Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma

Abstract

In multiple myeloma, novel treatments with proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs) have prolonged survival but the disease remains incurable. At relapse, next-generation sequencing has shown occasional mutations of drug targets but has failed to identify unifying features that underlie chemotherapy resistance. We studied 42 patients refractory to both PIs and IMiDs. Whole-exome sequencing was performed in 40 patients, and RNA sequencing (RNA-seq) was performed in 27. We found more mutations than were reported at diagnosis and more subclonal mutations, which implies ongoing evolution of the genome of myeloma cells during treatment. The mutational landscape was different from that described in published studies on samples taken at diagnosis. The TP53 pathway was the most frequently inactivated (in 45% of patients). Conversely, point mutations of genes associated with resistance to IMiDs were rare and were always subclonal. Refractory patients were uniquely characterized by having a mutational signature linked to exposure to alkylating agents, whose role in chemotherapy resistance and disease progression remains to be elucidated. RNA-seq analysis showed that treatment or mutations had no influence on clustering, which was instead influenced by karyotypic events. We describe a cluster with both amp(1q) and del(13) characterized by CCND2 upregulation and also overexpression of MCL1, which represents a novel target for experimental treatments. Overall, high-risk features were found in 65% of patients. However, only amp(1q) predicted survival. Gene mutations of IMiD and PI targets are not a preferred mode of drug resistance in myeloma. Chemotherapy resistance of the bulk tumor population is likely attained through differential, yet converging evolution of subclones that are overall variable from patient to patient and within the same patient.

Timing the initiation of multiple myeloma

“…To further investigate association between treatment and SBS-MM1, we analyzed exome data from two independent validation cohorts: (1) 72 patients with paired samples collected at diagnosis and relapse, with 70% cases exposed to alkylating agents (CoMMpass trial); and (2) 40 MM patients all previously exposed to alkylating agents and refractory to both bortezomib and lenalidomide ( Fig. 1d) 20,21 . In line with our observations, SBS-MM1 was not present in therapynaive samples but was detected in the same patients at relapse and in the independent relapsed/refractory cohort.…”

“…The second cohort was comprised by 40 MM patients refractory to both immunomodulatory agents and proteasome inhibitors (INT 15/14; EGAS00001003709) 20,21 . Tumor (CD138+ bone marrow plasma cells) and matched germline samples (DNA from buccal swabs) were processed from 40 patients (80 total samples).…”

The prognostic value of additional copies of 1q21 in multiple myeloma depends on the primary genetic event

“…Although another layer of complexity (eg, by showing clonal heterogeneity or many genes with recurrent mutations at low prevalence) was added, particularly by NGS, these studies also confirmed the importance of primary CA (ie, HRD and primary translocations) that define cytogenetic subgroups and give rise to a non-random accumulation of secondary events. [10][11][12] Fluorescence in situ hybridization (FISH) is implemented in standard clinical workflows for the detection of CA in order to identify high-risk patients. [13][14][15][16] Several CA, namely primary IGH translocations and secondary events, have been associated with adverse prognosis.…”

Patient Similarity Network of Newly Diagnosed Multiple Myeloma Identifies Patient Sub-groups with Distinct Genetic Features and Clinical Implications

“…We have previously described 1q12 pericentromeric instability of satellite DNA as a major cause of cause of many of the secondary sub-clonal karyotypic events in MM 45 . In this regard, a recent study of double-refractory MM found that karyotypic events influenced clustering of patients more than treatment or mutations, and that amp(1q) was the only high-risk feature predicting survival 46 . These authors suggest that chromosome instability enables sub-clones to enter different evolutionary trajectories and adapt to selective pressure of therapies and underlying treatment failures.…”