Sproat, Lisa Z.

SummaryWe report a comparative analysis of patients with therapy‐related acute lymphoblastic leukaemia (tr‐ALL) vs de novo ALL. We identified 331 patients with B‐ALL; 69 (21%) were classified as tr‐ALL. The most common prior malignancies were breast (23·2%) and plasma cell disorders (20·3%). Patients with tr‐ALL were older (median 63·2 vs. 46·2 years, P < 0.001), more often female (66·7% vs. 43·5%, P < 0·001), and more likely to have hypodiploid cytogenetics (18·8% vs. 5·0%, P < 0·001). In multivariable analysis, patients with tr‐ALL were less likely to achieve complete remission [odds ratio (OR) = 0·16, P < 0·001] and more likely to be minimal residual disease‐positive (OR = 4·86, P = 0·01) but had similar OS after diagnosis and allo‐haematopoietic cell transplantation.

Background: Gilteritinib is approved for the treatment of relapsed/refractory (R/R) AML and FLT3-mutation (FLT3mut+). However, the gilteritinib phase 3 ADMIRAL study (Perl et al NEJM 2019) enrolled prior to widespread adoption of either midostaurin as a component of standard intensive induction and consolidation or post-transplant FLT3inhibitor (FLT3i) maintenance. Some mechanisms of drug resistance can be shared across FLT3i's, suggesting response to gilteritinib might differ in patients treated with frontline FLT3i. A better understanding of how prior therapy modulates response to gilteritinib is necessary to clarify this novel agent's role in the current FLT3-mutated AML treatment algorithm. Methods: This is an ongoing multi-institutional analysis from 13 US centers identifying patients who received gilteritinib alone or as combination therapy for the treatment of R/R FLT3mut+ AML. Patients who received gilteritinib as a part of an ongoing trial were excluded. Response criteria were identical to the ADMIRAL trial. For patients with available data and a composite complete remission (CRc), we defined clinically measurable residual disease (cMRD) negative status by bone marrow flow cytometry using a cutoff of &lt;1 x 10x105 cells as well as polymerase chain reaction (PCR) for FLT3 mutation with a minimum sensitivity of 5%. Survival from the time of gilteritinib initiation was recorded. Multivariate analysis included all variables collected to determine interaction with patient outcome (CR and survival data). Kaplan-Meier curves and log rank test were used for survival analysis after gilteritinib initiation. Results: 72 patients treated with prior FLT3i exposure received gilteritinib for treatment of R/R FLT3mut+ AML. Patient characteristics are presented in table-1 with 46 (64%) previously receiving midostaurin, 19 (26%) sorafenib, and 7 (10%) other FLT3i. 8 (11%) received more than one prior TKI. NGS at diagnosis were available in 66 patients (92%) and co-mutations in DNMT3A, NPM1 and NRAS were observed in more than 10% of patients. Average duration of gilteritinib therapy was 5.7 months (range: 0.2-25 months). 27 (37.5%) received stem cell transplant (SCT) before gilteritinib and 15 (21%) underwent SCT after gilteritinib. The composite CR rate (CRc, defined as CR + CRi + CRp) was 51.4% (n= 37 patients). With regard to specific FLT3i's, we found no significant difference in median survival (7.1 months and 6.4 months for midostaurin and sorafenib, respectively) or remission rates (CRc 54% and 47% for prior midostaurin and sorafenib, respectively). The CRc rate for patients who received only prior 7+3 and midostaurin with or without consolidation was 58% with a median survival of 7.8 months. A trend toward higher CRc rate was noted in patients treated with gilteritinib in combination regimens rather than as a single agent (64% vs 43%, respectively, p=0.09 using Chi-square test). No survival advantage for combination therapy was seen over single agent. Survival was longest in patients who obtained a CR, particularly a cMRD negative response; this remained significant after censoring at the time of SCT (figures 1&2). Patients who received SCT after gilteritinib had significantly longer survival than non-transplanted patients (9.3 months vs 5.6 months, respectively, HR 0.44, 95% CI 0.2-0.8)(figure-3). Patients with concurrent mutations of NPM1/DNMT3A had a trend toward a higher CRc compared to FLT3 mutation alone (71% vs 50%, p= 0.2) but similar survival. With regard to mutations associated with drug resistance to other FLT3i's, patients with both FLT3-ITD and FLT3-D835 mutation had similar response and survival to FLT3-ITD alone. However, patients with MAPK pathway activating mutations (e.g. NRAS and PTPN11) had lower CRc (37.5% vs 59.5%) and poorer median survival than other patients (3.3 months vs 7.5 months) (HR 2.2- 95% CI 1.1-4.4) p value &lt;0.01(figure-4). Conclusions: In this multi-center, retrospective analysis, gilteritinib remains a clinically active agent after treatment failure of prior FLT3i's (midostaurin or sorafenib). Mutations activating MAPK pathway have been implicated in secondary gilteritinib resistance but are seldom co-mutated at initial FLT3mut+ AML diagnosis. While further study is required, we hypothesize that their detection after frontline FLT3i therapy may represent treatment-emergent clones with propensity for pan-FLT3i resistance. Disclosures Zeidan: Cardiff Oncology: Consultancy, Honoraria, Other; Trovagene: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Otsuka: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Celgene / BMS: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; BeyondSpring: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Taiho: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Acceleron: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Aprea: Research Funding; ADC Therapeutics: Research Funding; MedImmune/Astrazeneca: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Ionis: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Astex: Research Funding; CCITLA: Other; Leukemia and Lymphoma Society: Other; Agios: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding. Yilmaz:Pint Pharma: Honoraria; Pfizer: Research Funding; Daicho Sankyo: Research Funding. Foran:Agios: Honoraria, Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Boehringer Ingelheim: Research Funding; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Revolution Medicine: Consultancy. Daver:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Syndax: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: 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; Karyopharm: Research Funding; Servier: Research Funding; Genentech: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novimmune: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trovagene: Research Funding; Fate Therapeutics: Research Funding; ImmunoGen: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trillium: Consultancy, Membership on an entity's Board of Directors or advisory committees. Perl:Novartis: Honoraria, Other, Research Funding; Agios: Consultancy, Honoraria, Other; Biomed Valley Discoveries: Research Funding; Jazz: Honoraria, Other; FORMA Therapeutics: Consultancy, Honoraria, Other; Syndax: Consultancy, Honoraria; Actinium Pharmaceuticals Inc: Consultancy, Honoraria, Research Funding; AbbVie Inc: Consultancy, Honoraria, Other, Research Funding; Loxo Oncology Inc, a wholly owned subsidiary of Eli Lilly & Company: Consultancy, Honoraria, Other; Bayer HealthCare Pharmaceuticals: Research Funding; New Link Genetics: Honoraria, Other; Astellas: Consultancy, Honoraria, Other: writing/editorial support, travel costs for meeting presentations related to study, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Other: Writing/editorial support, travel costs for meetings, Research Funding; Leukemia & Lymphoma Society, Beat AML: Consultancy; Arog Pharmaceuticals Inc: Other: uncompensated consulting, travel costs for meetings; FUJIFILM Pharmaceuticals USA, Inc: Research Funding; Takeda: Honoraria, Other: Travel costs for meeting. Altman:Kartos: Research Funding; Celgene: Research Funding; Boehringer Ingelheim: Research Funding; ImmunoGen: Research Funding; Amgen: Research Funding; Aprea: Research Funding; Amphivena: Research Funding; Genentech: Research Funding; Novartis: Consultancy; Syros: Consultancy; Janssen: Consultancy; Immune Pharmaceuticals: Consultancy; ASH: Consultancy; Bristol-Myers Squibb: Consultancy; Glycomimetics: Other: Data safety and monitoring committee; Daiichi Sankyo: Other: Advisory Board - no payment but was reimbursed for travel; Kura Oncology: Other: Scientific Advisory Board - no payment accepted, Research Funding; BioSight: Other: No payment but was reimbursed for travel , Research Funding; AbbVie: Other: advisory board, Research Funding; Agios: Other: advisory board, Research Funding; Theradex: Other: Advisory Board; Astellas: Other: Advisory Board, Speaker (no payment), Steering Committee (no payment), Research Funding; PrIME Oncology: Consultancy; PeerView: Consultancy; Cancer Expert Now: Consultancy; France Foundation: Consultancy; Fujifilm: Research Funding. OffLabel Disclosure: Some of the patients we are reporting on received gilteritinib in combination with other agents which is off-label use.

Introduction: Population studies have identified genes with germline polymorphisms associated with acute myeloid leukemia (AML) risk and outcome. However, somatic mutations in these genes have not been reported in an AML clinical population and whether they are associated with epidemiologic exposures, clinical AML phenotypes and outcome after therapy. Methods: We systemically interrogated PubMed database (1998-2018), to identify genes with germline polymorphisms associated with AML risk, response to chemotherapy or outcome. To determine the prevalence and relevance of somatic mutations in these genes in an unselected AML population, we performed an analysis using Whole-Exome Sequencing (WES) on remnant diagnostic cytogenetic pellets from 98 patients from the Mayo Clinic AML Epidemiology Cohort, a detailed and highly-annotated cohort of 295 consecutive AML patients treated at Mayo Clinic Florida & Arizona between October, 2000 and December, 2011. Patient characteristics are shown in Table 1. Samples were sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and somatic mutations including non-synonymous and truncating single nucleotide variants and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, & Mayo Clinic internal biobank genetic variants database. Copy number aberrations were identified & filtered using public copy number polymorphism databases. The association analyses were performed at the gene level, with a primary endpoint of whether a given patient harbored a somatic mutation in any genes linked to AML risk or outcome in literature, and to determine the associations of these mutations with epidemiologic exposures, AML phenotype and clinical outcomes. Results: From the literature search, we identified 77 unique genes with known germline polymorphisms associated with AML risk, response to chemotherapy or outcome. Fifty-eight of these were found to be somatically mutated in our WES dataset, with subsequent analysis focusing on the 11 genes (ABCB1, CYP1A1, CYP2B6, EPHX1, ERCC1, ERCC2, ERCC5, JAK2, MEFV, MTRR, and TERT) that had greater than 5 patients with nonsynonymous somatic mutations in the given gene. Significant associations with epidemiologic exposures and outcomes were noted in patients with somatic mutations in ERCC2, CYP1A1 and ERCC5 genes. Table 2 shows a comparison of patient characteristics and associations according to the presence of somatic mutations in these genes. Patients with mutations in CYP1A1 had a significantly younger age at AML diagnosis (Median: 51.7 vs. 71.0 years, P=.02) and significantly shorter OS in age-adjusted analysis (HR=4.45, P=.003). The former is a novel finding, whereas the latter is consistent with previous reports. Patients with mutations in ERCC2 more commonly used statins (66.7% vs. 21.7%, P=.03). Patients with ERCC5 mutations had a lower rate of tobacco use (20.0% vs. 54.5%, P=.049). In unadjusted analysis, there was a significant association between presence of somatic mutations in JAK2 and poorer survival after AML diagnosis (HR=2.83, P=.017), but this attenuated and did not retain significance when adjusting for age at AML diagnosis (HR=2.22, P=.067). Conclusion: Our exploratory study describes a novel association of CYP1A1 somatic nonsynonymous mutations with age of AML onset, as well as novel associations of ERCC2 and ERCC5 mutations with epidemiologic exposures in an unselect cohort of patients with AML. We confirm the association of CYP1A1 with inferior overall survival after AML diagnosis. These findings suggest that some genes associated with AML risk may also harbor somatic mutations that are clinically relevant. These results will guide a planned confirmatory prospective study to determine frequency and impact of both germline and somatic mutations of risk genes in AML patients, and may contribute to a better understanding leukemia risk assessment and potentially to prevention strategies. Disclosures Finn: Jazz Pharmaceuticals: Speakers Bureau; Celgene: Speakers Bureau; Seattle Genetics: Speakers Bureau. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Foran:Revolution Medicine: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Agios: Honoraria, Research Funding.

Introduction Novel high-risk groups have been identified in adult ALL, including secondary (sALL) and Philadelphia-like ALL (Ph-like, based on CRLF2, IgH, ABL2, JAK2 and other tyrosine kinase translocations), and those with minimal residual disease >0.1% (MRD+) after induction therapy. Novel targeted therapies are now routinely incorporated into 1st line regimens, including tyrosine kinase inhibitors (BCR-ABL1-pos), rituximab (CD20+) and blinatumomab (Blina) for MRD+. The impact of these novel high risk groups and therapies after alloHCT is unknown; therefore, we evaluated their impact on overall survival (OS), relapse rate (REL), non-relapse mortality (NRM) and acute and chronic GVHD. Methods We evaluated pts receiving 1st Allo-HCT for ALL at Mayo Clinic (Rochester, Phoenix, and Jacksonville) from 2008-2018 for outcomes of interest, specifically the impact of novel therapies and risk groups. Associations of patient factors with outcomes were examined using univariable (UVA) and multivariable (MVA) Cox proportional hazards regression models, where the cause-specific hazard of the given outcome was modeled to account for the competing risk of death. Results We identified 261 consecutive AlloHCT recipients during the study period. Median age at transplant was 48 years (18-72) and 147 (56.3%) were male. The median comorbidity (HCT-CI) score was 2 (0-8). 213 pts (81.6%) had B-lineage ALL, of which 85 (32.6%) were BCR-ABL-pos, 17 (6.5%) Ph-like (identified by FISH), 16 (6.1%) hypoploidy/near triploidy (Hy/Tri), and 67 (25.7%) pre-B ALL NOS. The remaining 48 (18.4%) had T-ALL. 30 pts (11.5%) had sALL (i.e. prior chemo/radiotherapy for another malignancy). HyperCVAD was the most common 1st line regimen (68.2%). 243 (93.1%) pts achieved Complete Remission (CR1) after induction therapy, and 203 (77.8%) were in CR1 at the time of alloHCT. Blina was administered for MRD+ in 14 pts (5.4%), and for relapsed/refractory ALL (R/R) in 13 (27% of R/R pts), 7 of whom received Blina as initial therapy for R/R. Donors were matched unrelated in 149 (57.1%), matched related in 98 (37.5%), and haploidentical in 14 (5.4%). Peripheral blood (PB) grafts were used in 233 (89.3%). 103 (54.5%) were donor:recipient (D:R) sex-matched, and 86 D:R mismatched [47 (24.9%) M:F; and 39 (20.6%) F:M]. Myeloablative conditioning was used for the majority (78.5%) mostly with Cy/TBI (60.5%). Standard GVHD prophylaxis regimens were used. Outcomes Median follow-up after transplant was 22.4 months (0.5-135), and 51 (19.5%) had REL. The 1, 2 and 5-year survival rates were 71.9%, 64.9%, and 54.1%, respectively (Figure 1). Acute GVHD developed in 144 (55.2%) and chronic GVHD in 100 (38.3%). Ph-like ALL, Blina for MRD+, Blina for R/R, sALL and CD20-pos had no independent impact on OS. In contrast, age>60, Hy/Tri, and >CR1 at alloHCT were associated with worse OS in UVA, however, in MVA only pre-B ALL NOS was associated with better OS. Female:male D:R status was associated with inferior OS. Blina for R/R disease was associated with increased risk of REL in UVA [HR 5.26 95% CI (1.33, 20.00), p=0.017], whereas other novel high risk groups had no impact on REL. In contrast, T-ALL, Hy/Tri and >CR1 at AlloHCT were associated with increased REL in UVA, but only T-ALL and Hy/Tri continued to predict for increased REL in MVA. Secondary ALL was associated with increased NRM in UVA [HR 1.96 95% CI (1.07, 3.57), p=0.028], whereas other novel high risk groups had no impact on NRM. In contrast, age>60, >CR1 at AlloHCT and D:R sex mismatch were associated with higher NRM in UVA, but only sex mismatch and >CR1 at AlloHCT were associated with higher NRM in MVA. TBI use was associated with higher risk of acute GvHD (p=0.008) and ATG use with lower risk chronic GVHD (p<0.001). Similarly non-PB grafts were associated with a lower risk of chronic GVHD (p=0.005). Results for OS, REL, NRM, acute and chronic GVHD analysis are shown in Table 1. Conclusion Novel high risk groups (CD20+, Ph-like and sALL) do not appear to adversely impact OS after alloHCT, although sALL was associated with increased risk of NRM. Interestingly, pre-B-ALL NOS appear to be associated with favorable OS. Novel targeted therapies also do not independently predict outcome, with the exception of Blina for R/R ALL which may be associated with REL after subsequent alloHCT (a subgroup for whom novel maintenance strategies should be explored). Our analysis highlights the importance of allo-HCT for novel high risk ALL subgroups. Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy. Foran:Agios: Honoraria, Research Funding.

Introduction There have been few recent therapeutic advances in T-acute lymphoblastic leukemia/lymphoma (T-ALL/LBL), a rare and aggressive malignancy. Intensive chemotherapy +/- allogeneic transplantation (AlloHCT) can effect cure, realized by only a minority of adults. In distinction to B-ALL, there have been no safe/effective targeted therapies developed in T-ALL/LBL. We therefore performed a focused tissue array to identify novel tumor proteins, including CCR4; evaluated together with established immunophenotypic (IP) T-ALL/LBL subtypes [early-T-precursor (ETP), early non-ETP (Pre/Pro-T), common & late thymocyte]. We evaluated the clinical phenotype and outcome together with clinical and epidemiologic data in patients diagnosed at the 3-site Mayo Clinic Cancer Center (MCCC: Rochester, MN; Phoenix, AZ; and Jacksonville, FL). Methods Following IRB approval, we identified 50 consecutive T-ALL/LBL patients from 1997 -2019 diagnosed at the 3-site MCCC. Available remnant leukemia/lymphoma paraffin blocks were identified (n=28). Using immunohistochemistry (IHC) we evaluated expression of leukemic antigens of interest (CCR4, CD47, BCL2, BCL6, PD-L1, CD38 and CD123); these were selected based on clinical availability of novel targeted agents, approved or in development for other indications. Tissue array studies were performed and interpreted by a single hematopathologist (L.J) blinded to clinical data, using positive and negative controls, according to standard techniques. We also evaluated the clinical and epidemiological parameters, including different IP subtypes [ETP: CD1a-, sCD3- & CD8-, Pre/Pro-T: CD1a-, sCD3- & CD8+ or CD8- (11 marker T-ALL IP score was used to distinguish CD8- ETP vs. Pre/Pro-T), thymic: CD1a+ and mature: CD1a- & sCD3+] (Khogeer et al., Br J Haematol., 2019) & the presence of the unique MLLT10-PICALM fusion (n=6), as well as therapy and outcome. Comparisons of characteristics and outcomes of interest were made using a Wilcoxon rank sum test (continuous characteristics) or Fisher's exact test (categorical characteristics), unadjusted Cox proportional hazards regression models (overall survival), or unadjusted logistic regression models (complete remission after first line treatment). Results We identified the expression of novel targetable tissue proteins in all adult T-ALL/LBL cases [Table 1]. BCL2, CD38 & CD47 were expressed in majority of the cases, and CCR4 [Fig. 1] was expressed in 11/28 (39.3%) cases. CCR4 expression was significantly more common in the Pre/Pro-T (75%) vs. other IP subtypes (19%) (p=0.011); there was no other association of CCR4 expression with clinical characteristics/outcomes. We also observed differences in T-ALL vs. T-LBL, specifically T-ALL patients were more likely to be male (71% vs. LBL 38.9%, p=0.038). Surprisingly, T-LBL patients were more likely to have a family history of leukemia/lymphoma (41.2% vs. T-ALL 0%, p<0.001). In addition, a significantly different distribution of IP subtype in T-LBL was noted [Table 2]. Not surprisingly, T-LBL patients were more likely to receive 1st line Hyper-CVAD therapy (88.2% v. T-ALL 43.3%, p=0.005), & had a longer delay from diagnosis to initiation of therapy (median 14 vs. 4 days, p=0.012), however this did not appear to impact clinical outcome. In contrast, we observed an important association of IP subtype with outcome after therapy, including complete remission (p=0.035), & a trend suggesting differences in survival (p=0.069) [Table 3]. However, MLLT10-PICALM was not associated with any unique clinical features or with outcome (death, p=0.85; CR, p=0.98), although 4/6 patients underwent AlloHCT, suggesting an important role of AlloHCT in this subgroup. No other significant association of epidemiologic risk factors with phenotype or outcome was noted. Conclusion Using focused tissue array we have identified expression of tumor associated proteins in T-ALL/LBL including CCR4 (Pre/Pro-T IP) & others, which may be targets of therapeutic agents like mogamulizumab. Furthermore, our analysis demonstrates an important clinical impact of IP subtype in T-ALL/LBL, as well as important clinical & therapeutic differences in T-ALL vs. LBL. This study will help guide development of targeted clinical trials in T-ALL/LBL (CCR4 trial already in development). Further analyses are planned to determine the clinical & epidemiologic association of genetic lesions in this cohort. Disclosures Foran: Agios: Honoraria, Research Funding.

Abstract Background: We previously demonstrated that putative clinical epidemiologic exposures associated with leukemia risk are prevalent among AML patients, and some are associated with unique cytogenetic risk group and with clinical phenotype (Finn, Cancer Epidemiol, 2015). Herein, we studied genome-wide DNA methylation in a cohort of AML patients to evaluate the association of individual hyper- and hypo-methylated CpG sites with epidemiologic exposures and overall survival. Methods: The Mayo Clinic AML Epidemiology Cohort is a highly annotated retrospective case series of 295 consecutive patients (pts) with AML diagnosed and treated at Mayo Clinic Florida and Arizona, with central cytogenetics performed in all cases. The prevalence of clinical epidemiologic exposures, past medical and family history as well as medication use and lifestyle was systematically obtained. After IRB approval, we interrogated the cytogenetic database and successfully obtained leukemia DNA from available remnant diagnostic cytogenetic cell pellets in a cohort of 148 AML patients in the Mayo epidemiology case series and performed an assessment of genome-wide DNA methylation using the Infinium HumanMethylation450K BeadChip. Samples were processed using the R Bioconductor package 'minfi' using Subset Within Array Quantile Normalization (PMID: 22703947). Individual CpGs that did not reach a detection p-value of <0.05 were filtered out. An internal control was included on each array to control for significant batch effects. To determine differential methylation status of 473,864 individual CpG sites (after exclusion of 11,648 that did not pass detection p-value QC), CpG sites with low interpatient variability, a standard deviation <0.05 of methylation values, and an interquartile range <0.05 of methylation values and X/Y chromosome probes were excluded from analysis. Epidemiologic and important clinical variables occurring in at least 10 pts or previously-identified as of unique interest but in fewer than 10 pts were evaluated, including sex, BMI, performance status and comorbidities, tobacco and alcohol use, family history of hematologic malignancy, medications of interest, history of toxin exposure, and history of immunosuppression and/or solid organ transplant or of secondary and therapy-related AML (t-AML). Associations of differential hypo or hypermethylation at 281,259 CpG sites with epidemiologic exposures/clinical variables were evaluated using Spearman's test of correlation (continuous or ordinal exposures), a Wilcoxon rank sum test (dichotomous exposures), or a Kruskal-Wallis rank sum test (multi-category exposures). A Bonferroni correction was applied for multiple testing, after which p <1.8 x 10-7 was considered as significant. To reduce the likelihood of false-negative findings, we additionally considered p <5 x 10-6 as indicating suggestive evidence of an association. CpG sites and associated gene and function was determined using Illumina manifest file & www.ncbi.nlm.nih.gov/gene. Results: Statistically significant associations (p <1.8 x 10-7) with individual epidemiologic and clinical exposures were identified for 109 unique CpG sites, corresponding to differential methylation in the genes listed in Table. Specifically, obesity (predominantly hypomethylation), specific cytogenetic lesions and risk group, and gender were highly significantly associated with unique CpG methylation status, but not smoking, toxin exposure, family history, comorbidity or performance status, secondary or t-AML, immunosuppression, medication use, of family history in the analysis. A further 353 unique CpG sites had defined suggestive associations (ongoing analysis). We also identified 8 additional CpG sites where differential methylation was associated with overall survival (p <5 x 10-6, Table). Conclusion: Obesity, cytogenetic lesions, and sex are associated with differential methylation of unique CpG sites at AML diagnosis, using stringent univariate statistical criteria. Significant CpG sites were identified in genes previously linked to AML biology and prognosis (DOCK6, HOXB3, MIR10A, FOXN3/CHES1, GPX1, MYST2/KAT7, PTPRD), but some represent novel findings in AML. These preliminary results suggest an association of some AML risk factors and clinical variables with unique gene methylation and will undergo validation in a prospective AML epidemiology dataset. Disclosures Cerhan: Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Foran:Agios: Research Funding; Xencor, Inc.: Research Funding.

Abstract Introduction: Donor T cell chimerism is tested frequently early after allogeneic hematopoietic cell transplantation (HCT). However, the predictive ability of testing this early after HCT, i.e. at day +30 or day +60, has not been well described, outside of smaller single center studies. Herein, we evaluate the correlation of early donor T cell chimerism with clinical outcomes of overall survival (OS) and relapse in patients undergoing HCT for various hematological malignancies. Methods: We identified patients who received HCT with 8/8 matched unrelated donors at our center between 2007 and 2016 and obtained the clinical data retrospectively. Chimerism studies were included for patients who had testing done at day+30 and/ or day +60. Chimerism is tested using PCR based technique. Due to limited variability in chimerism levels <100% donor chimerism, a cut-off of 100% was used for analysis. Hence, patients were divided into those who achieved full donor chimerism in CD3 fraction (100%) and those in whom CD3 donor chimerism was < 100% at the respective time points. Clinical outcomes evaluate for this abstract were OS and time to relapse. Univariate and multivariate Cox proportional hazard regression models were used using variables of interest, the later adjusted for age at HCT, use of ATG, conditioning regimen and disease risk index (DRI). Results: Baseline patient and HCT data: There were 209 patients who met the selection criteria of which 4 died within 30 days from HCT and hence, were not included in the analysis. Among the 205, 87 (42%) were women and median age at HCT was 55 (range, 18 - 74) years. The hematological malignancy diagnosis was acute myeloid leukemia (AML)/ myelodysplastic syndrome (MDS) in 112 (55%), acute lymphoblastic leukemia (ALL) in 35 (17%), chronic leukemias in 13 (6%), lymphomas in 13 (6%) and myeloproliferative neoplasm in 20 (10%); with DRI being very high in 9 (5%), high in 53 (27%), intermediate in 120 (60%) and low in 17 (9%) patients. Myeloablative conditioning was used in 81 (40%) and reduced intensity conditioning in 124 (60%). Graft versus host disease prophylaxis used was calcineurin inhibitor with methotrexate of mycophenolate in all patients while anti-thymocyte globulin was used in 125 (61%) patients. All patients received a peripheral blood graft. Outcomes: Median follow-up for all included patients was 615 (range, 30 - 3147) days. At day +30, 138 patients had achieved 100% donor CD3 chimerism of 189 patients in whom this data was available (73%) while at day +60, 131 (76%) out of 173 had 100% donor CD3 chimerism. In the univariate model, CD3 donor chimerism level at day +30 as well as day +60, was not predictive of OS (HR 1.5, 95% CI 0.82 - 2.9; p = 0.18 for day +30, HR 1.8, 95% CI 0.81 - 4.0, p = 0.15 for day +60). As for time to relapse, CD3 chimerism did not significantly affect the risk of relapse at these time points (HR 0.43, 95% CI 0.17 - 1.1, p = 0.08 for day +30; HR 0.55, 95% CI 0.18 - 1.6, p = 0.28 for day +60). In the multivariate model also, after adjustment as described above, CD3 at day +30 or at day +60 was not significantly associated with the risk of OS or time to relapse (Figure 1). Kaplan Meier curves for OS for CD3 chimerism at day +30 and day +60 are shown in Figure 2. Conclusions: In this study, T cell chimerism as early as day +30 or day +60 does not seem to predict OS or relapse in patients undergoing HCT for various hematological malignancies. Given the limitations of a smaller retrospective design, this must be validated in a larger study, possibly using registry data. If these findings are indeed confirmed, then the practice of testing chimerism early and frequently, that adds additional expense to the overall cost of HCT, must be reconsidered. Disclosures Palmer: Novartis: Research Funding.

Abstract Introduction: Primary refractory and early relapsed acute myeloid leukemia (RR-AML) continue to pose a therapeutic challenge. Salvage therapy treatment regimens for refractory and relapsed disease are not standardized but include the commonly-used mitoxantrone, etoposide, and cytarabine (MEC) and cladribine, cytarabine, filgrastim, and mitoxantrone (CLAG-M). Previous studies have suggested a potential benefit of CLAG-M, and therefore we performed an analysis of consecutive patients selected to receive either CLAG-M or MEC as salvage therapy for RR-AML. Methods: The study included 150 consecutive patients with RR-AML who received either CLAG-M or MEC between 09/01/2009 and 12/31/2017. Patients were identified through a pharmacy database based on use of mitoxantrone. Baseline disease and patient-related characteristics and clinical outcomes including allogeneic transplantation (ASCT) were obtained by systematic review of EMR. Overall survival (OS) and progression free survival (PFS) were estimated according to the Kaplan Meier method and log-rank test was used to compare outcomes between patients who received either of the two regimens. Results: There were 150 consecutive treated patients with RR-AML included in this analysis, 34 patients received CLAG-M and 116 patients received MEC. The median age was 57 years (18-76), and, and 52% were male. Forty-seven (31%) were treated for early relapsed disease (<6 months after successful induction), 17% (>6 months after induction), and the remainder had primary refractory disease (mean number of induction regimens was 1.8, range 1-6). AML risk was defined by cytogenetic criteria. There were a predominance of intermediate-risk subtypes at 47% (71/150) and followed by high-risk at 37% (55/150). Overall CR/CRi rates for CLAG-M and MEC were 74% (23/31) and 58% (63/108) in patients eligible for analysis (p=0.18). The median follow-up from relapse was 23.5 months (1-76). The median OS was 9.5 months for CLAG-M and 10.0 months for MEC (HR=0.88, 95%CI=0.54-1.41, p=0.59). In total, 76 patients (51%) were able to proceed to ASCT following salvage therapy with either CLAG-M or MEC. Among transplant recipients 56% (19/34) and 49% (57/116) were treated with CLAG-M and MEC, respectively. Median OS after ASCT was 13.0 months for CLAG-M and 31.0 months for MEC (HR=1.76, 95%CI=0.87-3.56, p=0.12). The median OS for refractory AML was 13.0 and 66.0 months for CLAG-M and MEC recipients, respectively (HR=0.92, 95%CI=0.46-1.84, p=0.24). Median OS for those with early relapse was 12.0 months for CLAG-M and 10.0 months for MEC (HR=0.69, 95%CI=0.22-2.11, p=0.51). Lastly, among those who had late relapse, median OS was 9.0 and 48.0 months for CLAG-M and MEC, respectively (HR=17.6, 95%CI=1.57-198, p<0.001). A univariate analysis was performed to investigate the impact of factors associated with OS, including treatment, age, gender, whether they proceeded to ASCT, cytogenetic risk type, and donor source. ASCT was associated with significant improvement in both PFS (HR=0.24, 95%CI=0.16- 0.37, p<0.001) and OS (HR=0.26, 95%CI=0.17-0.40, p<0.001) in this cohort. Age greater than 65 was associated with worse PFS (HR=1.02, 95%CI=1.00-1.03, p=0.04) but not OS (HR=1.01, 95%CI=1.00-1.03, p=0.06) after controlling for other variables including the impact of ASCT. Discussion: Despite a lower 30-day induction mortality we did not identify significant differences in outcomes among patients selected to receive CLAG-M vs. MEC. There was a statistically significant improvement in survival in patients who had late relapses and were treated with MEC, and a trend towards improvement in OS of those treated with MEC who proceeded to ASCT. As expected, ASCT was associated with significant improvement in OS in this cohort, and our results strongly support the use of ASCT as consolidation of remission after relapse for AML. Our data suggests that MEC may be a superior regimen, in particular including those with late relapse. Figure. Figure. Disclosures Foran: Agios: Research Funding; Xencor, Inc.: Research Funding. Al-Kali:Novartis: Research Funding. Palmer:Novartis: Research Funding.