Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups.
2017
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 myelomacases 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 inhibitorand
immunomodulatory drug-treated patients with long follow-up, including events with context-specific prognostic value, such as deletions of the
PRDM1gene. 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 myelomaat diagnosis may lead to improved disease classification and prognostication.
Keywords:
-
Correction
-
Source
-
Cite
-
Save
57
References
88
Citations
NaN
KQI