High Throughput Digital Quantification of Genomic Copy Number Alterations in Multiple Myeloma
Authors: Kulkarni Shashikant , Elliott Nathan , Fiala Mark , Paasch Jacob , Tomasson Michael H. , Stockerl-Goldstein Keith E. , DiPersio John F. , Geiss Gary , Vij Ravi , Hucthagowder Vishwanathan 
Published: October 2019

Abstract
Abstract 1830
Multiple myeloma (MM) is a fatal disease characterized by clonal expansion of malignant plasma cells. The etiopathogenesis of MM is not fully understood. Several numerical and structural chromosomal aberrations have been identified as diagnostic markers and predictors of evolution in MM. Cytogenetic studies in MM patients are often not informative due to technical difficulties related to low proliferation of malignant plasma cells and outgrowth of non-malignant cells. Fluorescence in-situ hybridization (FISH) on CD138+ sorted plasma cells is probably the best method for maximizing diagnostic yield in MM, but is limited to the genomic regions queried. To overcome the limitations of the amount of clinical material available and to be able to interrogate large number of MM specific genomic aberrations, we developed and validated a MM genomic copy number signature. This signature comprised of 183 MM specific genes, was developed by pooling data from extensive meta-analyses on publically available raw data from ∼450 MM patients and copy number data generated by high-resolution SNP arrays (Affymetrix) from 39 MM patients in our cohort. To validate this signature of a large number of genes, we tested a recently developed innovative high throughput digital technology NanoString - nCounter assay. This technology captures and counts individual DNA molecules without enzymatic reactions or bias and is notable for its high levels of sensitivity, linearity, multiplex capability, and digital readout. It requires minimal input of DNA (∼300ng) making it a valuable tool for genomic copy number signature validation, diagnostic testing, and large translational studies, all of which often are limited by the very small amounts of clinical material available. Digital data was generated using nCounter analysis in 42 newly diagnosed, untreated MM patients. To identify the true acquired somatic copy number changes matched germline (skin) and tumor (sorted CD138+ cells) were analyzed from each of these MM patients. All of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The dynamic range in copy number calls with this assay is very large since there are no saturation issues and there is very low background. In this study, we were able to detect a maximum of 9 copies in some of the targets. We observed amplification of chromosomes 1q(51%), 3(65%), 5(65%), 7(70%), 9(56%), 11(72%), 15(56%), 19(53%), 21(42%), and deletion of chromosomes 1p(25%), 6q(28%), 8p(42%), 12p(40%), 13(47%), 14(26%) and 16q(49%). Interestingly, cytoband 2p11.2 and 14q32.33 consisting IGK and IGH genes were deleted in 75% and 93% of the patient population respectively. Overall, our results correlate well with the known pattern of genomic aberrations in MM. Additional analysis in an extended panel with clinically categorized samples is carried on to test the utility of this myeloma specific gene signature. To the best of our knowledge this is the first application of a high-throughput digital system to validate genomic copy number signature in cancer.

Disclosures:
No relevant conflicts of interest to declare.