristics remain ill-defined as some patients relapse early who were defined as low risk based on their genomic profile at diagnosis. It is critical to establish a definition of high risk disease in order to move towards risk-adapted treatment approaches. Defining risk at diagnosis is important to both effectively design future clinical trials and guide which clinical data is needed in routine practice. The goal of this review paper is to summarize and compare the various established risk stratification systems, go beyond the R-ISS and international myeloma working group risk stratifications to evaluate specific molecular and cytogenetic abnormalities and how they impact prognosis independently. In addition, we explore the wealth of new genomic information from recent whole genome/exome sequencing as well as gene expression data and review known clinical factors affecting outcome such as disease burden and early relapse as well as patient related factors such as race. Finally, we provide an outlook on developing a new high risk model system and how we might make sense of co-occurrences, oncogenic dependencies, and mutually exclusive mutations.
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8
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Soh KT, Wallace PK. Evaluation of measurable residual disease in multiple myeloma by multiparametric flow cytometry: Current paradigm, guidelines, and future applications. Int J Lab Hematol 2021; 43 Suppl 1:43-53. [PMID: 34288449 DOI: 10.1111/ijlh.13562] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 03/22/2021] [Accepted: 04/07/2021] [Indexed: 12/16/2022]
Abstract
Multiple myeloma (MM) is a heterogeneous group of mature B-cell diseases that are typically characterized by the presence and accumulation of abnormal plasma cells (PCs), which results in the excess production of monoclonal immunoglobulin and/or light chain found in the serum and/or urine. Multiparametric flow cytometry (MFC) is an indispensable tool to supplement the diagnosis, classification and monitoring of the disease due to its high patient applicability, excellent sensitivity and encouraging results from various clinical trials. In this regard, minimal or, more appropriately, measurable residual disease (MRD) negativity by MFC has been recognized as a powerful predictor of favourable long-term outcomes. Before flow cytometry can be effectively implemented in the clinical setting for MM MRD testing, sample preparation, panel configuration, analysis and gating strategies must be optimized to ensure accurate results. This manuscript will discuss the current consensus guidelines for flow cytometric processing of samples and reporting of results for MM MRD testing. We also discuss alternative approaches to detect plasma cells in the presence of daratumumab treatment. Finally, there is a lack of information describing the subclonal distribution of myeloma cells based on their protein expression. The advent of high-dimensional analysis may assist in following the evolution of antigen expression patterns on abnormal plasma cells in patients with relapsed/refractory disease. This in turn can help identify clonal subtypes that are more aggressive for potential informed decision. An analysis using t-SNE to identify the emergence of PCs subclones by MFC, along with the analysis of their immunophenotypic profiles are presented as a future perspective.
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Affiliation(s)
- Kah Teong Soh
- Department of Flow and Image Cytometry, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Paul K Wallace
- Department of Flow and Image Cytometry, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
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9
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Newcomb R, Dean E, McKinney BJ, Alvarez JV. Context-dependent effects of whole-genome duplication during mammary tumor recurrence. Sci Rep 2021; 11:14932. [PMID: 34294755 PMCID: PMC8298634 DOI: 10.1038/s41598-021-94332-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 07/06/2021] [Indexed: 12/24/2022] Open
Abstract
Whole-genome duplication (WGD) generates polyploid cells possessing more than two copies of the genome and is among the most common genetic abnormalities in cancer. The frequency of WGD increases in advanced and metastatic tumors, and WGD is associated with poor prognosis in diverse tumor types, suggesting a functional role for polyploidy in tumor progression. Experimental evidence suggests that polyploidy has both tumor-promoting and suppressing effects, but how polyploidy regulates tumor progression remains unclear. Using a genetically engineered mouse model of Her2-driven breast cancer, we explored the prevalence and consequences of whole-genome duplication during tumor growth and recurrence. While primary tumors in this model are invariably diploid, nearly 40% of recurrent tumors undergo WGD. WGD in recurrent tumors was associated with increased chromosomal instability, decreased proliferation and increased survival in stress conditions. The effects of WGD on tumor growth were dependent on tumor stage. Surprisingly, in recurrent tumor cells WGD slowed tumor formation, growth rate and opposed the process of recurrence, while WGD promoted the growth of primary tumors. These findings highlight the importance of identifying conditions that promote the growth of polyploid tumors, including the cooperating genetic mutations that allow cells to overcome the barriers to WGD tumor cell growth and proliferation.
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Affiliation(s)
- Rachel Newcomb
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, 27710, USA
| | - Emily Dean
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, 27710, USA
| | - Brock J McKinney
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, 27710, USA
| | - James V Alvarez
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, 27710, USA.
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10
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Hassan H, Szalat R. Genetic Predictors of Mortality in Patients with Multiple Myeloma. APPLICATION OF CLINICAL GENETICS 2021; 14:241-254. [PMID: 33953598 PMCID: PMC8092627 DOI: 10.2147/tacg.s262866] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 03/31/2021] [Indexed: 12/19/2022]
Abstract
Multiple myeloma (MM) is a heterogeneous disease featured by clonal plasma cell proliferation and genomic instability. The advent of next-generation sequencing allowed unraveling the complex genomic landscape of the disease. Several recurrent genomic aberrations including immunoglobulin genes translocations, copy number abnormalities, complex chromosomal events, transcriptomic and epigenomic deregulation, and mutations define various molecular subgroups with distinct outcomes. In this review, we describe the recurrent genomic events identified in MM impacting patients’ outcome and survival. These genomic aberrations constitute new markers that could be incorporated into a prognostication model to eventually guide therapy at every stage of the disease.
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Affiliation(s)
- Hamza Hassan
- Department of Hematology and Medical Oncology, Boston University Medical Center, Boston, MA, USA
| | - Raphael Szalat
- Department of Hematology and Medical Oncology, Boston University Medical Center, Boston, MA, USA.,Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
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11
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Locher M, Steurer M, Jukic E, Keller MA, Fresser F, Ruepp C, Wöll E, Verdorfer I, Gastl G, Willenbacher W, Weger R, Nachbaur D, Wolf D, Gunsilius E, Zschocke J, Steiner N. The prognostic value of additional copies of 1q21 in multiple myeloma depends on the primary genetic event. Am J Hematol 2020; 95:1562-1571. [PMID: 32936982 PMCID: PMC7756645 DOI: 10.1002/ajh.25994] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 09/02/2020] [Accepted: 09/04/2020] [Indexed: 12/19/2022]
Abstract
Hyperdiploidy (HRD) and specific immunoglobulin heavy locus (IGH) translocations are primary chromosomal abnormalities (CA) in multiple myeloma (MM). In this retrospective study of 794 MM patients we aimed to investigate clinical features and common CA including gain(1q) in separate subgroups defined by primary CA. In the entire group, we confirmed that gain(1q) was associated with short time to next treatment and adverse overall survival (OS). The impact was worse for four or more copies of 1q21 as compared to three copies. However, in a subgroup of patients with clonal gain(11q) and without known primary IGH translocations (CG11q), already three copies of 1q21 were associated with a poor outcome; in the absence of gain(1q), patients in this subgroup had a remarkably long median OS of more than nine years. These cases were associated with HRD, coexpression of CD56 and CD117, male gender, and IgG subtype. In non‐CG11q patients, four or more copies of 1q21 (but not three copies) had a significant adverse impact on outcome. Several associations with CA and clinical findings were observed for the defined subgroups. As an example, we found a predominance of early tetraploidy, plasma cell leukemia, and female gender in the t(14;16) subgroup. Our results underscore the importance of subgrouping in MM.
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Affiliation(s)
- Maurus Locher
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Michael Steurer
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
| | - Emina Jukic
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Markus A. Keller
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Friedrich Fresser
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Carmen Ruepp
- Department of Internal Medicine St. Vinzenz Krankenhaus Betriebs GmbH Zams Austria
| | - Ewald Wöll
- Department of Internal Medicine St. Vinzenz Krankenhaus Betriebs GmbH Zams Austria
| | - Irmgard Verdorfer
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Günther Gastl
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
| | - Wolfgang Willenbacher
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
- ONCOTYROL ‐ Center for Personalized Cancer Medicine Innsbruck Austria
| | - Roman Weger
- ONCOTYROL ‐ Center for Personalized Cancer Medicine Innsbruck Austria
| | - David Nachbaur
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
| | - Dominik Wolf
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
- Medical Clinic 3, Oncology, Hematology, Immuno‐Oncology and Rheumatology University Hospital Bonn Bonn Germany
| | - Eberhard Gunsilius
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
| | - Johannes Zschocke
- Institute of Human Genetics Medical University of Innsbruck Innsbruck Austria
| | - Normann Steiner
- Department of Internal Medicine V Medical University of Innsbruck Innsbruck Austria
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Smadbeck J, Peterson JF, Pearce KE, Pitel BA, Figueroa AL, Timm M, Jevremovic D, Shi M, Stewart AK, Braggio E, Riggs DL, Bergsagel PL, Vasmatzis G, Kearney HM, Hoppman NL, Ketterling RP, Kumar S, Rajkumar SV, Greipp PT, Baughn LB. Mate pair sequencing outperforms fluorescence in situ hybridization in the genomic characterization of multiple myeloma. Blood Cancer J 2019; 9:103. [PMID: 31844041 PMCID: PMC6914798 DOI: 10.1038/s41408-019-0255-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 10/21/2019] [Accepted: 11/04/2019] [Indexed: 02/07/2023] Open
Abstract
Fluorescence in situ hybridization (FISH) is currently the gold-standard assay to detect recurrent genomic abnormalities of prognostic significance in multiple myeloma (MM). Since most translocations in MM involve a position effect with heterogeneous breakpoints, we hypothesize that FISH has the potential to miss translocations involving these regions. We evaluated 70 bone marrow samples from patients with plasma cell dyscrasia by FISH and whole-genome mate-pair sequencing (MPseq). Thirty cases (42.9%) displayed at least one instance of discordance between FISH and MPseq for each primary and secondary abnormality evaluated. Nine cases had abnormalities detected by FISH that went undetected by MPseq including 6 tetraploid clones and three cases with missed copy number abnormalities. In contrast, 19 cases had abnormalities detected by MPseq that went undetected by FISH. Seventeen were MYC rearrangements and two were 17p deletions. MPseq identified 36 MYC abnormalities and 17 (50.0% of MYC abnormal group with FISH results) displayed a false negative FISH result. MPseq identified 10 cases (14.3%) with IgL rearrangements, a recent marker of poor outcome, and 10% with abnormalities in genes associated with lenalidomide response or resistance. In summary, MPseq was superior in the characterization of rearrangement complexity and identification of secondary abnormalities demonstrating increased clinical value compared to FISH.
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Affiliation(s)
- James Smadbeck
- Center for Individualized Medicine-Biomarker Discovery, Mayo Clinic, Rochester, MN, USA
| | - Jess F Peterson
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Kathryn E Pearce
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Beth A Pitel
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Andrea Lebron Figueroa
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Michael Timm
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Dragan Jevremovic
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Min Shi
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - A Keith Stewart
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Esteban Braggio
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Daniel L Riggs
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - P Leif Bergsagel
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - George Vasmatzis
- Center for Individualized Medicine-Biomarker Discovery, Mayo Clinic, Rochester, MN, USA
| | - Hutton M Kearney
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Nicole L Hoppman
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Rhett P Ketterling
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Shaji Kumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - S Vincent Rajkumar
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Patricia T Greipp
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Linda B Baughn
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
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