TY - JOUR
T1 - Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups
AU - Bolli, Niccolo
AU - Biancon, Giulia
AU - Moarii, Matahi
AU - Gimondi, Silvia
AU - Li, Yilong
AU - de Philippis, Chiara
AU - Maura, Francesco
AU - Sathiaseelan, Vijitha
AU - Tai, Yu-Tzu
AU - Mudie, Laura
AU - O'Meara, Sarah
AU - Raine, Keiran
AU - Teague, Jon W
AU - Butler, Adam P
AU - Carniti, Cristiana
AU - Gerstung, Moritz
AU - Bagratuni, Tina
AU - Kastritis, Efstathios
AU - Dimopoulos, Meletios
AU - Corradini, Paolo
AU - Anderson, Kenneth C
AU - Moreau, Philippe
AU - Minvielle, Stephane
AU - Campbell, Peter J
AU - Papaemmanuil, Elli
AU - Avet-Loiseau, Herve
AU - Munshi, Nikhil C
PY - 2018/12
Y1 - 2018/12
N2 - 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.
AB - 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.
U2 - 10.1038/s41375-018-0037-9
DO - 10.1038/s41375-018-0037-9
M3 - Article
C2 - 29789651
VL - 32
SP - 2604
EP - 2616
JO - Leukemia
JF - Leukemia
SN - 0887-6924
IS - 12
ER -