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Giacomini A, Taranto S, Gazzaroli G, Faletti J, Capoferri D, Marcheselli R, Sciumè M, Presta M, Sacco A, Roccaro AM. The FGF/FGFR/c-Myc axis as a promising therapeutic target in multiple myeloma. J Exp Clin Cancer Res 2024; 43:294. [PMID: 39482742 PMCID: PMC11529022 DOI: 10.1186/s13046-024-03217-2] [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: 08/19/2024] [Accepted: 10/26/2024] [Indexed: 11/03/2024] Open
Abstract
Among blood cancers, multiple myeloma (MM) represents the second most common neoplasm and is characterized by the accumulation and proliferation of monoclonal plasma cells within the bone marrow. Despite the last few decades being characterized by the development of different therapeutic strategies against MM, at present such disease is still considered incurable. Although MM is highly heterogeneous in terms of genetic and molecular subtypes, about 67% of MM cases are associated with abnormal activity of the transcription factor c-Myc, which has so far revealed a protein extremely difficult to target. We have recently demonstrated that activation of fibroblast growth factor (FGF) signaling protects MM cells from oxidative stress-induced apoptosis by stabilizing the oncoprotein c-Myc. Accordingly, secretion of FGF ligands and autocrine activation of FGF receptors (FGFR) is observed in MM cells and FGFR3 genomic alterations represent some 15-20% MM cases and are associated with poor outcome. Thus, FGF/FGFR blockade may represent a promising strategy to indirectly target c-Myc in MM. On this basis, the present review aims at providing an overview of recently explored connections between the FGF/FGFR system and c-Myc oncoprotein, sustaining the therapeutic potential of targeting the FGF/FGFR/c-Myc axis in MM by using inhibitors targeting FGF ligands or FGF receptors. Importantly, the provided findings may represent the rationale for using FDA approved FGFR TK inhibitors (i.e. Pemigatinib, Futibatinib, Erdafitinib) for the treatment of MM patients presenting with an aberrant activation of this axis.
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Affiliation(s)
- Arianna Giacomini
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
| | - Sara Taranto
- Clinical Trial Center, Translational Research and Phase I Unit, ASST Spedali Civili Di Brescia, Brescia, Italy
| | - Giorgia Gazzaroli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Jessica Faletti
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Davide Capoferri
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Raffaella Marcheselli
- Clinical Trial Center, Translational Research and Phase I Unit, ASST Spedali Civili Di Brescia, Brescia, Italy
| | - Margherita Sciumè
- Clinical Trial Center, Translational Research and Phase I Unit, ASST Spedali Civili Di Brescia, Brescia, Italy
| | - Marco Presta
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Antonio Sacco
- Clinical Trial Center, Translational Research and Phase I Unit, ASST Spedali Civili Di Brescia, Brescia, Italy
| | - Aldo M Roccaro
- Clinical Trial Center, Translational Research and Phase I Unit, ASST Spedali Civili Di Brescia, Brescia, Italy.
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2
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Dupéré-Richer D, Riva A, Barwick BG, Maji S, Casellas Román H, Li J, De U, Sobh A, Quickstad G, Piper C, Kulis M, Ezponda T, Martín-Subero JI, Tonon G, Zhang W, Mitsiades CS, Boise LH, Bennett RL, Licht JD. KDM6A regulates immune response genes in multiple myeloma. Blood 2024; 144:1508-1520. [PMID: 39046770 DOI: 10.1182/blood.2024024518] [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: 03/07/2024] [Revised: 06/14/2024] [Accepted: 07/01/2024] [Indexed: 07/25/2024] Open
Abstract
ABSTRACT The histone H3 at lysine 27 (H3K27) demethylase lysine demethylase 6A (KDM6A) is a tumor suppressor in multiple cancers, including multiple myeloma (MM). We created isogenic MM cells disrupted for KDM6A and tagged the endogenous protein to facilitate genome-wide studies. KDM6A binds genes associated with immune recognition and cytokine signaling. Most importantly, KDM6A binds and activates NLRC5 and CIITA, which encode regulators of major histocompatibility complex genes. Patient data indicate that NLRC5 and CIITA are downregulated in MM with low KDM6A expression. Chromatin analysis shows that KDM6A binds poised and active enhancers and KDM6A loss led to decreased H3K27ac at enhancers, increased H3K27me3 levels in body of genes bound by KDM6A, and decreased gene expression. Reestablishing histone acetylation with an HDAC3 inhibitor leads to upregulation of major histocompatibility complex expression, offering a strategy to restore immunogenicity of KDM6A-deficient tumors. Loss of Kdm6a in Kirsten rat sarcoma virus (K-RAS)-transformed murine fibroblasts led to increased growth in vivo associated with decreased T-cell infiltration.
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Affiliation(s)
- Daphné Dupéré-Richer
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Alberto Riva
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL
| | - Benjamin G Barwick
- Department of Hematology and Medical Oncology, School of Medicine, Emory University, Winship Cancer Institute, Atlanta, GA
| | - Sayantan Maji
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Heidi Casellas Román
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL
| | - Jianping Li
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Umasankar De
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Amin Sobh
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Gabrielle Quickstad
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Crissandra Piper
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Marta Kulis
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - Teresa Ezponda
- Hemato-Oncology Department, Cima Universidad de Navarra, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, Barcelona, Spain
| | - José Ignacio Martín-Subero
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Departamento de Fundamentos Clínicos, Universitat de Barcelona, Barcelona, Spain
| | - Giovanni Tonon
- Center for Translational Genomics and Bioinformatics, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Weizhou Zhang
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | | | - Lawrence H Boise
- Department of Hematology and Medical Oncology, School of Medicine, Emory University, Winship Cancer Institute, Atlanta, GA
| | - Richard L Bennett
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
| | - Jonathan D Licht
- Division of Hematology/Oncology, University of Florida Health Cancer Center, University of Florida, Gainesville, FL
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3
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Skerget S, Penaherrera D, Chari A, Jagannath S, Siegel DS, Vij R, Orloff G, Jakubowiak A, Niesvizky R, Liles D, Berdeja J, Levy M, Wolf J, Usmani SZ, Christofferson AW, Nasser S, Aldrich JL, Legendre C, Benard B, Miller C, Turner B, Kurdoglu A, Washington M, Yellapantula V, Adkins JR, Cuyugan L, Boateng M, Helland A, Kyman S, McDonald J, Reiman R, Stephenson K, Tassone E, Blanski A, Livermore B, Kirchhoff M, Rohrer DC, D'Agostino M, Gamella M, Collison K, Stumph J, Kidd P, Donnelly A, Zaugg B, Toone M, McBride K, DeRome M, Rogers J, Craig D, Liang WS, Gutierrez NC, Jewell SD, Carpten J, Anderson KC, Cho HJ, Auclair D, Lonial S, Keats JJ. Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes. Nat Genet 2024; 56:1878-1889. [PMID: 39160255 PMCID: PMC11387199 DOI: 10.1038/s41588-024-01853-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 06/28/2024] [Indexed: 08/21/2024]
Abstract
Multiple myeloma is a treatable, but currently incurable, hematological malignancy of plasma cells characterized by diverse and complex tumor genetics for which precision medicine approaches to treatment are lacking. The Multiple Myeloma Research Foundation's Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile study ( NCT01454297 ) is a longitudinal, observational clinical study of newly diagnosed patients with multiple myeloma (n = 1,143) where tumor samples are characterized using whole-genome sequencing, whole-exome sequencing and RNA sequencing at diagnosis and progression, and clinical data are collected every 3 months. Analyses of the baseline cohort identified genes that are the target of recurrent gain-of-function and loss-of-function events. Consensus clustering identified 8 and 12 unique copy number and expression subtypes of myeloma, respectively, identifying high-risk genetic subtypes and elucidating many of the molecular underpinnings of these unique biological groups. Analysis of serial samples showed that 25.5% of patients transition to a high-risk expression subtype at progression. We observed robust expression of immunotherapy targets in this subtype, suggesting a potential therapeutic option.
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Affiliation(s)
- Sheri Skerget
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Daniel Penaherrera
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Ajai Chari
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Sundar Jagannath
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - David S Siegel
- Hackensack University Medical Center, Hackensack, NJ, USA
| | - Ravi Vij
- Division of Oncology, Washington University, St. Louis, MO, USA
| | | | | | | | - Darla Liles
- Division of Hematology/Oncology, East Carolina University, Greenville, NC, USA
| | | | - Moshe Levy
- Baylor Scott and White Research Institute, Dallas, TX, USA
| | - Jeffrey Wolf
- Department of Medicine, UCSF Medical Center, San Francisco, CA, USA
| | | | - Austin W Christofferson
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Sara Nasser
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Jessica L Aldrich
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Christophe Legendre
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Brooks Benard
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Chase Miller
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Bryce Turner
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Ahmet Kurdoglu
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Megan Washington
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Venkata Yellapantula
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Jonathan R Adkins
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Lori Cuyugan
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Martin Boateng
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Adrienne Helland
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Shari Kyman
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Jackie McDonald
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Rebecca Reiman
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Kristi Stephenson
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Erica Tassone
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | | | | | | | - Mattia D'Agostino
- Division of Hematology, AOU Città della Salute e della Scienza di Torino, University of Torino and Department of Molecular Biotechnology and Health Sciences, Torino, Italy
| | - Manuela Gamella
- Division of Hematology, AOU Città della Salute e della Scienza di Torino, University of Torino and Department of Molecular Biotechnology and Health Sciences, Torino, Italy
| | | | | | - Pam Kidd
- Spectrum Health, Grand Rapids, MI, USA
| | | | | | | | | | - Mary DeRome
- Multiple Myeloma Research Foundation, Norwalk, CT, USA
| | | | - David Craig
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Winnie S Liang
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Norma C Gutierrez
- Department of Hematology, University Hospital of Salamanca, IBSAL, Cancer Research Center-IBMCC (USAL-CSIC), CIBERONC, Salamanca, Spain
| | | | - John Carpten
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | - Hearn Jay Cho
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Multiple Myeloma Research Foundation, Norwalk, CT, USA
| | | | - Sagar Lonial
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
| | - Jonathan J Keats
- Integrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
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Vigliotta I, Solli V, Armuzzi S, Martello M, Poletti A, Taurisano B, Pistis I, Mazzocchetti G, Borsi E, Pantani L, Marzocchi G, Testoni N, Zamagni E, Terracciano M, Tononi P, Garonzi M, Ferrarini A, Manaresi N, Cavo M, Terragna C. Circulating Multiple Myeloma Cells (CMMCs) as Prognostic and Predictive Markers in Multiple Myeloma and Smouldering MM Patients. Cancers (Basel) 2024; 16:2929. [PMID: 39272787 PMCID: PMC11393854 DOI: 10.3390/cancers16172929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 08/16/2024] [Accepted: 08/21/2024] [Indexed: 09/15/2024] Open
Abstract
In recent years, liquid biopsy has emerged as a promising alternative to the bone marrow (BM) examination, since it is a minimally invasive technique allowing serial monitoring. Circulating multiple myeloma cells (CMMCs) enumerated using CELLSEARCH® were correlated with patients' prognosis and measured under treatment to assess their role in monitoring disease dynamics. Forty-four MM and seven smouldering MM (SMM) patients were studied. The CMMC medians at diagnosis were 349 (1 to 39,940) and 327 (range 22-2463) for MM and SMM, respectively. In the MM patients, the CMMC count was correlated with serum albumin, calcium, β2-microglobulin, and monoclonal components (p < 0.04). Under therapy, the CMMCs were consistently detectable in 15/40 patients (coMMstant = 1) and were undetectable or decreasing in 25/40 patients (coMMstant = 0). High-quality response rates were lower in the coMMstant = 1 group (p = 0.04), with a 7.8-fold higher risk of death (p = 0.039), suggesting that continuous CMMC release is correlated with poor responses. In four MM patients, a single-cell DNA sequencing analysis on residual CMMCs confirmed the genomic pattern of the aberrations observed in the BM samples, also highlighting the presence of emerging clones. The CMMC kinetics during treatment were used to separate the patients into two subgroups based on the coMMstant index, with different responses and survival probabilities, providing evidence that CMMC persistence is associated with a poor disease course.
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Affiliation(s)
- Ilaria Vigliotta
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
| | - Vincenza Solli
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Silvia Armuzzi
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Marina Martello
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Andrea Poletti
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Barbara Taurisano
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Ignazia Pistis
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
| | - Gaia Mazzocchetti
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Enrica Borsi
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
| | - Lucia Pantani
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
| | - Giulia Marzocchi
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Nicoletta Testoni
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Elena Zamagni
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Mario Terracciano
- Menarini Silicon Biosystems SpA, Via Giuseppe di Vittorio, Castel Maggiore, 40013 Bologna, Italy
| | - Paola Tononi
- Menarini Silicon Biosystems SpA, Via Giuseppe di Vittorio, Castel Maggiore, 40013 Bologna, Italy
| | - Marianna Garonzi
- Menarini Silicon Biosystems SpA, Via Giuseppe di Vittorio, Castel Maggiore, 40013 Bologna, Italy
| | - Alberto Ferrarini
- Menarini Silicon Biosystems SpA, Via Giuseppe di Vittorio, Castel Maggiore, 40013 Bologna, Italy
| | - Nicolò Manaresi
- Menarini Silicon Biosystems SpA, Via Giuseppe di Vittorio, Castel Maggiore, 40013 Bologna, Italy
| | - Michele Cavo
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
| | - Carolina Terragna
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia "Seràgnoli", 40138 Bologna, Italy
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Akkari Y, Baughn LB, Kim A, Karaca E, Raca G, Shao L, Mikhail FM. Section E6.1-6.6 of the American College of Medical Genetics and Genomics (ACMG) Technical Laboratory Standards: Cytogenomic studies of acquired chromosomal abnormalities in neoplastic blood, bone marrow, and lymph nodes. Genet Med 2024; 26:101054. [PMID: 38349293 DOI: 10.1016/j.gim.2023.101054] [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: 12/06/2023] [Accepted: 12/08/2023] [Indexed: 04/09/2024] Open
Abstract
Cytogenomic analyses of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes are instrumental in the clinical management of patients with hematologic neoplasms. Cytogenetic analyses assist in the diagnosis of such disorders and can provide important prognostic information. Furthermore, cytogenetic studies can provide crucial information regarding specific genetically defined subtypes of these neoplasms that may have targeted therapies. At time of relapse, cytogenetic analysis can confirm recurrence of the original neoplasm, detect clonal disease evolution, or uncover a new unrelated neoplastic process. This section deals specifically with the technical standards applicable to cytogenomic studies of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes. This updated Section E6.1-6.6 supersedes the previous Section E6 in Section E: Clinical Cytogenetics of the American College of Medical Genetics and Genomics Technical Standards for Clinical Genetics Laboratories.
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Affiliation(s)
- Yassmine Akkari
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH
| | - Linda B Baughn
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Annette Kim
- Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Ender Karaca
- Department of Pathology, Baylor University Medical Center, Dallas, TX; Texas A&M School of Medicine, Texas A&M University, Dallas, TX
| | - Gordana Raca
- Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Lina Shao
- Department of Pathology, University of Michigan, Ann Arbor, MI
| | - Fady M Mikhail
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL
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6
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Dupéré-Richer D, Riva A, Maji S, Barwick BG, Román HC, Sobh A, Quickstad G, Li J, De U, Piper C, Kulis M, Ezponda T, Martin-Subero JI, Tonon G, Zhang W, Mitsiades CS, Boise LH, Bennett RL, Licht JD. KDM6A Regulates Immune Response Genes in Multiple Myeloma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.12.579179. [PMID: 38405853 PMCID: PMC10888870 DOI: 10.1101/2024.02.12.579179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The histone H3K27 demethylase KDM6A is a tumor suppressor in multiple cancers, including multiple myeloma (MM). We created isogenic MM cells disrupted for KDM6A and tagged the endogenous protein to facilitate genome wide studies. KDM6A binds genes associated with immune recognition and cytokine signaling. Most importantly, KDM6A binds and activates NLRC5 and CIITA encoding regulators of Major Histocompatibility Complex (MHC) genes. Patient data indicate that NLRC5 and CIITA, are downregulated in MM with low KDM6A expression. Chromatin analysis shows that KDM6A binds poised and active enhancers and KDM6A loss led to decreased H3K27ac at enhancers, increased H3K27me3 levels in body of genes bound by KDM6A and decreased gene expression. Reestablishing histone acetylation with an HDAC3 inhibitor leads to upregulation of MHC expression, offering a strategy to restore immunogenicity of KDM6A deficient tumors. Loss of Kdm6a in murine RAS-transformed fibroblasts led to increased growth in vivo associated with decreased T cell infiltration. Statement of significance We show that KDM6A participates in immune recognition of myeloma tumor cells by directly regulating the expression of the master regulators of MHC-I and II, NLRC5 and CIITA. The expression of these regulators can by rescued by the HDAC3 inhibitors in KDM6A-null cell lines.
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7
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Camuset M, Le Calvez B, Theisen O, Godon C, Grain A, Thomas C, Couec M, Béné MC, Rialland F, Eveillard M. Added value of molecular karyotype in childhood acute lymphoblastic leukemia. CANCER INNOVATION 2023; 2:513-523. [PMID: 38125768 PMCID: PMC10730002 DOI: 10.1002/cai2.67] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 03/02/2023] [Indexed: 12/23/2023]
Abstract
Background Thanks to an improved therapeutic regimen in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL), 5 year-overall survival now exceeds 90%. Unfortunately, the 25% of children who relapse have an initial poor prognosis, potentially driven by pre-existing or emerging molecular anomalies. The latter are initially and essentially identified by cytogenetics. However, some subtle alterations are not visible through karyotyping. Methods Single nucleotide polymorphisms (SNP) array is an alternative way of chromosomal analysis allowing for a more in-depth evaluation of chromosomal modifications such as the assessment of copy number alterations (CNA) and loss of heterozygosity (LOH). This method was applied here in retrospective diagnosis/relapse paired samples from seven children with BCP-ALL and in a prospective cohort of 38 newly diagnosed childhood cases. Results In the matched study, compared to the initial karyotype, SNP array analysis reclassified two patients as poor prognosis cases. Modulation during relapse was seen for 4 CNA and 0.9 LOH. In the prospective study, SNP reclassified the 10 patients with intermediate karyotype as 7 good prognosis and 3 poor prognosis. Ultimately, in all the children tested, SNP array allowed to identify additional anomalies compared to conventional karyotype, refine its prognostic value and identify some druggable anomalies that could be used for precision medicine. Overall, the anomalies detected could be segregated in four groups respectively involved in B-cell development, cell proliferation, transcription and molecular pathways. Conclusion SNP therefore appears to be a method of choice in the integrated diagnosis of BCP ALL, especially for patients initially classified as intermediate prognosis. This complementary method of both cytogenetics and high throughput sequencing allows to obtain further classified information and can be useful in case of failure of these techniques.
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Affiliation(s)
- Margaux Camuset
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Baptiste Le Calvez
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Olivier Theisen
- Hematology Biology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Catherine Godon
- Hematology Biology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Audrey Grain
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Caroline Thomas
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Marie‐Laure Couec
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Marie C. Béné
- Hematology Biology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Fanny Rialland
- Pediatric Oncology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
| | - Marion Eveillard
- Hematology Biology, CHU Nantes, Nantes UniversitéUniv Angers, INSERM, CNRS, CRCI2NANantesFrance
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Liu DD, Muliaditan D, Viswanathan R, Cui X, Cheow LF. Melt-Encoded-Tags for Expanded Optical Readout in Digital PCR (METEOR-dPCR) Enables Highly Multiplexed Quantitative Gene Panel Profiling. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301630. [PMID: 37485651 PMCID: PMC10520687 DOI: 10.1002/advs.202301630] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/27/2023] [Indexed: 07/25/2023]
Abstract
Digital PCR (dPCR) is an important tool for precise nucleic acid quantification in clinical setting, but the limited multiplexing capability restricts its applications for quantitative gene panel profiling. Here, this work describes melt-encoded-tags for expanded optical readout in digital PCR (METEOR-dPCR), a simple two-step assay that enables simultaneous quantification of a large panel of arbitrary genes in a dPCR platform. Target genes are quantitatively converted into DNA tags with unique melting temperatures through a ligation approach. These tags are then counted and distinguished by their melt-curve profiles on a dPCR platform. A multiplexing capacity of M^N, where M is the number of resolvable melting temperature and N is the number of fluorescence channel, can be achieved. This work validates METEOR-dPCR with simultaneous DNA copy number profiling of 60 targets using dPCR in cancer cells, and demonstrates its sensitivity for estimating tumor fraction in mixed tumor and normal DNA samples. The rapid, quantitative, and highly multiplexed METEOR-dPCR assay will have wide appeal for many clinical applications.
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Affiliation(s)
- Dong Dong Liu
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
| | - Daniel Muliaditan
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
- Genome institute of SingaporeAgency for ScienceTechnology and ResearchSingapore138672Singapore
| | - Ramya Viswanathan
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Xu Cui
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
| | - Lih Feng Cheow
- Institute for Health Innovation and TechnologyNational University of SingaporeSingapore117599Singapore
- Department of Biomedical EngineeringFaculty of EngineeringNational University of SingaporeSingapore117583Singapore
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9
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Flietner E, Yu M, Poudel G, Veltri AJ, Zhou Y, Rajagopalan A, Feng Y, Lasho T, Wen Z, Sun Y, Patnaik MM, Callander NS, Asimakopoulos F, Wang D, Zhang J. Molecular characterization stratifies VQ myeloma cells into two clusters with distinct risk signatures and drug responses. Oncogene 2023; 42:1751-1762. [PMID: 37031341 PMCID: PMC10367583 DOI: 10.1038/s41388-023-02684-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 03/22/2023] [Accepted: 03/24/2023] [Indexed: 04/10/2023]
Abstract
Multiple myeloma (MM) is a cancer of malignant plasma cells in the bone marrow and extramedullary sites. We previously characterized a VQ model for human high-risk MM. The various VQ lines display different disease phenotypes and survival rates, suggesting significant intra-model variation. Here, we use whole-exome sequencing and copy number variation (CNV) analysis coupled with RNA-Seq to stratify the VQ lines into corresponding clusters: Group A cells had monosomy chromosome (chr) 5 and overexpressed genes and pathways associated with sensitivity to bortezomib (Btz) treatment in human MM patients. By contrast, Group B VQ cells carried recurrent amplification (Amp) of chr3 and displayed high-risk MM features, including downregulation of Fam46c, upregulation of cancer growth pathways associated with functional high-risk MM, and expression of Amp1q and high-risk UAMS-70 and EMC-92 gene signatures. Consistently, in sharp contrast to Group A VQ cells that showed short-term response to Btz, Group B VQ cells were de novo resistant to Btz in vivo. Our study highlights Group B VQ lines as highly representative of the human MM subset with ultrahigh risk.
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Affiliation(s)
- Evan Flietner
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Pathology and Laboratory Medicine, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Mei Yu
- Versiti Blood Research Institute, Milwaukee, WI, 53226, USA
| | - Govinda Poudel
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Yun Zhou
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Adhithi Rajagopalan
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Yubin Feng
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Terra Lasho
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55902, USA
| | - Zhi Wen
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA
| | - Yuqian Sun
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Mrinal M Patnaik
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55902, USA
| | - Natalie S Callander
- Division of Hematology/Oncology, Department of Medicine, UW Comprehensive Cancer Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Fotis Asimakopoulos
- Division of Blood and Marrow Transplantation, Department of Medicine and Moores Cancer Center, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Demin Wang
- Versiti Blood Research Institute, Milwaukee, WI, 53226, USA.
| | - Jing Zhang
- McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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10
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Li T, Yao L, Hua Y, Wu Q. Comprehensive analysis of prognosis of cuproptosis-related oxidative stress genes in multiple myeloma. Front Genet 2023; 14:1100170. [PMID: 37065484 PMCID: PMC10102368 DOI: 10.3389/fgene.2023.1100170] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/21/2023] [Indexed: 04/03/2023] Open
Abstract
Introduction: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy. The patients’ survival outcomes vary widely. Establishing a more accurate prognostic model is necessary to improve prognostic precision and guide clinical therapy.Methods: We developed an eight-gene model to assess the prognostic outcome of MM patients. Univariate Cox analysis, Least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses were used to identify the significant genes and construct the model. Other independent databases were used to validate the model.Results: The results showed that the overall survival of patients in the high-risk group was signifificantly shorter compared with that of those in the low-risk group. The eight-gene model demonstrated high accuracy and reliability in predicting the prognosis of MM patients.Discussion: Our study provides a novel prognostic model for MM patients based on cuproptosis and oxidative stress. The eight-gene model can provide valid predictions for prognosis and guide personalized clinical treatment. Further studies are needed to validate the clinical utility of the model and explore potential therapeutic targets.
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11
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Winkler W, Farré Díaz C, Blanc E, Napieczynska H, Langner P, Werner M, Walter B, Wollert-Wulf B, Yasuda T, Heuser A, Beule D, Mathas S, Anagnostopoulos I, Rosenwald A, Rajewsky K, Janz M. Mouse models of human multiple myeloma subgroups. Proc Natl Acad Sci U S A 2023; 120:e2219439120. [PMID: 36853944 PMCID: PMC10013859 DOI: 10.1073/pnas.2219439120] [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: 11/17/2022] [Accepted: 01/26/2023] [Indexed: 03/01/2023] Open
Abstract
Multiple myeloma (MM), a tumor of germinal center (GC)-experienced plasma cells, comprises distinct genetic subgroups, such as the t(11;14)/CCND1 and the t(4;14)/MMSET subtype. We have generated genetically defined, subgroup-specific MM models by the GC B cell-specific coactivation of mouse Ccnd1 or MMSET with a constitutively active Ikk2 mutant, mimicking the secondary NF-κB activation frequently seen in human MM. Ccnd1/Ikk2ca and MMSET/Ikk2ca mice developed a pronounced, clonally restricted plasma cell outgrowth with age, accompanied by serum M spikes, bone marrow insufficiency, and bone lesions. The transgenic plasma cells could be propagated in vivo and showed distinct transcriptional profiles, resembling their human MM counterparts. Thus, we show that targeting the expression of genes involved in MM subgroup-specific chromosomal translocations into mouse GC B cells translates into distinct MM-like diseases that recapitulate key features of the human tumors, opening the way to a better understanding of the pathogenesis and therapeutic vulnerabilities of different MM subgroups.
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Affiliation(s)
- Wiebke Winkler
- Immune Regulation and Cancer, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Carlota Farré Díaz
- Immune Regulation and Cancer, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Eric Blanc
- Core Unit Bioinformatics, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin10117, Germany
| | - Hanna Napieczynska
- Animal Phenotyping, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
| | - Patrick Langner
- Animal Phenotyping, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
| | - Marvin Werner
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Barbara Walter
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Brigitte Wollert-Wulf
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Tomoharu Yasuda
- Immune Regulation and Cancer, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
| | - Arnd Heuser
- Animal Phenotyping, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
| | - Dieter Beule
- Core Unit Bioinformatics, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin10117, Germany
| | - Stephan Mathas
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
| | - Ioannis Anagnostopoulos
- Institute of Pathology, Universität Würzburg and Comprehensive Cancer Centre Mainfranken, Würzburg97080, Germany
| | - Andreas Rosenwald
- Institute of Pathology, Universität Würzburg and Comprehensive Cancer Centre Mainfranken, Würzburg97080, Germany
| | - Klaus Rajewsky
- Immune Regulation and Cancer, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
| | - Martin Janz
- Biology of Malignant Lymphomas, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin13125, Germany
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité – Universitätsmedizin Berlin, Berlin13125, Germany
- Hematology, Oncology and Cancer Immunology, Charité – Universitätsmedizin Berlin, Berlin13125, Germany
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12
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Jakubikova J, Cholujova D, Beke G, Hideshima T, Klucar L, Leiba M, Jamroziak K, Richardson PG, Kastritis E, Dorfman DM, Anderson KC. Heterogeneity of B cell lymphopoiesis in patients with premalignant and active myeloma. JCI Insight 2023; 8:159924. [PMID: 36752202 PMCID: PMC9977435 DOI: 10.1172/jci.insight.159924] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 12/15/2022] [Indexed: 02/09/2023] Open
Abstract
To better characterize the heterogeneity of multiple myeloma (MM), we profiled plasma cells (PCs) and their B cell lymphopoiesis in the BM samples from patients with monoclonal gammopathy of undetermined significance, smoldering MM, and active MM by mass cytometry (CyTOF) analysis. Characterization of intra- and interneoplastic heterogeneity of malignant plasmablasts and PCs revealed overexpression of the MM SET domain (MMSET), Notch-1, and CD47. Variations in upregulation of B cell signaling regulators (IFN regulatory factor 4 [IRF-4], CXCR4, B cell lymphoma 6 [Bcl-6], c-Myc, myeloid differentiation primary response protein 88 [MYD88], and spliced X box-binding protein 1 [sXBP-1]) and aberrant markers (CD319, CD269, CD200, CD117, CD56, and CD28) were associated with different clinical outcomes in clonal PC subsets. In addition, prognosis was related to heterogeneity in subclonal expression of stemness markers, including neuroepithelial stem cell protein (Nestin), SRY-box transcription factor 2 (Sox2), Krüppel-like factor 4 (KLF-4), and Nanog. Furthermore, we have defined significantly elevated levels of MMSET, MYD88, c-Myc, CD243, Notch-1, and CD47 from hematopoietic stem cells to PCs in myeloma B cell lymphopoiesis, noted even in premalignant conditions, with variably modulated expression of B cell development regulators, including IRF-4, Bcl-2, Bcl-6, and sXBP-1; aberrant PC markers (such as CD52, CD44, CD200, CD81, CD269, CD117, and CXCR4); and stemness-controlling regulators, including Nanog, KLF-4, octamer-binding transcription factor 3/4 (Oct3/4), Sox2, and retinoic acid receptor α2 (RARα2). This study provides the rationale for precise molecular profiling of patients with MM by CyTOF technology to define disease heterogeneity and prognosis.
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Affiliation(s)
- Jana Jakubikova
- Dana-Farber Cancer Institute, Department of Medical Oncology, Jerome Lipper Multiple Myeloma Center, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Department of Tumor Immunology, Cancer Research Institute, Biomedical Research Center,,Centre for Advanced Materials Application, and
| | - Danka Cholujova
- Department of Tumor Immunology, Cancer Research Institute, Biomedical Research Center,,Centre for Advanced Materials Application, and
| | - Gabor Beke
- Institute of Molecular Biology, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Teru Hideshima
- Dana-Farber Cancer Institute, Department of Medical Oncology, Jerome Lipper Multiple Myeloma Center, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Lubos Klucar
- Institute of Molecular Biology, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Merav Leiba
- Department of Hematology, Samson Assuta Ashdod University Hospital, Ashdod, Israel.,Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Krzysztof Jamroziak
- Department of Hematology, Transplantation and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
| | - Paul G. Richardson
- Dana-Farber Cancer Institute, Department of Medical Oncology, Jerome Lipper Multiple Myeloma Center, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Efstathios Kastritis
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - David M. Dorfman
- Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Kenneth C. Anderson
- Dana-Farber Cancer Institute, Department of Medical Oncology, Jerome Lipper Multiple Myeloma Center, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
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13
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Cholujova D, Koklesova L, Lukacova Bujnakova Z, Dutkova E, Valuskova Z, Beblava P, Matisova A, Sedlak J, Jakubikova J. In vitro and ex vivo anti-myeloma effects of nanocomposite As 4S 4/ZnS/Fe 3O 4. Sci Rep 2022; 12:17961. [PMID: 36289430 PMCID: PMC9606304 DOI: 10.1038/s41598-022-22672-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 10/18/2022] [Indexed: 02/06/2023] Open
Abstract
Nanoparticles in medicine can integrate actively targeted imaging agents and drug delivery vehicles, and combining multiple types of therapeutics in a single particle has numerous advantages, especially in multiple myeloma. MM is an incurable hematological disorder characterized by clonal proliferation of plasma cells in the bone marrow. In this study, we evaluated the anti-myeloma activity of 3 nanocomposites (3NPs): As4S4/ZnS/Fe3O4 (1:4:1), As4S4/ZnS/Fe3O4 with folic acid (FA), and As4S4/ZnS/Fe3O4 with FA and albumin with reduced survival MM cell lines and primary MM samples by each of 3NP. Cytotoxic effects of 3NPs were associated with caspase- and mitochondria-dependent apoptosis induction and reduced c-Myc expression. Modulation of cell cycle regulators, such as p-ATM/ATM and p-ATR/ATR, and increases in p-Chk2, cyclin B1, and histones were accompanied by G2/M arrest triggered by 3NPs. In addition, 3NPs activated several myeloma-related signaling, including JNK1/2/3, ERK1/2 and mTOR. To overcome BM microenvironment-mediated drug resistance, nanocomposites retained its anti-MM activity in the presence of stroma. 3NPs significantly decreased the stem cell-like side population in MM cells, even in the context of stroma. We observed strong synergistic effects of 3NPs combined with lenalidomide, pomalidomide, or melphalan, suggesting the potential of these combinations for future clinical studies.
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Affiliation(s)
- Danka Cholujova
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia ,grid.419303.c0000 0001 2180 9405Centre for Advanced Materials Application, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84511 Slovakia
| | - Lenka Koklesova
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia ,grid.7634.60000000109409708Department of Obstetrics and Gynecology, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, 03601 Slovakia
| | - Zdenka Lukacova Bujnakova
- grid.419303.c0000 0001 2180 9405Department of Mechanochemistry, Institute of Geotechnics, Slovak Academy of Sciences, Watsonova 45, Košice, 04001 Slovakia
| | - Erika Dutkova
- grid.419303.c0000 0001 2180 9405Department of Mechanochemistry, Institute of Geotechnics, Slovak Academy of Sciences, Watsonova 45, Košice, 04001 Slovakia
| | - Zuzana Valuskova
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia
| | - Patricia Beblava
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia
| | - Anna Matisova
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia
| | - Jan Sedlak
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia
| | - Jana Jakubikova
- grid.420087.90000 0001 2106 1943Department of Tumor Immunology, Biomedical Research Center, Cancer Research Institute, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84505 Slovakia ,grid.419303.c0000 0001 2180 9405Centre for Advanced Materials Application, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84511 Slovakia
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14
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Aarabi M, Yoest JM, Farah R, Rajkovic A, Swerdlow SH, Yatsenko SA. A Novel Integrated Approach for Cytogenomic Evaluation of Plasma Cell Neoplasms. J Mol Diagn 2022; 24:1067-1078. [PMID: 35940519 DOI: 10.1016/j.jmoldx.2022.07.002] [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: 03/26/2022] [Revised: 06/24/2022] [Accepted: 07/19/2022] [Indexed: 12/29/2022] Open
Abstract
Plasma cell neoplasm (PCN) is associated with characteristic chromosomal aberrations of diagnostic and prognostic significance. The presence of a small percentage of neoplastic cells is a drawback in the application of karyotyping and fluorescence in situ hybridization for the evaluation of bone marrow aspirate. The analysis of samples enriched for CD138+ cells has improved the detection rate. However, fluorescence in situ hybridization requires several probes and may not be completed due to a limited number of isolated cells. To address the issues experienced with the conventional approach, a novel integrated protocol that consists of whole-genome amplification of DNA isolated from CD138+ cells, followed by microarray as well as one fluorescence in situ hybridization assay for balanced IGH gene rearrangements, has been developed. In the present study in a cohort of 56 patients with clinical suspicion for PCN, compared to conventional cytogenetic analysis, this approach provided higher yield in the detection of PCN-related abnormalities, irrespective of the initial percentage of plasma cells. Whole-genome profiling uncovered recurrent chromosomal abnormalities of prognostic value, including unbalanced alterations within the MYC locus, 16q loss, and hypodiploidy, that were not otherwise detectable by conventional methods. The proposed approach is cost-efficient and provides a superior detection rate, required for proper risk stratification and differential diagnosis of PCN regardless of initial plasma cell percentage.
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Affiliation(s)
- Mahmoud Aarabi
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jennifer M Yoest
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Rafic Farah
- Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Aleksandar Rajkovic
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Pathology, University of California-San Francisco, San Francisco, California; Department of Obstetrics, Gynecology and Reproductive Sciences, University of California-San Francisco, San Francisco, California; Institute of Human Genetics, University of California-San Francisco, San Francisco, California
| | - Steven H Swerdlow
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Svetlana A Yatsenko
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania.
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15
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Ayna Duran G, Benderli Cihan Y. Autophagy-related genes affect the survival of multiple myeloma patients depending on chromosomal abnormality. ASIAN BIOMED 2022; 16:249-264. [PMID: 37551318 PMCID: PMC10321186 DOI: 10.2478/abm-2022-0028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
Background Targeting autophagy at gene level may be promising in multiple myeloma (MM) treatment depending on chromosomal abnormality (ABN) status. Objectives We aimed to investigate the role of ABN on survival of MM patients and to identify prognosis related autophagy-related genes (ARGs) for patients with or without ABN. Methods Gene intensity values of 222 ARG for 548 MM patients were obtained from the Affymetrix Human Genome U133 Plus 2.0 Array (GPL570) platform containing 54,675 probes (GSE24080). A dataset containing data from 1576 MM patients with 1q21 amplification (GSE4204, GSE4452, GSE4581, and GSE2658) was used for validation. Survival analysis of the patients was analyzed using univariate and multivariate Cox regression method with the help of R3.53 programming language and Kaplan-Meier graphics were created. The Gene Ontology enRIchmentanaLysis and visuaLizAtion (GOrilla) tool was used to define the related biological processes and pathways. Results The overall survival (OS) and event-free survival (EFS) in all MM patients were strongly influenced by ABN. In the group of patients with ABN, 41 ARGs were found to be important in prognosis, whereas in the group of patients without ABN, 13 ARGs were found to be important in prognosis. CDKN1A, FKBP1B, FOXO3, and NCKAP1 ARGs were commonly significant in both groups and found to be survival triggering. Conclusions The classification of MM patients according to the absence or presence of ABN is important in the determination of survival status. Detection of survival related ARGs in patients with chromosomal anomalies may be a new therapeutic target in treatment.
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Affiliation(s)
- Gizem Ayna Duran
- Department of Biomedical Engineering, Faculty of Engineering, Izmir University of Economics, Balçova, İzmir35330, Turkey
| | - Yasemin Benderli Cihan
- Department of Radiation Oncology, Kayseri City Education and Research Hospital, Kocasinan, Kayseri38080, Turkey
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16
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Kaur G, Jena L, Gupta R, Farswan A, Gupta A, Sriram K. Correlation of changes in subclonal architecture with progression in the MMRF CoMMpass study. Transl Oncol 2022; 23:101472. [PMID: 35777247 PMCID: PMC9253848 DOI: 10.1016/j.tranon.2022.101472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 06/03/2022] [Accepted: 06/20/2022] [Indexed: 11/28/2022] Open
Abstract
Multiple myeloma (MM) is a heterogeneous plasma cell proliferative disorder that arises from its premalignant precursor stages through a complex cascade of interactions between clonal mutations and co-evolving microenvironment. The temporo-spatial evolutionary trajectories of MM are established early during myelomatogenesis in precursor stages and retained in MM. Such molecular events impact subsequent disease progression and clinical outcomes. Identification of clonal sweeps of actionable gene targets in MM could reveal potential vulnerabilities that may exist in early stages and thus potentiate prognostication and customization of early therapeutic interventions. We have evaluated clonal evolution at multiple time points in 76 MM patients enrolled in the MMRF CoMMpass study. The major findings of this study are (a) MM progresses predominantly through branching evolution, (b) there is a heterogeneous spectrum of mutational landscapes that include unique actionable gene targets at diagnosis compared to progression, (c) unique clonal gains/ losses of mutant driver genes can be identified in patients with different cytogenetic aberrations, (d) there is a significant correlation between co-occurring oncogenic mutations/ co-occurring subclones e.g., with mutated TP53+SYNE1, NRAS+MAGI3, and anticorrelative dependencies between FAT3+FCGBP gene pairs. Such co-trajectories may synchronize molecular events of drug response, myelomatogenesis and warrant future studies to explore their potential for early prognostication and development of risk stratified personalized therapies in MM.
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Affiliation(s)
- Gurvinder Kaur
- Laboratory Oncology Unit, Dr. B. R.A. IRCH, AIIMS, New Delhi
| | - Lingaraja Jena
- Laboratory Oncology Unit, Dr. B. R.A. IRCH, AIIMS, New Delhi
| | - Ritu Gupta
- Laboratory Oncology Unit, Dr. B. R.A. IRCH, AIIMS, New Delhi.
| | - Akanksha Farswan
- SBILab, Department of Electronics and Communication Engineering, IIIT, Delhi
| | - Anubha Gupta
- SBILab, Department of Electronics and Communication Engineering, IIIT, Delhi.
| | - K Sriram
- Department of Computational Biology & Centre for Computational Biology, IIIT, Delhi
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17
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Hergott CB, Kim AS. Molecular Diagnostic Testing for Hematopoietic Neoplasms: Linking Pathogenic Drivers to Personalized Diagnosis. Clin Lab Med 2022; 42:325-347. [PMID: 36150815 DOI: 10.1016/j.cll.2022.04.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Molecular diagnostics inhabit an increasingly central role in characterizing hematopoietic malignancies. This brief review summarizes the genomic targets important for many major categories of hematopoietic neoplasia by focusing on disease pathogenesis. In myeloid disease, recurrent mutations in key functional classes drive clonal hematopoiesis, on which additional variants can specify clinical presentation and accelerate progression. Lymphoblastic leukemias are frequently initiated by oncogenic fusions that block lymphoid maturation while, in concert with additional mutations, driving proliferation. The links between genetic aberrations and lymphoma patient outcomes have been clarified substantially through the clustering of genomic profiles. Finally, the addition of next-generation sequencing strategies to cytogenetics is refining risk stratification for plasma cell myeloma. In all categories, molecular diagnostics shed light on the unique mechanistic underpinnings of each individual malignancy, thereby empowering more rational, personalized care for these patients.
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Affiliation(s)
- Christopher B Hergott
- Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Annette S Kim
- Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.
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18
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Saadoune C, Nouadi B, Hamdaoui H, Chegdani F, Bennis F. Multiple Myeloma: Bioinformatic Analysis for Identification of Key Genes and Pathways. Bioinform Biol Insights 2022; 16:11779322221115545. [PMID: 35958298 PMCID: PMC9358573 DOI: 10.1177/11779322221115545] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 06/26/2022] [Indexed: 01/02/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy in which monoclonal plasma cells multiply in the bone marrow and monoclonal immunoglobulins are overproduced in older people. Several molecular and cytogenetic advances allow scientists to identify several genetic and chromosomal abnormalities that cause the disease. The comprehension of the pathophysiology of MM requires an understanding of the characteristics of malignant clones and the changes in the bone marrow microenvironment. This study aims to identify the central genes and to determine the key signaling pathways in MM by in silico approaches. A list of 114 differentially expressed genes (DEGs) is important in the prognosis of MM. The DEGs are collected from scientific publications and databases (https://www.ncbi.nlm.nih.gov/). These data are analyzed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software (https://string-db.org/) through the construction of protein-protein interaction (PPI) networks and enrichment analysis of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, by CytoHubba, AutoAnnotate, Bingo Apps plugins in Cytoscape software (https://cytoscape.org/) and by DAVID database (https://david.ncifcrf.gov/). The analysis of the results shows that there are 7 core genes, including TP53; MYC; CDND1; IL6; UBA52; EZH2, and MDM2. These top genes appear to play a role in the promotion and progression of MM. According to functional enrichment analysis, these genes are mainly involved in the following signaling pathways: Epstein-Barr virus infection, microRNA pathway, PI3K-Akt signaling pathway, and p53 signaling pathway. Several crucial genes, including TP53, MYC, CDND1, IL6, UBA52, EZH2, and MDM2, are significantly correlated with MM, which may exert their role in the onset and evolution of MM.
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Affiliation(s)
- Chaimaa Saadoune
- Laboratory of Immunology and Biodiversity, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Casablanca, Morocco
| | - Badreddine Nouadi
- Laboratory of Immunology and Biodiversity, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Casablanca, Morocco
| | - Hasna Hamdaoui
- Laboratory of Immunology and Biodiversity, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Casablanca, Morocco.,Laboratory of Medical Genetics, University Hospital Center Tangier-Tetouan-Al Hoceima, Tangier, Morocco
| | - Fatima Chegdani
- Laboratory of Immunology and Biodiversity, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Casablanca, Morocco
| | - Faiza Bennis
- Laboratory of Immunology and Biodiversity, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Casablanca, Morocco
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19
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Sklavenitis-Pistofidis R, Getz G, Ghobrial I, Papaioannou M. Multiple Myeloma With Amplification of Chr1q: Therapeutic Opportunity and Challenges. Front Oncol 2022; 12:961421. [PMID: 35912171 PMCID: PMC9331166 DOI: 10.3389/fonc.2022.961421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Multiple myeloma (MM) is an incurable plasma cell malignancy with a heterogeneous genetic background. Each MM subtype may have its own therapeutic vulnerabilities, and tailored therapy could improve outcomes. However, the cumulative frequency of druggable targets across patients is very low, which has precluded the widespread adoption of precision therapy for patients with MM. Amplification of the long arm of chromosome 1 (Amp1q) is one of the most frequent genetic alterations observed in patients with MM, and its presence predicts inferior outcomes in the era of proteasome inhibitors and immunomodulatory agents. Therefore, establishing precision medicine for MM patients with Amp1q stands to benefit a large portion of patients who are otherwise at higher risk of relapse. In this article, we review the prevalence and clinical significance of Amp1q in patients with MM, its pathogenesis and therapeutic vulnerabilities, and discuss the opportunities and challenges for Amp1q-targeted therapy.
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Affiliation(s)
- Romanos Sklavenitis-Pistofidis
- Harvard Medical School, Boston, MA, United States
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, United States
- Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Gad Getz
- Harvard Medical School, Boston, MA, United States
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, United States
- Department of Pathology, Massachusetts General Hospital, Boston, MA, United States
| | - Irene Ghobrial
- Harvard Medical School, Boston, MA, United States
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, United States
| | - Maria Papaioannou
- Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Hematology Unit, 1st Internal Medicine Department, AHEPA University Hospital, Thessaloniki, Greece
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20
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Mazzocchetti G, Poletti A, Solli V, Borsi E, Martello M, Vigliotta I, Armuzzi S, Taurisano B, Zamagni E, Cavo M, Terragna C. BoBafit: a copy number clustering tool designed to refit and recalibrate the baseline region of tumors’ profiles. Comput Struct Biotechnol J 2022; 20:3718-3728. [PMID: 35891790 PMCID: PMC9294200 DOI: 10.1016/j.csbj.2022.06.062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 11/16/2022] Open
Abstract
Tools generating CN profiles derive the baseline region from samples’ median CN signal. This canonical approach might cause wrongly estimated CN profile in complex karyotypes. CNAs call is crucial for patients’ risk stratification aimed at personalized treatment. BoBafit computes the correct baseline region and the CN profile, taking into account tumor genomic complexity and samples-specific alterations. BoBafit should be implemented within CN analysis pipelines especially for clinical aims.
Human cancer arises from a population of cells that have acquired a wide range of genetic alterations, most of which are targets of therapeutic treatments or are used as prognostic factors for patient’s risk stratification. Among these, copy number alterations (CNAs) are quite frequent. Currently, several molecular biology technologies, such as microarrays, NGS and single-cell approaches are used to define the genomic profile of tumor samples. Output data need to be analyzed with bioinformatic approaches and particularly by employing computational algorithms. Molecular biology tools estimate the baseline region by comparing either the mean probe signals, or the number of reads to the reference genome. However, when tumors display complex karyotypes, this type of approach could fail the baseline region estimation and consequently cause errors in the CNAs call. To overcome this issue, we designed an R-package, BoBafit, able to check and, eventually, to adjust the baseline region, according to both the tumor-specific alterations’ context and the sample-specific clustered genomic lesions. Several databases have been chosen to set up and validate the designed package, thus demonstrating the potential of BoBafit to adjust copy number (CN) data from different tumors and analysis techniques. Relevantly, the analysis highlighted that up to 25% of samples need a baseline region adjustment and a redefinition of CNAs calls, thus causing a change in the prognostic risk classification of the patients. We support the implementation of BoBafit within CN analysis bioinformatics pipelines to ensure a correct patient’s stratification in risk categories, regardless of the tumor type.
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21
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Alberge JB, Kraeber-Bodéré F, Jamet B, Touzeau C, Caillon H, Wuilleme S, Béné MC, Kampfenkel T, Sonneveld P, van Duin M, Avet-Loiseau H, Corre J, Magrangeas F, Carlier T, Bodet-Milin C, Chérel M, Moreau P, Minvielle S, Bailly C. Molecular Signature of 18F-FDG PET Biomarkers in Newly Diagnosed Multiple Myeloma Patients: A Genome-Wide Transcriptome Analysis from the CASSIOPET Study. J Nucl Med 2022; 63:1008-1013. [PMID: 35086897 PMCID: PMC9258580 DOI: 10.2967/jnumed.121.262884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/14/2021] [Indexed: 01/03/2023] Open
Abstract
The International Myeloma Working Group recently fully incorporated 18F-FDG PET into multiple myeloma (MM) diagnosis and response evaluation. Moreover, a few studies demonstrated the prognostic value of several biomarkers extracted from this imaging at baseline. Before these 18F-FDG PET biomarkers could be fully endorsed as risk classifiers by the hematologist community, further characterization of underlying molecular aspects was necessary. Methods: Reported prognostic biomarkers (18F-FDG avidity, SUVmax, number of focal lesions, presence of paramedullary disease [PMD] or extramedullary disease) were extracted from 18F-FDG PET imaging at baseline in a group of 139 patients from CASSIOPET, a companion study of the CASSIOPEIA cohort (ClinicalTrials.gov identifier NCT02541383). Transcriptomic analyses using RNA sequencing were realized on sorted bone marrow plasma cells from the same patients. An association with a high-risk gene expression signature (IFM15), molecular classification, progression-free survival, a stringent clinical response, and minimal residual disease negativity were explored. Results:18F-FDG PET results were positive in 79.4% of patients; 14% and 11% of them had PMD and extramedullary disease, respectively. Negative 18F-FDG PET results were associated with lower levels of expression of hexokinase 2 (HK2) (fold change, 2.1; adjusted P = 0.04) and showed enrichment for a subgroup of patients with a low level of bone disease. Positive 18F-FDG PET results displayed 2 distinct signatures: either high levels of expression of proliferation genes or high levels of expression of GLUT5 and lymphocyte antigens. PMD and IFM15 were independently associated with a lower level of progression-free survival, and the presence of both biomarkers defined a group of "double-positive" patients at very high risk of progression. PMD and IFM15 were related neither to minimal residual disease assessment nor to a stringent clinical response. Conclusion: Our study confirmed and extended the association between imaging biomarkers and transcriptomic programs in MM. The combined prognostic value of PMD and a high-risk IFM15 signature may help define MM patients with a very high risk of progression.
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Affiliation(s)
- Jean-Baptiste Alberge
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France
| | - Françoise Kraeber-Bodéré
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, University Hospital, Nantes, France;,Nuclear Medicine Unit, ICO-Gauducheau, Nantes-Saint-Herblain, France;,Haematology Department, University Hospital, Nantes, France
| | - Bastien Jamet
- Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, University Hospital, Nantes, France
| | - Cyrille Touzeau
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Haematology Department, University Hospital, Nantes, France
| | - Hélène Caillon
- Haematology Department, University Hospital, Nantes, France
| | | | | | | | - Pieter Sonneveld
- Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands; and
| | - Mark van Duin
- Erasmus University Medical Center Cancer Institute, Rotterdam, The Netherlands; and
| | - Herve Avet-Loiseau
- Unité de Génomique du Myélome, Institut Universitaire du Cancer de Toulouse, Institut National de la Santé, Oncopole, Toulouse, France
| | - Jill Corre
- Unité de Génomique du Myélome, Institut Universitaire du Cancer de Toulouse, Institut National de la Santé, Oncopole, Toulouse, France
| | - Florence Magrangeas
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Haematology Department, University Hospital, Nantes, France
| | - Thomas Carlier
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, University Hospital, Nantes, France
| | - Caroline Bodet-Milin
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, University Hospital, Nantes, France
| | - Michel Chérel
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, ICO-Gauducheau, Nantes-Saint-Herblain, France
| | - Philippe Moreau
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Haematology Department, University Hospital, Nantes, France
| | - Stéphane Minvielle
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Haematology Department, University Hospital, Nantes, France
| | - Clément Bailly
- Université de Nantes, CHU Nantes, CNRS, Inserm, CRCINA, Nantes, France;,Site de Recherche Intégrée sur le Cancer (SIRIC), Imaging and Longitudinal Investigations to Ameliorate Decision-Making (ILIAD), INCA-DGOS-Inserm 12558, Nantes, France;,Nuclear Medicine Unit, University Hospital, Nantes, France
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22
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Kastritis E, Migkou M, Dalampira D, Gavriatopoulou M, Fotiou D, Roussou M, Kanellias N, Ntanasis-Stathopoulos I, Malandrakis P, Theodorakakou F, Sevastoudi A, Eleutherakis-Papaiakovou E, Triantafyllou T, Terpos E, Katodritou E, Dimopoulos MA. Chromosome 1q21 Aberrations Identify Ultra High-Risk Myeloma with Prognostic and Clinical Implications. Am J Hematol 2022; 97:1142-1149. [PMID: 35731917 DOI: 10.1002/ajh.26639] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 05/02/2022] [Accepted: 06/13/2022] [Indexed: 11/09/2022]
Abstract
Numerical abnormalities of chromosome 1q (+1q21) are common in patients with newly diagnosed multiple myeloma (MM) but their prognostic impact remains a matter of debate. In addition, the impact of the number of copies of 1q21 is not known. We analyzed 912 consecutive patients with symptomatic MM to evaluate the prognostic implications of +1q21 and of their copy number variations, as assessed by FISH. At the time of initial diagnosis 249 (27.3%) patients had +1q21, of which 150 (16.4%) had 3 copies and 99 (10.9%) had 4 or more copies. Presence of +1q21 was associated with advanced ISS stage (p=0.003), concurrent presence of other cytogenetics aberrations and advanced R-ISS stage (p<0.001). Patients with +1q21 had inferior PFS (median 34 vs 20 months, p<0.001) and OS (median 75 vs 44 months, p<0.001) but the copy number of 1q21 had no additional prognostic impact. In multivariate analysis, adjusting for R-ISS, age, treatment and HDM, +1q21 remained an independent prognostic factor both for PFS (p<0.001) and OS (p=0.008). The detrimental prognostic effect of +1q21 was more profound in R-ISS-3 patients, identifying a subgroup with OS of just 16 months (vs 46 for R-ISS-3 without +1q21, p<0.001). We further validated our findings in an independent cohort of 272 patients. In conclusion, presence of +1q21 is associated with more advanced disease, inferior PFS and OS but especially patients with R-ISS-3 disease and +1q21 have a very poor outcome comprising an ultra-high-risk group. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Efstathios Kastritis
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Magdalini Migkou
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Dimitra Dalampira
- Department of Hematology, Theageneion Cancer Hospital, Thessaloniki, Greece
| | - Maria Gavriatopoulou
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Despina Fotiou
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Maria Roussou
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Nikolaos Kanellias
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Ioannis Ntanasis-Stathopoulos
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Panagiotis Malandrakis
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Foteini Theodorakakou
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | | | | | | | - Evangelos Terpos
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Eirini Katodritou
- Department of Hematology, Theageneion Cancer Hospital, Thessaloniki, Greece
| | - Meletios A Dimopoulos
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
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23
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Crabtree M, Cai J, Qing X. Conventional Karyotyping and Fluorescence In Situ Hybridization for Detection of Chromosomal Abnormalities in Multiple Myeloma. J Hematol 2022; 11:87-91. [PMID: 35837374 PMCID: PMC9275438 DOI: 10.14740/jh1007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 06/18/2022] [Indexed: 12/12/2022] Open
Abstract
Background Multiple myeloma (MM) is a genetically heterogeneous disease, with cytogenetic findings that determine disease behavior. Genetic abnormalities can be assessed by fluorescence in situ hybridization (FISH) analysis and/or G-banded karyotyping. The two methods produce unique and overlapping information, and the clinical utility of using both is investigated here. Methods Seventy patients diagnosed with MM at a hospital in Southern California were retrospectively reviewed for the FISH and G-banded karyotyping results obtained from bone marrow specimens. Results Karyotype was normal in 71% (50/70), abnormal in 27% (19/70), and inadequate in 1% (1/70). Among patients with abnormal karyotype, FISH provided additional information about genetic aberrations in 95% of cases (18/19). Among cases with abnormal FISH, karyotype provided additional information about genetic aberrations in 27% of cases (18/66). When numerical abnormalities were present (detected by FISH and/or karyotype), FISH detected them in 95% (54/57), of which karyotype missed 70% (38/54) of the time. Karyotyping detected numerical abnormalities in 33% (19/57), which FISH missed 16% (3/19) of the time. Conclusions Karyotyping and FISH analysis in MM each provide unique information. For most patients, performing both tests together will provide more information than either test alone.
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Affiliation(s)
- Matthew Crabtree
- Department of Pathology, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jennifer Cai
- Department of Pathology, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Xin Qing
- Department of Pathology, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
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24
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Wiedmeier-Nutor JE, Bergsagel PL. Review of Multiple Myeloma Genetics including Effects on Prognosis, Response to Treatment, and Diagnostic Workup. Life (Basel) 2022; 12:life12060812. [PMID: 35743843 PMCID: PMC9225019 DOI: 10.3390/life12060812] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/10/2022] [Accepted: 05/20/2022] [Indexed: 12/03/2022] Open
Abstract
Multiple myeloma is a disorder of the monoclonal plasma cells and is the second most common hematologic malignancy. Despite improvements in survival with newer treatment regimens, multiple myeloma remains an incurable disease and most patients experience multiple relapses. Multiple myeloma disease initiation and progression are highly dependent on complex genetic aberrations. This review will summarize the current knowledge of these genetic aberrations, how they affect prognosis and the response to treatment, and review sensitive molecular techniques for multiple myeloma workup, with the ultimate goal of detecting myeloma progression early, allowing for timely treatment initiation.
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25
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Tang HKK, Fung CY, Morgan GJ, Kumar S, Siu L, Ip HWA, Yip SF, Lau KNH, Lau CK, Lee H, Leung KH, Kho B, Wong H, Ngai C, Hwang YY, Sim J, Kwong YL, Chim CS. The impact of bortezomib-based induction in newly diagnosed multiple myeloma with chromosome 1q21 gain. Ther Adv Hematol 2022; 13:20406207221082043. [PMID: 35465644 PMCID: PMC9019371 DOI: 10.1177/20406207221082043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 02/04/2022] [Indexed: 11/17/2022] Open
Abstract
Introduction: Bortezomib has been reported to favourably impact the outcomes of t(4;14) and del(17p) in multiple myeloma (MM), but its impact on gain 1q (+1q) is unknown. Methods: To address this, 250 patients treated with bortezomib-based induction were analysed. All myeloma samples had fluorescence in situ hybridization (FISH) performed on CD138-sorted bone marrow aspirate, and plasma cells were analysed using DNA probes specific for the following chromosomal aberrations: del(13q14), del(17p), t(14;16), t(4;14), and +1q. Presence of +1q was defined as the presence of at least three copies of 1q21 at the cut off level of 20% of bone marrow plasma cells. Results: +1q identified in 167 (66.8%) and associated with t(4;14) and high lactate dehydrogenase (LDH). +1q was not associated with response rate but shorter event-free survival (EFS) (median EFS 35 vs 55 months, p = 0.05) and overall survival (OS) (median OS 74 vs 168 months, p = 0.00025). Copy number and clone size did not impact survival. Multivariate analysis showed +1q was an independent adverse factor for OS together with International Staging System (ISS)3, high LDH, del(17p) and t(4;14). When a risk score of 1 was assigned to each independent adverse factor, OS was shortened incrementally by a risk score from 0 to 4. Post-relapse/progression survival was inferior in those with +1q (median 60 vs 118 months, p = 0.000316). Autologous stem cell transplantation (ASCT) improved OS for those with +1q (median OS 96 vs 49 months, p = 0.000069). Conclusion: +1q is an adverse factor for OS in MM uniformly treated with bortezomib-based induction but was partially mitigated by ASCT. A risk scoring system comprising +1q, LDH, high-risk FISH, and ISS is a potential tool for risk stratification in MM.
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Affiliation(s)
- Hoi Ki Karen Tang
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Chi Yeung Fung
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | | | - Shaji Kumar
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Lisa Siu
- Department of Pathology, Queen Elizabeth Hospital, Kowloon, Hong Kong
| | - Ho Wan Alvin Ip
- Department of Pathology, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Sze Fai Yip
- Department of Medicine, Tuen Mun Hospital, Tuen Mun, Hong Kong
| | | | - Chi Kuen Lau
- Department of Medicine, Tseung Kwan O Hospital, Kowloon, Hong Kong
| | - Harold Lee
- Department of Medicine, Princess Margaret Hospital, Kowloon, Hong Kong
| | - Kwan Hung Leung
- Department of Medicine, United Christian Hospital, Kowloon, Hong Kong
| | - Bonnie Kho
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong
| | - Howard Wong
- Department of Medicine, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong
| | - Cheong Ngai
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Yu Yan Hwang
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Joycelyn Sim
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Yok Lam Kwong
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Pok Fu Lam Road, Hong Kong
| | - Chor Sang Chim
- Department of Medicine, Queen Mary Hospital, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam Road, Hong Kong Department of Medicine, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong
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Waldschmidt JM, Yee AJ, Vijaykumar T, Pinto Rengifo RA, Frede J, Anand P, Bianchi G, Guo G, Potdar S, Seifer C, Nair MS, Kokkalis A, Kloeber JA, Shapiro S, Budano L, Mann M, Friedman R, Lipe B, Campagnaro E, O’Donnell EK, Zhang CZ, Laubach JP, Munshi NC, Richardson PG, Anderson KC, Raje NS, Knoechel B, Lohr JG. Cell-free DNA for the detection of emerging treatment failure in relapsed/ refractory multiple myeloma. Leukemia 2022; 36:1078-1087. [PMID: 35027656 PMCID: PMC8983453 DOI: 10.1038/s41375-021-01492-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 11/24/2021] [Accepted: 12/02/2021] [Indexed: 12/12/2022]
Abstract
Interrogation of cell-free DNA (cfDNA) represents an emerging approach to non-invasively estimate disease burden in multiple myeloma (MM). Here, we examined low-pass whole genome sequencing (LPWGS) of cfDNA for its predictive value in relapsed/ refractory MM (RRMM). We observed that cfDNA positivity, defined as ≥10% tumor fraction by LPWGS, was associated with significantly shorter progression-free survival (PFS) in an exploratory test cohort of 16 patients who were actively treated on diverse regimens. We prospectively determined the predictive value of cfDNA in 86 samples from 45 RRMM patients treated with elotuzumab, pomalidomide, bortezomib, and dexamethasone in a phase II clinical trial (NCT02718833). PFS in patients with tumor-positive and -negative cfDNA after two cycles of treatment was 1.6 and 17.6 months, respectively (HR 7.6, P < 0.0001). Multivariate hazard modelling confirmed cfDNA as independent risk factor (HR 96.6, P = 6.92e-05). While correlating with serum-free light chains and bone marrow, cfDNA additionally discriminated patients with poor PFS among those with the same response by IMWG criteria. In summary, detectability of MM-derived cfDNA, as a measure of substantial tumor burden with therapy, independently predicts poor PFS and may provide refinement for standard-of-care response parameters to identify patients with poor response to treatment earlier than is currently feasible.
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Affiliation(s)
- Johannes M. Waldschmidt
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrew J. Yee
- Harvard Medical School, Boston, MA, USA,Massachusetts General Hospital, Boston, MA, USA
| | - Tushara Vijaykumar
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Ricardo A. Pinto Rengifo
- Broad Institute of MIT and Harvard, Cambridge, MA, USA,Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Julia Frede
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Praveen Anand
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Giada Bianchi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Guangwu Guo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sayalee Potdar
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Charles Seifer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Monica S. Nair
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Antonis Kokkalis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jake A. Kloeber
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | | | - Mason Mann
- Massachusetts General Hospital, Boston, MA, USA
| | | | - Brea Lipe
- University of Rochester, Rochester, NY, USA
| | | | - Elizabeth K. O’Donnell
- Harvard Medical School, Boston, MA, USA,Massachusetts General Hospital, Boston, MA, USA
| | - Cheng-Zhong Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA,Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jacob P. Laubach
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Nikhil C. Munshi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Paul G. Richardson
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Kenneth C. Anderson
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Noopur S. Raje
- Harvard Medical School, Boston, MA, USA,Massachusetts General Hospital, Boston, MA, USA
| | - Birgit Knoechel
- Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA,Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jens G. Lohr
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard Medical School, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Trasanidis N, Katsarou A, Ponnusamy K, Shen YA, Kostopoulos IV, Bergonia B, Keren K, Reema P, Xiao X, Szydlo RM, Sabbattini PMR, Roberts IAG, Auner HW, Naresh KN, Chaidos A, Wang TL, Magnani L, Caputo VS, Karadimitris A. Systems medicine dissection of chr1q-amp reveals a novel PBX1-FOXM1 axis for targeted therapy in multiple myeloma. Blood 2022; 139:1939-1953. [PMID: 35015835 DOI: 10.1182/blood.2021014391] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/20/2021] [Indexed: 11/20/2022] Open
Abstract
Understanding the biological and clinical impact of copy number aberrations (CNAs) on the development of precision therapies in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring an adverse prognosis in several types of cancer, including in the blood cancer multiple myeloma (MM). Although several genes across chromosome 1 (chr1q) portend high-risk MM disease, the underpinning molecular etiology remains elusive. Here, with reference to the 3-dimensional (3D) chromatin structure, we integrate multi-omics data sets from patients with MM with genetic variables to obtain an associated clinical risk map across chr1q and to identify 103 adverse prognosis genes in chr1q-amp MM. Prominent among these genes, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed superenhancers, PBX1 directly regulates critical oncogenic pathways and a FOXM1-dependent transcriptional program. Together, PBX1 and FOXM1 activate a proliferative gene signature that predicts adverse prognosis across multiple types of cancer. Notably, pharmacological disruption of the PBX1-FOXM1 axis with existing agents (thiostrepton) and a novel PBX1 small molecule inhibitor (T417) is selectively toxic against chr1q-amp myeloma and solid tumor cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes, and proposes novel CNA-targeted therapy strategies in MM and other types of cancer.
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Affiliation(s)
- Nikolaos Trasanidis
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Alexia Katsarou
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Foundation Trust, London, United Kingdom
| | - Kanagaraju Ponnusamy
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Yao-An Shen
- Department of Pathology
- Department of Oncology
- Department of Gynecology and Obstetrics, and
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Ioannis V Kostopoulos
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Department of Biology, School of Science, National and Kapodistrian University of Athens, Athens, Greece
| | - Bien Bergonia
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Keren Keren
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Paudel Reema
- Imperial Experimental Cancer Medicine Centre and Cancer Research UK Imperial Centre, London, United Kingdom
| | - Xiaolin Xiao
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Richard M Szydlo
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Pierangela M R Sabbattini
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Irene A G Roberts
- Department of Paediatrics and Medical Research Council Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, United Kingdom
- Oxford Biomedical Research Centre Blood Theme, National Institute for Health Research Oxford Biomedical Centre, Oxford, United Kingdom
| | - Holger W Auner
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Foundation Trust, London, United Kingdom
| | - Kikkeri N Naresh
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Foundation Trust, London, United Kingdom
- Imperial Experimental Cancer Medicine Centre and Cancer Research UK Imperial Centre, London, United Kingdom
| | - Aristeidis Chaidos
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Foundation Trust, London, United Kingdom
| | - Tian-Li Wang
- Department of Pathology
- Department of Oncology
- Department of Gynecology and Obstetrics, and
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Luca Magnani
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom; and
| | - Valentina S Caputo
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Cancer Biology and Therapy Laboratory, School of Applied Science, London South Bank University, London, United Kingdom
| | - Anastasios Karadimitris
- Hugh and Josseline Langmuir Centre for Myeloma Research, Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Foundation Trust, London, United Kingdom
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28
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Oben B, Cosemans C, Geerdens E, Linsen L, Vanhees K, Maes B, Theunissen K, Cruys B, Lionetti M, Arijs I, Bolli N, Froyen G, Rummens JL. The Dynamics of Nucleotide Variants in the Progression from Low-Intermediate Myeloma Precursor Conditions to Multiple Myeloma: Studying Serial Samples with a Targeted Sequencing Approach. Cancers (Basel) 2022; 14:cancers14041035. [PMID: 35205782 PMCID: PMC8870380 DOI: 10.3390/cancers14041035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/28/2022] [Accepted: 02/16/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Multiple myeloma (MM), characterized by the expansion of plasma cells in the bone marrow, is the second most common hematological malignancy. This incurable cancer is consistently preceded by non-malignant asymptomatic precursor conditions known as monoclonal gammopathy of undetermined significance (MGUS) and/or smoldering multiple myeloma (SMM). These pre-stages are relatively frequent, but only a select percentage of them will progress to MM. However, it is still not possible to individually predict when and which patients will develop MM. Therefore, this study aimed to investigate the mutational profile in the progression in serial bone marrow samples with a custom targeted sequencing panel, designed to detect variants in myeloma-related genes. Remarkably, almost all variants identified in the MM samples were also already present in the pre-stages, sometimes even many years before the progression. These results provide new important insights into the molecular mechanisms of the precursor conditions and progression to MM. Abstract Multiple myeloma (MM), or Kahler’s disease, is an incurable plasma cell (PC) cancer in the bone marrow (BM). This malignancy is preceded by one or more asymptomatic precursor conditions, monoclonal gammopathy of undetermined significance (MGUS) and/or smoldering multiple myeloma (SMM). The molecular mechanisms and exact cause of this progression are still not completely understood. In this study, the mutational profile underlying the progression from low–intermediate risk myeloma precursor conditions to MM was studied in serial BM smears. A custom capture-based sequencing platform was developed, including 81 myeloma-related genes. The clonal evolution of single nucleotide variants and short insertions and deletions was studied in serial BM smears from 21 progressed precursor patients with a median time of progression of six years. From the 21 patients, four patients had no variation in one of the 81 studied genes. Interestingly, in 16 of the 17 other patients, at least one variant present in MM was also detected in its precursor BM, even years before progression. Here, the variants were present in the pre-stage at a median of 62 months before progression to MM. Studying these paired BM samples contributes to the knowledge of the evolutionary genetic landscape and provides additional insight into the mutational behavior of mutant clones over time throughout progression.
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Affiliation(s)
- Bénedith Oben
- Laboratory Experimental Hematology, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (C.C.); (L.L.); (J.-L.R.)
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- Correspondence:
| | - Charlotte Cosemans
- Laboratory Experimental Hematology, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (C.C.); (L.L.); (J.-L.R.)
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- Centre for Environmental Sciences, Hasselt University, 3590 Diepenbeek, Belgium
| | - Ellen Geerdens
- Laboratory Molecular Diagnostics, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (E.G.); (B.M.); (B.C.)
| | - Loes Linsen
- Laboratory Experimental Hematology, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (C.C.); (L.L.); (J.-L.R.)
- Activity Center Biobanking, University Hospitals Leuven, 3000 Leuven, Belgium
- University Biobank Limburg (UBiLim), Clinical Biobank, Jessa Hospital, 3500 Hasselt, Belgium
| | - Kimberly Vanhees
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- University Biobank Limburg (UBiLim), Clinical Biobank, Jessa Hospital, 3500 Hasselt, Belgium
| | - Brigitte Maes
- Laboratory Molecular Diagnostics, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (E.G.); (B.M.); (B.C.)
| | - Koen Theunissen
- Department Hematology, Jessa Hospital, 3500 Hasselt, Belgium;
| | - Bert Cruys
- Laboratory Molecular Diagnostics, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (E.G.); (B.M.); (B.C.)
| | - Marta Lionetti
- Department Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; (M.L.); (N.B.)
| | - Ingrid Arijs
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- Laboratory for Translational Genetics, Department Human Genetics, University of Leuven, 3000 Leuven, Belgium
- Belgian Inflammatory Bowel Disease Research and Development (BIRD), 1930 Zaventem, Belgium
| | - Niccolò Bolli
- Department Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy; (M.L.); (N.B.)
- Unità Operativa Complessa di Ematologia, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Guy Froyen
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- Laboratory Molecular Diagnostics, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (E.G.); (B.M.); (B.C.)
| | - Jean-Luc Rummens
- Laboratory Experimental Hematology, Department Clinical Biology, Jessa Hospital, 3500 Hasselt, Belgium; (C.C.); (L.L.); (J.-L.R.)
- Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium; (K.V.); (I.A.); (G.F.)
- University Biobank Limburg (UBiLim), Clinical Biobank, Jessa Hospital, 3500 Hasselt, Belgium
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29
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Puła A, Robak P, Mikulski D, Robak T. The Significance of mRNA in the Biology of Multiple Myeloma and Its Clinical Implications. Int J Mol Sci 2021; 22:12070. [PMID: 34769503 PMCID: PMC8584466 DOI: 10.3390/ijms222112070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 10/28/2021] [Accepted: 11/04/2021] [Indexed: 11/16/2022] Open
Abstract
Multiple myeloma (MM) is a genetically complex disease that results from a multistep transformation of normal to malignant plasma cells in the bone marrow. However, the molecular mechanisms responsible for the initiation and heterogeneous evolution of MM remain largely unknown. A fundamental step needed to understand the oncogenesis of MM and its response to therapy is the identification of driver mutations. The introduction of gene expression profiling (GEP) in MM is an important step in elucidating the molecular heterogeneity of MM and its clinical relevance. Since some mutations in myeloma occur in non-coding regions, studies based on the analysis of mRNA provide more comprehensive information on the oncogenic pathways and mechanisms relevant to MM biology. In this review, we discuss the role of gene expression profiling in understanding the biology of multiple myeloma together with the clinical manifestation of the disease, as well as its impact on treatment decisions and future directions.
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Affiliation(s)
- Anna Puła
- Department of Hematology, Medical University of Lodz, 93-510 Lodz, Poland;
| | - Paweł Robak
- Department of Experimental Hematology, Medical University of Lodz, 93-510 Lodz, Poland;
| | - Damian Mikulski
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, 92-215 Lodz, Poland;
| | - Tadeusz Robak
- Department of Hematology, Medical University of Lodz, 93-510 Lodz, Poland;
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31
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Molecular and functional profiling identifies therapeutically targetable vulnerabilities in plasmablastic lymphoma. Nat Commun 2021; 12:5183. [PMID: 34465776 PMCID: PMC8408158 DOI: 10.1038/s41467-021-25405-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 08/04/2021] [Indexed: 12/20/2022] Open
Abstract
Plasmablastic lymphoma (PBL) represents a rare and aggressive lymphoma subtype frequently associated with immunosuppression. Clinically, patients with PBL are characterized by poor outcome. The current understanding of the molecular pathogenesis is limited. A hallmark of PBL represents its plasmacytic differentiation with loss of B-cell markers and, in 60% of cases, its association with Epstein-Barr virus (EBV). Roughly 50% of PBLs harbor a MYC translocation. Here, we provide a comprehensive integrated genomic analysis using whole exome sequencing (WES) and genome-wide copy number determination in a large cohort of 96 primary PBL samples. We identify alterations activating the RAS-RAF, JAK-STAT, and NOTCH pathways as well as frequent high-level amplifications in MCL1 and IRF4. The functional impact of these alterations is assessed using an unbiased shRNA screen in a PBL model. These analyses identify the IRF4 and JAK-STAT pathways as promising molecular targets to improve outcome of PBL patients. Plasmablastic lymphoma (PBL) is an aggressive lymphoma subtype characterized by poor prognosis but the molecular knowledge of the disease is limited. Here, the authors perform whole exome sequencing and copy number determination of primary samples highlighting IRF4 and JAK-STAT pathways as therapeutic targets for PBL.
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32
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Zanwar S, Kumar S. Disease heterogeneity, prognostication and the role of targeted therapy in multiple myeloma. Leuk Lymphoma 2021; 62:3087-3097. [PMID: 34304677 DOI: 10.1080/10428194.2021.1957875] [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] [Indexed: 10/20/2022]
Abstract
Multiple myeloma (MM) is a clonal plasma cell malignancy with a heterogeneous disease course. Insights into the genetics of the disease have identified certain high-risk cytogenetic features that are associated with adverse outcomes. While the advances in therapy have translated into dramatic improvements in the outcome of patients with MM, those with high-risk genetic features continue to perform poorly. This has resulted in a need for clinical trials focusing on the high-risk subgroup of MM as they search for additional biomarkers and therapeutic targets continue. In this review, we discuss the currently existing data on prognostic and predictive biomarkers in MM and speculate the role of treatment stratification based on the genetic features of the disease.
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Affiliation(s)
- Saurabh Zanwar
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Shaji Kumar
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA
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33
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Farre L, Sanz G, Ruiz-Xivillé N, Castro de Moura M, Martin-Tejera JF, Gonçalves-Ribeiro S, Martinez-Iniesta M, Calaf M, Luis Mosquera J, Martín-Subero JI, Granada I, Esteller M, Domingo-Domenech E, Climent F, Villanueva A, Sureda A. Extramedullary multiple myeloma patient-derived orthotopic xenograft with a highly altered genome: combined molecular and therapeutic studies. Dis Model Mech 2021; 14:dmm048223. [PMID: 33988237 PMCID: PMC8325009 DOI: 10.1242/dmm.048223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 05/05/2021] [Indexed: 12/29/2022] Open
Abstract
Extramedullary multiple myeloma (EMM) has an overall survival of 6 months and occurs in 20% of multiple myeloma (MM) patients. Genetic and epigenetic mechanisms involved in EMM and the therapeutic role of new agents for MM are not well established. Besides, well-characterized preclinical models for EMM are not available. Herein, a patient-derived orthotopic xenograft (PDOX) was generated from a patient with an aggressive EMM to study in-depth genetic and epigenetic events, and drug responses related to extramedullary disease. A fresh punch of an extramedullary cutaneous lesion was orthotopically implanted in NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ(NSG) mouse. The PDOX mimicked histologic and phenotypic features of the tumor of the patient. Cytogenetic studies revealed a hyperploid genome with multiple genetic poor-prognosis alterations. Copy number alterations (CNAs) were detected in all chromosomes. The IGH translocation t(14;16)(q32;q23)IGH/MAF was already observed at the medullary stage and a new one, t(10;14)(p?11-12;q32), was observed only with extramedullary disease and could be eventually related to EMM progression in this case. Exome sequencing showed 24 high impact single nucleotide variants and 180 indels. From the genes involved, only TP53 was previously described as a driver in MM. A rather balanced proportion of hyper/hypomethylated sites different to previously reported widespread hypomethylation in MM was also observed. Treatment with lenalidomide, dexamethasone and carfilzomib showed a tumor weight reduction of 90% versus non-treated tumors, whereas treatment with the anti-CD38 antibody daratumumab showed a reduction of 46%. The generation of PDOX from a small EMM biopsy allowed us to investigate in depth the molecular events associated with extramedullary disease in combination with drug testing.
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Affiliation(s)
- Lourdes Farre
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - Gabriela Sanz
- Department of Clinical Hematology, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, 08908 L'Hospitalet del Llobregat Barcelona, Spain
| | - Neus Ruiz-Xivillé
- Hematological Laboratory, Germans Trias i Pujol Hospital, Catalan Institute of Oncology, 08916 Badalona, Barcelona, Spain
- Cancer and Leukemia Epigenetics and Biology and Experimental and Clinical Hematology Programs, Josep Carreras Leukaemia Research Institute, 08916 Badalona, Barcelona, Spain
| | - Manuel Castro de Moura
- Cancer and Leukemia Epigenetics and Biology and Experimental and Clinical Hematology Programs, Josep Carreras Leukaemia Research Institute, 08916 Badalona, Barcelona, Spain
| | - Juan Francisco Martin-Tejera
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - Samuel Gonçalves-Ribeiro
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - Maria Martinez-Iniesta
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - Monica Calaf
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - Jose Luis Mosquera
- IDIBELL Bioinformatic Unit – Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
| | - José Ignacio Martín-Subero
- Biomedical Epigenomics Group, Institut d'investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), University of Barcelona, 08036 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain
| | - Isabel Granada
- Hematological Laboratory, Germans Trias i Pujol Hospital, Catalan Institute of Oncology, 08916 Badalona, Barcelona, Spain
- Cancer and Leukemia Epigenetics and Biology and Experimental and Clinical Hematology Programs, Josep Carreras Leukaemia Research Institute, 08916 Badalona, Barcelona, Spain
| | - Manel Esteller
- Cancer and Leukemia Epigenetics and Biology and Experimental and Clinical Hematology Programs, Josep Carreras Leukaemia Research Institute, 08916 Badalona, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cancer, Carlos III Institute of Health, 28029 Madrid, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, 08036 Barcelona, Spain
| | - Eva Domingo-Domenech
- Department of Clinical Hematology, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, 08908 L'Hospitalet del Llobregat Barcelona, Spain
| | - Fina Climent
- Centro de Investigación Biomédica en Red de Cancer, Carlos III Institute of Health, 28029 Madrid, Spain
- Department of Pathology, Hospital Universitari de Bellvitge – Bellvitge Biomedical Research Institute, 08907 L'Hospitalet de Llobregat, Barcelona, Spain
| | - Alberto Villanueva
- Group of Chemoresistance and Predictive Factors, Subprogram Against Cancer Therapeutic Resistance, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L'Hospitalet del Llobregat, Barcelona, Spain
- Xenopat S.L., Business Bioincubator, Bellvitge Health Science Campus, 08907 L'Hospitalet de Llobregat, Barcelona, Spain
| | - Anna Sureda
- Department of Clinical Hematology, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, 08908 L'Hospitalet del Llobregat Barcelona, Spain
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Hung D, Lenton D, Eslick R, Blennerhassett R, Joshi M, McCaughan G, Day S, Wright D. Chromosome microarray characterisation of chromosome arm 12p loss associated with complex molecular karyotype and recurrent adverse cytogenetic markers in multiple myeloma. Genes Chromosomes Cancer 2021; 60:668-677. [PMID: 34041820 DOI: 10.1002/gcc.22975] [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: 11/27/2020] [Revised: 05/19/2021] [Accepted: 05/19/2021] [Indexed: 11/10/2022] Open
Abstract
Copy number loss within chromosome 12 short arm (12p) has gained attention as an adverse cytogenetic marker in multiple myeloma. The prognostic significance and characterisation of the common minimal deleted region remains controversial between various studies with loss of CD27 proposed as the putative critical gene. We aimed to determine the frequency of 12p loss, its correlation with adverse cytogenetic markers further to define and characterise 12p deletions. Our study included a prospective cohort of 574 multiple myeloma patients referred for cytogenetic testing, including interphase fluorescence in situ hybridisation for IGH (14q32.33) translocations and chromosome microarray. Loss of 12p was detected in 54/574 (9.4%) patients and when compared with the non-12p loss group [520/574 (90.6%)], 12p loss patients demonstrated a statistically significant association with specific recurrent cytogenetic markers: complex molecular karyotypes (98.1% vs 45.2%), 1p loss (50.0% vs 20.2%), t(4;14) (20.4% vs 7.7%), 8p loss (37.0% vs 15.0%), 13/13q loss (70.4% vs 41.7%), and 17p loss (33.3% vs 6.5%). The size and location of 12p losses were heterogeneous with a common 0.88 Mb minimally deleted region that included ~9 genes from ETV6 to CDKN1B in 52/54 (~96.3%) patients but did not include CD27. Our findings support 12p loss being a secondary chromosome abnormality frequently co-occurring with adverse cytogenetic markers and complex molecular karyotypes indicative of chromosome instability.
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Affiliation(s)
- Dorothy Hung
- Cytogenetics Department, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Douglas Lenton
- Clinical Haematology Services, Orange, New South Wales, Australia
| | - Renee Eslick
- Haematology Department, Liverpool Hospital, Liverpool, New South Wales, Australia
| | | | - Maansi Joshi
- Department of Haematology, Nepean Hospital, Kingswood, New South Wales, Australia
| | - Georgia McCaughan
- Haematology Department, Westmead Hospital, Westmead, New South Wales, Australia
| | - Samantha Day
- Haematology Department, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Dale Wright
- Cytogenetics Department, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
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35
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Clinical characteristics and treatment outcomes of newly diagnosed multiple myeloma with chromosome 1q abnormalities. Blood Adv 2021; 4:3509-3519. [PMID: 32750129 DOI: 10.1182/bloodadvances.2020002218] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/26/2020] [Indexed: 11/20/2022] Open
Abstract
A gain in chromosome 1q (+1q) is among the most common cytogenetic abnormalities in multiple myeloma (MM). It is unclear whether +1q is independently associated with decreased overall survival (OS). The objective of this study was to evaluate the impact of +1q on clinical characteristics, treatment response, and survival outcomes. We included 1376 Mayo Clinic patients diagnosed with MM from 2005 to 2018 who underwent fluorescence in situ hybridization testing at diagnosis with a panel including the +1q probe. A gain in 1q was found in 391 patients (28%) and was associated with anemia, hypercalcemia, high tumor burden, International Staging System (ISS) stage 3, high-risk (HR) translocations, and chromosome 13 abnormalities. There was no difference in overall response or deeper responses to proteasome inhibitor (PI)-, immunomodulatory drug (iMiD)-, or PI plus IMiD-based induction. Time to next treatment was shorter in patients with +1q compared with those without +1q (19.9 vs 27.7 months; P < .001). On univariate analysis, +1q was associated with increased risk of death (risk ratio [RR], 1.9; P < .001), and decreased OS was seen in all treatment groups. +1q was independently associated with decreased OS on multivariate analysis when other HR cytogenetic abnormalities, ISS stage 3, and age ≥70 years were included (RR, 1.5; P < .001). Gain of >1 copy of 1q was not associated with worse OS compared with gain of 1 copy (4.9 vs 4.3 years; P = .21). +1q was associated with high tumor burden, advanced disease stage, and HR translocations. It is independently associated with decreased OS, even in the setting of novel therapy and transplant.
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36
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Schmidt TM, Fonseca R, Usmani SZ. Chromosome 1q21 abnormalities in multiple myeloma. Blood Cancer J 2021; 11:83. [PMID: 33927196 PMCID: PMC8085148 DOI: 10.1038/s41408-021-00474-8] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 03/15/2021] [Accepted: 03/29/2021] [Indexed: 12/11/2022] Open
Abstract
Gain of chromosome 1q (+1q) is one of the most common recurrent cytogenetic abnormalities in multiple myeloma (MM), occurring in approximately 40% of newly diagnosed cases. Although it is often considered a poor prognostic marker in MM, +1q has not been uniformly adopted as a high-risk cytogenetic abnormality in guidelines. Controversy exists regarding the importance of copy number, as well as whether +1q is itself a driver of poor outcomes or merely a common passenger genetic abnormality in biologically unstable disease. Although the identification of a clear pathogenic mechanism from +1q remains elusive, many genes at the 1q21 locus have been proposed to cause early progression and resistance to anti-myeloma therapy. The plethora of potential drivers suggests that +1q is not only a causative factor or poor outcomes in MM but may be targetable and/or predictive of response to novel therapies. This review will summarize our current understanding of the pathogenesis of +1q in plasma cell neoplasms, the impact of 1q copy number, identify potential genetic drivers of poor outcomes within this subset, and attempt to clarify its clinical significance and implications for the management of patients with multiple myeloma.
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Affiliation(s)
| | - Rafael Fonseca
- Department of Hematology, Mayo Clinic, Scottsdale, AZ, USA
| | - Saad Z Usmani
- Plasma Cell Disorders Division, Levine Cancer Institute/Atrium Health, Charlotte, NC, USA.
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37
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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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38
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Liu Y, Ye X, Zhan X, Yu CY, Zhang J, Huang K. TPQCI: A topology potential-based method to quantify functional influence of copy number variations. Methods 2021; 192:46-56. [PMID: 33894380 DOI: 10.1016/j.ymeth.2021.04.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 04/18/2021] [Accepted: 04/19/2021] [Indexed: 12/21/2022] Open
Abstract
Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI).
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Affiliation(s)
- Yusong Liu
- Collage of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, China; Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Xiufen Ye
- Collage of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, China
| | - Xiaohui Zhan
- Indiana University School of Medicine, Indianapolis, IN 46202, USA; National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518037, China; Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Christina Y Yu
- Indiana University School of Medicine, Indianapolis, IN 46202, USA; Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA
| | - Jie Zhang
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Kun Huang
- Indiana University School of Medicine, Indianapolis, IN 46202, USA; Regenstrief Institute, Indianapolis, IN 46202, USA.
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39
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Couto Oliveira A, Ribeiro IP, Pires LM, Gonçalves AC, Paiva A, Geraldes C, Roque A, Sarmento-Ribeiro AB, Barbosa de Melo J, Carreira IM. Genomic characterisation of multiple myeloma: study of a Portuguese cohort. J Clin Pathol 2021; 75:422-425. [PMID: 33653728 DOI: 10.1136/jclinpath-2020-207204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 12/21/2020] [Accepted: 02/18/2021] [Indexed: 11/04/2022]
Abstract
Multiple myeloma (MM) genomic complexity reflects in the variable patients' clinical presentation. Genome-wide studies seem to be a reasonable alternative to identify critical genomic lesions. In the current study, we have performed the genomic characterisation of a Portuguese cohort of patients with MM by array comparative genomic hybridisation. Overall, the most frequently detected alterations were 13q deletions, gains of 1q, 19p, 15q, 5p and 7p and trisomy 9. Even though some identified genomic alterations were previously associated with a prognostic value, other abnormalities remain with unknown, but putative significance for patients' clinical practice. These genomic alterations should be further assessed as possible biomarkers.
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Affiliation(s)
- Alexandra Couto Oliveira
- University of Coimbra, Cytogenetics and Genomics Laboratory, Faculty of Medicine, Coimbra, Portugal
| | - Ilda Patrícia Ribeiro
- University of Coimbra, Cytogenetics and Genomics Laboratory, Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal
| | - Luís Miguel Pires
- University of Coimbra, Cytogenetics and Genomics Laboratory, Faculty of Medicine, Coimbra, Portugal
| | - Ana Cristina Gonçalves
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal.,University of Coimbra, Laboratory of Oncobiology and Haematology and University Clinic of Haematology, Faculty of Medicine, Coimbra, Portugal
| | - Artur Paiva
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Cytometry Operational Management Unit, Clinical Pathology Service, Centro Hospitalar e Universitário de Coimbra EPE, Coimbra, Portugal
| | - Catarina Geraldes
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal.,University of Coimbra, Laboratory of Oncobiology and Haematology and University Clinic of Haematology, Faculty of Medicine, Coimbra, Portugal.,Clinical Haematology Department, Centro Hospitalar e Universitário de Coimbra EPE, Coimbra, Portugal
| | - Adriana Roque
- Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal.,Clinical Haematology Department, Centro Hospitalar e Universitário de Coimbra EPE, Coimbra, Portugal
| | - Ana Bela Sarmento-Ribeiro
- University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal.,University of Coimbra, Laboratory of Oncobiology and Haematology and University Clinic of Haematology, Faculty of Medicine, Coimbra, Portugal.,Clinical Haematology Department, Centro Hospitalar e Universitário de Coimbra EPE, Coimbra, Portugal
| | - Joana Barbosa de Melo
- University of Coimbra, Cytogenetics and Genomics Laboratory, Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal
| | - Isabel Marques Carreira
- University of Coimbra, Cytogenetics and Genomics Laboratory, Faculty of Medicine, Coimbra, Portugal .,University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) and Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, Coimbra, Portugal.,University of Coimbra, Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra, Portugal.,Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal
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40
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Lee N, Kim SM, Lee Y, Jeong D, Yun J, Ryu S, Yoon SS, Ahn YO, Hwang SM, Lee DS. Prognostic value of integrated cytogenetic, somatic variation, and copy number variation analyses in Korean patients with newly diagnosed multiple myeloma. PLoS One 2021; 16:e0246322. [PMID: 33544757 PMCID: PMC7864461 DOI: 10.1371/journal.pone.0246322] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/15/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND To investigate the prognostic value of gene variants and copy number variations (CNVs) in patients with newly diagnosed multiple myeloma (NDMM), an integrative genomic analysis was performed. METHODS Sixty-seven patients with NDMM exhibiting more than 60% plasma cells in the bone marrow aspirate were enrolled in the study. Whole-exome sequencing was conducted on bone marrow nucleated cells. Mutation and CNV analyses were performed using the CNVkit and Nexus Copy Number software. In addition, karyotype and fluorescent in situ hybridization were utilized for the integrated analysis. RESULTS Eighty-three driver gene mutations were detected in 63 patients with NDMM. The median number of mutations per patient was 2.0 (95% confidence interval [CI] = 2.0-3.0, range = 0-8). MAML2 and BHLHE41 mutations were associated with decreased survival. CNVs were detected in 56 patients (72.7%; 56/67). The median number of CNVs per patient was 6.0 (95% CI = 5.7-7.0; range = 0-16). Among the CNVs, 1q gain, 6p gain, 6q loss, 8p loss, and 13q loss were associated with decreased survival. Additionally, 1q gain and 6p gain were independent adverse prognostic factors. Increased numbers of CNVs and driver gene mutations were associated with poor clinical outcomes. Cluster analysis revealed that patients with the highest number of driver mutations along with 1q gain, 6p gain, and 13q loss exhibited the poorest prognosis. CONCLUSIONS In addition to the known prognostic factors, the integrated analysis of genetic variations and CNVs could contribute to prognostic stratification of patients with NDMM.
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Affiliation(s)
- Nuri Lee
- Department of Laboratory Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Sung-Min Kim
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Youngeun Lee
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
| | - Dajeong Jeong
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jiwon Yun
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
| | - Sohee Ryu
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
| | - Sung-Soo Yoon
- Department of Internal Medicine, Clinical Research Institute, Seoul National University Hospital, Cancer Research Institute, Seoul National University, College of Medicine, Seoul, Korea
| | - Yong-Oon Ahn
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Sang Mee Hwang
- Department of Laboratory Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Dong Soon Lee
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
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41
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Afram G, Susek KH, Uttervall K, Wersäll JD, Wagner AK, Luong V, Lund J, Gahrton G, Alici E, Nahi H. Improved survival in multiple Myeloma patients undergoing autologous stem cell transplantation is entirely in the standard cytogenetic risk groups. Eur J Haematol 2021; 106:546-554. [PMID: 33471414 DOI: 10.1111/ejh.13585] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 12/11/2022]
Abstract
INTRODUCTION Novel drugs and drug combinations have improved outcomes for multiple myeloma patients. However, subgroups of patients still have a poor progression-free survival (PFS) and overall survival (OS). In an attempt to identify how the novel drugs affect the outcome in standard-risk and high-risk patients, respectively, we have investigated 715 multiple myeloma (MM) patients who have undergone high dose treatment followed by autologous stem cell transplantation at our center during 1995 - 2020. Outcomes during three time periods, 1995-1999 (period I), 2000-2009 (period II), and 2010-2020 (period III), were compared separately for standard-risk and high-risk patients. Risk stratification was based on chromosome analysis for periods II and III. RESULTS The whole cohort of patients showed significantly improved OS with time during the three periods being at a median of 5.8, 7.0, and 10.0 years, respectively. There is also a weak tendency for improved PFS, that is, a median of 2.4, 2.6, and 2.9 years, respectively, during the same periods. However, the separate analysis of standard-risk and high-risk patients showed that the overall improvement with time was due to improved standard-risk patients (median OS 8.4 years for the period I and not reached for period II and III). In contrast, no significant improvement was seen in high-risk patients. For patients with del17p, PFS was even worse during period III as compared to period II (median 1.6 vs 3.2 years respectively). CONCLUSION Our results show that the dramatic improvement in outcome for MM patients during the last 20 years only applies for standard-risk patients, while high-risk MM patients still are doing poorly, indicating that the novel drugs developed during this time are preferentially effective in standard-risk patients. New treatment modalities like CAR-T cells, CAR-NK cells, and/or bispecific antibodies should be tried in clinical studies early in the course of the disease, especially in patients with high-risk cytogenetics.
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Affiliation(s)
- Gabriel Afram
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
| | - Katharina Helene Susek
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Katarina Uttervall
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
| | - Johanna Dehlsen Wersäll
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Arnika Kathleen Wagner
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
| | - Vincent Luong
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Lund
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Gösta Gahrton
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Evren Alici
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
| | - Hareth Nahi
- Department of Medicine, Center for Hematology and Regenerative Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.,Haematology Center, Karolinska University Hospital, Stockholm, Sweden
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42
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Hanamura I. Gain/Amplification of Chromosome Arm 1q21 in Multiple Myeloma. Cancers (Basel) 2021; 13:cancers13020256. [PMID: 33445467 PMCID: PMC7827173 DOI: 10.3390/cancers13020256] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/07/2021] [Accepted: 01/09/2021] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Multiple myeloma (MM), a plasma cell neoplasm, is an incurable hematological malignancy. Gain/amplification of chromosome arm 1q21 (1q21+) is the most common adverse genomic abnormality associated with disease progression and drug resistance. While possible mechanisms of 1q21+ occurrence and candidate genes in the 1q21 amplicon have been suggested, the precise pathogenesis of MM with 1q21+ is unknown. Herein, we review the current knowledge about the clinicopathological features of 1q21+ MM, which can assist in effective therapeutic approaches for MM patients with 1q21+. Abstract Multiple myeloma (MM), a plasma cell neoplasm, is an incurable hematological malignancy characterized by complex genetic and prognostic heterogeneity. Gain or amplification of chromosome arm 1q21 (1q21+) is the most frequent adverse chromosomal aberration in MM, occurring in 40% of patients at diagnosis. It occurs in a subclone of the tumor as a secondary genomic event and is more amplified as the tumor progresses and a risk factor for the progression from smoldering multiple myeloma to MM. It can be divided into either 1q21 gain (3 copies) or 1q21 amplification (≥4 copies), and it has been suggested that the prognosis is worse in cases of amplification than gain. Trisomy of chromosome 1, jumping whole-arm translocations of chromosome1q, and tandem duplications lead to 1q21+ suggesting that its occurrence is not consistent at the genomic level. Many studies have reported that genes associated with the malignant phenotype of MM are situated on the 1q21 amplicon, including CKS1B, PSMD4, MCL1, ANP32E, and others. In this paper, we review the current knowledge regarding the clinical features, prognostic implications, and the speculated pathology of 1q21+ in MM, which can provide clues for an effective treatment approach to MM patients with 1q21+.
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Affiliation(s)
- Ichiro Hanamura
- Division of Hematology, Department of Internal Medicine, Aichi Medical University School of Medicine, 1-1, Karimata, Yazako, Nagakute, Aichi 480-1195, Japan
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43
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Chen C, Lim AST, Lau LC, Lim TH, Heng EYH, Tien SL. Implementation of cytogenomic microarray with plasma cell enrichment enables better abnormality detection and risk stratification in patients with plasma cell neoplasia than conventional cytogenetics and fluorescence in situ hybridization. Cancer Genet 2020; 252-253:25-36. [PMID: 33341677 DOI: 10.1016/j.cancergen.2020.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/21/2020] [Accepted: 12/04/2020] [Indexed: 11/16/2022]
Abstract
The detection of chromosomal abnormalities is important in the diagnosis, prognosis and disease monitoring in plasma cell neoplasia (PCN). However, the gold standard diagnostic techniques of conventional cytogenetics (CC) and fluorescence in situ hybridization (FISH) are hampered by culture difficulties and probe availability. Cytogenomic microarray (CMA), however, is able to surmount such limitations and generate a comprehensive genomic profile with the implementation of plasma cell (PC) enrichment. In this study, we examined 89 bone marrow specimens with CC and FISH without PC enrichment, 35 of which were examined with CMA after PC enrichment. Results revealed that after PC enrichment, CMA was able to detect chromosomal abnormalities in 34 of 35 specimens tested (97.1%), compared to 21 and 32 specimens (60% and 91.4%, respectively) achieved by CC and FISH, respectively, which were similar to the abnormality detection rates among all 89 specimens (59.5% by CC and 92.1% by FISH). In addition, as the only technique capable of detecting copy neutral loss of heterozygosity (CN-LOH) and chromothripsis, CMA appears to be the most powerful tool in risk stratification as it successfully re-stratified 9 (25.7%) and 12 (34.3%) specimens from standard risk (determined by CC and FISH, respectively) to high risk. Based on the encouraging data presented by our study and others, we conclude that implementation of CMA with PC enrichment is of great value in routine clinical workup in achieving a more complete genetic profile of patients with PCN.
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Affiliation(s)
- Chuanfei Chen
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore.
| | - Alvin Soon Tiong Lim
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore
| | - Lai Ching Lau
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore
| | - Tse Hui Lim
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore
| | - Evelyn Yee Hsieh Heng
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore
| | - Sim Leng Tien
- Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital, Singapore; Department of Haematology, Singapore General Hospital, Singapore
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Sessa M, Cavazzini F, Cavallari M, Rigolin GM, Cuneo A. A Tangle of Genomic Aberrations Drives Multiple Myeloma and Correlates with Clinical Aggressiveness of the Disease: A Comprehensive Review from a Biological Perspective to Clinical Trial Results. Genes (Basel) 2020; 11:E1453. [PMID: 33287156 PMCID: PMC7761770 DOI: 10.3390/genes11121453] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 11/24/2020] [Accepted: 12/01/2020] [Indexed: 12/12/2022] Open
Abstract
Multiple myeloma (MM) is a genetically heterogeneous disease, in which the process of tumorigenesis begins and progresses through the appearance and accumulation of a tangle of genomic aberrations. Several are the mechanisms of DNA damage in MM, varying from single nucleotide substitutions to complex genomic events. The timing of appearance of aberrations is well studied due to the natural history of the disease, that usually progress from pre-malignant to malignant phase. Different kinds of aberrations carry different prognostic significance and have been associated with drug resistance in some studies. Certain genetic events are well known to be associated with prognosis and are incorporated in risk evaluation in MM at diagnosis in the revised International Scoring System (R-ISS). The significance of some other aberrations needs to be further explained. Since now, few phase 3 randomized trials included analysis on patient's outcomes according to genetic risk, and further studies are needed to obtain useful data to stratify the choice of initial and subsequent treatment in MM.
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Affiliation(s)
- Mariarosaria Sessa
- Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S.Anna, University of Ferrara, 44121 Ferrara, Italy
| | - Francesco Cavazzini
- Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S.Anna, University of Ferrara, 44121 Ferrara, Italy
| | - Maurizio Cavallari
- Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S.Anna, University of Ferrara, 44121 Ferrara, Italy
| | - Gian Matteo Rigolin
- Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S.Anna, University of Ferrara, 44121 Ferrara, Italy
| | - Antonio Cuneo
- Hematology Section, Department of Medical Sciences, Azienda Ospedaliero-Universitaria, Arcispedale S.Anna, University of Ferrara, 44121 Ferrara, Italy
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45
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Samur MK, Aktas Samur A, Fulciniti M, Szalat R, Han T, Shammas M, Richardson P, Magrangeas F, Minvielle S, Corre J, Moreau P, Thakurta A, Anderson KC, Parmigiani G, Avet-Loiseau H, Munshi NC. Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group. J Clin Oncol 2020; 38:3107-3118. [PMID: 32687451 PMCID: PMC7499613 DOI: 10.1200/jco.20.00461] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/05/2020] [Indexed: 02/06/2023] Open
Abstract
PURPOSE Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060). We integrated genomic markers with clinical data. RESULTS We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair-associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.
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Affiliation(s)
- Mehmet Kemal Samur
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Anil Aktas Samur
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Mariateresa Fulciniti
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Raphael Szalat
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Tessa Han
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA
| | - Masood Shammas
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Paul Richardson
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Florence Magrangeas
- Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France
| | - Stephane Minvielle
- Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France
| | - Jill Corre
- University Cancer Center of Toulouse Institut National de la Santé, Toulouse, France
| | - Philippe Moreau
- Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France
| | | | - Kenneth C. Anderson
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Giovanni Parmigiani
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Hervé Avet-Loiseau
- University Cancer Center of Toulouse Institut National de la Santé, Toulouse, France
| | - Nikhil C. Munshi
- Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA
- VA Boston Healthcare System, Boston, MA
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46
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Cytogenetics in the genomic era. Best Pract Res Clin Haematol 2020; 33:101196. [DOI: 10.1016/j.beha.2020.101196] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 04/30/2020] [Accepted: 05/27/2020] [Indexed: 02/06/2023]
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47
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Offidani M, Boccadoro M, Di Raimondo F, Petrucci MT, Tosi P, Cavo M. Expert Panel Consensus Statement for Proper Evaluation of First Relapse in Multiple Myeloma. Curr Hematol Malig Rep 2020; 14:187-196. [PMID: 31077067 DOI: 10.1007/s11899-019-00507-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
PURPOSE OF REVIEW A working group of six expert physicians convened to assess the spectrum of multiple myeloma relapse presentations, discussed the features that can define the disease as aggressive and not aggressive, and established whether this information could help in selecting treatment together with the characteristics of disease and of patients and type of prior therapy. RECENT FINDINGS The working group agreed that relapse should be distinguished between biochemical and clinical according to IMWG. Moreover, the expert panel defined "aggressive disease" as a clinical condition that requires therapy able to induce a rapid and as deep as possible response to release symptoms and to avoid impending danger of new events. According to this definition, relapse was considered aggressive if it presents with at least one of the following features: doubling of M protein rate over 2 months, renal insufficiency, hypercalcemia, extramedullary disease, elevated LDH, high plasma cell proliferative index, presence of plasma cells in peripheral blood, or skeletal-related complications. Moreover, the panel agreed that this classification can be useful to choose therapy in first relapse together with other patient, disease, and prior therapy characteristics. So, this item was included in a new therapeutic algorithm. The treatment choice in MM at relapse is wider than in the past with the availability of many new therapeutic regimens leading to increased diversity of approaches and relevant risk of inappropriate treatment decisions. A practical classification of relapses into aggressive or non-aggressive, included in a decisional algorithm on MM management at first relapse, could help to make the appropriate treatment decisions.
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Affiliation(s)
- M Offidani
- Clinica di Ematologia, A.O.U. Ospedali Riuniti di Ancona, via Conca, 71, 60126, Ancona, Italy.
| | - M Boccadoro
- Myeloma Unit, Division of Hematology, University of Torino, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza di Torino, Torino, Italy
| | - F Di Raimondo
- Division of Hematology, AOU Policlinico-OVE, University of Catania, Catania, Italy
| | - M T Petrucci
- Department of Cellular Biotechnologies and Hematology, Sapienza University of Rome, Rome, Italy
| | - P Tosi
- Hematology Unit, Infermi Hospital Rimini, Rimini, Italy
| | - M Cavo
- Institute of Hematology Seragnoli, DIMES, University of Bologna, Bologna, Italy
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48
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Hong HG, Chen X, Kang J, Li Y. The Lq- NORM LEARNING FOR ULTRAHIGH-DIMENSIONAL SURVIVAL DATA: AN INTEGRATIVE FRAMEWORK. Stat Sin 2020; 30:1213-1233. [PMID: 32742137 PMCID: PMC7394456 DOI: 10.5705/ss.202017.0537] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
In the era of precision medicine, survival outcome data with high-throughput predictors are routinely collected. Models with an exceedingly large number of covariates are either infeasible to fit or likely to incur low predictability because of overfitting. Variable screening is key in identifying and removing irrelevant attributes. Recent years have seen a surge in screening methods, but most of them rely on some particular modeling assumptions. Motivated by a study on detecting gene signatures for multiple myeloma patients' survival, we propose a model-free L q -norm learning procedure, which includes the well-known Cramér-von Mises and Kolmogorov criteria as two special cases. The work provides an integrative framework for detecting predictors with various levels of impact, such as short- or long-term impact, on censored outcome data. The framework naturally leads to a scheme which combines results from different q to reduce false negatives, an aspect often overlooked by the current literature. We show that our method possesses sure screening properties. The utility of the proposal is confirmed with simulation studies and an analysis of the multiple myeloma study.
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Affiliation(s)
- H. G. Hong
- Department of Statistics and Probability, Michigan State University, East Lansing, Michigan 48823, USA
| | - X. Chen
- Center of Statistical Research, Southwestern University of Finance and Economics, China
| | - J. Kang
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Y. Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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49
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Ye CJ, Chen J, Liu G, Heng HH. Somatic Genomic Mosaicism in Multiple Myeloma. Front Genet 2020; 11:388. [PMID: 32391059 PMCID: PMC7189895 DOI: 10.3389/fgene.2020.00388] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 03/27/2020] [Indexed: 02/06/2023] Open
Affiliation(s)
- Christine J Ye
- The Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Jason Chen
- The Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Guo Liu
- Center for Molecular Medicine and Genomics, Wayne State University School of Medicine, Detroit, MI, United States
| | - Henry H Heng
- Center for Molecular Medicine and Genomics, Wayne State University School of Medicine, Detroit, MI, United States.,Department of Pathology, Wayne State University School of Medicine, Detroit, MI, United States
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50
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Mikulasova A, Ashby C, Tytarenko RG, Qu P, Rosenthal A, Dent JA, Ryan KR, Bauer MA, Wardell CP, Hoering A, Mavrommatis K, Trotter M, Deshpande S, Yaccoby S, Tian E, Keats J, Auclair D, Jackson GH, Davies FE, Thakurta A, Morgan GJ, Walker BA. Microhomology-mediated end joining drives complex rearrangements and overexpression of MYC and PVT1 in multiple myeloma. Haematologica 2020; 105:1055-1066. [PMID: 31221783 PMCID: PMC7109748 DOI: 10.3324/haematol.2019.217927] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 06/13/2019] [Indexed: 12/22/2022] Open
Abstract
MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1,267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3 We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in overexpression of key genes and chromatin immunoprecipitation-sequencing identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.
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Affiliation(s)
- Aneta Mikulasova
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Cody Ashby
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Ruslana G Tytarenko
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Pingping Qu
- Cancer Research and Biostatistics, Seattle, WA, USA
| | | | - Judith A Dent
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Katie R Ryan
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Michael A Bauer
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | | | | | - Matthew Trotter
- Celgene Institute for Translational Research Europe, Seville, Spain
| | - Shayu Deshpande
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Shmuel Yaccoby
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Erming Tian
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Jonathan Keats
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | - Graham H Jackson
- Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK
| | - Faith E Davies
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | | | - Gareth J Morgan
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Brian A Walker
- Myeloma Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
- Division of Hematology Oncology, Indiana University, Indianapolis, IN, USA
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