As a consequence of the Multiple Myeloma Research Consortia (MMRC) genomics initiative, whole exome sequencing data has now been obtained on 213 primary MM samples essentially defining the exome mutation landscape for this disease. Using early access information from the MMRC we selected a panel of 39 genes, representing all expressed genes with nonsynonymous mutations found in ≥3% of MM cases, to which we then added eight additional genes targeted by the most commonly used therapies in MM, to help identify mutations associated with resistance to IMiDs (CRBN, CUL4A, CUL4B, DDB1 and IRF4), proteasome inhibitors (PSMG2, PSMB5) or glucocorticoid therapies (NR3C1). We tested this Multiple Myeloma Mutation Panel (M3P) in CD138+ bone marrow cells from 77 newly diagnosed, high risk, del17p MM patients with known clinical outcomes, obtained from the German DSMM study group. 43 of which also had a germline sample to analyze and 3 patients had a second subsequent sample from a later timepoint

Methods

The 47 M3P genes were sequenced using semiconductor technology (IonTorrent PGM, Life Technologies). The coding regions of the 47 genes were amplified in 200 bp libraries using customized oligos (Ion Ampliseq designer). Overall 2875 amplicons were analyzed per sample, multiplexed in two library preparations. Templating and Enrichment of DNA libraries was done using the IonOneTouch2 and IonOneTouch ES automated systems. Batches of 4-8 samples were barcoded using the Ion Xpress™ Barcode Adapters (Life Technologies), pooled and sequenced using the 318TMv2 chip (Life technologies). Data were visualized using IGV software (Broad Institute) and analyzed using IonReporter software (Life Technologies). Damaging mutations were collated using SIFT and PolyPhen. Publicly available databases including COSMIC and Oncomine were used to identify genes predicted to be cancer related.

Results

To validate the technology we first compared results using M3P to a previously sequenced MM whole genome. All genes in the M3P appeared adequately amplified by the designed primers. All mutations identified by the previously run WGS were successfully identified using the M3P sequencing panel. Subsequently, 33 tumor-germline pair samples, 43 single tumor samples and 1 temporally distinct paired sample for a total cohort of 77 patients have been analyzed. Under current conditions M3P achieved a mean 244X depth sequencing coverage per nucleotide for the tumor and a mean 179X depth sequencing coverage for the germline samples, respectively. Data on 33 tumor-germline comparisons so far show nonsynonymous mutations in 30 of the 47 genes with a mean of 2.7 mutations per sample (range 0-9) and 50.0% of mutations are predicted damaging by PolyPhen or SIFT. Ten genes were found to be mutated in more than 10% of the samples including genes previously known to be commonly mutated in MM: TP53, KRAS, NRAS and BRAF but also in NEB, ZFHX4, ANK2, MLL3, FAT3 and SP140. Interestingly, 46.6% of the mutations identified were present in less than 10% of reads, suggesting a high frequency of minor clones already present at the time of diagnosis. Of note, mutations once thought to be mutually exclusive such as KRAS and NRAS, were simultaneously detected in 2 patients. Analysis of the first sequential paired sample revealed nonsynonymous mutation changes over time with loss of a KRAS mutation, clonal expansion of a TP53 mutation and gain of additional FAT3, FAT1, SPEN, VCAN and FAM46C mutations, indicating the value of the panel in tracking clonal evolution over time. No further FAM46C mutations were detected in any of our newly diagnosed high risk cohort samples, which is significantly different from results in the MMRC genomics initiative, where FAM46C mutations were the fifth most common mutations (10.8%), suggesting that FAM46C mutation may be more frequent in lower risk patients or in relapse samples.

Conclusion

The M3P gene panel represents all genes with nonsynonymous mutations found in ≥3% of MM cases from the MMRC genomics initiative and incorporates additional genes that are known to be involved in the development of drug resistance. Thus this panel may serve as a tool to further improve MM classification, more precisely predict prognosis track clonal evolution and better guide treatment decisions. Our ongoing analysis will provide a comprehensive picture of the genetic landscape of a defined high risk MM cohort of del17p patients.

Disclosures:

Einsele:Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity’s Board of Directors or advisory committees. Stewart:Onyx: Consultancy, Research Funding; Millennium: Honoraria, Research Funding; Celgene: Honoraria; BMS: Honoraria.

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