Bustoros M*,
Anand S*,
Sklavenitis-Pistofidis R, Redd R, Boyle EM,
Zhitomirsky B,
Dunford AJ, Tai YT, Chavda SJ, Boehner C, Neuse CJ, Rahmat M, Dutta A, Casneuf T, Verona R, Kastritis E, Trippa L,
Stewart C, Walker BA, Davies FE, Dimopoulos MA, Bergsagel PL, Yong K, Morgan GJ,
Aguet F,
Getz G#^, Ghobrial IM
#^
Nature Communications
(2022)
Abstract
Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models.