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The gut microbiome influences cancer development and the efficacy and safety of chemotherapy, but little is known about its effects on lymphoma. We obtained stool samples from treatment-naïve, newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) (n = 189). We first performed 16S ribosomal RNA gene sequencing (n = 158) and then conducted whole-genome shotgun sequencing (n = 106) with additional samples. We compared the microbiome data from these patients with those of healthy controls and assessed whether microbiome characteristics were associated with treatment outcomes. The alpha diversity was significantly lower in patients with DLBCL than in healthy controls (P < 0.001), and the microbial composition differed significantly between the groups (P < 0.001). The abundance of Enterobacteriaceae family belonging to the Proteobacteria phylum was markedly higher in patients than in healthy controls. Functional analysis of the microbiome revealed an association with opportunistic pathogenesis through type 1 pili, biofilm formation, and antibiotics resistance. Enterobacteriaceae members were significantly enriched in patients who experienced febrile neutropenia and in those who experienced relapse or progression (P < 0.001). Interestingly, greater abundance of Enterobacteriaceae correlated with shorter progression-free survival (P = 0.007). The cytokine profiles of patients whose microbiome was enriched with Enterobacteriaceae were significantly associated with interleukin 6 (P = 0.035) and interferon-g (P = 0.045) levels. In summary, patients with DLBCL exhibited gut microbial dysbiosis. The abundance of Enterobacteriaceae correlated with treatment outcomes and febrile neutropenia. Further study is required to elucidate the origin and role of gut dysbiosis in DLBCL.

Next-generation sequencing (NGS) has been applied to define clinically relevant somatic mutations and classify subtypes in acute myeloid leukemia (AML). Persistent allelic burden after chemotherapy is associated with higher relapse incidence, but presence of allelic burden in AML patients after receiving allogeneic hematopoietic cell transplantation (HCT) has not been examined longitudinally. As such, we aimed to assess the feasibility of NGS in monitoring AML patients receiving HCT. Using a targeted gene panel, we performed NGS in 104 AML patients receiving HCT using samples collected at diagnosis, pre-HCT, and post-HCT at day 21 (post-HCTD21). NGS detected 256 mutations in 90 of 104 patients at diagnosis, which showed stepwise clearances after chemotherapy and HCT. In a subset of patients, mutations were still detectable pre-HCT and post-HCT. Most post-HCT mutations originate from mutations initially detected at diagnosis. Post-HCTD21 allelic burdens in relapsed patients were higher than in nonrelapsed patients. Post-HCTD21 mutations in relapsed patients all expanded at relapse. Assessment of variant allele frequency (VAF) revealed that overall VAF post-HCTD21 (VAF0.2%-post-HCTD21) is associated with an increased risk of relapse (56.2% vs 16.0% at 3 years; P < .001) and worse overall survival (OS; 36.5% vs 67.0% at 3 years; P = .006). Multivariate analyses confirmed that VAF0.2%-post-HCTD21 is an adverse prognostic factor for OS (hazard ratio [HR], 3.07; P = .003) and relapse incidence (HR, 4.75; P < .001), independent of the revised European LeukemiaNet risk groups. Overall, current study demonstrates that NGS-based posttransplant monitoring in AML patients is feasible and can distinguish high-risk patients for relapse.

As interest in elderly Acute Myeloid Leukemia (AML) patients increases, American society of hematology (ASH) 2020 guidelines for treating newly diagnosed AML in older adults suggested diverse treatment options. The guidelines suggest using monotherapy over combination of hypomethylation agent (HMAs) with other agents in newly diagnosed AML in older adults due to similar efficacy and the potential for more toxicity. HMAs alone is still used widely as an alternative treatment for patients who cannot use venetoclax due to the high cost and poor performance score. If there are early predictors of responsiveness to Decitabine mono therapy, it will be helpful to decide whether to combine Novel agents. This retrospective cohort study from a single institution aimed to evaluate the prognostic significance of Variant allele frequency (VAF) changes in elderly patients after 4 th cycle of decitabine. Total 123 patients with elderly AML were eligible. 57 patients performed follow-up bone marrow biopsy and 49 patients were available of follow up targeted NGS samples from biopsy after 4th cycle of decitabine. To clarify the immortal timed bias, landmark analyses were performed with patients (n=84) who remained at least the median time to perform follow-up bone marrow biopsy after 4th cycle of decitabine treatment. 24 patients (54.5%, 24 of 44) showed more than 50% decrease of VAF after 4 th cycle of decitabine (figure 1a). DMNT3A, TET2, IDH1, IDH2, and SETBP1 and SMC1A showed less than 50% of the decreases of VAF. Patients with DNA methylation genes showed significantly reduced VAF less than 50% (figure 1b). A significant difference of ∆VAF was observed depending on CR status (p=0.021). The survival outcome of patients who showed more than 50% decrease of initial VAF after 4th cycle of decitabine was significantly better than that that with less than 50% decrease of VAF(1-year OS VAF decrease ≥ 50% (n=23), 75.0%; VAF decrease < 50% (n=20), 38.5%; no mutation (n=12), 45.5%; not available of follow up targeted NGS sample (n=29), 16.6%; p < 0.001, figure 2a). Mutations in DNMT3A, TET2, and ASXL1 (DTA genes) were detected in samples from 19 patients at diagnosis. After the exclusion of DTA mutations, the survival outcome improved prognostic risk stratification power of NGS-based MRD assessment in AML. The survival outcome of patients who showed more than 50% decrease of initial VAF after 4th cycle of decitabine was significantly better than that that with less than 50% decrease of VAF(1-year OS VAF decrease ≥ 50% (n=24), 75.0%; VAF decrease < 50% (n=19), 35.1%; no mutation (n=12), 50.1%; not available of follow up targeted NGS sample (n=29), 16.6%; p Figure 1 Figure 1. Disclosures Kim: Bristol-Meier Squibb: Research Funding; Paladin: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Introduction Acute myeloid leukemia (AML) that develops from pre-existing hematologic diseases, rather than developing de novo, is known as secondary AML (sAML). A number of hematologic malignancies can progress to sAML. However, the molecular and genetic characteristics behind the progression of hematologic malignancies to sAML remain unclear. To address this question and dissect the order of mutation acquisition throughout the course of the disease, we performed whole-exome sequencing and targeted deep sequencing on serial samples. Patients and Methods This study examined several cohorts with a combined total of 124 patients. This study was approved by research ethics boards at relevant institutions and samples were taken after informed consent. The discovery cohort (C1) consisted of 31 patients diagnosed with myelodysplasia who all progressed to sAML. Whole-exome sequencing (WXS) was performed for each case on bone marrow samples taken at the diagnosis of the antecedent malignancy and after sAML progression, as well as fractionated T-cell samples (CD3+). WXS (Agilent SureSelect v4) was performed on the 93 samples as per the manufacturer's protocol using an Illumina HiSeq 2000. The other cohorts included 72 non-progressed MDS patients (C2a, median follow-up of 3.5 years) and an additional 21 sAML patients (C2b) progressed to sAML from MDS, for whom samples from the MDS stage were not available. Targeted sequencing was performed using an Agilent custom probe set of the selected 92 genes. We multiplexed and sequenced the samples using an Illumina Hiseq 2000. Targeted deep sequencing was performed on all cohorts. Genomon-ITD was used to detect FLT3-ITD. Results The mean read depth retrieved for target regions for WXS data was 73x. After calling and prioritizing variants, we found a mean and median of 7.7 and 6 significant variants per patient at the time of initial diagnosis, and 12.4 and 10 variants after sAML progression, respectively. We also detected that FLT3-ITD emerged in 2 patients after sAML progression. The presence of variants in T-cell samples in 5 C1 and 20 C2a patients provides evidence on the relative timing of early events for a subset of patients. Both cohorts notably lack activated signaling pathway variants at this stage (Figure A). The T-cell variants in 5 C1 patients with pathway associations were all in genes involved in DNA methylation (DNMT3A, IDH1/2, and TET2) or splicing machinery (SRSF2 and SF3B1). This pattern was verified in 20 C2a patients except for a single case that had an NRAS-G13D mutation. These patients showed evidence of having clonal hematopoiesis. At MDS, there were a significant number of cases with variants in genes involved in DNA methylation and/or splicing machinery (35.5% and 48.3%, respectively). However, the portion of cases with variants affecting these pathways increased significantly at the MDS stage, but did not change much by the sAML stage (Figure C-D). On the other hand, variants in genes involved in activated signaling pathways showed a distinctive pattern. The portion of cases with variants affecting activated signaling pathways noticeably increased at the sAML step (25.8% to 54.8%) (Figure B). The changes in VAF between stages within cases of these variants revealed a similar pattern. In summary, clonal evolution patterns can be postulated based on the acquisition/expansion of mutations related to the three signature pathways (Figure E). Forty-eight percent of patients showed growth or development of clones containing activated signaling pathway variants at the sAML stage. Sixteen percent of patients developed the MDS from preleukemic mutations associated with DNA methylation or splicing machinery, and 26% first developed clones of this category at the MDS stage (a total of 42%). Conclusion Mutations in DNA methylation and splicing machinery genes are early disease events, expanding at the MDS stage but not during progression. On the other hand, activated signaling pathway mutations expand during progression, demonstrating that distinct categories of genetic lesions play roles at different stages of sAML in a generally fixed order. Figure Figure. Disclosures No relevant conflicts of interest to declare.

MDM2, a critical negative regulator of p53, is often overexpressed in leukemia, but few p53 mutations are found, suggesting that p53-independent MDM2 expression occurs due to alterations in MDM2 upstream regulators. In this study, a high MDM2 transcription level was observed (41.17%) regardless of p53 expression in patient with acute myeloid leukemia (AML). Therefore, we performed genome-scale functional screening of the human genes modulating MDM2 expression in a p53-independent manner. We searched co-expression profiles of genes showing a positive or negative pattern with MDM2 expression in a DNA microarray database, selected1089 links, and composed a screening library of 368 genes. Using MDM2 P1 and P2 promoter-reporter systems, we screened clones regulating MDM2 transcriptions in a p53-independent manner by overexpression. Nine clones from the screening library showed enhanced MDM2 promoter activity and MDM2 expression in p53-deficient HCT116 cells. Among them, six clones, including NTRK2, GNA15, SFRS2, EIF5A, ELAVL1, and YWHAB mediated MAPK signaling for expressing MDM2. These results indicate that p53-independent upregulation of MDM2 by increasing selected clones may lead to oncogenesis in AML and that MDM2-modulating genes are novel potential targets for AML treatment.

Most Saccharomyces spp. cannot degrade or ferment dextrin, which is the second most abundant carbohydrate in wort for commercial beer production. Dextrin-degrading brewer's bottom and top yeasts expressing the glucoamylase gene (GAM1) from Debaryomyces occidentalis were developed to produce low-carbohydrate (calorie) beers. GAM1 was constitutively expressed in brewer's yeasts using a rDNA-integration system that contained yeast CUP1 gene coding for copper resistance as a selective marker. The recombinants secreted active glucoamylase, displaying both α-1,4- and α-1,6-debranching activities, that degraded dextrin and isomaltose and consequently grew using them as sole carbon source. One of the recombinant strains expressing GAM1 hydrolyzed 96 % of 2 % (w/v) dextrin and 98 % of 2 % (w/v) isomaltose within 5 days of growth. Growth, substrate assimilation, and enzyme activity of these strains were characterized.

Background: Hypomethylating agents (HMAs) are used to treat patients with lower-risk myelodysplastic syndrome (LR-MDS) relapsing after the use of hematopoietic cytokines or presenting initially with more than two lineages of cytopenias. However, the significance of underlying genetics and allelic burden changes after HMAs are still under investigation. This study investigated the effects of allelic burden changes on the long-term outcomes in LR-MDS patients treated with HMAs. Methods: This study included 61 patients with LR-MDS treated with azacitidine. Bone marrow samples were taken at diagnosis and follow-up after median 4 cycles. Targeted deep sequencing on a custom myeloid gene panel of 84 genes (Agilent SureSelect) was performed on trios of T-cell, pre-HMA, and post-HMA samples on 61 LR-MDS patients. Patients were divided into groups according to the post-HMA variant allele frequency (VAF): low-VAF (< 2%), high-VAF (≥ 2%), and no-mutation group (absence of mutations at diagnosis and follow-up). Overall survival (OS) was defined as the time from the azacitidine treatment until death from any cause, which was analyzed using the Kaplan-Meier method and the groups were compared using the log-rank test. The cumulative incidence of AML was calculated using the Gray method, considering death without AML as a competing risk. Fine-Gray proportional hazard regression with a competing event was used to identify risk factors for the incidence of AML. Results: Median age was 67 years (range 31-81), and 41 patients (67%) were male. IPSS risk group were low in 2 patients (3%) and intermediate-1 in 59 (97%). At diagnosis, 38 patients harbored at least one mutation. Most frequently mutated genes were ASXL1 (n=11, 18%), TET2 (n=10, 16%), and SRSF2 (n=7, 11%) followed by RUNX1, SF3B1, U2AF1, IDH2, and DNMT3A. Azacitidine was administered median 8 cycles (range 2-44). The overall response (CR, PR, HI) was achieved in 18 patients (30%). With median follow-up duration of 31 months (range 4.7-135 months), leukemic transformation occurred in 11 patients (18%). Mutational allelic burdens were decreased from median 20.9% (range 0.1-67.2) to 11.0% (range 0.0-74.9%). At follow-up, 5 patients were low-VAF group and 33 were high-VAF group. OS rate was not different between the low-VAF and high-VAF group (50% vs 46% at 3 years; p=0.80). Three-year cumulative incidence of AML was higher in high-VAF group compared to low-VAF (0%) and no-mutation group (4.8%, p=0.02). However, non-leukemic mortality was higher in low-VAF group than no-mutation group (60% vs 23%, p=0.09), which explains similar OS rate between low-VAF and high-VAF group. In the multivariate analysis, high-VAF was an independent predictive factor for an AML transformation in LR-MDS patients treated with azacitidine (HR 5.20, p=0.04). Conclusion: The current study showed that the high residual allelic burden is associated with an increased AML transformation in LR-MDS patients treated with azacitidine, irrespective of the clinical response. The higher non-leukemic mortality explains inferior OS in low-VAF group compared to no-mutation group. Figure Disclosures No relevant conflicts of interest to declare.

To contruct amylolytic industrial strains of Saccharomyces cerevisiae which produce ethanol efficiently from raw starch, the Bacillus amyloliquefaciens α-amylase genes (Amy) or Aspergillus awamori glucoamylase genes (GA1) was separately introduced into the ribosomal DNA loci in the chromosomes of the raw starch fermenting-parental strain (ATCC 9763/YIpδAGSAδ), using double 18S rDNA-integration system. Ethanol production after 3 days of fermentation by the strain that produced ethanol most efficiently from raw starch (ATCC 9763/YIpδAGSAδ/YIpAG2rD) among the transformant strains was 1.5-times higher than that by the parental strain. This new strain generated 9.2% (v/v) ethanol (72 g/L) from 20% (w/v) raw corn starch and consumed 75% of the raw starch content during the same period.

Ethanol production using hemicelluloses has recently become a focus of many researchers. In order to promote D: -xylose fermentation, we cloned the bacterial xylA gene encoding for xylose isomerase with 434 amino acid residues from Agrobacterium tumefaciens, and successfully expressed it in Saccharomyces cerevisiae, a non-xylose assimilating yeast. The recombinant strain S. cerevisiae W303-1A/pAGROXI successfully colonized a minimal medium containing D: -xylose as a sole carbon source and was capable of growth in minimal medium containing 2% xylose via aerobic shake cultivation. Although the recombinant strain assimilates D: -xylose, its ethanol productivity is quite low during fermentation with D: -xylose alone. In order to ascertain the key enzyme in ethanol production from D: -xylose, we checked the expression levels of the gene clusters involved in the xylose assimilating pathway. Among the genes classified into four groups by their expression patterns, the mRNA level of pyruvate decarboxylase (PDC1) was reduced dramatically in xylose media. This reduced expression of PDC1, an enzyme which converts pyruvate to acetaldehyde, may cause low ethanol productivity in xylose medium. Thus, the enhancement of PDC1 gene expression may provide us with a useful tool for the fermentation of ethanol from hemicellulose.

Introduction NGS-based detection of minimal residual disease (MRD) has been successfully demonstrated for its correlation with relapse risk in AML. However, in a subtype of AML, CBF-AML, its clinical relevance of residual allelic burden at complete remission (CR) has not been fully explored. The standard MRD detection method in CBF-AML is quantitative PCR (qPCR). In this study, we aimed to explore applicability and feasibility of NGS-based MRD detection in CBF-AML taking various approaches, rather than simply using residual allele burden at CR. Patients and Methods Fifty-three patients (pts) diagnosed with CBF-AML were enrolled in this study (31 pts with RUNX1-RUNX1T1 and 22 pts with CBFB-MYH11). All 53 patients achieved complete remission (CR). We performed targeted deep sequencing on 84 genes in 106 samples collected at diagnosis and at CR as well as T-cell (n = 53, CD3+) fraction as a control using Illumina Hiseq 2500. Mean on-target coverage for 159 sequenced was 1,572x. The level of RUNX1-RUNX1T1 was measured at diagnosis and at CR for 29 patients using qPCR. Results At diagnosis, 99 mutations from 49 pts (n = 49/53, 92%) were detected, where median number of mutations for 49 pts was 2 (range 1-6). Consistent with previous studies, KIT (36%), NRAS (32%), KRAS (17%), ASXL2 (15%) were commonly mutated. Among mutations detected at diagnosis, cKIT-D816 mutation and mutations in genes in DNA methylation pathway (DNMT3A and TET2) were associated with higher risk of relapse (5.29, [1.89 - 14.87], p = 0.002 and 3.15 [1.07 - 9.26], p= 0.037, respectively). In CR samples, 46 mutations from 32 pts were still detectable (46/99, 46%, mean VAF: 0.60%, range 0.04%-6.28%, Fig A). Only 4 mutations from 2 pts were over 2.5% (2 in TET2, 1 in ASXL1, and 1 in U2AF1). When tracing back at diagnosis, allelic burden of 46 mutations detected at remission were higher than 53 cleared mutations (p < 0.002), indicating clonal mutations are more likely to be detected at CR (Fig A). They were mostly in genes associated with activated signaling (32/46, 70%). When considering complete clearance rate, mutations in genes associated with activated signaling, DNA methylation, and spliceosome tended to be persistent at CR (32/64, 4/5, and 1/1), whereas mutations in cohesin complex and chromatin modifiers were mostly completely cleared (0/8 and 4/13). We then assessed clinical relevance of mutation clearance from various perspectives. We did not find association of mutation clearance at 0.3% (MC03) with OS (p = 0.43) or with relapse risk (p = 0.8, Fig B). Complete mutation clearance also did not show significant association with OS and relapse risk. Among 29 pts with RUNX1-RUNX1T1 with available qPCR data, 20 pts were MRD-positive by qPCR at CR. Nine pts who achieved MRD-negative also achieved MC03 as well. When considering only MRD-positive pts, achievement of MC03 did not affect OS (p = 0.69) and relapse incidence (p = 0.86, Fig C). Lastly, we assessed whether persistence of high risk mutations at CR (cKIT-D816, DNMT3A, and TET2) is associated with higher risk of relapse, but complete clearance of KIT-D816 mutation also did not affect OS and relapse incidence (p = 0.94 and p = 0.40, respectively, Fig D). We were not able to analyze DNMT3A and TET2 mutations as only 1/5 mutation was cleared. Conclusion Current study demonstrates that low residual allelic burden measured by NGS at CR does not provide additional clinically relevant information in addition to baseline mutation profile nor qPCR-based MRD in CBF-AML Figure. Figure. Disclosures No relevant conflicts of interest to declare.

Introduction Myelodysplastic syndrome (MDS) is a heterogeneous group of myeloid disorder characterized by defective bone marrow (BM) hematopoiesis with peripheral blood cytopenias and risk for progression to acute myeloid leukemia. Accurate determination of prognosis is critical to select an appropriate therapy and to detect any case progressing to leukemic transformation which brings ominous prognosis in patients with MDS. Despite clinical risk models, additional molecular data are needed to enhance the prediction of patients' clinical courses and to aid disease management. Therefore, the present study attempted to classify the higher risk MDS (HR-MDS) patients according to their molecular risk through targeted RNA-sequencing, to correlate it with clinical risk models, and analyzed molecular risk grouping for prognostic stratification power, especially for leukemic transformation in higher-risk patients with MDS treated with hypomethylating agents (HMA) including azacitidine or decitabine. Patients and Methods A total of 30 patients were included with HR-MDS by International Prognostic Scoring System (IPSS). Overall, 60 bone marrow samples (30 diagnosis and follow-up pairs) were subject for targeted RNA-seq using Illumina TruSight Pan-Cancer panel. After read mapping by Tophat2, gene count was measured using HTSeq followed by DEseq2 for differential gene expression quantification. All 60 samples as well as 30 samples from T-cell fraction (CD3+, as a control) were also subjected for DNA-seq targeting a panel of 84 commonly mutated genes in myeloid malignancies (Agilent SureSelect). All downstream computational and statistical analyses were performed using R and Python. Results The median age was 65 years (range 40-84 years) with 16 male patients (53%). Twenty-seven (90%) and 3 (10%) patients were intermediate-2 and high risk by IPSS, respectively. According to revised IPSS (IPSS-R), the distribution of risk groups was as follows: low (n=5, 17%), intermediate (n=8, 27%), high (n=11, 37%), and very high (n=6, 20%). A total of 56 mutations were detected in the diagnostic samples from 30 patients. Frequently mutated genes were DDX41 (n=5) and TP53 (n=4). Best response to HMA (16 azacitidine and 14 decitabine) was achieved in median 4 cycles (range 3-8). Complete response (CR) including marrow CR was achieved in 18 patients (60%), and 10 patients (33%) received allogeneic hematopoietic cell transplantation. Overall survival (OS) rate was not well correlated with IPSS-R risk groups. With median follow-up duration of 28.2 months (range 3.8-95), 3-years' OS rate showed 40%, 75%, 36%, and 67% in low, intermediate, high, and very high risk, respectively. Unsupervised clustering using top 100 genes with highest variance revealed 3 distinct clusters (n=8, 9, and 13 in group 1, 2, and 3), 3-years' OS rate of which showed 73%, 57%, and 35% in group 1, 2, and 3, respectively (p=0.004 between group 3 vs group 1/2). Despite inferior long-term outcomes in the group 3, the baseline clinical variables of some patients were classified as favorable implying that clinical factor does not reflect adverse long-term outcomes: 4 out of 13 patients with low risk by IPSS-R eventually experienced adverse outcome. The 3-years' leukemic transformation rate was 0%, 33% and 57% in group 1, 2, and 3 (p=0.039 between group 3 vs group 1/2). In the multivariate analyses, besides achievement of CR, the risk group 3 by RNA-seq were identified as independent adverse prognostic factors for OS (p=0.007, HR 6.75 [1.68-27.17]) as well as leukemic transformation (p=0.013, HR 6.91 [1.49-31.95]). In the gene set enrichment analysis using MSigDB, hematopoietic stem cell genes were enriched in RNA-seq group 3, suggesting that the high-risk signature on RNA-seq is linked with stemness of hematopoietic stem cells. Conclusion RNA-seq can be utilized to identify the higher risk patients with MDS. The higher risk group by RNA-seq enriched with genes with hematopoietic stem cells, which suggests that stemness in hematopoietic stem cells is linked with resistance to HMA therapy and increasing risk of leukemic transformation in HR-MDS. Figure. Figure. Disclosures No relevant conflicts of interest to declare.

Introduction Recent studies utilizing NGS demonstrated that residual allelic burden at complete remission (CR) is associated with worse overall survival (OS) and relapse incidence in AML. Quantitative PCR (qPCR) based disease monitoring is current practice in CBF-AML. However, qPCR requires standardization and the result for the same sample may vary depending on several factors. Also, other known prognostic factors such as cKIT mutation require an additional test. As RNA-seq can detect gene rearrangement as well as somatic mutations, we hypothesized that RNA-seq on samples taken at diagnosis and at remission can be used to monitor these genetic alterations simultaneously and can be utilized for minimal residual disease (MRD) monitoring in CBF-AML. Patients and Methods This study included 42 CBF-AML patients (23 RUNX1-RUNX1T1 and 19 CBFB-MYH11 AML). Overall, 84 bone marrow samples (42 diagnosis-CR pairs) were subjected to targeted RNA-seq using Illumina TruSight Pan-Cancer panel. After read mapping, gene count was measured using HTSeq followed by DEseq2 for gene expression quantification. Average number of sequenced reads was 3.5M reads with 87% overall mapping rate. Gene fusions in diagnostic samples were detected using EricScript. All 84 samples as well as 42 samples from T-cell fraction (CD3+, as a control) were also subjected to DNA sequencing, targeting a panel of 84 genes (Agilent SureSelect custom gene panel). Average on-target coverage was 1,606x. All other computational analyses were done using R and python. Results In diagnostic samples, class-defining gene fusion events were detected in all 42 patients. In CR samples, we tracked identical junctions identified in corresponding diagnostic samples. As expected, both CBFB-MYH11 and RUNX1-RUNX1T1 showed significant reduction in all CR samples compared to their corresponding diagnostic samples (p < 2.2e-13 and p < 6.3e-05, Fig A and B). CBFB-MYH11 was detectable in 6/19 CR samples (32%) and RUNX1-RUNX1T1 was detectable in 15/23 CR samples (65%). Reduction level of RUNX1-RUNX1T1 measured by RNA-seq showed positive correlation with the reduction level measured by qPCR (Pearson's Rho = 0.74, p < 5.4e-05, Fig C). As per mutational profile at diagnosis, we detected 74 mutations in 38 samples (n=38/42, 90%). NRAS (36%), KIT (36%), KRAS (17%) and, ASXL2 (17%) were commonly mutated. Survival analyses on each gene and each protein locus identified cKIT-D816 mutation as an adverse prognostic factor (HR = 3.57, [1.15 - 11.11], p = 0.028). We were able to detect all cKIT-D816 mutations in RNA-seq. Using information from NGS, we built a prognostic model for RUNX1-RUNX1T1 AML (n = 23). Decision tree analysis identified three distinct subgroups of RUNX1-RUNX1T1 AML on the basis of reduction level of RUNX1-RUNX1T1 and mutation profile (Fig D). Consistent with previous studies, 3-log or deeper reduction of RUNX1-RUNX1T1 transcript level was the most significant prognostic factor (low risk group). The algorithm further divided the patients who failed to achieve 3-log reduction according to the presence of cKIT-D816 mutation at diagnosis (intermediate and high risk group). For three defined groups, 2-year OS rates were 87%, 74%, and 33% (p = 0.08, Fig E) and 2-year relapse incidence rates were 13%, 42%, and 67% (p = 0.048, Fig F). Conclusion RNA-seq can be utilized to quantify RUNX1-RUNX1T1 and CBFB-MYH11 transcripts on diagnostic and CR samples in CBF-AML. We also showed that RNA-seq can stratify RUNX1-RUNX1T1 AML patients into three risk groups according to their long-term prognosis. Figure. Figure. Disclosures No relevant conflicts of interest to declare.

Introduction: Myelodysplastic syndromes (MDS) are clonal hematopoietic disorders characterized by dysplastic changes in one or more cellular lineages causing impaired bone marrow function. One third of patients diagnosed with MDS progress to secondary acute myeloid leukemia (sAML). These patients have significantly worse prognoses than de novo AML patients. Azacitidine (AZA), a hypomethylating agent is commonly used to treat MDS patients as a frontline therapy. Although its survival benefits over supportive care in a randomized trial has been demonstrated, the underlying genetics and clonal dynamics upon AZA response/AML progression have not been well examined. Using next generation sequencing (NGS) technology, we attempted to assess the clinical relevance of somatic mutations and their dynamics as they relate to AZA treatment in MDS patients using longitudinal samples. Patients and Methods: Ninety-five MDS patients (56 lower risk and 39 higher risk MDS based on the revised IPSS scoring system) were enrolled in this study. The median age of the 95 patients is 67 years (range of 31 Ð 84) and median follow-up duration was 747 days (range of 137-3328 days). We performed targeted deep sequencing (entire exon region of a panel of 84 myeloid genes, Agilent custom probe set) on 285 bone-marrow samples including the longitudinal samples taken at diagnosis (n=95) and post-AZA treatment, (median 4 cycles) as well as T-cell fraction (CD3+). We multiplexed and sequenced the samples using an Illumina Hiseq 2000. After read mapping and variant calling, hierarchical clustering, pathway and survival analyses were performed in R. Results: Targeted sequencing on the myeloid gene panel revealed 176 mutations in 68 patients (68/95, 71.6%) with a median of 2 mutations per patient (ranges 2-6). The average on-target coverage for 285 sequenced samples was 1205x. Twenty-five of 44 mutated genes were recurrently mutated. ASXL1 was the most frequently mutated in the cohort (21%), followed by TET2 (15%), DNMT3A (11%), and SRSF2 (11%). Mutated genes were then grouped into 8 biological pathways, defined in The Cancer Genome Atlas (TCGA) AML study. The most frequent biological pathway with mutated genes at diagnosis was DNA methylation (28.4%), followed by spliceosome (25.2%), chromatin modifiers (22.1%), myeloid transcription factors (TFs) (11.6%), activated signaling (11.6%), tumor suppressors (12.6%), and cohesin complex (6.3%). When assessing the differences in patterns of variant allele frequency (VAF), we found significant VAF reduction in responders compared to non-responders (p = 0.007, repeated measures using general linear model, Figure A). Multivariate analyses revealed that mutation burden in different genes and biological pathways have distinct impact on AZA response, AML transformation, and overall survival. Higher bone marrow blast percentage (5%) was associated with all three measures (Figure B). Most significantly, mutations in activated signaling pathway genes are associated with AML progression (p=0.002). In addition, we could not detect decreased VAFs in activated signalling pathway genes even in responders (Figure C-D). Patients with SRSF2 mutations tend to respond to AZA (OR 14.084, p=0.003). Mutations in tumor suppressors (HR 4.825, p Conclusion: These data and analyses show that reduction in mutation burden is correlated with AZA response. Mutations in different genes and biological pathways are associated with distinct clinical measures that tumor suppressors and myeloid TFs were identified as poor prognostic factors in terms of OS. Persistent mutation burden in activated signaling pathways is a strong predictor for AML transformation. In summary, longitudinal tracking of MDS patients using NGS may improve criteria for AZA response and early detection of AML progression. Figure 1. Figure 1. Disclosures Jang: Alexion Pharmaceuticals, Inc: Consultancy, Honoraria, Research Funding.

Introduction: The discoveries of JAK2-V617F as well as MPL and CARL mutations have greatly clarified the underlying genetics of Philadelphia negative myeloproliferative disease (MPN). Mutation status on these three genes, especially JAK2-V617F, can characterize over 90% of MPN patients. However, the heterogeneity of MPN in terms of its AML transformation and treatment response remains unclear. To assess the difference in mutational status between MPN patients who progress to secondary AML and those who do not, we aim to examine longitudinal samples taken from multiple time points using next generation sequencing. Patients and Methods: Bone-marrow (BM) samples were collected from 19 MPNpatientsfrom2003 to 2012atChonnamNational UniversityHwasunHospital.The diagnosis of MPN was established according to the revised criteria of the World Health Organization.Longitudinal samples were taken at the time of diagnosis and at a follow-up as well as its T-cell fractions (CD+3) isolated from the peripheral blood using MAC separation column.Targeted sequencing was performed using an Agilent custom probe set of a panel of 84 myeloid genes. We multiplexed and sequenced the samples using an IlluminaHiseq2000. Results: The mean on-target coverage for the 57 sequenced samples was 861.4x. We detected a total of 48 somatic mutations in 25 genes in 17 patients (89%) throughout the course of the disease. Five of the 25 genes were recurrently mutated (JAK2, IDH2, ASXL1, SRSF2 and, TP53). As expected, JAK2-V617F was the most commonly observed (15/17 patients). One of the patients without JAK2-V617F carried a MPL mutation and another was triple negative.At the time of follow-up, 12 patients had chronic MPN (11 stable disease and 1 spleen response) withRuxolitinib treatment for a median duration of 373 days (range 255 - 729). Among 7 progressed patients, 5 patients had additional mutation at diagnosis of MPN other than JAK2 or MPL: MPN-13 (DNMT3A and ASXL1), MPN-14 (SRSF2 and IDH2), MPN-15 (IDH2), MPN16 (U2AF1), MPN-17 (IDH2 and SRSF2) as shown in figures. On the other hand, 4/12 non-progressed patients carried additional mutations: MPN-01 (ZRSR2), MPN-05 (ASXL1, CBL, FGR, KMT2D and TET2), MPN-10 (ASXL1, CDH13, EED, EZH2, MN1, NF1 and TRRAP), MPN-11 (FOXP1). In summary, only ASXL1 and JAK2-V617F were recurrently mutated among the non-progressed group. At the time of leukemic transformation, 6 out of 7 patients acquired new mutations: MPN-13 (SETBP1 and TP53), MPN-14 (RUNX1, ASXL1, and IDH1), MPN-15 (TP53 and CASP8), MPN-16 (TP53), MPN-18 (CEBPA), and MPN-20 (ASXL1). In the remaining case (MPN-17), increase of JAK2-V617F VAF was also observed. In summary, TP53 mutation was the most common mutation to acquire by the time of leukemic transformation (n=3). Other mutations acquired by this stage were in SETBP1, RUNX1, IDH1, CEBPA, and ASXL1. We did not observe any significant difference in the allelic burden increase of JAK2-V617F from diagnosis to follow-up between the non-progressed and progressed groups (Figure A). Conclusion: There is no significant difference in mutation burden increase of JAK2-V617F between patients who progressed to secondary AML and patients that did not. Acquisition of mutations other than JAK2-V617F at both diagnosis and at follow-up is associated with the risk of transformation to secondary AML. Mutation profiling using a myeloid gene panel at timed follow-up after MPN diagnosis can be more helpful than monitoring JAK2-V617F status in these patients. Figure Figure. Disclosures No relevant conflicts of interest to declare.

Background and Objectives Acute Myeloid Leukemia (AML) is a cytogenetically and molecularly heterogeneous disease. In the recent decades, many genetic mutations and their clinical significances in AML have been identified with the development of new genomics technology. Based on these advances, new 2 entities were added to the WHO 2008 classification : AML with mutated NPM1 and AML with mutated CEBPA. Likewise, AML with RUNX1 mutation are now considered as a new provisional entity in the next update of WHO classification. In this work, we characterized patients with cytogenetically normal AML according to RUNX1 mutational status and analyzed several co-mutations by next generation sequencing. Patients and Methods A total of 419 patients were included in the present study who met the following eligibility criteria: 1) age ≥ 15 years; 2) a diagnosis of AML with normal karyotype confirmed by conventional cytogenetic analysis. Analysis of genetic mutations were performed using targeted resequencing by Illumina Hiseq 2000 (Sureselect custom probe set targeting 94 myeloid gene panel including RUNX1 mutation). Samples for the confirmation of first complete response were also analyzed in 163 patients. The majority of patients (97%) received '3+7' standard induction chemotherapy. Median age was 53(range 15-84). Results Overall, most common mutations for this cohort were NPM1(33.9%), DNMT3A(30.3%), NRAS(20.2%), IDH2(15.0%), FLT3(12.2%), CEBPA(11.1%). RUNX1 mutations were found in 22 of 419 (5.4%) patients. 7 of 13 available samples in complete remission still had RUNX1 mutation. The patients with RUNX1 mutations were older than those with wild-type RUNX1. (p=0.006) and RUNX1 mutation had a trend of male preponderance. The WBC count and blast percentage of peripheral blood and bone marrow were not different according to RUNX1 mutational status. The complete response rate was significantly lower in RUNX1 mutated group compared with wild-type group. (57% vs. 84%, p=0.005) In univariable survival analysis, RUNX1 mutations were significantly associated with inferior event-free survival (EFS) (p Conclusion In cytogenetically normal AML, RUNX1 mutation is observed in 5.4% and is mutually exclusive of the NPM1 and CEBPA mutation. Older age and lower complete response rate is correlated with RUNX1 mutation. In univariable survival analysis, RUNX1 mutation is associated with poor clinical outcomes. Disclosures No relevant conflicts of interest to declare.

BACKGROUND: Acute myeloid leukemia (AML) is a biologically heterogeneous disease that can be classified into three distinct categories. For example, AML can develop after a prior myeloid malignancy such as myelodysplastic syndrome (MDS). This is known as secondary AML. In previous studies, the genetic basis of secondary AML has been shown such as mutations in genes involved in splicing machinery. However, the progression from MDS to AML has not been studied extensively. In this study, we performed whole-exome sequencing on 26 patients at the time of MDS and AML to dissect the mutational profiles and clonal evolution from MDS to AML. METHODS: We reviewed the cryopreserved samples from 2003 October to 2013 June in Chonnam National University Hwasun Hospital. We only selected the patients who preserved paired sample at the time of MDS and AML. Germline and tumor samples at the time of MDS and AML were analyzed using whole exome sequencing (Agilent SureSelect v3, HiSeq 2000). Targeted sequencing for selected variants were performed to validate the result. RESULTS: Exome sequencing was performed as per the manufacturer's protocol using an Illumina HiSeq 2000 sequencer. DNA from T-cell was used as a control for variant calling in all 26 cases. Exome sequencing reads processing includes mapping to human genome hg19, marking PCR duplicates, realignment of indels, fixing mate information, and discard the reads with more than 1 mismatch to reduce the false positive rate. In the end, we have on-target-coverage of 72x. Lastly, 80% of target positions are mapped more than 30x. To detect variants that may have been filtered out due to our stringent criteria, we compiled a variant list consisting of all unique variants from all cases in this study as well as the unique variants from two other studies not already found in any of our cases, searched for these variants in each of the cases, and classified them into three tiers within each case: Tier 1. Variants that are statistically significant and meet our criteria in at least one of the MDS or sAML samples within each case. Tier 2. Variants that occur in Tier 1 from any other case with a minumum VAF of 10% in at least one of the MDS or sAML samples per each case. Tier 3. Reported variants from previous studies, which have a VAF of at least 10% in either MDS or sAML in each case. We identified the mean and median of 11.59 and 11 variants, respectively. In total, we identified 313 unique somatic mutations, consisting of 205 non-synonymous SNVs, 66 synonymous SNVs, 8 frame-shift deletions, 5 frame-shift insertion, 20 stop-gain mutation, 1 non-frameshift insertion, 4 non-frameshift deletion, and 8 splicing variants from 273 genes. Among them, 18 genes were recurrently mutated including U2AF1 and TP53. We are currently validating these variants using targeted deep sequencing with much higher coverage. Our pathway analyses confirm that 13/26 patients have mutations and 12/26 patients have mutations in pathways related to splicing machinery and/or epigenetics (total n=17). Our analyses confirm that 21/26 patients have at least 1 mutation in at least one of the pathways in 8 commonly mutated pathways related to AML. In addition, we found that variants in these pathways are mutually exclusive, which means that two mutations in same pathways are highly unlikely to occur in a single patient. Using such time series data, we have inferred clonal evolution of these cases. Our analyses postulate the hierarchy of mutated pathways in secondary AML as well as hierarchy of variants. CONCLUSION: In this study, we have performed the whole exome sequencing of 26 secondary AML patients at the time of MDS and AML. Our extensive analyses reveal the order of gene mutations, inferring the hierarchy of mutated pathways during the progression. Also, our study shows that time series analysis contrasting MDS and AML periods provides a much more comprehensive view of clonal structure and evolution. Disclosures Kim: Novartis Pharmaceuticals: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding.

Background: Stem cells display remarkably high levels of 5-hydroxymethylcytosine (5hmC) and, both TET2 or IDH1/2 mutations can impair 5hmC generation. However, the implications of 5hmC have not been evaluated comprehensively in patients with normal karyotype (NK)-AML, especially in aspect of prognostic value in survivals. Methods: A total of 407 patients were included in the present study, and all met the following eligibility criteria: 1) age ≥ 15 years; 2) a diagnosis of NK-AML confirmed by conventional cytogenetic analysis; and, 3) treatment with induction chemotherapy using a standard protocol (a 3-day course of anthracycline with a 7-day course of cytosine arabinoside). NK-AML patients were diagnosed from October 1998 to September 2012 in seven participating institutes. Among 407 patients with NK-AML who received induction therapy, we selected the 376 patients available the analysis of 5-hmC, retrospectively. For quantitation of 5hmC, Quest 5-hmC DNA ELISA kits (Zymo Research) were used following the manufacturer's protocol. TET2 or IDH1/2 mutation analysis were performed using direct sequencing. We analyzed for 5hmC levels in patients with TET2 or IDH1/2 mutations and, to know the correlation of 5hmC levels with mutant alleles. Results: The prevalence rates for the mutations were 13.0% in TET2mut, 7.2% in IDH1 and,14.1% in IDH2mut. Mutation rates of TET2 or IDH1/2 was 34.6% (130/376). We examined whether the range of 5hmC values correlated with each mutations. TET2, IDH1/2 mutated patients had significant lower levels of 5hmC compared with patients without any TET2 or IDH1/2 mutations (all, p0.05). To identify the role of 5hmC levels in clinical significances, we sub-classified this group with tertile category for 5hmC values. However, we could not find the clinical significant in OS, EFS and relapse risk according to the 5hmC levels (all, p>0.05). Conclusion: TET2 or IDH1/2 mutated patients had lower levels of 5hmC. 5hmC levels distributed with wide range in patients with TET2 and IDH1/2 wild type and tightly clustered in patients with TET2, IDH1 or IDH2 mutations. Apart from affecting the methylation status of the DNA, other processes may be influenced by 5hmC levels in patients with NK-AML with TET2 wild-type and IDH1/2 wild type. In addition, 5hmC may not be a prognostic value to predict the survivals of relapse risk in NK-AML. Disclosures Jang: Alexion Pharmaceuticals: Research Funding. Kim:Novartis Pharmaceuticals: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding.

BACKGROUND: Tyrosine kinase inhibitor (TKI) resistance is the most relevant event during the treatment of chronic myeloid leukemia (CML), which correlates with high risk of treatment failure, disease progression and death, explaining half of treatment failed CML patients. However, the remaining half with TKI resistance does not show any ABL1 tyrosine kinase domain (TKD) mutation indicating the presence of alternative pathogenic pathways behind TKI resistance. Thus we hypothesized that the novel mutation besides ABL1-TKD mutation occurs during the development of TKI resistance. Using whole exome sequencing, we screened 13 pairs of CML cases with TKI resistance, but without ABL1-TKD mutation. The present study attempts to: 1) explore novel mutation(s) developing TKI resistance to CML treatment and 2) validate the somatic variants in an independent cohort of CML patients (n=100). METHODS: Thirteen CML cases with TKI resistance but not having ABL1 TKD mutation were included prospectively. Reason for TKI resistance includes Loss of MCyR (n=7) with (n=2) or without additional cytogenetic abnormality (ACA; n=5), progression to blastic crisis (n=3), development of ACA (n=1), development of clonal evolution in Ph neg clone (n=1), primary cytogenetic resistance (n=1). TKI resistance were demonstrated to imatinib (n=12), dasatinib (n=5), nilotinib (n=4) or ponatinib (n=2). The latest treatment includes ponatinib (n=3), dasatinib (n=8) alone (n=4), with smoothen inhibitor (n=2), or with after systemic chemotherapy (n=2), omacetaxine (n=1), and nilotinib (n=1). Disease stage at the time of exome sequencing was chronic phase (n=10) or blastic crisis (n=3). Germline and tumor samples at the time of TKI resistance were compared using whole exome sequencing (Illumina TruSeq kit, HiSeq 2000). Targeted sequencing for selected variants was performed to validate the result. All patients were confirmed the absence of ABL1-TKD mutations using Sanger sequencing. RESULTS: 1) Exome sequencing (Illumina Truseq kit) was performed as per the manufacturer's protocol using an Illumina HiSeq 2000 sequencer. DNA from buccal mucosa was used as a control for variant calling. Exome sequencing reads processing includes mapping to human genome hg19, marking PCR duplicates, realignment of indels, fixing mate information, and discard the reads with more than 2 mismatches to increase the true positive rate. In the end, we have on-target-coverage of 57x. Lastly, 72% of target positions are mapped more than 30x. 2) One hundred nineteen somatic variants were identified in 13 patients in 108 genes. Among them 5 genes have variants in multiple patients including DNMT3A (n=3), ASXL1 (n=2), NPIPB5 (n=2), ATXN3 (n=2) and EFEMP1 (n=2) . We also found at least 1 mutation in well-known driver genes in 6 patients (6/13 = 46%). 3) Three out of 4 patients with ACA carry variants at least one of DNMT3A (n=2), ASXL1 (n=2), and SETBP1 (n=1). Also, 2 out of 3 cases progressed to blastic crisis demonstrate variants in DNMT3A (n=1) and IDH1 (n=1). 4) Interestingly, in one patient, exome sequencing reveals ABL1-TKD mutation (T315I), which was not detected at the initial screening by Sanger sequencing. 5) The result of targeted sequencing in an independent cohort of CML patients (n=100) will be presented in the annual meeting of American Society of Hematology in Dec 2015. CONCLUSION: Our study suggest that DNMT3A and ASXL1 mutations seem to be the driver mutations involved in the development of TKI resistance/progression, independent of ABL1-TKD mutation. Also, exome sequencing can detect ABL1-TKD mutations including T315I prior to be detected by initial Sanger sequencing. Disclosures Lipton: Ariad: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding. Kim:Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding.

Liver X receptors (LXRs) are nuclear hormone receptors that behave as lipid sensors of cellular cholesterol and fatty acid. Although LXR activation can alleviate hypercholesterolemia by inducing cholesterol efflux, it also results in undesirable effects of fatty acid synthesis, resulting in hepatic steatosis and hyperlipidemia. Therefore, it is critical to identify LXR{alpha} inhibitory agents that would repress fatty acid synthesis and hepatic lipid accumulation. In current study, screening of plant extracts used for traditional oriental medicine resulted in the identification of two candidates demonstrating selective LXR{alpha} inhibitory activity. These were whole leaf methanol extracts of Parthenocissua tricuspidata (MEH184) and Euscaphis japonica (MEH185). Both MEH184 and MEH185 decreased transcriptional activity of LXR{alpha} and the expression of LXR{alpha} target genes, such as FAS and ADD1/SREBP1c. Additionally, MEH184 and MEH184 significantly reduced lipogenesis and adipocyte differentiation. Together, the data imply that MEH184 and MEH185 possess selective antagonistic properties on LXR{alpha} to downregulate lipogenesis.