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Introduction Despite significant progress in the understanding of the molecular pathogenesis of myeloproliferative neoplasms (MPN) and the identification of high molecular risk (HMR) genes (i.e. ASXL1, EZH2, IDH1 and IDH2 genes), the mechanisms by which different cell types predominate in the different disease subtypes and their implications for prognosis remain uncertain. Given the recently described association of senescence and fibrosis in a number of pathologies by Menoz-Espin et al, we hypothesized that genes implicated in oncogene-induced senescence (OIS) and senescence associated secretory phenotype (SASP) may contribute to the pathogenesis of these neoplastic bone marrow disorders that frequently show evidence of fibrosis. Specifically, we were interested in the gene expression levels in different disease subtypes, at a cell-type level, and whether these patterns of differential expression were distinct from the transforming JAK-STAT pathway and the HMR genes. Aim To elucidate the role of OIS and SASP genes in the pathogenesis of MPN subtypes by determining the differential expression of the genes in specific cell types in patients with MPN. Methods We performed gene expression profiling on normal controls (NC) and patients with MPN who were diagnosed with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) according to the 2008 WHO diagnostic criteria. Two cohorts of patients, the patient and validation cohorts, from 3 tertiary-level hospitals were recruited prospectively over 3 years. Peripheral blood samples were taken and sorted into polymorphonuclear cells (PMN), mononuclear cells (MNC) and T cells. RNA was extracted from each cell population. Gene expression profiling of the human transcriptome was performed using microarray and RNA sequencing on the patient and validation cohorts respectively. Gene expression analyses (GEA) were performed on 4 sets of genes derived from publicly available or custom derived gene set enrichment analysis: 92 OIS genes, 88 SASP genes (Gil et al), 4 HMR genes, and 126 genes associated with JAK-STAT pathway. Gene expression levels for each cell type in each disease were compared with NC to obtain the differential expression of the genes. RNA-seq analysis of samples from the validation cohort was used to validate the microarray results from the patient cohort. Results Twenty-eight patients (10 ET, 11 PV and 7 PMF) and 11 NC were recruited into the patient cohort. Twelve patients (4 ET, 4 PV and 4 PMF) and 4 NC were recruited into the validation cohort. After combination of the microarray and RNA-seq datasets, GEA of the OIS genes revealed the differential expressions of MCTP1 and SULT1B1 genes by PMN in PV but of none in PMF. In contrast, the BEX1 gene was identified as differentially expressed by MNC in PMF but none in PV. GEA of the SASP genes revealed differential expression of THBS1 gene by MNC in PMF but of none in PV. None of the SASP genes were differentially expressed by PMN in either PV or PMF. No differentially expressed genes were identified by PMN or MNC in ET, or by T cells in any of the diseases. Notably, GEA of the HMR genes and genes associated with the JAK-STAT pathways did not show any differential expression in any disease subtype by any cell type. Conclusions We have found strikingly distinct patterns of differential expression of senescence associated genes by PMN (in PV) and MNC (in PMF). These results provide a novel insight into the mechanisms underlying the different phenotype of the MPN subtypes and also to the cells responsible for mediating the differences. The lack of differential expression of OIS and SASP genes in ET may reflect the milder clinical phenotype of the disease. Although mutations in the HMR genes are associated with poor prognosis in PMF, the lack of differential expression in these genes and genes associated with the JAK-STAT pathway is in keeping with their mutated status and suggests that they give rise to the disease phenotypes via altering downstream expression of genes associated in other pathways such as the senescence pathways studied here. Further studies are warranted to investigate the role of these genes and the pathways involved in senescence at a cell-type specific level in order to gain further insight into how they can potentially give rise to the various disease phenotypes in MPN and unmask potential therapeutic targets. Disclosures Aitman: Illumina: Honoraria.

Introduction The discoveries of JAK2 V617F and CALR mutations have significantly improved our understanding of MPN and its subtypes. Somatic JAK2 V617F mutation is present in almost all patients with polycythemia vera (PV) and in 50% to 60% of those with essential thrombocythemia (ET) or primary myelofibrosis (PMF).Somatic CALR mutations are generally absent in PV but their frequencies are approximately 20-25% in ET and PMF. Initial reports suggested that these variants were mutually exclusive. However subsequently co-occurrence has been reported and it is suggested but not yet confirmed that this may confer a distinct phenotype. The role of germline variation is unknown. We report here the first occurrence of a germline CALR variant in association with a somatic JAK2 V617F mutation. Case report A 73-year old Malay gentleman was noted to have an abnormal cardiac rhythm and function during admission for herniorrhaphy. On further questioning, he reported a 2 month history of reduced cognitive function, short term memory loss, occasional urinary incontinence and involuntary movements. Splenomegaly was noted and blood test showed Hb 205 g/L, WCC 33.5 x 109/L and platelet 304 x 109/L. Cardiac investigations revealed an anteroseptal myocardial infarction requiring an angioplasty and stent insertion. Targeted Ion Torrent high-throughput sequencing and fragment analysis showed a somatic JAK2 V617F mutation and a germline 3bp in-frame deletion c.1213_1215delGAG (p.Glu405del) in exon 9 of CALR. Discussion Although somatic CALR exon 9 mutations are mostly found in patients with ET and PMF who are JAK2-negative, coexistence of somatic JAK2 V617F and CALR exon 9 alterations have been reported previously, mostly in patients with ET. To the best of our knowledge, this is the first case of a patient with PV presenting with a somatic JAK2 V617F mutation and a germline CALR variant, Glu405del, comprising a 3 bp in-frame deletion in exon 9. According to existing databases, this CALR variant is a previously undescribed germline variant not found in the 60,000 exomes on the ExAC database; but one instance of an overlapping p.Glu405_Asp408del was reported (frequency of 2 x 10-5). Although it is at present of unknown clinical significance, it is predicted by in silico modeling as being likely pathogenic: MutationTaster predicted both splice-site and protein feature changes, including loss of an endoplasmic reticulum export motif. Unlike the "classical" CALR-positive patients who present at a younger age with a higher platelet count, this patient presented incidentally at the age of 73 with a normal platelet count but a rather severe clinical phenotype with significant thrombosis requiring surgical intervention. Further studies are required to examine in detail the molecular signatures in this group of patients and whether they represent a distinct group of patients with clinical phenotypes which are different from the "classical" cases. Disclosures Aitman: Illumina: Honoraria. Laffan:CSL: Other: Travel support; Octapharma: Speakers Bureau.

Background The past decade has witnessed a significant progress in the understanding of the molecular pathogenesis of myeloproliferative neoplasms (MPN). A large number of genes have now been implicated in the pathogenesis of MPN but their relative importance, the mechanisms by which they cause different cell types to predominate and their implications for prognosis remain unknown. Aim The aim of this study was to perform targeted next generation sequencing on different cell types directed at a panel of mutations shown to be associated with MPN in order to identify driver mutations and novel variants, to determine their relative importance to pathogenesis and to predict survival in patients with MPN. Methods We performed targeted sequencing on normal controls (NC) and patients with MPN from 3 different races (Malay, Chinese and Indian) in Malaysia who were diagnosed with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) according to the 2008 WHO diagnostic criteria for MPN. Patients from 3 tertiary-level hospitals were recruited prospectively over 3 years and informed consents were obtained. Peripheral blood samples were taken and sorted into polymorphonuclear cells (PMNs), mononuclear cells (MNCs) and T cells. DNA was extracted from the different cell population and high-throughput sequencing was performed using an Ion Torrent PGM and AmpliSeq targeting platform, with a panel of 26 MPN-related genes. Results Twenty-nine patients (11 ET, 11 PV, 7 PMF) and 3 NC were recruited into the study. Ten of 29 (34.5%) and 9 of 29 (31%) patients were Malay and Chinese men respectively. Twenty-four of 29 (82.8%) patients harbored the JAK2V617F mutation which was detected in 7 (63.6%) ET, 11 (100%) PV and 6 (85.7%) PMF patients. The allelic frequency of JAK2V617F mutation was highest in PMF. 11 of the 24 JAK2V617F positive patients (2 ET, 5 PV and 4 PMF) also harbored potentially pathogenic variants involving the ASXL1, CALR, CBL, CHEK2, DNMT3A, TET2, U2AF1, RUNX1 , SF3B1 and TP53 genes. In patients who were found to have both JAK2V617F mutation and a TET2 variant, the allelic frequencies of the TET2 variantswere significantly lower than the JAK2V617F mutations. Conversely, in 1 ET patient with high TET2 allelic frequency, JAK2V617F mutation was not detected. Several novel variants involving the CHEK2, DNMT3A, RUNX1, SF3B1 and TET2 genes were identified in the study. All the novel variants were somatic (detected predominantly in the PMNs) except CHEK2 which was detected in all 3 cell types (PMNs, MNCs and T cells) at approximately 50% allele frequency. A similar spectrum of mutations was found in PMNs and MNCs, usually at a lower frequency in MNCs. Somatic mutations were absent or detected at very low frequencies in T cells. One of the 7 JAK2V617F positive ET patients harbored 4 somatic variants in CHEK2, SF3B1, TET2 and TP53 genes, with the highest allelic frequencies in the PMNs for 2 variants and MNCs for the other 2 variants. Three of the 4 JAK2V617F negative ET patients had CALR, MPL exon 10, SH2B3 and TET2 variants. One of the 3 ET patients with CALR and TET2 variant presented with a very high platelet count of 2251 x 109/L. One PV patient who harbored both JAK2V617F and CALR mutations presented with high haemoglobin and white cell counts. The CALR mutation in this patient was thought to be germline as it was detected in all cell types at approximately 50% allelic frequencies. The 2 PV patients who harbored both JAK2V617F and DNMT3A mutations presented with more severe phenotype with leukocytosis, splenomegaly of >15cm, constitutional and vasomotor symptoms requiring treatment with Hydroxycarbamide. The 3 PMF patients with JAK2V617F mutation in combination with ASXL1, DNMT3A, RUNX1, TET2 and U2AF1 variants also presented with severe clinical phenotypes, 2 of whom died within 2 years from diagnosis. Conclusion JAK2V617F is the commonest somatic mutation detected in MPN patients in Malaysia and is predominantly found in the PMNs. Nearly half of the JAK2V617F positive patients also harbor other potentially pathogenic variants. Several novel somatic and one germline variants were found in this study. Patients who harbor the JAK2V617F in combination with ASXL1, DNMT3A, RUNX1, TET2 and U2AF1 putatively pathogenic variants were found to have more severe clinical phenotypes with very poor prognosis. Further studies are required to explore cell type differences, prognosis and clonal evolution in MPN. Disclosures Aitman: Illumina: Honoraria.

Background The past decade has witnessed a significant progress in the understanding of the molecular pathogenesis of myeloproliferative neoplasms (MPN). A large number of genes have now been implicated in the pathogenesis of MPN but their relative importance, the mechanisms by which they cause different cell types to predominate and their implications for prognosis remain unknown. We hypothesized that there are other genes which may contribute to the pathogenesis of the different disease subtypes detectable only by cell-type specific analysis. Aim The aim of this study was to perform gene expression profiling on different cell types from patients with MPN in order to identify novel variants and driver mutations, to elucidate the pathogenesis and to identify predictors of survival in patients with MPN in a multiracial country. Methods We performed gene expression profiling on normal controls (NC) and patients with MPN from 3 different races (Malay, Chinese and Indian) in Malaysia who were diagnosed with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) according to the 2008 WHO diagnostic criteria for MPN. Two cohorts of patients, the patient and validation cohorts, from 3 tertiary-level hospitals were recruited prospectively over 3 years and informed consents were obtained. Peripheral blood samples were taken and sorted into polymorphonuclear cells (PMNs), mononuclear cells (MNCs) and T cells. RNA was extracted from each cell population. Gene expression profiling was performed using the Illumina HumanHT-12 Expression Beadchip for microarray and the Illumina Nextera XT DNA Sample Preparation Kit for next generation sequencing on the patient and validation cohorts respectively. Results Twenty-eight patients (10 ET, 11 PV and 7 PMF) and 11 NC were recruited into the patient cohort. Twelve patients (4 ET, 4 PV and 4 PMF) and 4 NC were recruited into the validation cohort. Gene expression levels for each cell type in each disease were compared with NC. In the patient cohort, the number of differentially expressed genes in ET, PV and PMF was 0, 141 and 15 respectively for PMNs (p < 0.05 after multiple testing correction) and 5, 170 and 562 respectively for MNCs (p < 0.05). No differentially expressed genes were identified for T cells in any of the three disease groups. RNA-seq analysis of samples from the validation cohort was used to corroborate these findings. After combination, we were able to confirm differential expression of 0, 14 and 7 genes in ET, PV and PMF respectively for PMNs (p < 0.05) and 51 genes in only PMF for MNCs (p < 0.05). The validated differentially expressed genes for PMNs and MNCs were mutually exclusive except for one gene. The differentially expressed genes in PV and PMF for PMNs were involved in cellular processes and metabolic pathways whereas the differentially expressed genes for PMF in MNCs were involved in regulation of cytoskeleton, focal adhesion and cell signaling pathways. Conclusion This is the first study to use microarray and next generation sequencing techniques to compare cell type-specific expression of genes between different subtypes of MPN. The lack of differential expression in T cells validates the techniques used and indicates that they are not part of the neoplastic clone. Differential expression of genes for MNCs was seen only in PMF which may be related to their more severe phenotype. Interestingly, there were fewer differentially expressed genes in PMF compared to PV for PMNs. The lack of differential expression in ET may either reflect the relatively milder phenotype of the disease or that differential expression is limited to megakaryocytes-platelets which were not studied. The lists of mutually exclusive cell type-specific differentially expressed genes for PMNs and MNCs provide further insight into the pathogenesis of MPN and into the differences between its different forms. The identified genes also indicate further routes for investigation of pathogenesis and possible disease-specific targets for therapy. Disclosures Aitman: Illumina: Honoraria.

Background The past decade has witnessed a significant progress in the understanding of the molecular pathogenesis of myeloproliferative neoplasms (MPN). Mutations in a large number of genes have now been implicated in the pathogenesis of MPN but these do not yet explain the differentiation into the separate MPN syndromes and do not give full prediction of the wide variation in prognosis. We hypothesized that epigenetic mechanisms may help explain these phenomena at a cell-type specific level. Aim The aim of this study was to perform DNA methylation profiling on different cell types from patients with MPN in order to identify regulatory loci adjacent to genes whose differential expression could elucidate the pathogenesis and predict survival in patients with MPN in a multiracial country. Methods We performed DNA methylation profiling on normal controls (NC) and patients with MPN from 3 different races (Malay, Chinese and Indian) in Malaysia who were diagnosed with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) according to the 2008 WHO diagnostic criteria for MPN. Two cohorts of patients, the patient and validation cohorts, from 3 tertiary-level hospitals were recruited prospectively over 3 years and informed consents were obtained. Peripheral blood samples were taken and sorted into polymorphonuclear cells (PMNs), mononuclear cells (MNCs) and T cells. DNA was extracted from each cell population. DNA methylation profiling was performed using the Illumina HumanMethylation450 Beadchip for microarray and subsequent confirmation was performed using the Fluidigm Access Array/Illumina Miseq next generation sequencing platform on the patient and validation cohorts respectively. Results Twenty-nine patients (11 ET, 11 PV and 7 PMF) and 11 NC were recruited into the patient cohort. Twelve patients (4 ET, 4 PV and 4 PMF) and 4 NC were recruited into the validation cohort. Methylation levels of the CpG sites for each cell type in each disease were compared with NC. In the patient cohort, the number of differentially methylated CpG sites in ET, PV and PMF was 1889, 6545 and 11,372 respectively for PMNs (p < 0.0001) and 732, 7700 and 49,219 respectively for MNCs (p < 0.0001). For T cells, the number of differentially methylated CpG sites in ET, PV and PMF were significantly less with 297, 1091 and 987 CpG sites respectively (p < 0.0001). Quantile-quantile plots showed a continuum of progressive skewness from ET to PV to MF for both PMNs and MNCs. However, this appearance was not seen in all 3 diseases for T cells. A total of 43 CpG sites showing the most significant difference in degrees of methylation from the different categories above were selected and all successfully validated using the Fluidigm/Miseq next generation sequencing platform on the validation cohort. For PMNs, 11 of the 14 CpG sites were associated with genes primarily involved in cell signaling pathways. For MNCs, 9 of the 15 CpG sites were associated with genes primarily involved in metabolic pathways and transcription regulation. Remarkably, there was no overlap between the validated PMN and MNC differentially methylated CpG sites or between disease subtypes. Fourteen differentially methylated CpG sites were validated in T cells. Conclusion This is the first study to use microarray and next generation sequencing platforms to compare cell type-specific methylation of CpG sites between different subtypes of MPN. The significantly lower differential methylation and the lack of skewness in the quantile-quantile plot in T cells validate the techniques used and indicate that they are not part of the neoplastic clone. The continuum of increasing number of differentially methylated CpG sites from ET to PV to MF in both PMNs and MNCs may be related to the increasing severity of the disease phenotypes. Differential methylation was greatest in PMF and was most markedly seen in MNCs which may be related to their more severe phenotype. The pattern of cell type-specific differentially methylated CpG sites and the lack of overlap between cell types and diseases provide further insight into the pathogenesis of MPN and into the mechanisms giving rise to the different disease subtypes. Differentially methylated CpG sites and the linked genes also indicate further routes of investigation and possible disease-specific targets for therapy not identified by mutation or gene expression analyses. Disclosures Aitman: Illumina: Honoraria.

Recent studies indicate that 40% of CML patients on imatinib who achieve complete molecular remission (CMR; equivalent to MR4 or better in current terminology) remain disease-free after drug discontinuation, raising the possibility of an “operational cure”. However, the safe introduction of TKI withdrawal into clinical practice would require a method of evaluating risk of relapse, which is likely to be related to the presence of residual disease undetectable by RT-qPCR. A PCR method based on the use of genomic DNA has been shown to be more sensitive for the detection of residual disease than one that relies on cDNA and may, therefore, help to predict outcome post-withdrawal. However, the former method is arduous requiring a customised patient-specific assay. We describe here a method based on targeted next-generation sequencing (NGS) which allows the rapid identification of BCR-ABL1 breakpoints and the generation of DNA-based qPCR assays. The location of the BCR-ABL1 fusion junction was mapped in disease samples from 32 CML patients using Illumina's MiSeq platform. A custom TruSeq DNA target enrichment system (Illumina) was used to enrich for fragments containing sequences from the BCR and ABL1 genes using probes covering both genes including an additional 50kb of sequence in both 5’ and 3’ directions. All 32 patients’ t(9;22) translocation junctions were successfully mapped using a custom designed bioinformatics algorithm. To date we have designed and validated DNA qPCR assays for 26 of these. On testing consecutive clinical samples from all 26 patients after achievement of MR4 or better (previously defined as CMR; mean 6 samples per patient), the DNA-qPCR assays detected residual disease in 8 out of 26 patients (31%), demonstrating that a DNA-based method is capable of identifying the presence of residual leukaemia in a proportion of patients who would be defined as “disease-free” using conventional RNA-based methodology. One area in which inaccuracy may be introduced into the DNA qPCR technique is in the use of a standard curve generated using serial dilutions of patient’s diagnostic material. We therefore sought to further enhance the sensitivity of a DNA-based approach by optimising this technique for use on a digital quantitative PCR (dqPCR) platform, which provides absolute molecular quantification without the need for standard curve. Using DNA dqPCR on a Fludigm BioMark HD instrument, we measured the level of BCR-ABL1 in 48 samples from 6 CML patients after achievement of a sustained response of MR4 or better. At the time point at which patients were first determined to have achieved at least MR4, all samples tested positive by DNA dqPCR. However, in subsequent samples collected two years following achievement of at least an MR4 (the point of entry into ongoing withdrawal trials, at which point all six patients had achieved MR4.5 or better), we found that patients fell into two distinct categories: 1) those whose disease continued to be detectable by DNA dqPCR (n=3), and 2) those whose disease had fallen to a level that was no longer detectable by DNA dqPCR (n=3). In contrast the conventional BCR-ABL1 DNA qPCR method detected disease in only one of these six patients at this time point, suggesting superior sensitivity of a digital PCR-based screening platform. From this pilot study we conclude that NGS-facilitated DNA dqPCR may be used to stratify patients with RT-qPCR-undetectable disease according to residual disease burden and may therefore prove valuable in the identification of patients for whom TKI therapy could be safely reduced or stopped. Disclosures: Milojkovic: BMS: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; Novartis: Honoraria. Apperley:Novartis: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria; Pfizer, Ariad: Honoraria (not direct from company), Honoraria (not direct from company) Other.