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Affiliation 1Muhimbili University of Health and Allied Sciences, Dar es salaam, Tanzania. 2Department of Oncology, University of Oxford, Oxford UK. 3Dar es salaam University College of Education, Dar es salaam, Tanzania. ABSTRACT. Background; SCD constitutes to be a major public health problem in Tanzania. NBS for SCD identify infants with SCD at birth and subsequently enroll them into SCD comprehensive care program and it has been reported to reduce early childhood mortality and morbidity due to SCD and increase life expectancy. There are different methods for Newborn screening for SCD such as HPLC, IEF, DNA analysis, sickle scan and hemotype SC that helps in early detection of SCD and other haemoglobinopathies but we are lacking sufficient information on alternative screening methods that can be used for NBS in Tanzania so this study is aiming at investigating the effectiveness and feasibility of NBS laboratory tests. Aim of the study; To evaluate newborn screening Laboratory assays for sickle cell disease and other haemoglobinopathies in Tanzania. Methodology; This will be a retrospective and prospective study which will be conducted in Dar es Salaam and Mwanza.1000 newborns and 100 children with SCD under five years old will be enrolled. DBS samples will be collected and analyzed by DNA Analysis, sickle scan, Hemotype SC, HPLC, and IEF. SPSS version 16.0 will be used to analyze data. Statistically, significant tests will be declared at a level of p-value < 0.05. Progress: Initially we have conducted a pilot of 12 individuals who were screened for SCD and turned out to be carriers ( Hb AS). However these individuals continuously reported to experience painful events. Initial analysis has include Hb subtyping and quantification by HPLC,Sickle scan and HemotypeSC to ascertain indicator for thalassaemia syndrome. Definitive analysis involved sequencing of thalassaemia and SCD associated regions by using Oxford Nanopore Technology and NGS Expected outcomes; The findings of this study will inform Newborn screening stakeholders on the best point of care screening test and definitive test, in terms of turnaround time and cost. Such findings will assist in planning and scaling up of newborn screening services across the country. Corresponding Author; HChristopher, Email; hchristopher@blood.ac.tz, Tel; +255762175732. Disclosures Schuh: AbbVie: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Speakers Bureau; Kite: Speakers Bureau; Gilead: Speakers Bureau; Seattle Genetics: Speakers Bureau; Jazz Pharmaceuticals: Speakers Bureau; Bristol-Myers Squibb: Research Funding; Janssen: Speakers Bureau; Verastem: Speakers Bureau.

Background Chronic Lymphocytic Leukemia (CLL) is characterised by a highly heterogeneous natural history and treatment response. Indeed, 50% of immunoglobulin heavy chain variable region (IgHV) hypermutated patients have an excellent progression free survival (PFS) after chemoimmunotherapy. Conversely, 25% of FCR treated patients relapse within 24 months (high risk CLL). Recent studies have shown that complex karyotype with or without TP53 disruption predicts for relapse after BCL2 therapy and BTK inhibitors. However, TP53 is the only marker for which routine testing is available. Overall, nearly 80% of patients relapsing after frontline FCR do not present a known poor risk genomic marker. Additional candidate genomic predictors of poor outcome including mutations in coding regions of NOTCH1, SF3B1 and RPS15, non-coding regions of NOTCH1 and enhancer regions of PAX5, telomere length, IgHV status, and DNA Damage Repair (DDR) germline mutations including TP53 and ATM have been reported in CLL. Further, the role of mutational signatures and regions of kataegis also merit additional investigation in progressive CLL. Evaluating all candidate predictors requires complex time consuming, multi-modality testing outside the scope of routine clinical diagnostic practice, however, in isolation, each has low predictive value. Here, we show preliminary data on a novel patient stratification method based on whole genome sequencing (WGS) data incorporating multiple genomic features in a single test. Patients and Methods Tumor (peripheral blood) and germline (saliva) samples were collected from 321 patients from 6 UK trials via the Genomics England CLL pilot: ARCTIC (n=61), AdMIRe (n=64), CLL 210 (n=30), CLEAR (n=12), RIAltO (n=88) and FLAIR (n=66). We performed WGS on the HiSeqX (Illumina). After read alignment, we detected somatic variants using Strelka 2.4.7 for small variants detection (SNV and InDels), Manta 0.28.0 for structural variant (SV) detection, and Canvas 1.3.1 for copy number variant (CNV) detection (Illumina). Non-coding regions were annotated with information from primary CLL, CLL cell lines and B-cell ENCODE databases. Mutational signatures and putative regions of kataegis were calculated based on Alexandrov et al. (Nature, 2013) and Lawrence et al. (Nature, 2013). Telomere lengths were assessed using Telomerecat. Data aggregation was performed using contingency tables combined with non-negative matrix factorization. Results Mean coverage was 94.2X for tumor and 28.5X for germline samples. We found a median of 9172 SNPs/sample after filtering and 2348 indels/sample across 321 patients. High risk CLL was enriched for genomic complexity and poor prognostic mutations. The most frequently mutated genes were SF3B1 (17%), TP53 (13%), NOTCH1 (12%), IGLL5 (12%), and ATM (11%). Analysis of non-coding regions using DNA methylation markers, ATAC-seq and Hi-C revealed potential candidate regions associated with early relapse. Using CNA and SV data, we identified interesting patterns of genomic complexity and structural variants, including a trend towards enrichment of del8p in Relapse/Refractory and FCR non-responders. Additionally, we investigated mutation signatures and kataegis across coding and non-coding regions of the genome. We correlated exonic regions of DDR genes in germline data with clinical outcomes and extended this to genes mutated in both tumor and germline data, termed germline-tumor double-hits. We examined the relationship between the Alexandrov hypermutation signature, IgHV status (determined by % homology to the reference genome) and PFS, and combined mutational density at the Ig locus with mutation signature aiming to predict IgHV status. Finally, we produced a binary contingency matrix, using non-negative matrix factorization to cluster the samples. This method highlighted patient groups with shared genomic profiles. Conclusion We present preliminary data on a patient stratification method derived from WGS of 321 paired germline and CLL trial samples. Our predictive signature includes driver gene mutations, CNAs, IgHV status, genomic complexity, telomere length, overall mutation burden and genes with germline-tumor double-hits. Our comprehensive, NGS-based patient stratification attempts to predict patient outcome in a single sequencing run. Disclosures Becq: Illumina: Employment. He:Illumina: Employment. Ross:Illumina: Employment. Bentley:Illumina: Employment. Pettitt:Celgene: Research Funding; Gilead: Research Funding; Roche: Research Funding; GSK/Novartis: Research Funding; Napp: Research Funding; AstraZeneca: Research Funding; Chugai: Research Funding. Hillmen:Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Research Funding; Celgene: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Schuh:Giles, Roche, Janssen, AbbVie: Honoraria.

Introduction Chronic Lymphocytic Leukaemia (CLL) is the most prevalent leukaemia in the Western world and characterised by clinical heterogeneity. IgHV mutation status, mutations in the TP53 gene and deletions of the p-arm of chromosome 17 are currently used to predict an individual patient's response to therapy and give an indication as to their long-term prognosis. Current clinical guidelines recommend screening patients prior to initial, and any subsequent, treatment. Routine clinical laboratory practices for CLL involve three separate assays, each of which are time-consuming and require significant investment in equipment. Nanopore sequencing offers a rapid, low-cost alternative, generating a full prognostic dataset on a single platform. In addition, Nanopore sequencing also promises low failure rates on degraded material such as FFPE and excellent detection of structural variants due to long read length of sequencing. Importantly, Nanopore technology does not require expensive equipment, is low-maintenance and ideal for patient-near testing, making it an attractive DNA sequencing device for low-to-middle-income countries. Methods Eleven untreated CLL samples were selected for the analysis, harbouring both mutated (n=5) and unmutated (n=6) IgHV genes, seven TP53 mutations (five missense, one stop gain and one frameshift) and two del(17p) events. Primers were designed to amplify all exons of TP53, along with the IgHV locus, and each primer included universal tails for individual sample barcoding. The resulting PCR amplicons were prepared for sequencing using a ligation sequencing kit (SQK-LSK108, Oxford Nanopore Technologies, Oxford, UK). All IgHV libraries were pooled and sequenced on one R9.4 flowcell, with the TP53 libraries pooled and sequenced on a second R9.4 flowcell. Whole genome libraries were prepared from 400ng genomic DNA for each sample using a rapid sequencing kit (SQK-RAD004, Oxford Nanopore Technologies, Oxford, UK), and each sample sequenced on individual flowcells on a MinION mk1b instrument (Oxford Nanopore Technologies, Oxford, UK). We developed a bespoke bioinformatics pipeline to detect copy-number changes, TP53 mutations and IgHV mutation status from the Nanopore sequencing data. Results were compared to short-read sequencing data obtained earlier by targeted deep sequencing (MiSeq, Illumina Inc, San Diego, CA, USA) and whole genome sequencing (HiSeq 2500, Illumina Inc, San Diego CA, USA). Results Following basecalling and adaptor trimming, the raw data were submitted to the IMGT database. In the absence of error correction, it was possible to identify the correct VH family for each sample; however the germline homology was not sufficient to differentiate between IgHVmut and IgHVunmut CLL cases. Following bio-informatic error correction and consensus building, the percentage to germline homology was the same as that obtained from short-read sequencing and nanopore sequencing also called the same productive rearrangements in all cases. A total of 77 TP53 variants were identified, including 68 in non-coding regions, and three synonymous SNVs. The remaining 6 were predicted to be functional variants (eight missense and two stop-gains) and had all been identified in early MiSeq targeted sequencing. However, the frameshift mutation was not called by the analysis pipeline, although it is present in the aligned reads. Using the low-coverage WGS data, we were able to identify del(17p) events, of 19Mb and 20Mb length, in both patients with high confidence. Conclusions Here we demonstrate that characterization of the IgHV locus in CLL cases is possible using the MinION platform, provided sufficient downstream analysis, including error correction, is applied. Furthermore, somatic SNVs in TP53 can be identified, although similar to second generation sequencing, variant calling of small insertions and deletions is more problematic. Identification of del(17p) is possible from low-coverage WGS on the MinION and is inexpensive. Our data demonstrates that Nanopore sequencing can be a viable, patient-near, low-cost alternative to established screening methods, with the potential of diagnostic implementation in resource-poor regions of the world. Disclosures Schuh: Giles, Roche, Janssen, AbbVie: Honoraria.

International audience; Although TP53, NOTCH1, and SF3B1 mutations may impair prognosis of patients with chronic lymphocytic leukemia (CLL) receiving frontline therapy, the impact of these mutations or any other, alone or in combination, remains unclear at relapse. The genome of 114 relapsed/refractory patients included in prospective trials was screened using targeted next-generation sequencing of the TP53, SF3B1, ATM, NOTCH1, XPO1, SAMHD1, MED12, BIRC3, and MYD88 genes. We performed clustering according to both number and combinations of recurrent gene mutations. The number of genes affected by mutation was ≥2, 1, and 0 in 43 (38%), 49 (43%), and 22 (19%) respectively. Recurrent combinations of ≥2 mutations of TP53, SF3B1, and ATM were found in 22 (19%) patients. This multiple-hit profile was associated with a median progression-free survival of 12 months compared with 22.5 months in the remaining patients (P = .003). Concurrent gene mutations are frequent in patients with relapsed/refractory CLL and are associated with worse outcome

SAMHD1 is a deoxynucleoside triphosphate triphosphohydrolase and a nuclease that restricts HIV-1 in noncycling cells. Germ-line mutations in SAMHD1 have been described in patients with Aicardi-Goutières syndrome (AGS), a congenital autoimmune disease. In a previous longitudinal whole genome sequencing study of chronic lymphocytic leukemia (CLL), we revealed a SAMHD1 mutation as a potential founding event. Here, we describe an AGS patient carrying a pathogenic germ-line SAMHD1 mutation who developed CLL at 24 years of age. Using clinical trial samples, we show that acquired SAMHD1 mutations are associated with high variant allele frequency and reduced SAMHD1 expression and occur in 11% of relapsed/refractory CLL patients. We provide evidence that SAMHD1 regulates cell proliferation and survival and engages in specific protein interactions in response to DNA damage. We propose that SAMHD1 may have a function in DNA repair and that the presence of SAMHD1 mutations in CLL promotes leukemia development.

The association between somatic JAK2 mutation and myeloproliferative neoplasms (MPNs) is now well established. However, because JAK2 mutations are associated with heterogeneous clinical phenotypes and often occur as secondary genetic events, some aspects of JAK2 mutation biology remain to be understood. We recently described a germline JAK2V617I mutation in a family with hereditary thrombocytosis and herein characterize the hematopoietic and signaling impact of JAK2V617I. Through targeted sequencing of MPN-associated mutations, exome sequencing, and clonality analysis, we demonstrate that JAK2V617I is likely to be the sole driver mutation in JAK2V617I-positive individuals with thrombocytosis. Phenotypic hematopoietic stem cells (HSCs) were increased in the blood and bone marrow of JAK2V617I-positive individuals and were sustained at higher levels than controls after xenotransplantation. In signaling and transcriptional assays, JAK2V617I demonstrated more activity than wild-type JAK2 but substantially less than JAK2V617F. After cytokine stimulation, JAK2V617I resulted in markedly increased downstream signaling compared with wild-type JAK2 and comparable with JAK2V617F. These findings demonstrate that JAK2V617I induces sufficient cytokine hyperresponsiveness in the absence of other molecular events to induce a homogeneous MPN-like phenotype. We also provide evidence that the JAK2V617I mutation may expand the HSC pool, providing insights into both JAK2 mutation biology and MPN disease pathogenesis.

Background During B-cell development, somatic mutations are introduced into the variable region (V) of Immunoglobulin Heavy (IGH) genes by activation-induced cytidine deaminase (AID). In CLL, the degree of mutation in these regions is tied to clinical outcome, with IgHV hypermutated status (IgHV+, Methods Whole genome sequencing was performed on matched tumour and germline DNA from a cohort of 46 CLL patients, divided into two groups; 16 IgHV+ and 30 IgHV-. Sequence data was generated using the Illumina HiSeq 2500 platform, and somatic variants were generated by Strelka 2.4.7. SNVs were annotated using ANNOVAR (version 2015 Dec 14) and supplemented with information from primary CLL cell lines and B-cell ENCODE databases for the non-coding regions. Kataegis was identified based on the methods of Lawrence et al. (Nature, 2013) and Alexandrov et al. (Nature, 2013). Mutation signatures were analysed according to Alexandrov et al. (Nature, 2013). Results We identified a total of 64,420 high confidence somatic SNVs from 46 samples (mean=1400), of which 44% were from the IgHV+ cohort (mean=1680) and 56% from IgHV- (mean=1237). Of these; SNVs in coding regions (exons, introns, UTRs) occurred at significantly higher proportions in IgHV- patients (P=0.0004, Fishers Exact test). Mutations in predicted active DNAse hypersensitivity regions and H3k27 acetylated regions, however, were significantly more likely to occur in IgHV+samples (P Mutational signature analysis revealed three distinct signatures shared between the two cohorts. Two of these (Tsig1 and Tsig2) clustered with Alexandrov signature 1A, and the third to signature 1B (Tsig3), both of which were designated as ageing signatures. Despite this, our signatures significantly correlated with the proportion of mutated AID (P A total of 53 kataegis regions were identified across all patients, of which three were found on chromosomes 2, 14 and 22, corresponding to the IG loci. Coding mutation hotspots were located in known CLL driver genes, including TP53, ATM, IKZF3 and SF3B1. Non-coding recurrent hotspots caused by AID were found to predominately affect promoter and enhancer regions of key B-cell pathways, including BCL6, BCL2, BTG2, IGLL5, and PAX5. This observation is closely linked to the IgHV status; the IgHV+ cases frequently harboured mutated non-coding variants in genes involved in B cell signalling, whilst IgHV- cases were more likely to contain exonic driver mutations. Kataegis analysis also revealed novel non-coding mutations in recurrently mutated genes that were common in IgHV- cases, including CDK6 and BIRC3, and a non-coding RNA region on chromosome 9 that was hypermutated only in IgHV-cases. Conclusion Here, we present a whole genome sequencing study on 46 patients divided into two cohorts of IgHV+ and IgHV-. WGS revealed distinct changes in mutation distribution and signatures between these cohorts; differences that are mirrored in both the recurrently mutated gene profiles, and the regions of somatic hypermutation. We demonstrate that mutational differences in IgHV+ and IgHV- patients extend far beyond the IgHV regions and the 1% of the coding genome. This study paves the way for future work into understanding the genomic differences between these cohorts and thus, contribute to increasing our understanding of the molecular mechanisms underlying the different clinical outcomes. Disclosures Hillmen: Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Research Funding.

Abstract 1383 Explorative genome-wide next-generation sequencing of leukaemias and lymphomas has revealed a wide spectrum of acquired mutations and considerable tumour heterogeneity that might be responsible for disease initiation, resistance to treatments and relapse. There is, therefore, a clinical need to identify these genetic abnormalities in a diagnostic setting. Here, we present the development and validation of a targeted next generation mutation analysis tool. To compare the distribution pattern of genetic abnormalities in chronic lymphocytic leukemia (CLL), we performed targeted deep sequencing on CLL samples using a TruSeq custom designed targeted amplicon assay (TSCA, Illumina). We reveal differential mutation distribution patterns depending on clinical CLL subgroups. The TSCA panel was designed to amplify 21 genes (table 1) with known or suspected links to either the development of CLL or as response predictors, including TP53, SF3B1 (Puente, Nature, 2011; Quesada et al, 2012) and NOTCH1 (Rossi, Blood, 2012). Where genes have known mutational hotspots in CLL, only these regions were included in our panel, for example exons 5–8 of TP53. For genes such as MAP2K1, where mutations are distributed throughout the coding region, every exon was targeted. In total, we were able to design an amplicon panel able to cover 99% of our desired 36,035bp target region. Table 1. List of genes included in CLL custom amplicon panel ASXL1 ATM CHD2 DDX3X FBXW7 HMCN1 IRF4 KLHL6 LRP1B MAP2K1 MAPK1 MED12 NOTCH1 PCLO POT1 SAMHD1 SF3B1 TP53 XPO1 ZFPM2 ZMYM3 In order to validate our approach, we used samples previously subjected to whole genome sequencing as controls. Of the 13 individual mutations in the control cohort, we were successfully able to detect 10 (77%) with our custom assay to an average depth of 1380x. A 19bp deletion in TP53 failed to be picked up by the variant calling software, and 2 point mutations in ATM were not detected due to the targeted nature of the assay. There was a single false positive mutation across all samples in ZFPM2, caused by a sequencing error in a homopolymer region. The sample group consisted of 45 representative CLL cases, split into two cohorts. The first cohort consisted of 11 cases that have yet to receive any treatment, whilst the second cohort comprised 34 relapsed/refractory cases. Analysis of further samples is in progress. We performed library preparation according to the manufacturers instructions. Each sample was dual indexed with two 8bp “barcodes” prior to equimolar pooling, and the final pooled library was processed on an Illumina MiSeq instrument using the TruSeq 2×150bp paired end sequencing protocol. The run produced 1.6Gb of passed filter sequence data, with 92.8% of above the quality threshold of Q30. The average depth of coverage across all samples was 849x. Primary analysis of the sequencing data was performed using the cloud based data analysis package from Illumina, which carried out the alignment and variant calling. A conservative quality score threshold of >99 was set, with all variants above this carried forward for further analysis. Our custom amplicon panel detected mutations in 35 of the samples, comprising 8 indels and 45 point mutations. Of the 54 mutations, 40 were missense, 8 were frame-shifts, 1 was a nonsense mutation and 5 are predicted to have functional effects on splicing domains. The most frequently mutated gene was TP53, followed by SF3B1, PCLO and NOTCH1 (figure 1). Fig 1 Frequency of genes with somatic mutations in our CLL cohort. Fig 1. Frequency of genes with somatic mutations in our CLL cohort. Importantly, there was good correlation between mutation allele frequencies from whole genome sequencing, targeted deep sequencing and TSCA, demonstrating that the high sensitivity of large-scale genome sequencers can be reliably applied in a diagnostic setting. We describe mutation hotspots and mutation distribution patterns and link them to clinical behaviour. For example: SF3B1 mutations occurred in 15% of patients and were linked to reduced progression free survival. In conclusion, our technique allows for rapid mutation detection of the most frequently mutated genes in CLL. Further refinements in amplicon design and variant calling will lead to added precision. TSCA design and validation for other haematological diseases is in progress. Disclosures: No relevant conflicts of interest to declare.

Chronic lymphocytic leukemia is characterized by relapse after treatment and chemotherapy resistance. Similarly, in other malignancies leukemia cells accumulate mutations during growth, forming heterogeneous cell populations that are subject to Darwinian selection and may respond differentially to treatment. There is therefore a clinical need to monitor changes in the subclonal composition of cancers during disease progression. Here, we use whole-genome sequencing to track subclonal heterogeneity in 3 chronic lymphocytic leukemia patients subjected to repeated cycles of therapy. We reveal different somatic mutation profiles in each patient and use these to establish probable hierarchical patterns of subclonal evolution, to identify subclones that decline or expand over time, and to detect founder mutations. We show that clonal evolution patterns are heterogeneous in individual patients. We conclude that genome sequencing is a powerful and sensitive approach to monitor disease progression repeatedly at the molecular level. If applied to future clinical trials, this approach might eventually influence treatment strategies as a tool to individualize and direct cancer treatment.

Introduction: Chronic Lymphocytic Leukemia (CLL) is characterized by a heterogeneous clinical course. Currently, the mutational status of the immunoglobulin heavy chain variable (IgHV) region defines 2 risk groups: patients with ≥ 2% difference from the germline are considered as unmutated (UM) and have a poor prognosis while the opposite is observed for mutated (M) patients (Hamblin et al, 1999). Until now, clonality has been determined using PCR/gel electrophoresis and the percentage of IgHV mutations by Sanger sequencing using the Biomed-2 method (van Dongen, Leukemia 2003) which only allows for analysis of the major clone and assumes that only one clone per patient should be considered. Methods: in the present study, we sequenced the IgHV gene for 200 CLL patients with a median follow-up of 70 months (range, 1-309) by next-generation (NGS) and Sanger sequencing (SS) and investigated the impact on prognosis for the different subgroups. Briefly, 100ng of cDNA generated from RNA extracted from highly purified CD19+ cells obtained at diagnosis was amplified using IGH LEADER master mixes. For SS, clonality of PCR product was determined and monoclonal samples were directly sequenced. For NGS, PCR products were purified using magnetic beads, normalized and pooled to create a library for sequencing using the MiSeq v3 Reagent kit (600 cycles). Sequencing data was analyzed using LymphoTrack™ bioinformatics software and percentage of clone was based on the first 200 most abundant clones detected. Clones with an abundancy of < 2.5% were not considered. The IMGT database was used to calculate the percentage of mutation compared to germline. Results: Using SS, 49% (98/200) of patients were IgHV M, 38% (76/200) UM, while 13% (26/200) were polyclonal and further Sanger sequencing was inconclusive. Concordance between SS and NGS was 98.3%: for 90.2%, the major clone detected by NGS was the same by SS, for 8.5% the clone was the same but the percentage mutated compared to germ-line differed slightly with a median error of 0.6%, while for 1.7%, SS detected another clone which was less abundant by NGS. Interestingly, among patients considered as monoclonal by SS, 25.3% (44/174) were found to be polyclonal by NGS. NGS revealed that 35% (70/200) of patients display different IgHV re-arrangements in the same patient: the median frequency of the first two most abundant clones were 78.2% (range, 28.5-94.9) and 16.4% (range, 2.5-49.0) respectively. This implies that at least in these patients, leukemia-initiating events must occur prior to IgHV re-arrangement in a pro-B cell. Further in-depth studies of the HSC and early B cell progenitor compartments in these patients will be required to confirm these observations. In terms of prognosis, M, UM and polyclonal patients determined by SS had a median treatment-free survival (TFS) of 178, 29 and 129 months respectively (P309, 183 and >309 months (P251 (a), 178 (b), 56 (c) months (P=0.0014). Similar results were observed for SS-UM patients who were divided in 3 subgroups with a median TFS of 94 (c), 24 (d), and 19 (e) month (P=0.0296). When all patients where considered, IgHV-NGS classification stratified patients in 5 different subgroups with median TFS of >251 (a), 178 (b), 57 (c), 24 (d), 19 (e) months (P309, >309, 183, 88 months (P Conclusions: determination of IgHV mutational status by NGS has excellent concordance with classical SS and in addition enables the detection of small clones which has a significant impact on prognosis. This allows the analysis of all clones without labor intensive manipulations especially for polyclonal patients. Here we showed for the first time that one third of CLL patients present with multiple IgHV subclones that impact on prognosis and refine the previous SS-IgHV classification. Figure 1. Figure 1. Disclosures Schuh: Acerta Pharma BV: Research Funding.

Background Historically diagnosis and prognosis of myeloid disorders including acute myeloid leukemia (AML) have been determined using a combination of morphology, immunophenotype, cytogenetic and more recently single gene, if not single mutation, analysis. The introduction of NGS technology has resulted in an explosion in the quantity of mutation data available. However, the feasibility and utility of NGS technology with regards to decision-making in routine clinical practice of myeloid disorders is currently unknown. We therefore developed an advanced NGS tool for simultaneous assessment of multiple myeloid candidate genes from low amounts of input DNA and present clinical utility analysis below. Methods We designed a targeted resequencing assay using a TruSeq Custom Amplicon panel with the MiSeq platform (both Illumina) consisting of 341 amplicons (~56 kb) designed around exons of genes frequently mutated in myeloid malignancies (ASXL1, ATRX, CBL, CBLB, CBLC, CEBPA, CSF3R, DNMT3a, ETV6, EZH2, FLT3, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PDGFRA, PHF6, PTEN, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1, WT1 & ZRSR2). Filtering, variant calling and annotation were performed using Basespace and Variant Studio (Illumina) with additional indel detection achieved using Pindel. A cohort of samples previously characterised with conventional techniques was used for validation and the lower limit of detection established using qPCR. Post-validation, DNA from 152 diagnostic blood or bone marrow samples from patients with confirmed or suspected myeloid disorders; both AML (n=46) and disorders with the potential to transform to AML i.e. myelodysplasia (confirmed n=54, suspected n=10) and myeloproliferative neoplasms (n=42), were analysed using this assay. To gather clinical utility data we developed a reporting algorithm to feed back information to clinicians; only those variants with a variant allele frequency (VAF) of >10% and described as acquired in publically available databases were reported with the exception of novel mutations predicted to result in a truncated protein. Further utility data was obtained using published mutation algorithms to determine the proportion of patients in whom mutation data altered prognosis. Results In the validation cohort, initial concordance for detection of clinically significant mutations was 88% rising to 100% once Pindel was used to identify FLT3 ITDs. The lower limit of detection was 3% VAF, and mean amplicon coverage was 390 reads. Using our reporting algorithm 66% of patients in the post-validation cohort had a suspected pathogenic mutation relevant to a myeloid disorder, rising to 74% in patients with confirmed diagnoses. The median number of reported variants per sample for all diagnoses was one (range 0-6). When mutation data for patients with AML with intermediate risk cytogenetics was analysed using the algorithm of Patel et al (N Engl J Med. 2012;366:1079-1089), 4/22 (18%) moved into another risk category. A further two patients had double CEBPA mutations, improving their prognosis. Identification of complex mutations in KIT exon 8 in 2/6 patients with core binding factor AML resulted in more intensive MRD monitoring due to the increased risk of relapse. Interpretation of mutation data for patients with confirmed myelodysplasia using the work of Bejar et al (N Engl J Med. 2011;364:2496-2506) revealed 13/54 (24%) had a high risk mutation independently associated with poor overall survival. 2/8 (25%) patients with chronic myelomonocytic leukemia and 1/12 (8.3%) patients with primary myelofibrosis had high risk ASXL1 exon 12 mutations, independently associated with a poor prognosis. Among suspected diagnoses confirmatory mutations were found in 2/19 (11%), while the absence of mutations reduced the probability of myeloid disease in 11/19 (58%), in some cases sparing elderly patients invasive bone marrow sampling. A further 20 patients had clinically relevant mutations. Conclusions The NGS Myeloid Gene Panel provided extra information to clinicians in 57/152 patients (38%) helping inform diagnosis, individualize disease monitoring schedules and support treatment decisions. The targeted panel approach requires rigorous validation and standardisation in particular of bio-informatics pipelines, but can be adapted to incorporate new genes as their relevance is described and will become central to treatment decisions. Disclosures No relevant conflicts of interest to declare.

Background Chronic lymphocytic leukaemia (CLL) is characterised by clinical and biological heterogeneity. Despite significant advances in therapeutic management, CLL remains largely incurable. Current risk stratification is based on cytogenetic features (del(17p), del(11q), del(13q), +12). So far, sequencing studies in CLL have focussed predominantly on the exome. These have identified a number of genes that are recurrently mutated at low frequency such as TP53, SF3B1, ATM, NOTCH1, MYD88, and BIRC3. Apart from TP53 abnormalities, none of these are currently used to guide clinical decisions and it is unclear how they are implicated in disease pathogenesis. Methods In this study, we sought to further refine the molecular landscape of CLL using whole genome sequencing (WGS) of paired tumour and germline DNA samples from a cohort of clinically annotated patients with CLL. We sequenced a heterogeneous cohort of 41 samples (25 males, 16 females, median age 69 (range 49-94)) with a range of clinical features (49% fludarabine refractory, 61% unmutated IgVH). Whole genome sequencing libraries were generated using the Illumina TruSeq PCR-free sample preparation kit, with a median insert size of 400bp, and subjected to 100bp paired-end sequencing on an Illumina HiSeq 2500 platform. Both tumour and germline libraries were sequenced to an average depth of 38x. Sequencing reads were aligned using the Isaac algorithm and the Starling and Strelka algorithms were used for SNV and Indel calling in germline and tumour samples respectively. All variants with a read depth Results Whole genome sequencing revealed a total of 95,305 somatic indels and base substitutions, averaging 30.8 per patient (range 7-57) or 0.3 mutations per megabase. Of these mutations, 1266 occur in protein coding regions across 1108 genes, including 556 in 3’ and 5’ untranslated regions. Of these 1108 genes, we identified 93 as recurrently mutated (mutations present in more than one sample), including the previously described SF3B1 (12/41, 29.3%), TP53 (9/41, 22%), ATM (6/41, 14.6%), NOTCH1 (6/41, 14.6%), FAT1 (4/41, 9.8%) and BIRC3 (2/41, 4.9%). In addition to FAT1, we also identified two missense mutations in another cadherin superfamily member, FAT4(2/41, 4.9%), both occurring within the extracellular cadherin domains. Missense mutations were the most frequent (42.7%) followed by those in 3’ UTRs (36.1%), 5’ UTRs (7.7%), splice sites (6.1%), small indels (4.3%) and nonsense mutations (3.1%). In addition, 61.5% of missense mutations were identified as either deleterious or damaging by the SIFT or PolyPhen-2 algorithms. We used a modified version of the MutSigCV algorithm to identify genes with significantly higher mutation rates in the coding sequence. A similar statistical approach was used to identify significant mutations in untranslated regions. Importantly, a number of interesting candidate genes carried mutations in non-coding regions, including NFKBIZ (3/41, 7.3%), IGLL5 (3/41, 7.3%) and BCL2(2/41, 4.9%). Conclusion To our knowledge, this is the largest whole genome sequencing study in CLL so far. We present a comprehensive catalogue of genomic alteration in CLL and associate genome-wide patterns, including the presence of subclones, with clinical outcome. In addition to demonstrating the heterogeneous nature of the CLL genome, our data highlights the variety of mutations present in the regulatory regions of genes as well as structural variations, thus providing new insights for hypothesis-driven biomarker and therapeutic discovery. Disclosures Humphray: Illumina Cambridge Ltd: Employment. Becq:Illumina Cambridge Ltd: Employment. Bentley:Illumina Cambridge Ltd: Employment.

Background:Historically, the identification of minimal deleted regions (MDRs) has been a useful approach for pinpointing genes involved in the pathogenesis of human malignancies and constitutional disorders. Microarray technology has offered increased capability for newly identifying or refining existing MDRs and minimal overlapping regions (MORs) in cancer. Despite this, in chronic lymphocytic leukemia (CLL), published MORs that pinpoint only a few candidate genes have been limited and with the advent of NGS, the utility of high resolution array work as a discovery tool has become uncertain. Here, we show that profiling copy number abnormalities (CNAs) and cnLOH using arrays in a large patient series can still be a valuable approach for the identification of genes that are disrupted or mutated in CLL and have a role in CLL development and/or progression. Methods: 250 CLL patient DNAs from individuals enrolled in two UK-based Phase II randomised controlled trials (AdMIRe and ARCTIC trials) were tested using Infinium HumanOmni2.5-8 v1.1 according to manufacturer’s guidelines (Illumina Inc, San Diego, CA). Data were processed using GenomeStudioV2009.2 (Illumina Inc.) and analysed using Nexus Discovery Edition v6.1 (BioDiscovery, Hawthorne, CA). All Nexus plots were inspected visually to verify calls made, identify uncalled events and exclude likely false positives. To exclude common germline CNVs, the Database of Genomic Variants (DGV), a comprehensive catalog of structural variation in control data, was used. Copy number (CN) changes that encompassed fully changes noted in the DGV were excluded from further analysis. Regions of copy neutral loss of heterozygosity (cnLOH) were recorded if >1Mb in size, but were not used to define or refine MORs. Data from 1275 age-appropriate control samples minimised the reporting of common cnLOH events. All genomic coordinates were noted with reference to the GRCh37, hg19 assembly. MORs were investigated using Microsoft Excel filtering functions. A subset of genes (n=91) selected from MORs mainly on the basis of event frequency and/or number of genes within the MOR and/or literature interest were taken forward for targeted sequencing (exons only) of appropriate samples with/without CN Losses or cnLOH (Set 1 n=124; Set 2 n=126). These were tested using custom designed TruSeq Custom Amplicon panels (Illumina Inc) and processed according to manufacturer’s instructions. SAMHD1 was excluded from these panels since it had been studied separately within our laboratory. The data were analysed using an in-house bioinformatics pipeline that uses the sequence aligners MSR and Stampy and the variant callers GATK and Platypus, followed by stringent filtering. Results: Using our datasets we have identified >50 MORs previously unreported in the literature. Six of these showed copy number (CN) losses in >3% of patients studied. Furthermore, we have refined 14 MORs that overlapped with regions described previously and that had also a CN loss frequency of >3%. Thirteen MORs involved only a single reference gene, often a gene implicated previously in cancer (eg. SAMHD1, MTSS1, DCC and RFC1). Of the 91 genes taken forward for targeted sequencing, stringent data filtering led to a subset of 19 genes of interest harbouring exonic mutations. Genes with mutations identified include DCC, BAP1 and FBXW7, also implicated previously in cancer. Conclusion: We have generated high resolution CNA and cnLOH profiles for 250 first-line chemo-immunotherapy treated CLL patients and used this information to document newly identified MORs, to refine MORs reported previously and to identify mutation harbouring genes using targeted NGS. Functional knowledge supports our hypothesis that these genes may have a contributory role in CLL. For two genes, SAMHD1 and FBXW7, relevance in CLL has been established already. Taken together, our data validate the utility of high resolution arrays studies for the identification of candidate genes that may be involved in CLL development or progression when disrupted. Further studies are required to confirm a role for these genes in CLL and to elucidate the nature of the underlying biological mechanisms. Disclosures No relevant conflicts of interest to declare.

Background: Previous studies using next-generation sequencing (NGS) have led to the identification of a number of genes mutated frequently in CLL. Recent publications focus on the most recurrently mutated genes (TP53, SF3B1 and NOTCH1) which tend to be mutually exclusive. Large series of untreated patients have shown that these mutations have a prognostic impact. Relapse may be associated with more frequent mutational events. Further investigation of relapsed CLL genomes within a clinical trial setting using a comprehensive NGS gene panel is required. Methods: Using targeted NGS we determined the mutational spectrum of 118 refractory/relapsing CLL patients enrolled in one French and two UK prospective trials (ICLL01 from the French intergroup GCFLLC/MW-GOELAMS, NCRNCLL201, NCRNCLL202 respectively). Eighty percent of patients had an unmutated IGHV status and 21 (18%) patients carried a 17p deletion. Sequencing libraries were composed of a panel of nine recurrently mutated genes in CLL (i.e.TP53, SF3B1, ATM, NOTCH1, XPO1, SAMHD1, MED12, BIRC3 and MYD88) and run on the Illumina MiSeq instrument (Illumina Inc). On average 14.1 M reads were obtained per run of which 96.8% were identified reflecting an acceptable signal to noise ratio. Yield was 4.1 Gb and 95.9% of reads were above Q30 across 6 MiSeq runs. Data was analysed using our in-house bioinformatics pipeline consisting of a combination of two different aligners (Custom Amplicon Alignment, Illumina Inc and Stampy, Wellcome Trust centre for Human Genetics), two variant callers (GATK, Broad Institute and Platypus, Wellcome Trust centre for Human Genetics) and a stringent filtering process in order to detect SNVs and indels with a variant allele frequency down to 7%. Results: We identified a total of 196 mutations (mean=1.7/sample) in 95 (80%) patients: 138 missense mutations, 41 substitutions/indels, 12 nonsense and 5 splicing mutations. TP53, SF3B1 and ATM mutations occurred frequently in 29 (24.6%), 33 (28%) and 29 (24.6%) patients, respectively. Eighteen (15.3%) patients harbored a NOTCH1 mutation matching the range of reported frequency. Mutations in the other genes sequenced were distributed as follows: XPO1 mutations in 17 (14.4%), SAMHD1 mutations in 12 (10.2%), MED12 mutations in 10 (8.5%), BIRC3 mutations in 6 (5.1%) and MYD88 mutations in 3 (2.5%) patients. Twenty-three (20%) patients did not have any mutations present (Figure 1, cluster #1). A total of 51 (43%) patients had one gene mutated (Figure 1, cluster #2) and the remaining 44 (37%) patients had two or more genes mutated (Figure 1, clusters #3 & #4). Recurrent combinations of mutations (affecting more than 5% of patients) were found in a group of 23 (20%) patients. These combinations of mutations comprised of at least two of the following genes: TP53, SF3B1 and ATM (Figure 1, cluster #3, so called multiple-hit (MH) profile). Remarkably, mutations in these 3 genes were found significantly more frequently associated than in isolation. We then investigated the potential clinical relevance of the MH profile. This profile was associated with poorer ORR than the remaining cohort (43% vs 80%, P Conclusion: The mutational landscape of relapsing CLL is marked by a group of patients with combined mutations of the TP53, ATM and SF3B1 genes (multiple-hit profile) and is associated with an adverse prognostic impact. In addition to TP53 and SF3B1, ATM should be sequenced at relapse to predict outcome and guide subsequent therapeutic intervention. Further studies are required to confirm these findings and to understand the subclonal distribution of these mutations. Figure 1 Figure 1. Disclosures Hillmen: Pharmacyclics, Janssen, Gilead, Roche: Honoraria, Research Funding. Tournilhac:mundipharma: Honoraria, Other, Research Funding; GSK: Honoraria, Other, Research Funding; Roche: Honoraria, Other, Research Funding.

Background: Major progress has been made in understanding disease biology and therapeutic options for patients with chronic lymphocytic leukaemia (CLL). Recurrent mutations have been discovered using next generation sequencing, but with the exception of TP53 disruption their potential impact on response to treatment is unknown. In order to address this question, we characterised the genomic landscape of 250 first-line chemo-immunotherapy treated CLL patients within UK clinical trials using targeted resequencing and whole-genome SNP array. Methods: We studied patients from two UK-based Phase II randomised controlled trials (AdMIRe and ARCTIC) receiving FCR-based treatment in a first-line treatment setting. A TruSeq Custom Amplicon panel (TSCA, Illumina) was designed targeting 10 genes recurrently mutated in CLL based on recent publications.Average sequencing depth was 2260X. The cumulated length of targets sequenced was 7.87 kb from 330 amplicons covering 160 exons. Alignment and variant calling included a combination of three pipelines to confidently detect SNVs, indels and low level frequency mutations. SNP array testing was performed using HumanOmni2.5-8 BeadChips, (Illumina) and data analysed using Nexus 6.1 Discovery Edition, Biodiscovery. We performed targeted resequencing and genome-wide SNP arrays using selected samples’ germline material to confirm somatic mutations (n=40). Univariate and multivariate analyses using minimal residual disease (MRD) as the outcome measure were performed for 220 of the 250 patients. Results: Pathogenic mutations were identified in 165 (66%) patients, totalling 268 mutations in 10 genes. ATM was the most frequently mutated gene affecting 67 patients (29%) followed by SF3B1 (n=56, 24%), NOTCH1 (n= 32, 14%), TP53 (n= 21, 9%), BIRC3 (n= 17, 7%) and XPO1 (n=14, 6%). Less frequently recurrent mutations were seen in SAMHD1 (n=8, 3%), MYD88 (n= 4, 2%), MED12 (n=7, 3%) and ZFPM2 (n=5, 2%). Integrating sequencing and array results increased the patients with one or more CLL driver mutation from 66% to 94%. As previously reported del17p and TP53 mutations are co-occurring and associate with MRD positivity in all cases (n=15, p=0.0002). We report on minor TP53 subclones in 11 patients (VAF 1-5%), 8 of whom have MRD data available and were also associated with MRD positivity. Deletions of 11q were present in 44 patients. These lesions always included ATM but not always BIRC3. Bialleleic disruption was present in ATM for 27 patients (significantly associated with MRD positivity) and in BIRC3 for 4 patients. Rather surprisingly, trisomy 12 (n=33) and NOTCH1 mutations (n=28) were associated with MRD negativity (p=0.006 and 0.097, respectively). Analysing clonal and subclonal mutations per gene revealed the majority of mutations in SF3B1 and BIRC3 were subclonal (65% and 87% respectively). In contrast almost all SAMHD1 and MYD88 mutations were clonally distributed. There was an association between NOTCH1 subclonal mutations and MRD negativity, compared to clonal mutations, but this difference was not seen in the remaining mutated genes. From our copy number data, the presence of subclones was associated with MRD positivity (p=0.05). Combining important lesions in a multiple logistic regression analysis to predict MRD positivity, bialleleic ATM disruption, together with TP53 disruption, were the strongest predictors, followed by SAMHD1, whereas BIRC3 monoalleleic mutations were a medium predictor for MRD negativity. Conclusion: This is the first integrated genome-wide analysis of the distribution and associations of CLL drivers, using targeted deep resequencing and whole genome SNP arrays in an FCR-based first-line treatment setting. We have shown subclonal and clonal mutation profiles in all patients. For patients with two or more CLL-associated mutations we have begun to unravel clonal hierarchies. We have developed a comprehensive model using MRD as an outcome measure and have found bialleleic ATM mutations and SAMHD1 disruption to strongly predict for MRD positivity. Using MRD status as a robust proxy for PFS not only enables us to confirm results of previous studies, but is advantageous also in considerably reducing the timeframe for results. Indeed, we suggest that MRD status should be assessed routinely in future studies to complement modern integrated genomics approaches. Disclosures Hillmen: Pharmacyclics, Janssen, Gilead, Roche: Honoraria, Research Funding.

Abstract 713 Chronic lymphocytic leukaemia (CLL) has a highly variable clinical course. Recent whole genome sequencing (WGS) data reflects this heterogeneity revealing low level recurrent somatic mutations (Puente Nature 2011, Quesada Nat Gen 2011, Wang NEJM 2011, Schuh Blood 2012). Our WGS study of sequential samples from 3 patients revealed candidate founder mutations that were present in all cells at all time-points. We focus on one of the genes affected by founder mutations; SAMHD1. SAMHD1 has been identified as an anti-viral restriction factor that targets HIV-1 by blocking reverse transcription of viral RNA (Laguette Nature 2011, Hrecka Nature 2011). The recently elucidated triphosphohydrolase activity of SAMHD1 leads to depletion of deoxynucleotide triphosphates (dNTP) during reverse transcription, thus interrupting the viral replication cycle before integration into the genome (Goldstone Nature 2011). In constitutional disease, recessive mutations in SAMHD1 have been implicated in deregulation of the innate immune response and development of a congenital autoimmune encephalopathy, Aicardi–Gouti ères syndrome (AGS) (Crow Hum Mol Gen 2009). In our single institutional cohort of 100 1st line and relapsed CLL patients we identified 8 patients with acquired mutations in SAMHD1, of which 6 were chemorefractory (Table 1). This is much higher than the expected frequency of 25% chemorefractory patients in this cohort (Knight Leukemia 2012), implying a correlation between SAMHD1 mutations and poor outcome. In order to precisely establish the incidence of SAMHD1 mutations in patients requiring 1st line treatment, we sequenced 200 samples from patients recruited into first line UK clinical trials. We determined a mutation frequency of 3% (Table 1). Whole genome SNP arrays on our SAMHD1 mutated patients reveals monoalleleic deletions or copy neutral loss of heterozygosity at the SAMHD1 locus in 14 of 15 samples. TABLE 1: SAMHD1 mutated patients Sample Age IgHV mutation TP53 disruption Clinical Status Mutation 1 72 U Neg Pre Treatment c.-166G>T 2 72 M Neg Refractory M1K K523X 3 NK U Neg Refractory Y155C 4 65 U Neg Refractory R145X 5 NK NK NK Pre Treatment R145Q 6 63 U Neg Pre Treatment I136T 7 77 M Neg Refractory E355K 8 68 U Neg Refractory L431S 9 72 U Neg Refractory F545L 10 NK NK NK Pre Treatment W572X 11 69 NK NK Pre Treatment N/A 12 66 M Pos Refractory T365P 13 NK NK Neg Pre Treatment R371H 14 77 M Neg Refractory N/A 15 25 NK Neg AGS N/A U=Unmutated, M=Mutated. Next, we questioned whether patients with congenital SAMHD1 mutations are more susceptible to developing B-cell malignancies. We reviewed 20 patients with AGS and homozygous SAMHD1 mutations. Intriguingly, 2 of these patients have developed a B-cell malignancy. One of these patients presented at 1 month of age with features typical of AGS and has been subsequently diagnosed with CLL at the age of 25. Sequencing the SAMHD1 locus of both germline and CLL cells from this patient confirmed the homozygous 1609-1G4C mutation. We screened the patient's CLL cells for acquired mutations recently found to be recurrent in CLL. None of these genes were mutated suggesting the SAMHD1 germline mutation was sufficient to cause CLL. In addition, whole exome analysis is in progress for a more complete view of acquired mutations potentially contributing to CLL pathogenesis. To evaluate the interplay of recurrent somatic mutations in CLL in the context of our SAMHD1 mutations, we used a custom designed targeted sequencing panel (TruSeq Custom Amplicon, Illumina). SAMHD1 mutations were found exclusively in SF3B1 negative patients. Only one SAMHD1 patient had a TP53 mutation. To begin to functionally define the role of SAMHD1 mutations in CLL, we examined the impact of SAMHD1 mutations on SAMHD1 mRNA gene expression by quantitative PCR analysis of purified CLL cells and normal B cell controls. Expression in the mutated CLL cells was significantly lower compared to normal B cells. From this, we hypothesise that CLL cells with SAMHD1 mutations might show an increase in intracellular dNTP levels. We are currently evaluating the levels of dNTPs using a custom designed qPCR to measure dNTP incorporation onto template DNA. In conclusion, we provide the first evidence that the lentiviral restriction factor and dNTP triphosphohydrolase SAMHD1 acts as a tumour suppressor in human B cells. We propose that deregulation of the dNTP pool in B cells caused by mutations in SAMHD1 might contribute to lymphomagenesis. Disclosures: Ross: Illumina: Employment. Bentley:Illumina: Employment. Hillmen:Alexion Pharmaceuticals, Inc: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract 3590 Genome-wide array or sequencing analyses are powerful tools for identifying genetic aberrations in cancers including leukaemias. However, the majority of these aberrations are likely to be random passenger events that do not drive clonal expansion. Currently, it is unknown whether cancers are maintained by a finite set of recurrent mutations similar for each patient or whether and to what extent malignancies are ‘personalised’, and also how molecular disease drivers evolve over time in the context of clinical intervention. The answers to these questions will determine whether future treatment modalities must be tailored according to individual and dynamic cancer characteristics. We hypothesized that differential quantitative high-resolution genome-wide array analysis of sequential samples from the same patients before treatment and at subsequent relapse would have the potential to identify emerging structural abnormalities with relevance to disease progression and/or response to treatment in a given patient. In order to test this hypothesis, we chose B-cell chronic lymphocytic leukaemia (CLL), because of its unique clinical characteristics, as our model to begin to evaluate the potential role of ‘companion diagnostics’ for this condition. We analysed DNA samples of 80 patients with CLL using a 1 million high resolution SNP array. On 34 of them, sequential pre-treatment and relapse samples were available. The raw data was analysed using the OncoSNP analysis tool designed in-house specifically for cancer samples as it enables quantification of copy number alterations (CNA) and copy neutral loss of heterozygosity (cnLOH) based on B-allele frequency plots in complex mixtures. This allows low levels of aberrations to be detected and for mosaic samples to be identified. Results were compared against the data from the Wellcome Trust Case Control Consortium, the DGA and germline DNA in selected cases. Large CNAs (>1Mb) and cnLOH (>5Mb) without deletions of 11q22.3 or 17p13.1 were identified in a third of patients. These patients had an intermediate clinical risk score that increased with the number of large CNAs. SNP array demonstrated clonal evolution in 32% of patients in the sequential sample cohort. These consisted of extension of the 13q abnormality (2), loss of the 13q deletion (1), a 10q23.1-q25.1 deletion (1), gain of 2pter-p14 (1), deletion of 2q33.1-q36.3, (1) a heterozygous deletion of 2q37.1 (1), gain of 8q22.2-qter (1), deletion of 8p (1), amplification of 8q (1), deletion of 8q (1), loss of 16p13.3 (2), mosaic deletion of 17q11.2 (1), an expansion of chromosomes carrying a 19p13.2-p13.11 gain and a 19p13.11 loss (1), deletions within 3p (1), conversion of a gain of 12p12.2-q21.31 to a copy neutral loss of heterozygosity (cnLOH) (1), deletion of 17pter-13.1 (1), increased proportion of chromosomes with the 7q33–34 deletion (1), expansion of cnLOH for 20q11.22-qter (1) and an increased number of cells with a deletion of 2q22.2-q24.1 (1) found at relapse. Importantly, most CNAs occurring at relapse were recurrent in the entire cohort implying that these are non-random events that are important in disease progression. Analysis of the minimal deleted region (MDR) of these recurrent and relapse associated CNAs revealed genes important in lymphoid development, such as NFκB2 and TRAP1 found in the alternative NFκB pathway and BLIMP1 involved in B-cell differentiation. There were also recurrent abnormalities in the region coding for SP140 which has been implicated in familial CLL. Known cancer genes were also affected by these recurrent and relapse-associated CNAs such as RND3, RIF1, RFXANK, and RHOT1, which are all members of the RAS pathway family. Using the OncoSNP program it was possible to determine that most of these emerging abnormalities were present in low numbers at diagnosis (fig. 1) suggesting that treatment does not induce the genetic alterations but may select for them. Fig .1 CNA and B-allele frequency plots of pre-treatment and relapse samples of a patient demonstrating clonal evolution. A low level of cnLOH can be seen in the B-allele frequency plot at diagnosis (a) at the end of chromosome 8 (dashed box) which becomes more apparent at relapse (b). Fig .1. CNA and B-allele frequency plots of pre-treatment and relapse samples of a patient demonstrating clonal evolution. A low level of cnLOH can be seen in the B-allele frequency plot at diagnosis (a) at the end of chromosome 8 (dashed box) which becomes more apparent at relapse (b). In conclusion, this is the first attempt to quantify CNAs in sequential leukaemia samples. The results demonstrate that recurrent and relapse associated CNAs affect genes important in B-cell development and cancer progression. Disclosures: No relevant conflicts of interest to declare.

Approximately 30-40% of patients with myelodysplastic syndromes (MDS) develop acute myeloid leukemia (AML). Several recurrent mutations have been identified in MDS using next-generation sequencing (NGS) technology and recent studies have greatly illuminated the molecular landscape of this disorder. However, the molecular events driving MDS progression to AML remain poorly understood. In order to investigate the genetic basis of leukemic transformation in MDS during disease progression, we evaluated the frequency and chronology of the acquisition of mutations using a targeted NGS myeloid gene panel on serial (paired) samples from 41 MDS patients before (pre-progression) and after disease progression (post-progression) to a more advanced subtype (n=7) or to AML (n=34). The mutational profile was characterized using a TruSeq Custom Amplicon panel (Illumina) targeting the hotspots of 31 recurrently (>1%) mutated genes in myeloid malignancies. Samples were run on an Illumina MiSeq and variants were annotated and filtered using Illumina VariantStudio v2.1.36, and interpreted according to the ACMG recommendations. The proportion of sequencing reads reporting a given mutation (variant allele frequency, VAF) was used to estimate the fraction of tumor cells carrying that mutation, and to determine whether mutations are clonal (in all tumor cells) or subclonal (in a fraction of tumor cells). A total of 100 and 123 mutations across 23 genes were identified in pre- and post-progression samples, respectively. The number of mutations was generally higher in the post-progression samples: the number of cases with one or two mutations was 24 in pre-progression samples and 16 in post-progression samples, while the number of cases with three or four mutations was 12 in pre-progression samples and 18 in post-progression samples. Several cases showed ≥5 mutations. The most frequently mutated genes (in >15% of samples) were ASXL1, TET2, SRSF2, U2AF1, RUNX1 and TP53; ASXL1 was the top ranking mutated gene with a frequency of 44% in pre-progression samples and 46% in post-progression samples. SF3B1, the most frequently mutated gene in MDS, was mutated in only two cases in our cohort. This finding is consistent with the strong association of SF3B1 mutation with the low-risk MDS subtype RARS, and its status as a good prognostic marker. Our patient cohort is highly selected, comprised only of patients whose disease has progressed and our data thus indicate that ASXL1 mutations are strongly associated with MDS cases that show disease progression and conversely that SF3B1 mutations are rarely associated with MDS disease progression. Mutations of genes involved in splicing (U2AF1, SRSF2), chromatin modification (EZH2, ASXL1) and DNA methylation (TET2, IDH1/2) were present in the pre-progression samples for almost all cases with mutations of these genes; these mutations often occur in founding clones (VAF >40%) and may play a role in disease initiation. Mutations of genes involved in transcriptional regulation (RUNX1, ETV6, PHF6) and signal transduction (NRAS, KRAS) were found in many cases in the post-progression sample only, suggesting that these are often late events that may co-operate with early events to drive disease progression. Interestingly, co-occurrence of NRAS and ASXL1 mutations was a frequent event in post-progression samples (n=5) in our cohort. It has been reported that NRas mutation and Asxl1 loss co-operate to drive myeloid proliferation and myeloid leukemia in mice, and our data support this observation. The average VAF of some mutations changed markedly during disease progression, with NRAS showing the largest VAF fold increase among genes mutated in >5 cases. The majority of subclones containing mutations in RUNX1 or ASXL1 expanded with disease progression. EZH2 mutations were mainly in the founding clone, while TP53 mutations were mainly in a subclone. For six cases we sequenced an additional serial sample, thus giving more precise information on the mutational profile evolution during disease progression. This is the first study to investigate the mutation status of a large group of MDS patients showing disease progression by the study of serial samples using a NGS myeloid gene panel. This study informs the timing of mutation acquisition during disease initiation and progression in MDS and closely related conditions, illuminating the genetic basis of leukemic transformation in these disorders. Disclosures No relevant conflicts of interest to declare.