Статья

Genomic Classification and Individualized Prognosis in Multiple Myeloma

Francesco MauraMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLArjun Raj RajannaMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLBachisio ZicchedduMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLAlexandra M. PoosClinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, GermanyAndriy DerkachDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NYKylee MaclachlanMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NYMichael DuranteMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLBenjamin DiamondMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLMarios PapadimitriouMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLFaith E. DaviesMyeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NYEileen M. BoyleMyeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NYBrian A. WalkerDivision of Hematology Oncology, Melvin and Bren Simon Comprehensive Cancer Center, Indiana University, Indianapolis, INMalin HultcrantzMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NYAriosto SilvaDepartment of Malignant Hematology, Moffitt Cancer Center, Tampa, FLOliver HamptonJamie K. TeerDepartment of Biostatistics & Bioinformatics, Moffitt Cancer Center & Research Institute, Tampa, FLErin M. SiegelDepartment of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FLNiccolò BolliDepartment of Oncology and Onco-Hematology, University of Milan, Milan, ItalyGraham JacksonFreeman Hospital, The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle, United KingdomMartin KaiserThe Institute of Cancer Research, London, United KingdomCharlotte PawlynLeeds Cancer Research UK Clinical Trials Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, United KingdomGordon CookDivision of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USADickran KazandjianMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FLCaleb SteinDivision of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USAMarta ChesiDivision of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USALeif BergsagelDivision of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USAK. EliasHeidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, GermanyHartmut GoldschmidtHeidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, GermanyKatja WeiselDepartment of Oncology, Hematology and Blood and Marrow Transplant, University Medical Center Hamburg-Eppendorf, Hamburg, GermanyRoland FenkDepartment of Hematology, Oncology and Clinical Immunology, University-Hospital Duesseldorf, Duesseldorf, GermanyMarc S. RaabClinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, GermanyFritz Van RheeMyeloma Institute for Research & Therapy, University of Arkansas for Medical Sciences, Little Rock, ARSaad Z. UsmaniMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NYKenneth H. ShainDepartment of Malignant Hematology, Moffitt Cancer Center, Tampa, FLNiels WeinholdClinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, GermanyGareth J. MorganMyeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NYOla LandgrenMyeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL

2024en

ABI

Аннотация

PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

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Идентификаторы

DOI: 10.1200/jco.23.01277

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar