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4207 A Second Generation, Multiple Myeloma-Specific, Targeted Sequencing Platform for Detecting Translocations, Copy Number Alterations, and Single Nucleotide Variants

Myeloma: Biology and Pathophysiology, excluding Therapy
Program: Oral and Poster Abstracts
Session: 651. Myeloma: Biology and Pathophysiology, excluding Therapy: Poster III
Monday, December 7, 2015, 6:00 PM-8:00 PM
Hall A, Level 2 (Orange County Convention Center)

Brian S White, PhD1,2*, Irena Lanc, PhD1,3*, Daniel Auclair, PhD4*, Robert Fulton, PhD2*, Mark A Fiala, BS, CCRP1*, Justin King1*, Gregory Ahmann, BS5, Mary Derome, MS4*, Elaine R Mardis, PhD2*, Joan Levy, PhD4*, Ravi Vij, MD, MBA1, John F. DiPersio, MD, PhD1 and Michael Tomasson, MD1

1Division of Oncology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
2Washington University School of Medicine, Saint Louis, MO
3McDonnell Genome Institute, Washington University, Saint Louis, MO
4Multiple Myeloma Research Foundation, Norwalk, CT
5Division of Hematology - Oncology, Mayo Clinic, Scottsdale, AZ

Background:  Multiple myeloma (MM) is a hematologic cancer characterized by a diversity of genetic lesions—translocations, copy number alterations (CNAs), and single nucleotide variants (SNVs).  The prognostic value of translocations and of CNAs has been well established.  Determining the clinical significance of SNVs, which are recurrently mutated at much lower frequencies, and how this significance is impacted by translocations and CNAs requires additional, large-scale correlative studies.  Such studies can be facilitated by cost-effective targeted sequencing approaches. Hence, we designed a single-platform targeted sequencing approach capable of detecting all three variant types. 

Methods:  We designed oligonucleotide probes complementary to the coding regions of 467 genes and to the IgH and MYC loci, allowing a probe to closely match at most 5 regions within the genome. Genes were selected if they were expressed in an independent RNA-seq MM data set and harbored germline SNP-filtered variants that: (1) occurred with frequency >3%, (2) were clustered in hotspots, (3) occurred in recurrently mutated “cancer genes" (as annotated in COSMIC or MutSig), or (4) occurred in genes involved in DNA repair and/or B-cell biology. IgH and MYC tiling was unbiased (with respect to annotated features within the loci) and spanned from 50 kilobasepairs (kbps) upstream of both regions to 50 kbps downstream of IgH and 100 kbps downstream of MYC.

Results:  We performed targeted sequencing of 96 CD138-enriched samples derived from MM patients, as well as matched peripheral blood leukocyte normal controls.  Sequencing depth (mean 107X) was commensurate with that of available exome sequencing data from these samples (mean 71X).  Samples harbored a mean of 25 non-silent variants, including those in known MM-associated genes: NRAS (24%), KRAS (22%), FAM46C (17%), TP53 (10%), DIS3 (8%), and BRAF (3%). Variants detected by both platforms showed a strong correlation (r^2 = 0.8).  The capture array detected activating, oncogenic variants in NRAS Q61K (n=3 patients) and KRAS G12C/D/R/V (n=5) that were not detected in exome data.  Additionally, we found non-silent, capture-specific variants in MTOR (3%) and in two transcription-related genes that have been previously implicated in cancer: ZFHX4 (5%) and CHD3 (5%). To assess the potential role of deep subclonal variants and our ability to detect them, we performed additional sequencing (mean 565X) on six of the tumor/normal pairs.  This revealed 14 manually-reviewed, non-silent variants that were not detected by the initial targeted sequencing.  These had a mean variant allele frequency of 2.8% and included mutations in DNMT3A and FAM46C.  At least one of these 14 variants occurred in five of the six re-sequenced samples.  This highlights the importance of this additional depth, which will be used in future studies.  Our approach successfully detected CNAs near expected frequencies, including hyperdiploidy (52%), del(13) (43%), and gain of 1q (35%).  Similarly, it inferred IgH translocations at expected frequencies: t(4;14) (14%), t(6;14) (3%), t(11;14) (15%), and t(14;20) (1%).  As expected, translocations occur predominantly within the IgH constant region, but also frequently 5’ (i.e., telomeric) of the IGHM switch region, and occasionally within the V and D regions. We detected MYC-associated translocations, whose frequencies have been the subject of debate, at 10% (n=9 patients), with five involving IgH, three having both partners in or near MYC, and one having both types.  Finally, our platform detected novel IgH translocations with partners near DERL3 (n=2), MYCN (n=1), and FLT3 (n=1).  Additional evidence suggests that DERL3 and MYCN may be targets of IgH-induced overexpression: of 84 RNA-seq patient samples, six exhibited outlying expression of DERL3, including one sample in which we detected the translocation in corresponding DNA, and one exhibited outlying expression of MYCN.

Conclusion:  Our MM-specific targeted sequencing strategy is capable of detecting deeply subclonal SNVs, in addition to CNAs and IgH and MYC translocations.  Though additional validation is required, particularly with respect to translocation detection, we anticipate that such technology will soon enable clinical testing on a single sequencing platform.

Disclosures: Vij: Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy ; Takeda, Onyx: Research Funding .

*signifies non-member of ASH