Comprehensive Assessment of Immunoglobulin Translocation Detection in Multiple Myeloma By Whole Genome Sequencing

Background. As we move towards the adoption of sequencing-based assays for classification, prognosis, and treatment prediction in multiple myeloma it is essential to establish high quality reference sets for usage by the community. The sensitivity and specificity of detecting copy number changes and translocations monitored today by FISH can vary based on the technology and analysis platforms used. To create a reproducible set of defined breakpoint junctions for assay validation and technology assessment requirements we have defined to the best of our ability the breakpoint sequences of derivative chromosomes involved in classic and non-classic translocations in the MMRF CoMMpass study and 68 cell lines. Classic translocations are defined as immunoglobulin translocations commonly tested for in clinical FISH panels that bring an immunoglobulin (IgH, IgK, or IgL) enhancer in proximity with a known target genes leading to the overexpression of the gene. The non-classic translocations were separated into two groups: non-classic enhancer, bringing a target genes into proximity with a non-immunoglobulin enhancer; or non-classic target, events where an immunoglobulin enhancer is dysregulating a non-classic myeloma oncogene.

Methods. The MMRF CoMMpass whole genomes and RNAseq data was generated and analyzed at TGen. PCR-free whole genome sequencing libraries were created for the entire cell line panel and sequenced to >40x on a NovaSeq X Plus instrument. A subset of 8 cell lines were independently sequenced to >200x for sensitivity testing of two-fold dilutions of tumor content from 100% down to 0.78%. Translocations were called using four independent methods; Manta (default), TGen-Manta (IgH mapping optimized), Pairoscope, and GaMMiT. Additionally, the 8 cell lines used in the sensitivity efforts and those with difficult to define breakpoint locations where sequenced to >20x with long-read sequencing on a PacBio Revio or Oxford Nanopore PromethION.

Results. To define a final comprehensive translocation call set in the CoMMpass cohort we integrated the results between all callers, manually reviewed any single tool calls and compared calls with matched RNA expression data to confirm overexpression. This process identified immunoglobulin (IgH, IgK, and IgL) translocations dysregulating NSD2 (13.5%), CCND3 (2.1%), MYC (14.5%), MAFA (1.0%), CCND1 (21.1%), CCND2 (1.4%), MAF (4.9%), and MAFB (1.3%) in this large patient cohort. Unexpectedly, the classic high risk translocations t(4;14) and t(14;16) did not significantly decrease time to second line therapy or overall survival in this cohort.

To determine how frequently an expected FISH positive translocation call would be missed by sequencing we compared and reviewed our calls on the cell lines with published results. This identified 9 uncalled derivative chromosomes out of 91 (9.9%) expected events. In all cases there was an unexpected piece of DNA ranging from 0.2-338kb inserted between the enhancer and target gene containing chromosomes. These complex events were limited to events targeting MYC. In CoMMpass similar events were observed during manual curation but in all cases a second derivative chromosome existed and was detected. When comparing translocation detection sensitivity, we found event detection varied depending on the copy number state, number of derivatives, and breakpoint sequence context. At 100% tumor content all events were called at 50x coverage, however, at 50% tumor content two events required >100x coverage to be detectable and at 25% tumor one event required over 150x to be detected. Finally, by integrating the available breakpoints and target gene overexpression we have defined high confidence regions from which an event detected in a DNA sample is expected to cause target gene dysregulation.

Conclusion. The adoption of sequencing-based detection of translocations in the clinical work-up of multiple myeloma patients will expand the number of detected events over current FISH assays. However, in some rare cases with a single derivative the junction structure can prevent direct detection of a reportable event due to the insertion of unexpected DNA sequences. Most other detection limitations can be overcome with optimized analysis tools, increased insert or sequencing read lengths, and sequencing coverage.