ALBERT

Description: 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.

Description: 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.

Description: *Contributed equally as first authors. **Contributed equally as senior authors. Recurrent mutations within EGR2, a versatile transcription factor involved in differentiation of hematopoietic cells, were recently reported in 8% of advanced-stage chronic lymphocytic leukemia (CLL) patients, where they appear to be associated with a worse outcome. EGR2 is activated through ERK phosphorylation upon B-cell receptor (BcR) stimulation, and we have previously shown that EGR2 -mutated CLL patients display altered expression of EGR2 down-stream target genes compared to wildtype (wt) patients, thereby pointing to a pathogenic role for EGR2 mutations in dysregulating BcR signaling. To gain further insight into the incidence and prognostic impact of EGR2 mutations in CLL, we screened samples from a well-characterized series of 1430 patients, either by Sanger sequencing (n=1019) or targeted deep-sequencing (n=370), both covering the recently reported EGR2 hotspot in exon 2. In addition, whole-exome data was available for an additional 43 patients. Different cohorts were included in our analysis ranging from 'general practice' CLL (33% IGHV-unmutated (U-CLL), 6% TP53 -aberrant (TP53abn), n=693), to adverse-prognostic CLL (89% U-CLL, 26% TP53abn, n=325), patients belonging to clinically aggressive stereotyped subsets #1-3 & #5-8 (n=342), patients relapsing after FCR therapy (n=41) and Richter transformed cases (n=31), thus reflecting the heterogeneous nature of CLL. Nineteen EGR2 mutations were detected by Sanger sequencing, while 22 additional mutations were identified with deep-sequencing using a 5% variant allele frequency (VAF) cutoff (median 39%, range 5.6-63.9%, median coverage 43,000X). With the exception of one in-frame deletion, all mutations were missense alterations located within the three zinc-finger domains. Significant enrichment of EGR2 mutations was observed in adverse-prognostic (18/325, 5.5%) and FCR-relapsing (4/41, 9.8%) CLL compared to the 'general practice' cohort (18/693, 2.6%, Figure 1A). A surprisingly low frequency was observed among clinically aggressive stereotyped subsets (5/342, 1.5%), although the cause for this observation is currently unknown. Finally, 2/31 (6.5%) cases with Richter transformation carried an EGR2 mutation. Of the 4 FCR-relapsing, EGR2 -mutated cases with available overtime samples, all demonstrated a significant expansion of the EGR2 -mutated clone at relapse (VAF-increase between 15-41%). In addition, subclonal levels of EGR2 hotspot mutations (VAF 0.5-5%) were detected in an additional 13/370 (3.5%) cases by deep-sequencing. The majority of EGR2 -mutated CLL patients (32/39, 82%) concerned U-CLL and the following aberrations co-occurred: 11q-deletions (n=10), TP53abn (n=6), NOTCH1 (n=3)or SF3B1 (n=3) mutations. EGR2 -mutated patients displayed a significantly worse overall survival compared to wt patients (median survival 59 vs. 141 months, p=0.003, using a conservative 10% VAF cutoff), and a poor outcome similar to cases with TP53abn (Figure 1B). In multivariate analysis (n=583), EGR2 status remained an independent factor (p=0.038), along with stage (p=0.048) and IGHV status (p

Description: 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.

Description: 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

Description: 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.

Description: Key Points Acquired pathogenic mutations in SAMHD1 are found in up to 11% of relapsed/refractory patients with CLL. SAMHD1 is mobilized to sites of DNA damage.

Description: Key Points Targeted NGS of relapsed/refractory CLL reveals a high incidence of concurrent mutations that mostly affect the TP53, ATM, and SF3B1 genes. Concurrent mutations of the TP53, ATM, and/or SF3B1 genes confer short survival in patients with relapsed/refractory CLL.

Description: Key Points Germline JAK2V617I mutation as a sole genetic event does not suppress hematopoietic stem cells. JAK2V617I induces weaker constitutive activation than JAK2V617F but considerable cytokine hyperresponsiveness.