Leukemia · 2018 · 453 citations · 31 references
MedicineGeneticsMolecular GeneticsCancer GeneticsGenomicsMolecular OncologyCancer GenomicsClinical GenomicsGenomic ProfilingMolecular Risk FactorsMolecular Tumor ProfilingMultiple MyelomaCytogenetic Prognostic MarkersCytogenetic Risk StratificationExome SequencingGenomic Risk StratificationHigh-risk Multiple MyelomaPrognostic Molecular StratificationTp53 MutationsTumor Exome Sequencing
Newly diagnosed multiple myeloma patients with high‑risk disease lack effective treatment options, and existing clinical, cytogenetic, and gene‑expression risk markers have notable limitations. The study aims to improve risk stratification by incorporating molecular features into the assessment of high‑risk NDMM. Using a genome‑wide analysis of the largest available NDMM cohort, the authors identified DNA drivers of aggressive disease and integrated them with clinical data. The integrated model explained 34.3 % of PFS and 46.5 % of OS variance, identified a 6.1 % high‑risk “double‑hit” subgroup defined by bi‑allelic TP53 loss or CKS1B amplification on ISS III, and demonstrated that these patients have a median PFS of 15.4 months and OS of 20.7 months, underscoring the need for novel therapies.
Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.
31
International Staging System for Multiple Myeloma
Philip R. Greipp, Jesús F. San Miguel, Brian G.M. Durie et al. · Journal of Clinical Oncology · 2005 · 2.9K citations
Medicine, Hematology, Oncology +14
Initial genome sequencing and analysis of multiple myeloma
Michael A. Chapman, Michael S. Lawrence, Jonathan J. Keats et al. · Nature · 2011 · 1.4K citations · Full text
Life Sciences, Genetics, Oncology +15
Lenalidomide, Bortezomib, and Dexamethasone with Transplantation for Myeloma
Michel Attal, Valérie Lauwers‐Cancès, Cyrille Hulin et al. · New England Journal of Medicine · 2017 · 1.2K citations · Full text
Medicine, Oncology, Pharmacotherapy +17
Widespread Genetic Heterogeneity in Multiple Myeloma: Implications for Targeted Therapy
Jens G. Lohr, Petar Stojanov, Scott L. Carter et al. · Cancer Cell · 2014 · 1K citations · Full text