ALBERT

Description: Translating the genetic and epigenetic heterogeneity underlying human cancers into therapeutic strategies is an ongoing challenge. Large-scale sequencing efforts have uncovered a spectrum of mutations in many hematologic malignancies, including acute myeloid leukemia (AML), suggesting that combinations of agents will be required to treat these diseases effectively. Combinatorial approaches will also be critical for combating the emergence of genetically heterogeneous subclones, rescue signals in the microenvironment, and tumor-intrinsic feedback pathways that all contribute to disease relapse. To identify novel and effective drug combinations, we performed ex vivo sensitivity profiling of 122 primary patient samples from a variety of hematologic malignancies against a panel of 48 drug combinations. The combinations were designed as drug pairs that target nonoverlapping biological pathways and comprise drugs from different classes, preferably with Food and Drug Administration approval. A combination ratio (CR) was derived for each drug pair, and CRs were evaluated with respect to diagnostic categories as well as against genetic, cytogenetic, and cellular phenotypes of specimens from the two largest disease categories: AML and chronic lymphocytic leukemia (CLL). Nearly all tested combinations involving a BCL2 inhibitor showed additional benefit in patients with myeloid malignancies, whereas select combinations involving PI3K, CSF1R, or bromodomain inhibitors showed preferential benefit in lymphoid malignancies. Expanded analyses of patients with AML and CLL revealed specific patterns of ex vivo drug combination efficacy that were associated with select genetic, cytogenetic, and phenotypic disease subsets, warranting further evaluation. These findings highlight the heuristic value of an integrated functional genomic approach to the identification of novel treatment strategies for hematologic malignancies.

Description: Oncogenic ROS1 fusion proteins are molecular drivers in multiple malignancies, including a subset of non-small cell lung cancer (NSCLC). The phylogenetic proximity of the ROS1 and anaplastic lymphoma kinase (ALK) catalytic domains led to the clinical repurposing of the Food and Drug Administration (FDA)-approved ALK inhibitor crizotinib as a ROS1 inhibitor. Despite the antitumor activity of crizotinib observed in both ROS1- and ALK-rearranged NSCLC patients, resistance due to acquisition of ROS1 or ALK kinase domain mutations has been observed clinically, spurring the development of second-generation inhibitors. Here, we profile the sensitivity and selectivity of seven ROS1 and/or ALK inhibitors at various levels of clinical development. In contrast to crizotinib’s dual ROS1/ALK activity, cabozantinib (XL-184) and its structural analog foretinib (XL-880) demonstrate a striking selectivity for ROS1 over ALK. Molecular dynamics simulation studies reveal structural features that distinguish the ROS1 and ALK kinase domains and contribute to differences in binding site and kinase selectivity of the inhibitors tested. Cell-based resistance profiling studies demonstrate that the ROS1-selective inhibitors retain efficacy against the recently reported CD74-ROS1G2032R mutant whereas the dual ROS1/ALK inhibitors are ineffective. Taken together, inhibitor profiling and stringent characterization of the structure–function differences between the ROS1 and ALK kinase domains will facilitate future rational drug design for ROS1- and ALK-driven NSCLC and other malignancies.

Description: Despite the well-established success of ABL1 tyrosine kinase inhibitors (TKIs) in the treatment of patients with chronic myeloid leukemia (CML), approximately 20% of patients treated with frontline imatinib develop resistance by 5 years on therapy. The majority (~60%) of such resistant cases are explained by acquired mutations within the BCR-ABL1 kinase domain that compromise inhibitor binding, and nearly all of these mutations are effectively targeted by one or more of the 2nd and 3rd generation ABL1 kinase inhibitors. In contrast, the remaining ~40% of imatinib-resistant cases harbor no explanatory BCR-ABL1 kinase domain mutation, presumably attributable to BCR-ABL1 kinase-independent mechanisms. We hypothesized that resistance in these patients results from acquired auxiliary molecular aberrations which persistently activate signaling pathways downstream despite inhibition of BCR-ABL1 kinase activity. To identify such mechanisms, we performed whole exome sequencing and RNA sequencing on a cohort of 135 CML patients comprising the following subgroups: newly diagnosed/TKI naïve (n=28), BCR-ABL1 kinase-dependent resistance (n=31), and BCR-ABL1 kinase-independent resistance (n=65), and TKI-induced remission (n=7). Resistant patients were required to have demonstrated clinical resistance to one or more ABL1 kinase inhibitors in the form of suboptimal response or loss of cytogenetic response; the subtype of resistance was defined based on the presence or not of an explanatory BCR-ABL1 kinase domain mutation at the time of resistance. The majority of samples collected were from patients with chronic phase CML (n=97), although smaller cohorts of accelerated phase CML, blast crisis CML, and Ph+ ALL were also profiled (n=20, 19, and 9, respectively). Among the 44,413 protein-altering and 902 splice site variants detected across the 120 WES samples, there were on average 908 missense, 146 truncation and 69 splice variants per sample. Genes with truncation and missense variants were compared between BCR-ABL1 kinase-independent and -dependent resistant chronic phase samples. A total of 44 genes were seen with a frequency difference of at least 10%, including PLEKHG5 and NKD2 (30% and 28% difference, respectively), which are involved in regulation of NF-kB and Wnt signaling. Consistent with previous reports, we also detected EZH2 and TET2 as exclusively mutated in the BCR-ABL1 kinase-independent resistance patients (6% and 3%, respectively). Further analyses stratifying variants among resistant patients according to specific ABL1 kinase inhibitor therapy failed and comparing, where available, serial samples from pre- and post-treatment for clonal expansion are underway. Additionally, sufficient material was available to perform ex vivo small-molecule inhibitor screening for 48 patient specimens, the resultant data of which was used to generate putative effective drug target profiles and integrated with exome sequencing variants to prioritize variants of functional relevance (HitWalker; Bottomly et al., Bioinformatics 2013). Among 23 patient samples exhibiting BCR-ABL1 kinase-independent resistance, the mutated genes most frequently ranked in the top 10 functional-prioritized variants were: ABL1 (which included non-kinase domain variants; 34.7%), MAP3K1, MUC4, FGF20 (each 17.4%), ARHGEF15, MEF2A, EPHA8, TYRO3, BMP2K, and IRS1 (each 13.0%). Notably, the top six candidates are members of the neutrophin (ABL1, MAP3K1, and IRS1), EPHA forward (EPHA8, ARHGEF15), and p38 MAPK signaling pathways (MAP3K1 and MEF2A). Taken together, these findings suggest that several of the same pathogenic molecular abnormalities seen in other myeloid malignancies are also present in CML patients with BCR-ABL1 kinase-independent resistance, including a subset which align to persistent re-activation of signaling pathways involved in CML disease pathogenesis and progression. As such, genetic and/or functional profiling of these patients in the clinic may translate to actionable candidates for combination therapy to maximize disease control and improve patient outcomes. Disclosures Agarwal: CTI BioPharma Corp: Research Funding. Radich:Novartis: Consultancy, Research Funding; BMS: Consultancy; Ariad: Consultancy. Deininger:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Research Funding; CTI BioPharma Corp.: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees. Druker:Pfizer: Patents & Royalties; Dana-Farber Cancer Institute: Patents & Royalties: Millipore royalties via Dana-Farber Cancer Institute; Curis: Patents & Royalties; Array: Patents & Royalties; CTI: Consultancy, Equity Ownership; Pfizer: Patents & Royalties; Curis: Patents & Royalties; Array: Patents & Royalties; Dana-Farber Cancer Institute: Patents & Royalties: Millipore royalties via Dana-Farber Cancer Institute; Oncotide Pharmaceuticals: Research Funding; Novartis: Research Funding; BMS: Research Funding; ARIAD: Patents & Royalties: inventor royalties paid by Oregon Health & Science University for licenses, Research Funding; Roche: Consultancy; Gilead Sciences: Consultancy, Other: travel, accommodations, expenses; D3 Oncology Solutions: Consultancy; AstraZeneca: Consultancy; Ambit BioSciences: Consultancy; Agios: Honoraria; MolecularMD: Consultancy, Equity Ownership, Patents & Royalties; Lorus: Consultancy, Equity Ownership; Cylene: Consultancy, Equity Ownership.

Description: Background: Treatment of chronic myeloid leukemia (CML) with a tyrosine kinase inhibitor (TKI) offers significant improvements over previous treatments in terms of survival and toxicity yet has been associated with reduced health-related quality of life and very high cost. Discontinuing TKIs with regular monitoring is safe, but little is known about the impact of discontinuation on patient-reported outcomes (PROs). In the largest U.S. study to date, we evaluated molecular recurrence of CML and PROs after TKI discontinuation. Methods: The Life After Stopping TKIs (LAST) study was a prospective single-group longitudinal study. Key inclusion criteria were age 〉 18 years, patient on TKI therapy (imatinib, dasatinib, nilotinib, or bosutinib) for 〉 3 years with documented BCR-ABL 〈 0.01% by PCR for 〉 2 years, and no previous TKI resistance. We monitored disease outcome (PCRs by central lab) and PROs (PROMIS computerized adaptive tests via REDCap) monthly for the first 6 months, every 2 months until 24 months, then every 3 months until 36 months. Molecular recurrence was defined as 〉 0.1% BCR-ABL IS by central lab (loss of major molecular response [MMR]). We considered 3 points to be clinically meaningful and hypothesized that by 6 months after TKI discontinuation, fatigue, depression, sleep disturbance, and diarrhea would improve by at least 3 points each, corresponding to a standardized effect size of 0.3. Given reports of a withdrawal syndrome of musculoskeletal pain in some patients after discontinuation, pain was an additional outcome of particular interest. For each PRO domain, we estimated a polynomial piecewise linear mixed effects model that specified one nonlinear trajectory after TKI discontinuation and, for those with molecular recurrence, another trajectory after TKI restart. The models included patient-level random effects for the intercepts and linear slopes. Results: From 12/2014 to 12/2016, 172 patients enrolled from 14 U.S. sites. Median age was 60 years (range 21-86) and 89 (52%) were female. The median time on TKI prior to enrollment was 81 months (IQR 54-123). With a minimum follow-up of 24 months, 107 (62%) patients remained in a treatment free remission (TFR). Reasons for restarting therapy were: loss of MMR by central (n=56) or local (n=2) lab, patient decision (n=4), and withdrawal syndrome (n=3). Missing PRO data was minimal (〈 5%) with 〉 2000 assessments completed. For patients in TFR at 6 months, the average estimated improvement in fatigue was 2.6 points (95% CI 2.5-2.7), depression was 1.9 points (95% CI 1.8-1.9), sleep disturbance was 0.9 points (95% CI 0.8-1.0), and diarrhea was 2.7 points (95% CI 2.6-2.7). The average estimated worsening in pain interference (i.e., the extent to which pain affects daily life) was 0.4 points (95% CI 0.3-0.5). The figure shows the distribution of estimated change for each domain at 6 months. All patients showed improvements in depression, diarrhea, and fatigue. About 1 in 6 patients (17%) experienced a clinically meaningful (i.e., at least 3 points) improvement in fatigue and/or diarrhea at 6 months. Conclusion: The LAST study is the largest US TKI discontinuation study to date, and the first to include comprehensive PRO measurement. For patients in TFR at 6 months, TKI discontinuation conferred modest benefits in fatigue and diarrhea on average, with a negligible increase in pain interference. Some patients experienced more notable improvements in fatigue and diarrhea. Planned secondary analyses will include change over time up to 3 years and evaluation of additional PRO domains, including anxiety, physical function, social function, and sexual function. Our results provide important new evidence to support shared patient-provider clinical decision making regarding TKI discontinuation for patients with CML. Figure. Disclosures Radich: Novartis: Other: RNA Sequencing; TwinStrand Biosciences: Research Funding. Mauro:Pfizer: Consultancy; Takeda: Consultancy; Novartis Oncology: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy. Pinilla Ibarz:Sanofi: Speakers Bureau; Abbvie: Consultancy, Speakers Bureau; Teva: Consultancy; Janssen: Consultancy, Speakers Bureau; Novartis: Consultancy; Takeda: Consultancy, Speakers Bureau; Bayer: Speakers Bureau; TG Therapeutics: Consultancy; Bristol-Myers Squibb: Consultancy. Larson:Celgene: Consultancy; Novartis: Honoraria, Other: Contracts for clinical trials; Agios: Consultancy. Oehler:Blueprint Medicines: Consultancy; NCCN: Consultancy; Pfizer Inc.: Research Funding. Deininger:Humana: Honoraria; Incyte: Honoraria; Blueprint: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Research Funding; Ascentage Pharma: Consultancy, Honoraria; TRM: Consultancy; Sangoma: Consultancy; Fusion Pharma: Consultancy; Adelphi: Consultancy; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Sangamo: Consultancy. Shah:Bristol-Myers Squibb: Research Funding. Ritchie:Tolero: Other: Advisory board; Celgene: Other: Advisory board; Celgene, Novartis: Other: travel support; Jazz Pharmaceuticals: Research Funding; Celgene, Incyte, Novartis, Pfizer: Consultancy; AStella, Bristol-Myers Squibb, Novartis, NS Pharma, Pfizer: Research Funding; Ariad, Celgene, Incyte, Novartis: Speakers Bureau; Genentech: Other: Advisory board; Pfizer: Other: Advisory board, travel support; agios: Other: Advisory board. Silver:PharmEssentia: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Cortes:Sun Pharma: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Consultancy, Honoraria, Research Funding; BiolineRx: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Biopath Holdings: Consultancy, Honoraria; Immunogen: Consultancy, Honoraria, Research Funding; Merus: Consultancy, Honoraria, Research Funding; Astellas Pharma: Consultancy, Honoraria, Research Funding. Atallah:Jazz: Consultancy; Helsinn: Consultancy; Pfizer: Consultancy; Takeda: Consultancy, Research Funding; Jazz: Consultancy; Helsinn: Consultancy; Novartis: Consultancy.

Description: The majority of patients diagnosed with Philadelphia negative (Ph-) myeloproliferative neoplasms (MPNs) harbor somatic, gain-of-function mutations in JAK2, CALR or MPL. All of these mutations are associated with constitutive JAK/STAT signaling which confers a proliferative advantage to MPN cells and leads to malignant myeloid expansion at the expense of normal hematopoiesis. The bone marrow (BM) microenvironment in MPNs, particularly myelofibrosis (MF), is characterized by high concentrations of inflammatory cytokines, and we have previously shown that MF cells generate tumor necrosis factor alpha (TNF) in a JAK2-dependent manner. Elevated TNF promotes the survival of JAK2V617F mutant cells over their JAK2WT counterparts, creating a feedback loop in which the mutant cells enhance the inflammatory environment that supports their survival and expansion (Fleischman et al. Blood. 2011 Dec 8;118(24):6392-8). To determine which hematopoietic lineages contribute to increased levels of TNF in MPN, we measured intracellular TNF expression in immunophenotypically defined white blood or BM cells from MF patients and normal controls. TNF expression was relatively low in unstimulated cells. However, lipopolysaccharide (LPS) treatment induced a 16-fold greater increase of TNF expression in hematopoietic stem cells (HSCs) from MF patients relative to normal controls (p

Description: Background The efficacy and safety of subsequent TKIs in pts who have experienced failure of dasatinib is not fully known. Ponatinib, a pan-BCR-ABL inhibitor, was evaluated in a phase 2, international, open-label clinical trial (PACE). This post-hoc analysis explored the efficacy and safety of ponatinib following failure of dasatinib in CP-CML pts in the PACE trial. Methods The PACE trial enrolled 449 pts, including 270 with CP-CML. Pts had to be resistant or intolerant to dasatinib or nilotinib, or they had to have the T315I mutation at baseline. The primary endpoint in CP-CML was major cytogenetic response (MCyR) at any time within 12 months after treatment initiation. The trial is ongoing. Data as of 1 April 2013 are reported, with a minimum follow-up of 18 months for pts remaining on study. The efficacy and safety of ponatinib (45 mg QD) in 107 CP-CML pts following failure of dasatinib as the most recent prior therapy, irrespective of other TKI therapy, is presented (Group D). Eighteen pts who experienced failure of dasatinib but received ≥1 anticancer therapy, other than hydroxyurea or anagrelide, prior to ponatinib treatment were excluded from the analyses. Data are also presented for 2 subsets of Group D: 52 pts whose only TKI therapy was imatinib followed by dasatinib (Group I-D), and 46 pts whose only TKI therapy was imatinib, then nilotinib, and then dasatinib (Group I-N-D). An analysis of cross-intolerance was also conducted in 69 pts with prior dasatinib treatment at any time who discontinued dasatinib due to intolerance. Results Baseline characteristics are shown in the table. Group I-D tended to be younger, with less time since diagnosis versus Group I-N-D. At the time of analysis, 60%, 65%, and 54% of pts in Groups D, I-D, and I-N-D remained on study. The most common reasons for discontinuation were adverse events (AEs; 16%, 15%, 17%) and progressive disease (9%, 6%, 11%) in Groups D, I-D, and I-N-D. Efficacy end points are shown in the table. In Group D, MCyR was seen in pts with the following dasatinib-resistant mutations at baseline: V299L, 3/4 (75%); T315I, 17/23 (74%); F317L, 3/10 (30%). The most common treatment-related AEs were thrombocytopenia (44%, 37%, 57%), rash (39%, 39%, 39%), and dry skin (39%, 29%, 52%) in Groups D, I-D, and I-N-D. Serious cardiovascular, cerebrovascular, and peripheral vascular AEs occurred in 6%, 3%, and 3% of pts in Group D (treatment-related: 3%, 1%, 0%). Seventy-three of 217 pts receiving prior dasatinib at any time discontinued dasatinib due to intolerance. Of these 73 pts, 27 experienced the same AE(s) with ponatinib that led to dasatinib intolerance; 12 pts had grade 3/4 thrombocytopenia, 6 pts had other grade 3/4 AEs (3 with neutropenia, 1 each with pleural effusion, dyspnea, pulmonary hypertension), 8 pts had grade 1/2 AEs. Six of these 27 pts discontinued ponatinib due to the same AE that led to dasatinib intolerance. Thrombocytopenia was the primary AE involved in cross-intolerance (4 pts); congestive cardiac failure (grade 5) and pleural effusion each occurred once. Conclusions Ponatinib has substantial activity in pts with CP-CML following failure of dasatinib, with a safety profile reflective of this heavily pretreated population. Cross-intolerance between dasatinib and ponatinib was infrequent. Disclosures: Hochhaus: Ariad, Novartis, BMS, MSD, Pfizer: Research Funding; Novartis, BMS, Pfizer: Honoraria. Cortes:Ariad, Pfizer, Teva: Consultancy; Ariad, BMS, Novartis, Pfizer, Teva: Research Funding. Kim:BMS, Novartis,IL-Yang: Consultancy; BMS, Novartis, Pfizer,ARIAD,IL-Yang: Research Funding; BMS, Novartis,Pfizer,IL-Yang: Honoraria; BMS, Novartis,Pfizer: Speakers Bureau; BMS, Pfizer: Membership on an entity’s Board of Directors or advisory committees. Pinilla-Ibarz:Novartis, Ariad: Research Funding; Novartis, Ariad, BMS and Pfizer: Speakers Bureau. le Coutre:Novartis: Research Funding; Novatis, BMS, Pfizer: Honoraria. Paquette:ARIAD, BMS, Novartis: Consultancy, Honoraria, Speakers Bureau. Chuah:Novartis, Bristol-Myers Squibb: Honoraria. Nicolini:Novartis, Ariad and Teva: Consultancy; Novartis & Bristol Myers Squibb: Research Funding; Novartis, BMS, Teva, Pfizer, Ariad: Honoraria; Novartis, BMS, Teva: Speakers Bureau; Novartis, Ariad, Teva, Pfizer: Membership on an entity’s Board of Directors or advisory committees. Apperley:Novartis: Research Funding; Ariad, Bristol Myers Squibb, Novartis, Pfizer, Teva: Honoraria. Talpaz:Ariad, BMS, Sanofi, INCYTE: Research Funding; Ariad, Novartis: Speakers Bureau; Ariad, Sanofi, Novartis: Membership on an entity’s Board of Directors or advisory committees. DeAngelo:Araid, Novartis, BMS: Consultancy. Abruzzese:BMS, Novartis: Consultancy. Rea:BMS, Novartis, Pfizer, Ariad, Teva: Honoraria. Baccarani:Ariad, Novartis, BMS: Consultancy; Ariad, Novartis, BMS, Pfizer, Teva: Honoraria, Speakers Bureau. Müller:Novartis, BMS, Ariad: Consultancy, Honoraria; Novartis, BMS: Research Funding. Gambacorti-Passerini:Pfizer: Research Funding; Pfizer, BMS: Honoraria. Lustgarten:ARIAD: employees of and own stock/stock options in ARIAD Pharmaceuticals, Inc Other, Employment. Rivera:ARIAD: Employment. Clackson:ARIAD: employees of and own stock/stock options in ARIAD Pharmaceuticals, Inc Other, Employment. Turner:ARIAD: Employment. Haluska:ARIAD: employees of and own stock/stock options in ARIAD Pharmaceuticals, Inc Other, Employment. Deininger:BMS, ARIAD, NOVARTIS: Consultancy; BMS, NOVARTIS, CELGENE, GILEAD: Research Funding; ARIAD, NOVARTIS: Advisory Boards, Advisory Boards Other. Hughes:Novartis, BMS, ARIAD: Honoraria, Research Funding. Goldman:Ariad: Honoraria. Shah:Ariad, Bristol-Myers Squibb: Consultancy, Research Funding. Kantarjian:RIAD, Novartis, BMS, Pfizer: Research Funding.

Description: Chronic myelomonocytic leukemia (CMML) is a genetically heterogeneous hematopoietic stem cell disorder that combines features of a myelodysplastic syndrome and a myeloproliferative neoplasm and exhibits a strong bias towards older age. The prognosis of CMML is poor, with overall survival of less than 3 years in most studies, however recurrent somatic mutations explain only 15-24% of the clinical heterogeneity of CMML (Elena C. et al. Blood 128:1408-17, 2016). The extreme skewing of the CMML age distribution suggests that CMML reflects the malignant conversion of the myelomonocytic-biased differentiation characteristic of an aged hematopoietic system. We hypothesized that separating the contribution of the normal aging process from bona fide CMML-specific alterations will improve the molecular characterization and biological understanding of CMML. We decided to focus on monocytes as the phenotypic minimal common denominator of genetically heterogeneous diseases. CD14+ monocytes were sorted from the blood of untreated CMML patients (N=12, median age 77 years, range 61-90), age-matched healthy controls (old controls: N=12, median age 68 years, range 62-74) and young healthy controls (young controls: N=16, median age 29 years, range 24-44) and subjected to RNA sequencing and DNA methylation profiling. Differentially expressed genes in CMML monocytes compared to healthy controls were identified with DESeq2 using a 1% false discovery rate (FDR) and a fold-change cutoff set at 〉│2│ (Figure 1A). We identified the 2480 CMML-specific genes by subtracting all genes with significant differences in the young controls vs. old controls comparison from the CMML vs. old controls comparison. The top-25 most significantly upregulated genes (Figure 1B) included transcription factors, TNFα signaling genes, genes that regulate genomic stability, and genes involved in apoptosis. The most significantly downregulated transcripts were genes involved in response to DNA damage, RNA binding, monocyte differentiation and mediators of inflammatory process. To link these observations to function, we imputed the 2480 CMML-specific differentially expressed genes into the ingenuity pathway analysis (IPA) application. This analysis uncovered significant enrichment of pathways involved in: mitotic roles of Polo-like kinase, G2/M DNA damage checkpoint regulation, lymphotoxin β receptor signaling, IL-6 signaling and ATM signaling (Figure 1C). DNA methylation profiling revealed 909 differentially methylated regions (DMRs) between CMML and age-matched controls, with most regions being hypermethylated in CMML monocytes. Of these, 37% of the DMRs were intronic, 22% were exonic, 14 % were in the promoter region (Figure 1D), 10% were downstream, 10% were upstream, the remainder were 3' and 5'-overlaps. We also performed integrated analysis using the promoter DMRs and the gene expression profile to identify CMML-associated genes that are likely to be regulated by specific changes in methylation. We observed concomitant changes in CMML-specific mRNA transcripts and DNA methylation promoter regions in the CMML vs. old controls contrast for 10 genes (Figure 1E). AOAH, SERINC5, TAF3 and AHCYL1 were downregulated and hypermethylated; MS4A3, TNF, VCAM1, and IFT80, were upregulated and hypermethylated; TUBA1B was upregulated and hypomethylated and PITPNA was downregulated and hypomethylated. Our study is the first to combine transcriptional and methylation profiling for molecular characterization of CMML monocytes. Conclusions: (i) age-related gene expression changes contribute significantly to the CMML transcriptome; (ii) the CMML-specific transcriptome is characterized by differential regulation of transcription factors, inflammatory response genes and anti-apoptotic pathway genes; (iii) differences in promoter methylation represent only a small proportion of overall differences in methylation, suggesting that intragenic or intronic methylation is a major contributor to the leukemic phenotype; (iv) age-related changes may be necessary, but are not sufficient to realize the CMML phenotype. Figure 1. Figure 1. Disclosures Deininger: Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Blueprint: Consultancy.