Human Myeloma Cell Lines Mutation Landscape: Toward a Rationale Use of Cell Lines to Assess Drug Efficacy Prediction in Myeloma

Human myeloma cell lines (HMCLs) are widely used for the assessment of (new) drug efficacy in vitro or in vivo in mouse models. HMCLs have been mainly derived from patients at ultimate relapse and frequently from extramedullary disease, peripheral blood (secondary plasma cell leukemia), pleural effusion or ascites. Of HMCLs derived from patients at diagnosis most were from primary plasma cell leukemia. While HMCLs have been extensively characterized for 14q32 translocation and gene expression profile, the global mutation profile was never performed in a large collection of HMCLs. We thus performed a whole exon sequencing (WES) in 33 independent HMCLs displaying either recurrent 14q32 translocations (involving CCND1 or CCND3 [n=11], c-MAF or MAFB [n=8] and NSD2 gene [n=9]), an unknown non-recurrent translocation (n=3) or none translocation (n=2). We identified variants (missense, non-sense, essential splice, indels) and analyzed the copy number variation (CNV) to report deletion and amplification.

DNA was captured for exons and enriched with Sureselect target enrichment system (Agilent) then sequenced on HiSeq 2500. Fastq reads were aligned on hg19/GRCh37 reference genome, variants were called using GaTK. Single Nucleotide Polymorphisms (SNPs) were filtered out by removing over-represented variants (>15%), of the remaining variants, only non-neutral variants were kept, as defined by SnpEff algorithm. Copy Number Variations (CNV) data were calculated from read-depth using XHMM.

HMCLs display a median of 1603 mutations per sample impacting a median of 1345 genes per sample, MM1S and NAN7 harboring the highest and the lowest burden of mutations with 4725 and 1298 individual mutations, respectively. HMCLs harbored the same most frequent mutations found in primary myeloma cells that were KRAS, NRAS, BRAF, TP53, FAM46C and DIS3 . K/NRAS and TP53 were the most mutated genes across the collection (16 and 23 HMCLs, respectively). Presence of mutations was analyzed according to the heterogeneity in translocation and in the growth factor dependency (IGF1 versus IL6-dependent), to the mutant status of several genes (TP53, NRAS, KRAS ...) and to the cell response to several targeted and untargeted drugs. In order to provide a comprehensive landscape of abnormalities for all HMCLs (variants, CNV and Gene Expression Profiling [GEP], e.g. Figure 1), we also investigated the major pathways involved in growth and resistance, which are p53, DNA repair, epigenetic regulation, NFkB, ERK/MEK, AKT/mTOR, cell cycle and cell death pathways. For instance, the Multiple Factorial Analysis (MFA) of variants and GEP for p53 pathway is shown in Figure 2: HMCLs are segregated mostly according to TP53 or ATM status, mutations being mostly exclusive between the 2 genes. Contrary to TP53 mutations, ATM and ATR mutations are rare events (n=9 and 7, respectively), both occurring mostly in TP53 wild-type HMCLs. This global analysis underlines that, below TP53 status, quite all HMCLs display an abnormal p53 pathway.

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