ALBERT

Description: 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.

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: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.

Description: Abstract 1087 Background: Investigations of treatment options for established PTS are limited. Graduated compression stocking therapy (GCS) is often used in clinical practice despite limited research on effectiveness. We postulated that the venous hypertension seen in PTS leads to lymphatic overload and secondary lymphedema. Therefore, in patients with established PTS, we compared the efficacy of GCS alone to complex lymphedema therapy, a treatment that includes compression stocking use, exercise, patient education, skin care and manual lymphatic drainage. Methods: In an investigator-blind randomized controlled trial of 31 patients with a clinical diagnosis of PTS and prior history of DVT, we compared GCS alone using 30–40 mm Hg compression to complex lymphedema therapy. Primary outcomes were the 1- and 3-month changes in PTS severity by the Villalta score (higher score indicates more severe PTS) and disease-specific quality of life by the VEINES QOL score (high score indicates better QOL). Analysis was by intent-to-treat. Results: Overall, 39% of patients enrolled in the study had moderate or severe PTS: baseline mean PTS severity score was 9.9 (SD 7.1) in the lymphedema group and 10.9 (SD 5.3) in the GCS group (p=0.66). The complex lymphedema therapy group had a reduction in mean PTS severity score of -2.4 (p=0.02) at 1 month and -2.3 (p=0.05) at 3 months follow-up. The GCS group had a reduction in PTS severity score of -2.1 (p=0.03) at 1 month and -3.3 (p=0.03) at 3 months. The improvement in PTS severity score did not differ significantly between treatment groups (p=0.61 at 3 months). Neither group had a significant change in VEINES QOL score. Patients not routinely using GCS prior to trial entry derived a greater benefit from either intervention with a decrease in PTS severity score (-8.8 in nonusers vs -1.5 in those using GCS at baseline, p=0.07) and an increase in VEINES QOL score (+1.9 vs -2.0, p=0.02). At 3 months, average self-reported GCS use was 6.7 days/wk (lymphedema therapy) and 5.9 days/wk (GCS) with 78% of patients in the lymphedema therapy group receiving manual lymphatic drainage (home or therapist). Four patients experienced recurrent thrombosis on the trial (3 in GCS group; 1 in lymphedema therapy group); 1 stocking allergy and ulcer formation was also seen in the GCS group with no cardiopulmonary complications reported in either group. Conclusion: In this first clinical trial of complex lymphedema therapy for patients with established PTS, a short course of lymphedema therapy was safe and had a similar effect on PTS severity as compression stocking use. Disclosures: No relevant conflicts of interest to declare.

Description: Summary: High-throughput technologies can identify genes whose expression profiles correlate with specific phenotypes; however, placing these genes into a biological context remains challenging. To help address this issue, we developed nested Expression Analysis Systematic Explorer (nEASE). nEASE complements traditional gene ontology enrichment approaches by determining statistically enriched gene ontology subterms within a list of genes based on co-annotation. Here, we overview an open-source software version of the nEASE algorithm. nEASE can be used either stand-alone or as part of a pathway discovery pipeline. Availability: nEASE is implemented within the Multiple Experiment Viewer software package available at http://www.tm4.org/mev. Contact: cholmes@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.