Genomic Profiling of Smoldering Multiple Myeloma Identifies Patients at a High Risk of Disease Progression.
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Bustoros Mark, Sklavenitis-Pistofidis Romanos, Park Jihye, Redd Robert, Zhitomirsky Benny, Dunford Andrew J, Salem Karma, Tai Yu-Tzu, Anand Shankara, Mouhieddine Tarek H, Chavda Selina J, Boehner Cody, Elagina Liudmila, Neuse Carl Jannes, Cha Justin, Rahmat Mahshid, Taylor-Weiner Amaro, Van Allen Eliezer, Kumar Shaji, Kastritis Efstathis, Leshchiner Ignaty, Morgan Elizabeth A, Laubach Jacob, Casneuf Tineke, Richardson Paul, Munshi Nikhil C, Anderson Kenneth C, Trippa Lorenzo, Aguet François, Stewart Chip, Dimopoulos Meletios-Athanasios, Yong Kwee, Bergsagel P Leif, Manier Salomon, Getz Gad, Ghobrial Irene M
Аннотация
METHODS: We used next-generation sequencing to study 214 patients with SMM. We performed whole-exome sequencing on 166 tumors, including 5 with serial samples, and deep targeted sequencing on 48 tumors.
RESULTS: We observed that most of the genetic alterations necessary for progression have already been acquired by the diagnosis of SMM. Particularly, we found that alterations of the mitogen-activated protein kinase pathway (KRAS and NRAS single nucleotide variants [SNVs]), the DNA repair pathway (deletion 17p, TP53, and ATM SNVs), and MYC (translocations or copy number variations) were all independent risk factors of progression after accounting for clinical risk staging. We validated these findings in an external SMM cohort by showing that patients who have any of these three features have a higher risk of progressing to MM. Moreover, APOBEC associated mutations were enriched in patients who progressed and were associated with a shorter time to progression in our cohort.
CONCLUSION: SMM is a genetically mature entity whereby most driver genetic alterations have already occurred, which suggests the existence of a right-skewed model of genetic evolution from monoclonal gammopathy of undetermined significance to MM. We identified and externally validated genomic predictors of progression that could distinguish patients at high risk of progression to MM and, thus, improve on the precision of current clinical models.