TY - JOUR
TI - Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups
AU - Bolli, N.
AU - Biancon, G.
AU - Moarii, M.
AU - Gimondi, S.
AU - Li, Y.
AU - de Philippis, C.
AU - Maura, F.
AU - Sathiaseelan, V.
AU - Tai, Y.-T.
AU - Mudie, L.
AU - O’Meara, S.
AU - Raine, K.
AU - Teague, J.W.
AU - Butler, A.P.
AU - Carniti, C.
AU - Gerstung, M.
AU - Bagratuni, T.
AU - Kastritis, E.
AU - Dimopoulos, M.
AU - Corradini, P.
AU - Anderson, K.C.
AU - Moreau, P.
AU - Minvielle, S.
AU - Campbell, P.J.
AU - Papaemmanuil, E.
AU - Avet-Loiseau, H.
AU - Munshi, N.C.
JO - Leukemia Research
PY - 2018
VL - 32
TODO - 12
SP - 2604-2616
PB - Nature Publishing Group
SN - 0145-2126
TODO - 10.1038/s41375-018-0037-9
TODO - B lymphocyte induced maturation protein 1;  B Raf kinase;  interferon regulatory factor 4;  protein p53;  tumor necrosis factor receptor associated factor 3;  B lymphocyte induced maturation protein 1;  tumor marker, adult;  Article;  BRAF gene;  cancer prognosis;  cancer survival;  controlled study;  copy number variation;  CRBN gene;  DIS3 gene;  FAM46C gene;  female;  gene;  gene deletion;  gene function;  gene identification;  genetic association;  genome analysis;  genotype;  human;  IKZF1 gene;  IRF4 gene;  major clinical study;  male;  middle aged;  missense mutation;  multiple myeloma;  mutational analysis;  next generation sequencing;  oncogene K ras;  oncogene N ras;  PRDM1 gene;  predictive value;  priority journal;  SP140 gene;  survival analysis;  survival prediction;  TP53 gene;  TRAF3 gene;  gene expression regulation;  gene translocation;  genetics;  genomics;  high throughput sequencing;  multiple myeloma;  mutation;  pathology;  procedures;  prognosis, Biomarkers, Tumor;  DNA Copy Number Variations;  Female;  Gene Expression Regulation, Neoplastic;  Genomics;  Genotype;  High-Throughput Nucleotide Sequencing;  Humans;  Male;  Middle Aged;  Multiple Myeloma;  Mutation;  Positive Regulatory Domain I-Binding Factor 1;  Prognosis;  Translocation, Genetic
TODO - In multiple myeloma, next-generation sequencing (NGS) has expanded our knowledge of genomic lesions, and highlighted a dynamic and heterogeneous composition of the tumor. Here we used NGS to characterize the genomic landscape of 418 multiple myeloma cases at diagnosis and correlate this with prognosis and classification. Translocations and copy number abnormalities (CNAs) had a preponderant contribution over gene mutations in defining the genotype and prognosis of each case. Known and novel independent prognostic markers were identified in our cohort of proteasome inhibitor and immunomodulatory drug-treated patients with long follow-up, including events with context-specific prognostic value, such as deletions of the PRDM1 gene. Taking advantage of the comprehensive genomic annotation of each case, we used innovative statistical approaches to identify potential novel myeloma subgroups. We observed clusters of patients stratified based on the overall number of mutations and number/type of CNAs, with distinct effects on survival, suggesting that extended genotype of multiple myeloma at diagnosis may lead to improved disease classification and prognostication. © 2018, The Author(s).
ER -