ALBERT

Description: Multiple myeloma (MM) is a disease characterized by the abnormal proliferation of plasma cells in the bone marrow. We and others have recently demonstrated the existence of different myeloma subclones phylogenetically related to the founding clone. This intra-clonal heterogeneity is the basis for disease progression, treatment resistance, and relapse. However, the clinical and biological relevance of the presence and diversity of different myeloma subclones has not been fully established. In this study, we used whole exome sequencing (WES) plus a pull down of the MYC, IGH, IGL and IGK loci as a tool to analyze the largest series of presenting cases of myeloma (463 patients) to date, which were entered into the Myeloma XI trial (NCT01554852). DNA from both tumor and peripheral blood samples were used in the exome capture protocol following the SureSelect Target Enrichment System for Illumina Paired-End Sequencing Library v1.5. Exome reads were used to call single nucleotide variants (SNVs), indels, translocations, and copy number aberrations. The proportion of tumor cells containing an SNV was inferred. The presence and proportion of subclones were defined in a subset of 437 patients using a genetic algorithm based-tool (GAUCHO), which also calculated different indices of clonal diversity: number of clones, mean pairwise genetic divergence, Shannon and Inverse Simpson diversity index and Berger-Parker dominance index. Based on these results, we aimed to determine the clinical implications of the number of mutations and the subclonal diversity of MM at presentation in progression free (PFS) and overall survival (OS). We found that MM patients with t(14;16) and t(14;20) had more exonic mutations (not including Ig variants) than the rest of samples (median 87 versus 43, p25% of MM cells (low values of Berger-Parker Dominance index, n=56) had a significantly shorter PFS than those with a dominant clone accounting for more than 25% of cells with a median of 22 (95% CI, 12.3-26.3) vs. 27.5 months (95% CI, 23.9-30.9) respectively, p=0.02. Our results show that mutational load and subclonal diversity are poor prognostic factors in myeloma. Previous studies from massive-parallel sequencing and single cell analyses of myeloma plasma cells already revealed that myeloma had the features of an evolutionary ecosystem, where different tumour subclones coexist and have differential response to treatment. We have demonstrated in this study that measures of tumor diversity have important clinical consequences. To our knowledge, this is the first time that the use of clonal diversity indices as predictive biomarkers of progression is proposed in haematological malignancies, and more specifically, myeloma. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

Description: Dysregulation of the epigenome plays an important role in the pathogenesis of the plasma cell malignancy myeloma (MM). For example the H3K36 methyltransferase, MMSET, is overexpressed as a result of t(4;14) in 15% of patients and associated with a distinct DNA methylation pattern and shorter survival. Epigenetic modifiers may also be deregulated due to somatic mutations, seen in the histone demethylase, KDM6A/UTX (Van Haaften et al, Nat.Genet. 2009) and histone methyltransferase, MLL(Chapman et al, Nature 2011). We analysed the spectrum and clinical implications of epigenetic gene mutations in the largest series of newly diagnosed MM patients sequenced to date. Whole exome sequencing was performed on DNA extracted from tumour (CD138+) and peripheral blood samples from patients entering the NCRI Myeloma XI trial (n=463) using SureSelect (Agilent) with extra baits to cover IGH, IGK, IGL and MYC loci, median depth 60x. Data were processed to identify acquired variants, copy number, indels and translocation breakpoints and annotated for potentially deleterious mutations. Significantly mutated genes were detected using MutSigCV (v1.4) inputting all SNV and short indels (q-value threshold 0.1). Survival from initial randomization had median follow up of 25 months. The gene encoding the linker histone protein Histone 1.4, HIST1H1E was mutated in 2.8% of samples and one of the most significantly mutated genes in myeloma (p

Description: Introduction Multiple myeloma is a clinically highly heterogeneous disease, which is reflected by both a complex genome and epigenome. Dynamic epigenetic changes are involved at several stages of myeloma biology, such as transformation and disease progression. Our previous genome wide epigenetic analyses identified prognostically relevant DNA hypermethylation at specific tumor suppressor genes (Kaiser MF et al., Blood 2013), indicating that specific epigenetic programming influences clinical behavior. This clinically relevant finding prompted further investigation of the epigenomic structure of myeloma and its interaction with genetic aberrations. Material and Methods Genome wide DNA methylation of CD138-purified myeloma cells from 464 patients enrolled in the NCRI Myeloma XI trial at presentation were analyzed using the high resolution 450k DNA methylation array platform (Illumina). In addition, 4 plasma cell leukemia (PCL) cases (two t(11;14) and two (4;14)) and 7 myeloma cell lines (HMCL) carrying different translocations were analysed. Analyses were performed in R Bioconductor packages after filtering and removal of low quality and non-uniquely mapping probes. Results Variation in genome wide DNA methylation was analyzed using unsupervised hierarchical clustering of the 10,000 most variable probes, which revealed epigenetically defined subgroups of disease. Presence of recurrent IGH translocations was strongly associated with specific epigenetic profiles. All 60 cases with t(4;14) clustered into two highly similar sub-clusters, confirming that overexpression of the H3K36 methyltransferase MMSET in t(4;14) has a defined and specific effect on the myeloma epigenome. Interestingly, HMCLs KMS-11 and LP-1, which carry t(4;14), MM1.S, a t(14;16) cell line with an E1099K MMSET activating mutation as well as two PCLs with t(4;14) all clustered in one sub-clade. The majority (59/85) of t(11;14) cases showed global DNA hypomethylation compared to t(4;14) cases and clustered in one subclade, indicating a epigenetic programming effect associated with CCND1, with a subgroup of t(11;14) cases showing a variable DNA methylation pattern. In addition to translocation-defined subgroups, a small cluster of samples with a distinct epigenetic profile was identified. In total 7 cases with a shared specific DNA methylation pattern (median inter-sample correlation 0.4) were identified. The group was characterized by DNA hypermethylation (4,341 hypermethylated regions vs. 750 hypomethylated regions) in comparison to all other cases. Intersection of regions hypermethylated in this subgroups with ENCODE datasets revealed mapping to poised enhancers and promoters in H1-hESC, indicating functionally relevant epigenetic changes. Gene set enrichment analysis (KEGG) demonstrated enrichment of developmental pathway genes, e.g. Hedgehog signaling (adj p=5x10exp-13), amongst others and all four HOX clusters were differentially methylated in this group. Of note, three of seven cases in this subgroup carried a t(11;14) and all t(11;14) or t(11;14)-like HMCLs clustered closely together with these patient cases, but not with the cluster carrying the majority of t(11;14) myeloma or t(11;14) PCLs. This potentially indicates that t(11;14) HMCL could be derived from a subgroup of patients with specific epigenetic characteristics. Conclusion Our results indicate that the recurrent IGH translocations are fundamentally involved in shaping the myeloma epigenome through either direct upregulation of epigenetic modifiers (e.g. MMSET) or through insufficiently understood mechanisms. However, developmental epigenetic processes seem to independently contribute to the complexity of the epigenome in some cases. This work provides important insights into the spectrum of epigenetic subgroups of myeloma and helps identify subgroups of disease that may benefit from specific epigenetic therapies currently being developed. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

Description: Background Structural aberrations like copy number alterations (CNA) and translocations play a central role in multiple myeloma tumor biology. The analysis of CNA for complete molecular profiling of myeloma retains clinical significance in the context of recent next-generation sequencing (NGS) results which highlight the highly heterogeneous landscape of single nucleotide mutations, which are often sub-clonal. Detection of CNAs remains the domain of array-based technologies, as demonstrated by the use of copy number arrays by the TCGA consortium and others for CNA detection in NGS projects. High cost and infrastructure attached to CNA analysis by array limit access to this technology in many molecular diagnostic laboratories. We present here a robust and accessible method that combines two multiplex ligation-dependent probe amplification (MLPA) assays for the relevant CNAs in myeloma using low input amounts of purified tumor DNA. Methods Bone marrow myeloma cells from patients at presentation and at relapse from the Myeloma IX and Myeloma XI trials were purified to 〉95% purity by immunomagnetic separation (Miltenyi Biotech) and DNA was extracted using AllPrep columns (QIAGEN) for analysis by MLPA. A novel myeloma specific probemix was designed and technically validated by MRC-Holland (Amsterdam, The Netherlands), complementing the established myeloma specific probemix P425 (Alpar et al., Gen Chrom Cancer 2013). Results In total 130 purified myeloma cell DNA samples were successfully analyzed by MLPA, interrogating 43 different loci in the following regions: 6p22 - 6p12 [incl. CDKN1A]; 6q12 - 6q26 [incl. TNFAIP3, WTAP, PARK2]; 8p23 – 8p11 [incl. TNFRSF10A/B]; 8q12 – 8q24 [incl. MYC]; 11q13 – 11q25 [incl. CCND1, BIRC2, BIRC3]; 17p [all exons of TP53]; 22q11 – 22q13 [incl. HIRA, EP300]. The assay contains one probe for the detection of BRAF V600E, including determination of mutant allele ratio. This probemix complements another MLPA assay [P425] which interrogates prognostically and biologically relevant regions such as 1p32, 1q21-1q23, 13q14, 16q12-16q23, 17p13 and chr 5, 9 and 15 for detection of hyperdiploidy (HRD). The assay returned good quality results using as little as 25 ng DNA input material without modification of assay conditions. In this group of cases which were enriched with cases known to carry specific CNAs and mutations, frequent copy number aberrations encompassed loss of chr(6q), in the majority of cases (16%) affecting all genes investigated in the region 6q23 – 6q26. In addition, five cases (4%) with an isolated heterozygous deletion of TNFAIP3 at 6q23 and two cases with deletion of TNFAIP3 and WTAP were detected. Gains of MYC at 8q24 were observed in 13 cases (10%) of which 5 showed gains of other regions on 8q as well. BIRC3 and BIRC2 were both lost in 4 cases, including 1 homozygous deletion of both genes. All coding exons of TP53 were heterozygously deleted in 16% of cases in this group containing specifically selected relapsed cases. Gain of chromosome 11 was frequent (29%) and mostly associated with HRD, but gain(11q) without HRD was observed, including 3 cases with isolated gain of the CCND1locus at 11q13.3. Of 11 cases with a known BRAF V600E mutation identified by SSCA, 10 (91%) were detected by MLPA with the remaining mutation showing a signal just above detection limit by SSCA. Calculated median V600E mutant allele ratio in comparison to an artificial plasmid mix mimicking a heterozygous mutation was 39% (range 9%-77%), confirming our previous observation that this mutation is mostly heterozygous and sub-clonal in myeloma. Further cases at presentation from the Myeloma XI trial are currently being analyzed by MLPA and results will be presented at the meeting, including a comparison with matched CNA array data for a selection of cases as well as correlation with clinical data for trial cases. Discussion The combination of this panel with another MLPA probemix [P425], which has been extensively validated in over 1200 myeloma cases by our group, allows assaying of biologically and clinically relevant CNAs in myeloma as well as BRAF V600E mutation status. The tests can be run on standard laboratory equipment and require 25 ng of DNA as input material, making this method suitable for exploring the clinical impact of myeloma specific CNAs in large clinical trials with a potential of transferring the method to the routine diagnostic setting. Disclosures Walker: Onyx: Consultancy. Savola:MRC-Holland: Employment.

Description: Introduction: Current diagnostic standards for lymphoproliferative disorders include detection of clonal immunoglobulin (IG) and/or T cell receptor (TR) rearrangements, translocations, copy number alterations (CNA) and somatic mutations. These analyses frequently require a series of separate tests such as clonality PCR, fluorescence in situ hybridisation and/or immunohistochemistry, MLPA or SNParrays and sequencing. The EuroClonality-NGS DNA capture (EuroClonality-NDC) panel, developed by the EuroClonality-NGS Working Group, was designed to characterise all these alterations by capturing variable, diversity and joining IG and TR genes along with additional clinically relevant genes for CNA and mutation analysis. Methods: Well characterised B and T cell lines (n=14) representing a diverse repertoire of IG/TR rearrangements were used as a proficiency assessment to ensure 7 testing EuroClonality centres achieved optimal sequencing performance using the EuroClonality-NDC optimised and standardised protocol. A set of 56 IG/TR rearrangements across the 14 cell lines were compiled based on detection by Sanger, amplicon-NGS and capture-NGS sequencing technologies. For clinical validation of the NGS panel, clinical samples representing both B and T cell malignancies (n=280), with ≥ 5% tumour infiltration were collected from 10 European laboratories, with 88 (31%) being formalin fixed paraffin-embedded samples. Samples were distributed to the 7 centres for library preparation, hybridisation with the EuroClonality-NDC panel and sequencing on a NextSeq 500, using the EuroClonality-NDC standard protocol. Sequencing data were analysed using a customised version of ARResT/Interrogate, with independent review of the results by 2 centres. All cases exhibiting discordance between the benchmark and capture NGS results were submitted to an internal review committee comprising members of all participating centres. Results: All 7 testing centres detected all 56 rearrangements of the proficiency assessment and continued through to the validation phase. A total of 10/280 (3.5%) samples were removed from the validation analysis due to NGS failures (n=1), tumour infiltration 〈 5% (n=7), and sample misidentification (n=2). The EuroClonality-NDC panel detected B cell clonality (i.e. detection of at least one clonal rearrangement at IGH, IGK or IGL loci) in 189/197 (96%) B cell malignancies. Seven of the 8 discordant cases were post-germinal centre malignancies exhibiting Ig somatic hypermutation. The EuroClonality-NDC panel detected T cell clonality (i.e. detection of at least one clonal rearrangement at TRA, TRB, TRD or TRG loci) in 70/73 (96%) T cell malignancies. In all 3 discordant cases analysis of benchmark PCR data was not able to detect clonality at any TR loci. Next, we examined whether the EuroClonality-NDC panel could detect clonality at each of the individual loci, resulting in sensitivity values of 95% or higher for all IG/TR loci, with the exception of those where limited benchmark data were available, i.e. IGL (n=3) and TRA (n=7). The specificity of the panel was assessed on benign reactive lesions (n=21) that did not contain clonal IG/TR rearrangements based on BIOMED-2/EuroClonality PCR results; no clonality was observed by EuroClonality-NDC in any of the 21 cases. Limit of detection (LOD) assessment to detect IG/TR rearrangements was performed using cell line blends with each of the 7 centres receiving blended cell lines diluted to 10%, 5.0%, 2.5% and 1.25%. Across all 7 centres the overall detection rate was 100%, 94.1%, 76.5% and 32.4% respectively, giving an overall LOD of 5%. Sufficient data were available in 239 samples for the analysis of translocations. The correct translocation was detected in 137 out of 145 cases, resulting in a sensitivity of 95%. Table 1 shows how translocations identified by the EuroClonality-NDC protocol were restricted to disease subtypes known to harbour those types of translocations. Analysis of CNA and somatic mutations in all samples is underway and will be presented at the meeting. Conclusions: The EuroClonality-NDC panel, with an optimised laboratory protocol and bioinformatics pipeline, detects IG and TR rearrangements and translocations with high sensitivity and specificity with a LOD ≤ 5% and provides a single end-to-end workflow for the simultaneous detection of IG/TR rearrangements, translocations, CNA and sequence variants. Table. Disclosures Stamatopoulos: Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Klapper:Roche, Takeda, Amgen, Regeneron: Honoraria, Research Funding. Ferrero:Gilead: Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; EUSA Pharma: Membership on an entity's Board of Directors or advisory committees; Servier: Speakers Bureau. van den Brand:Gilead: Speakers Bureau. Groenen:Gilead: Speakers Bureau. Brüggemann:Incyte: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy. Langerak:Gilead: Research Funding, Speakers Bureau; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; Janssen: Speakers Bureau. Gonzalez:Roche: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau.

Description: Introduction Hyperdiploidy (HRD) comprises the largest pathogenetic subgroup of myeloma. However, its clinical and molecular characterisation is incomplete. Here, we investigate HRD using a novel high-throughput molecular analysis method (MyMaP - Myeloma MLPA and translocation PCR; Kaiser MF et al., Leukemia 2013; Boyle EM et al., Gen Chrom Canc 2015) in a large cohort of 1,036 patients from the UK NCRI Myeloma XI trial. Materials, Methods and Patients Copy number changes, including gain of chromosomes 5, 9 and 15, as well as translocation status were assayed for 1,036 patients enrolled in the UK NCRI Myeloma XI (NCT01554852) trial using CD138+ selected bone marrow myeloma cells taken at diagnosis. HRD was defined by triploidy of at least 2 of analysed chromosomes 5, 9 or 15. Analysis was performed on standard laboratory equipment with MyMaP, a combination of TC-classification based multiplex qRT-PCR and multiplex ligation-dependent probe amplification (MLPA; MRC Holland). The parallel assessment of multiple loci with copy number alteration (CNA) by MLPA allowed unbiased association studies using a Bayesian approach. Semi-quantitative gene expression data for CCND1 and CCND2 was generated as part of the multiplexed qRT-PCR analysis. Median follow up for the analysis was 24 months. Results Of the 1,036 analysed patients, 475 (46%) were HRD. Of these, 325 (68%) had gain(11q25), 141 (29.7%) gain(1q), 43 (9.1%) del(1p32) and 36 (7.5%) del(17p). Gain(11q25) was significantly associated with HRD (Bayes Factor BF01

Description: Introduction Identifying molecular high risk myeloma remains a diagnostic challenge. We previously reported co-segregation of 〉1 adverse lesion [t(4;14), t(14;16), t(14;20), gain(1q), del(17p)] by iFISH to specifically characterise a group of high risk patients (Boyd et al., Leukemia 2012). However, implementation of this approach is difficult using FISH because of its technical limitations. We recently developed and validated a novel high-throughput all-molecular testing strategy against FISH (MyMaP- Myeloma MLPA and translocation PCR; Kaiser MF et al., Leukemia 2013; Boyle EM et al., Gen Chrom Canc 2015). Here, we molecularly characterised 1,036 patients from the NCRI Myeloma XI trial using MyMaP and validated the co-segregation approach. Materials, Methods and Patients Recurrent translocations and copy number changes were assayed for 1,036 patients enrolled in the NCRI Myeloma XI (NCT01554852) trial using CD138+ selected bone marrow myeloma cells taken at diagnosis. The trial included an intensive therapy arm for younger and fitter and a non-intense treatment arm for elderly and frail patients. Analysis was performed using MyMaP, which comprises TC-classification based multiplex qRT-PCR and multiplex ligation-dependent probe amplification (MLPA; MRC Holland). Median follow up for the analysis was 24 months. Results Adverse translocations [t(4;14), t(14;16), t(14;20)] were present in 18.2% of cases, del(17p) in 9.3%, gain(1q) in 34.5% and del(1p32) in 9.4% of cases. All adverse lesions were associated with significantly shorter PFS and OS by univariate analysis (P 1 adverse lesion, 33.9% had one isolated adverse lesion and 52.6% had no adverse lesion. Presence of 〉1, 1 or no adverse lesion was associated with a median PFS of 17.0, 23.9 and 30.6 months (P =3.0x10-9) and OS at 24 months of 67.9%, 75.0% and 86.0% (P =1.8x10-7), respectively. Del(1p) was associated with shorter PFS and OS for the intensive, but not for the non-intensive therapy arm and was independent of the co-segregation model by multivariate analysis regarding OS (P =0.006). We thus included del(1p) as an additional adverse lesion in the model for younger patients. The groups with 〉1 (19.4% of cases), 1 (31.1%) and no adverse lesions (49.5%) were characterised by median PFS of 19.4, 29.4 and 39.1 months (P =1.2x10-10) and median 24-months survival of 73.8%, 86.4% and 91.5% (P =1.4x10-6), respectively. Hazard Ratio for 〉1 adverse lesion was 3.0 (95% CI 2.1-4.1) for PFS and 3.8 (95% CI 2.2-6.5) for OS. By multivariate analysis, co-segregation of adverse lesions was independent of ISS for PFS/OS in the entire group of 1,036 cases and in the intensive treatment arm. We integrated adverse lesions and ISS into a combined model defining High Risk (〉1 adv les + ISS 2 or 3; 1 adv les + ISS 3) and Low Risk (no adv les + ISS 1 or 2; 1 adv les + ISS 1) and the remainder as Intermediate Risk. The High Risk, Intermediate Risk and Low Risk groups of the total cohort included 11.2%, 41.2% and 41.6% of cases with median PFS of 15.8, 19.8 and 35.2 months (P