Brown, Elizabeth

Introduction The pathogenic role of somatic non-coding (nc) single nucleotide variants (SNVs) is underexplored in multiple myeloma (MM) and additional characterization of these regions has the potential to provide significant new insights into disease progression. To investigate the role of ncSNVs and their relationship with MM pathogenesis, we have characterized a novel series of WGS from 294 cases of MGUS, SMM, and MM using computational tools optimized to identify functional driver SNVs in these regions. We hypothesize the ncSNVs that co-localize to sites of super-enhancers (SEs) active in plasma cells (PC) are sites of high functional impact SNVs and these mutations lead to the dysregulated expression of genes that should be silent at the terminally differentiated stage of PCs, providing a selective advantage that shapes the fitness of the MM genomic landscape. Methods We analyzed 294 high-coverage matched tumor/normal pairs (80x tumor and 40x normal) derived from 21 MGUS, 86 SMM, 167 NDMM and 40 RRMM. In addition to previously sequenced samples, newly sequenced patients were obtained from NYU Langone Health, Memorial Sloan Kettering Cancer Center, University of Alabama at Birmingham and University of Miami following IRB-approved informed consent. DNA was extracted from CD138+ purified bone marrow plasma cells using standard approaches. We used the MGP1000 (https://github.com/pblaney/mgp1000) to process sequencing data which employs a union-consensus mechanism for determining the final set of variants. We collected enhancer elements (E/SEs) active in GC B-cells, ABC-DLBCL and GBC-DLBCL (Bal, et al. Nature, 2022) and PC specific E/SEs (Loven, et al. Cell 2013). FunSeq2 was used to score ncSNVs. GRAM was used to predict how variants alter TF binding and gene expression in a subset of 6 cases with paired WGS in our series and will expand this analysis on a validation set of 263 NDMM and 93 RRMM cases from University-Hospital Heidelberg enrolled in the GMMG-HD6 clinical trial. Results We identified 1,952,232 high-quality SNVs with 18,199 (0.93%) accumulating in 280 focal sites we termed “mutationally enriched regions” or MERs. To discern SNVs in MERs with the highest potential for imparting a selective advantage, we clustered mutations based on the density of FunSeq2 impact scores which uses reference data contexts on sequence conservation, modification of transcription factor (TF) binding, and gene linkage to regulatory elements and network hubs from pan-cancer studies. We show that MERs are enriched for ncSNVs with high impact scores (mean=2.57) compared to random similarly-sized regions of the genome (Fisher's exact test P<9.7e-12, OR=10.10 [3.88-37.40]). The high impact ncSNVs (hi-ncSNVs) in MERs (n=220) account for 8.09% of all hi-ncSNVs and are present in 46.3% of cases (136/294) with some patients having up to 7. The proportion of cases carrying a MER hi-ncSNVs was similar across disease stages (MGUS=42.9%, SMM=46.5%, MM=40.7%, and RR=47.5%). Analysis of the VAF of MER hi-ncSNVs shows a minor shift towards more clonal versus subclonal mutations (53.6% vs 46.4% VAF>=0.25) suggesting some high impact mutations are acquired in the GC but additional hi-ncSNV are acquired later in PC development, providing evidence that hi-ncSNVs accumulate in MERs throughout disease progression. We mapped these hi-ncSNVs to associated genes then intersected the loci with E/SEs active in GCBs and PCs to determine their functional context. This approach identified 12 genes affected by hi-ncSNVs including the previously identified nc-drivers NEAT1, MIR142, ZCCHC7, and IGLL5 as well as the PC differentiation genes IRF8, BACH2, proliferation genes RHOH, SPRED2, known coding MM drivers CCND1, ZFP36L1, and chr1q genes BTG2 and CROCC. We predicted the effect of ncSNVs on expression through modulation of TF binding at this set of putative nc drivers in MM and identified a trend towards increase in expression of SPRED2, CCND1, NEAT1, and IGLL5 compared to non-mutated cases (P=0.089). We will present data on the validation of this set of genes on a larger set of data derived from the Heidelberg group. Conclusions We identified a set of 12 putative nc driver genes in MM that modify expression and have the potential to significantly alter the pathogenesis of MM by providing a selective survival advantage. We will present the impact of these by clinical stage and on outcome.

Abstract Purpose: Multiple myeloma (MM) is the second most common hematological malignancy in the US. It is characterized by a clonal expansion of plasma cells in the bone marrow and extramedullary sites and is preceded by two precursor conditions including monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM). Strong evidence suggests a germline and environmental etiology. However, efforts to characterize heritable changes in gene activity, such as DNA methylation, have not been widely reported. Methods: We examined epigenome-wide DNA methylation as markers of MGUS, SMM and MM in peripheral blood obtained from treatment-naïve European American cases with heavy-chain IgG or IgA MGUS (n=60), SMM (n=31) and MM (n=54) and age- and sex-matched controls (n=79) included from the University of Alabama at Birmingham, University of Chicago and the Mayo Clinic, Rochester [54.5% males; mean age, 64 years (range, 36 to 86)]. We quantified DNA methylation of over 450,000 CpG and non-CpG loci using the Infinium HumanMethylation450 array (Illumina). Differentially methylated positions were calculated using a general linear model framework adjusted for confounders and cellular heterogeneity. Results: A total of 6 CpGs were differentially methylated in MM cases compared to controls at a level of genome-wide statistical significance. MM was associated with hypomethylation at differentially methylated positions inside SBNO2 (P=3.37x10-10), WIZ (P=1.12x10-8), CA6 (P=4.29x10-8) and ADORA1 (P=3.68x10-8) as well as intergenic positions proximal to TNFRSF8 (Chr 1p36.22; P=2.24x10-9) and ENDOV (Chr 17q25.3; P=2.74x10-8). Each of these loci, with the exception of CA6 and ADORA1, were hypomethylated in each of the 3 plasma cell dyscrasia phenotypes including MGUS and SMM and MM cases compared to controls (P<0.03), albeit not at a level of genome-wide statistical significance. Conclusions: These preliminary findings suggest that differences in DNA methylation may contribute to altered risk of MM, as well as its precursor conditions, and may play a role in plasma cell dyscrasia progression as a consequence of heritable changes in gene activity due to past exposures. Replication in a large yet similarly well-characterized population is warranted. Citation Format: Stephen D. Gragg, Devin Absher, Xiangqin Cui, Christina Pillion, Richard Myers, Shaji Kumar, Luciano Costa, Brian Chiu, Celine Vachon, Elizabeth Brown. Epigenome-wide association study reveals differential DNA methylation consistent with progression of multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1319. doi:10.1158/1538-7445.AM2017-1319