Abstract: Introduction: Patients (pts) with histologically aggressive MCL (HA-MCL; blastoid or pleomorphic) including [de novo (dnMCL) or those transformed from classic morphology (t-MCL)], exhibit a poor prognosis. This analysis provides a comprehensive assessment of so far the largest patient cohort with HA-MCL treated with various modalities. Methods: We included all HA-MCL pts [blastoid (n=142) or pleomorphic morphology (n=26)] at MD Anderson Cancer Center from 12/1997 to 07/2018. Among the 168 pts, 99 were dn-MCL and 69 were t-MCL. Pt characteristics were collected at the time of initial diagnosis in dnMCL and at transformation in t-MCL. Overall survival (OS) was defined from the time of initial diagnosis of HA-MCL to death/last follow-up and failure free survival (FFS) - time of starting first-line treatment after diagnosis of HA-MCL to treatment failure. Whole-exome sequencing (WES) with SureSelect Human All Exon V6 was performed on specimens from 100 pts (among them, 27 tumor-normal pairs and 73 tumors without matched germline), this included CNT (classic never transformed=52), dnMCL=27, t-MCL=21. Two t-MCL pts had tumors sequenced at both classic and HA-MCL phase. Results: Median age for all 168 pts was 65 years (range, 39 to 95). Median time from initial diagnosis of classic t-MCL to HA t-MCL was 39 months (5 to 240 months). The median follow up after the diagnosis of HA-MCL was 19 months (0.1-168). Main clinical features of HA-MCL were - 72% pts had stage IV disease, 67% with marrow involvement, 27% leukemic phase, 20% with B symptoms, 6% had ECOG PS (3-4) and central nervous system involvement in 9% pts. Other features were, median Ki-67% 70% (10-100%), complex karyotype 11%, LDH 〉 upper limit of normal 44%, Sox-11 positive in 82%, median β2M of 2.9 mg/dL. In pt subsets, t-MCL were distinct from dnMCL in having significantly higher median age, higher Ki-67% and lower proportion of marrow involvement at diagnosis. All pts with t-MCL had prior treatment for MCL before transformation. Overall, the median OS after diagnosis of HA-MCL was 32.5 months (45 and 13 months for dnMCL and t-MCL respectively; p=0.001) and the median FFS was 12.5 months (22 and 5 months for dnMCL and t-MCL respectively; p=0.001). In univariate analysis, factors significantly associated with inferior OS in HA-MCL were older age, high Ki-67%, higher LDH, elevated WBC count, higher β2M, lower hemoglobin, lower platelet counts and advanced ECOG-PS, presence of B symptoms, CNS involvement, complex karyotype and t-MCL. Recursive partitioning analysis revealed that Ki-67% ≥50%, LDH ≥1282, β2M ≥ 4, hemoglobin 〈 12 and platelet count 〈 58,000 were associated with significantly increased risk of death. In multivariate analysis (MVA), adjusting for the above variables, higher age (yrs), t-MCL category, Ki-67% ≥50%, ECOG-PS (1-4 compared to 0) and CNS involvement were significantly associated with inferior OS in HA-MCL. (Figure-1 A-D) For FFS, presence of t-MCL, poor ECOG-PS, LDH ≥ 663, CNS involvement were predictive of inferior FFS by MVA. Pts who received ibrutinib based therapies as their first line treatment for HA-MCL had longer FFS compared to intensive chemoimmunotherapy such as R-HCVAD; HR 0.40 (95%CI 0.16-0.99; p=0.04). Frequently mutated genes in HA-MCL were NF1 (34%), SDHA (34%), TP53 (31%), NOTCH1/2 (31%), ATM (26%), and KMT2D (23%). Tumors with different histology subtypes exhibited distinct mutation profiles. TP53 mutations were frequently seen in dnMCL than in t-MCL (39% vs. 20%) and rare in CNT (5%, p=0.0015, compared to dnMCL). SDHA was frequently mutated in dnMCL than in t-MCL or CNT (48% vs. 10% vs. 3%, p 〈 0.01). Deleterious ATM and FAT2 mutation were frequent in HA t-MCL than in classic phase of t-MCL (30% vs. 0%, p=0.2 and 40% vs. 0% respectively, p=0.2). Copy number analysis revealed similar pattern between CNT and classic phase t-MCL (except 19p gain which is 2x higher frequency in classic phase t-MCL than CNT), but distinct copy number gains were noted in HA t-MCL and dnMCL (Fig. 1E). Striking difference between dnMCL and HA t-MCL was observed on chromosome 17, with much higher levels of 17p loss and 17q gain in dnMCL than in HA t-MCL. Conclusions: Histologically aggressive MCL (dn or t-MCL) is a therapeutic challenge. Pts with t-MCL, Ki-67% ≥ 50%, poor PS and CNS involvement had the worst outcomes. Ibrutinib based treatments improve the outcomes of HA-MCL. Further comprehensive molecular analyses will be reported by our group. Disclosures Nastoupil: Spectrum: Honoraria; Janssen: Research Funding; Novartis: Honoraria; Merck: Honoraria, Research Funding; Juno: Honoraria; Gilead: Honoraria; Karus: Research Funding; TG Therappeutics: Research Funding; Genentech: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Champlin:Sanofi: Research Funding; Otsuka: Research Funding. Neelapu:Novartis: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Acerta: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Poseida: Research Funding; Cellectis: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karus: Research Funding; Unum Therapeutics: Membership on an entity's Board of Directors or advisory committees. Fowler:Pharmacyclics: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Wang:MoreHealth: Consultancy; Kite Pharma: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno: Research Funding; Acerta Pharma: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Research Funding; Dava Oncology: Honoraria; Pharmacyclics: Honoraria, Research Funding; Novartis: Research Funding.

Abstract: Introduction: A fraction of pts with classic variant MCL can transform to an aggressive histology (blastoid/pleomorphic) MCL. Outcomes of transformed pts are inferior to that of denovo blastoid variant MCL and classic variant MCL who never transformed (CNT) Jain P et al ASH 2018. Application of routinely available clinical variables at initial diagnosis to predict the future risk for transformation or time to transformation is an unmet need in MCL. Methods: We analyzed charts from 369 pts with MCL (293 were CNT and 76 were transformed MCL). Statistical analysis was performed from baseline pt characteristics collected from the time of initial diagnosis in CNT group and at the time of initial diagnosis of classic variant MCL who later transformed (t-MCL). Time to transformation (TTT) was calculated from initial diagnosis to the date of transformation in those who transformed and last follow up in those who never transformed. Univariate and multivariate logistic regression modeled the risk of transformation. Classification and regression tree (CART) analysis was performed to identify optimal cut off in categorical variables predictive of TTT. Results: Among the 369 pts, the median age was 62 yrs (range 34-90), 79% were males. Ki-67% values were available in 133 pts (36% of total) and median Ki-67% was 25% (range 1-80). 84% had initial bone marrow involvement and 12% had leukemic phase at diagnosis. The median follow up was 58.5 months and the median overall survival (OS) was 94.8 months and 47% were alive at the time of this analysis. Compared to pts in the CNT group, pts in t-MCL group exhibited differences in following baseline characteristics - higher values of median Ki-67% (30% vs 20% in t-MCL; p=0.04), higher LDH levels, higher proportions of pts with high risk simplified MIPI risk score, leukemic phase at initial diagnosis, complex karyotype and lower hemoglobin and lower proportion of pts achieving complete remission (CR) after first line treatment (78% in t-MCL vs 86% in CNT). In addition, first line treatments received by both groups were similar - R-HCVAD based, R-chemo based, ibrutinib based, chemotherapy alone and miscellaneous. Logistic regression model showed factors associated with the risk of transformation. In univariate analysis, higher risk was significantly associated with Ki-67% as a continuous variable - OR 1.03 (95% CI 1.01-1.05; p=0.006), leukemic phase at diagnosis, high risk MIPI score, complex cytogenetics. First line treatment with ibrutinib compared to R-HCVAD, autologous stem cell transplant SCT at any time point and higher number of nodal sites were associated with decreased risk of transformation. In multivariate analysis (MVA), higher number of nodal sites and SCT were associated with decreased risk of transformation. The median time to transformation in months for those who transformed was 39 (range 5-240 months) while in CNT it was 51 months (1-257 months). We further identified that incremental Ki-67% was significantly associated with TTT and OS (Figure-1A-B). Using CART analysis we identified Ki-67% ≥60 is significantly associated with shorter TTT (HR, 6.26; 95% CI 2.58-15.21; p & lt;0.001-1C). In addition, shorter TTT was associated with elevated LDH, high risk MIPI score, CNS involvement at baseline, higher WBC counts, leukemic phase MCL, complex cytogenetics and R-chemotherapy as first line treatment while longer TTT was associated with higher number of nodal sites, SCT at any time point, higher hemoglobin, CR after initial treatment (Figure-1D) and increased number of lines of treatment before transformation. In MVA, higher number of nodal sites, CR after initial treatment was predictive of longer TTT while CNS involvement at baseline and bone marrow involvement at baseline were predictive of shorter TTT. Further analysis on gene signature, type of treatments, response, VH gene mutation, Sox-11 status, somatic mutation status are ongoing and will be reported. Conclusions: This is the first analysis showing an association of routinely available clinical variables in determining risk for transformation of MCL and TTT. Routinely available variables such as incremental Ki-67%, LDH levels, number of nodal sites, ibrutinib based treatments, SCT, CR after first line treatment and leukemic phase at diagnosis reliably predicted for time to transformation in MCL. Disclosures Lee: Seattle Genetics, Inc.: Research Funding. Westin:Genentech: Other: Advisory Board, Research Funding; Curis: Other: Advisory Board, Research Funding; Juno: Other: Advisory Board; Celgene: Other: Advisory Board, Research Funding; Novartis: Other: Advisory Board, Research Funding; Kite: Other: Advisory Board, Research Funding; Unum: Research Funding; 47 Inc: Research Funding; MorphoSys: Other: Advisory Board; Janssen: Other: Advisory Board, Research Funding. Nastoupil:Bayer: Honoraria; Celgene: Honoraria, Research Funding; Genentech, Inc.: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; TG Therapeutics: Honoraria, Research Funding; Spectrum: Honoraria. Champlin:Sanofi-Genzyme: Research Funding; Actinium: Consultancy; Johnson and Johnson: Consultancy. Neelapu:Cellectis: Research Funding; Novartis: Consultancy; Precision Biosciences: Consultancy; BMS: Research Funding; Acerta: Research Funding; Incyte: Consultancy; Poseida: Research Funding; Unum Therapeutics: Consultancy, Research Funding; Cell Medica: Consultancy; Karus: Research Funding; Pfizer: Consultancy; Celgene: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Allogene: Consultancy. Fowler:TG Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding. Wang:Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Loxo Oncology: Research Funding; Celgene: Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau; Juno Therapeutics: Research Funding; Aviara: Research Funding; Dava Oncology: Honoraria; MoreHealth: Consultancy, Equity Ownership; Pharmacyclics: Honoraria, Research Funding; Acerta Pharma: Consultancy, Research Funding; Kite Pharma: Consultancy, Research Funding; Guidepoint Global: Consultancy; BioInvent: Consultancy, Research Funding; VelosBio: Research Funding.

Abstract: This analysis updates the experience of The University of Texas MD Anderson Cancer Center in 673 adults with relapsed‐refractory acute myeloid leukemia in salvage 2 since 2000. It may serve as a solid historic experience against which the results of novel agents in salvage 2 can be evaluated.

Abstract: Background: Preclinically blocking PD-1/PD-L1 pathways enhanced anti-leukemic responses. PD-1 positive CD8 T-cells were increased in the bone marrow (BM) of pts with AML (Daver et al, ASH 2016). Azacitidine up-regulates PD-1 and interferon-gamma signaling (Yang et al., Leukemia 2013). Methods: Pts were eligible for the AZA+Nivo (cohort 1) if they had relapsed/refractory AML (R/R AML), ECOG ≤ 2, and adequate organ function. The recommended phase 2 dose was established as AZA 75mg/m2 Days 1-7 with Nivo 3mg/kg Day 1 and 14. Courses were repeated approximately every 4-5 weeks indefinitely. 70 R/R AML pts have been treated; cohort 1 is closed. A subsequent cohort of AZA+Nivo+Ipi in R/R AML was opened (cohort 2), with the same eligibility criteria as cohort 1 except that enrollment was restricted to pts with salvage 1 and 2 AML. Ipi 1mg/kg Q6 weeks was added to the established AZA+Nivo schedule. This dosing was based on lung and melanoma dosing for Ipi + Nivo. Responses in both cohorts included best response within 3 months of therapy initiation. Results: Cohort 1: 70 R/R AML pts with median (med) age 70 years (range, 22-90), secondary AML (44%), poor risk cytogenetics (34%), med salvage 2 (range, 1-7) were enrolled. The ORR was 33% including 15 CR/CRi (22%) (4 CR, 11 CRi), 1 PR, and 7 HI maintained on study 〉 6 months (10%) without allogeneic stem cell transplant. Additionally, 6 pts (9%) remained on study with stable disease (SD) 〉 6 months. The remaining 41 pts (58%) had no response. 8-week (wk) mortality was 10%. Patients who achieved a CR/CRi/PR/HI/SD (n=29; 42%) had significantly improved overall survival (OS) compared with NRs (n=41; 58%) (16.1 versus 4.1 months; p 〈 0·001). By univariate analysis (UVA) improved ORR was seen in pts with pretherapy BM blast 〈 20%, circulating WBC 〈 /=10,000/mL, ASXL1 mutation, and no prior HMA-based therapy (Table 1). By UVA improved OS was seen in pts who achieved any response or SD (CR/CRi/PR/HI/SD), were salvage 1 status, and had ASXL1 mutation. The med OS with Aza+Nivo compared favorably to historical med OS with AZA-based protocols in salvage 1 or 2 pts at MDACC (6.0 versus 4.7 months; p=0.03)(Fig 1), with the most prominent improvement seen in salvage 1 pts (11.1 versus 4.1 months; P 〈 0.001). Grade 3/4 immune related adverse events (irAEs) were observed in 8 (11%) pts, including pneumonitis (n=3), colitis (n=2), and nephritis, skin rash, and hypophysitis (1 each). The majority (12 of 16; 75%) of these occurred in the first 8 wks after nivo initiation. These responded rapidly to steroids when initiated early. Flow-cytometry (MFC) was performed on pre- and post-therapy BMAs, after 2 doses (end of cycle 1 or EOC1) and 4 doses (EOC2) of nivol in 19 of 23 responders (R) (CR/CRi/PR/HI) (83%) and 28 of 41 NRs (68%). 36 parameter CyTOF was performed at same time-points in 5R and 5NRs. On pretherapy BMAs, R had a higher frequency of CD3+ (p=0.04) and CD8+ cells (p=0.09) on MFC (Fig 2A). CD3+ in the pretherapy BMA with a cut-off of 13.2%, had a sensitivity of 74% and a specificity of 65% for predicting response. The CD3+ was 〉 13.2% in 26 of 47 pts (55%) who had an evaluable pretherapy BMA. Immunohistochemistry confirmed that CD3+ cells were increased in pretherapy BMs in R. PhenoGraph clustering of all CD3-gated cells revealed 24 meta-clusters (Fig 2B). The frequency of an effector CD8+ T cell cluster (C2) expressing CD45RA+PD1loTbethiEomeslo was significantly higher in the pretherapy BMAs of R versus NRs (11.2% versus 2.5%; p=0.002), and was further expanded in R not in NRs in the EOC1, EOC2, and EOC4 BMAs (Fig 2C). Cohort 2: 20 pts with R/R AML, med salvage 2 (range 1-2), med age 68 (range, 25-83), secondary AML (36%), adverse cytogenetics (25%), and common molecular mutations TP53 in 5, RAS in 4, DNMT3A/ASXL1 in 2 pts each, were enrolled. 14 pts enrolled before May 1, 2018 were evaluable for response: 6 CR/CRp/CRi (43%) (including 2 CR, 2CRp, 2CRi), 2 stable disease 〉 6 mths, and 6 no response. The 8-wk mortality was 0. Grade 3/4 irAEs noted in 26% of the pts, most common pneumonitis. Med cycles to response of 2 (1-3). The med OS for all pts was not reached and the projected 1-yr OS in R/R AML was encouraging at 58% (Fig 1). Conclusion: AZA+Nivo was effective in pts with AML in Salvage 1 or those with increased pretherapy CD3+ BM infiltrate by MFC or IHC. BM CD3 and CD8 are simple assays to select pts for future trials of AZA+PD1 inhibitors in AML. AZA+Nivo+Ipi had a encouraging CR/CRp/CRi rate (43%) and med OS (NR) in pts with salvage 1/2 AML and is enrolling. Disclosures Daver: BMS: Research Funding; ImmunoGen: Consultancy; Sunesis: Consultancy; Incyte: Research Funding; Novartis: Consultancy; Karyopharm: Consultancy; Daiichi-Sankyo: Research Funding; Novartis: Research Funding; Pfizer: Consultancy; Karyopharm: Research Funding; Pfizer: Research Funding; Kiromic: Research Funding; ARIAD: Research Funding; Otsuka: Consultancy; Sunesis: Research Funding; Incyte: Consultancy; Alexion: Consultancy. Cortes:novartis: Research Funding. Ravandi:Bristol-Myers Squibb: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Sunesis: Honoraria; Jazz: Honoraria; Xencor: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Astellas Pharmaceuticals: Consultancy, Honoraria; Xencor: Research Funding; Sunesis: Honoraria; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Macrogenix: Honoraria, Research Funding; Macrogenix: Honoraria, Research Funding; Abbvie: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau. Kadia:Takeda: Consultancy; Abbvie: Consultancy; BMS: Research Funding; BMS: Research Funding; Pfizer: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Research Funding; Celgene: Research Funding; Abbvie: Consultancy; Jazz: Consultancy, Research Funding; Novartis: Consultancy; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Novartis: Consultancy; Jazz: Consultancy, Research Funding. Konopleva:Stemline Therapeutics: Research Funding; Immunogen: Research Funding; abbvie: Research Funding; cellectis: Research Funding. DiNardo:Celgene: Honoraria; Medimmune: Honoraria; Abbvie: Honoraria; Karyopharm: Honoraria; Bayer: Honoraria; Agios: Consultancy. Pemmaraju:daiichi sankyo: Research Funding; SagerStrong Foundation: Research Funding; Affymetrix: Research Funding; novartis: Research Funding; abbvie: Research Funding; stemline: Consultancy, Honoraria, Research Funding; plexxikon: Research Funding; samus: Research Funding; celgene: Consultancy, Honoraria; cellectis: Research Funding.

Abstract: We developed and implemented an objective toxicity scoring system to be used during endoscopic evaluation of the upper gastrointestinal (GI) tract in order to directly assess changes in toxicity during the radiation treatment of pancreatic cancer. We assessed and validated the upper GI toxicity of 19 locally advanced pancreatic cancer trial patients undergoing stereotactic body radiation therapy (SBRT). Wilcoxon-signed rank tests were used to compare pre- and post-SBRT scores. Comparison of the toxicity scores measured before and after SBRT revealed a mild increase in toxicity in the stomach and duodenum (p 〈 0.005), with no cases of severe toxicity observed. Kappa and AC1 statistics analysis were used to evaluate interobserver agreement. Our toxicity scoring system was reliable in determining GI toxicity with a good overall interobserver agreement for pre-treatment scores (stomach, κ = 0.71, p 〈 0.005; duodenum, κ = 0.88, p 〈 0.005) and post-treatment scores (stomach, κ = 0.71, p 〈 0.005; duodenum, κ = 0.76, p 〈 0.005). The AC1 statistics yielded similar results. With future usage, we hope this scoring system will be a useful tool for objectively and reliably assessing changes in GI toxicity during the treatment of pancreatic cancer and for GI toxicity assessments and comparisons during radiation therapy research trials.

Abstract: Introduction Since the advent of tyrosine kinase inhibitors (TKIs) in 2001, the treatment goals in the management of chronic myeloid leukemia (CML) have evolved according to international recommendations. The 2009 European LeukemiaNet (ELN) proposed a category of "suboptimal response". The 2013 recommendations introduced a "warning response" category that saw some "suboptimals" in 2009 becoming failures in 2013. The clinical implications of this intermediate category and the difference in categorizations has not been fully explored. As new recommendations are being prepared, we seek to compare the outcomes of patients with suboptimal/warning using 2009 and 2013 guidelines. Methodology We analyzed 730 patients treated with front-line TKIs in various clinical trials and identified patients who meet the criteria for suboptimal response at 3, 6 and 12 months according to the 2009 ELN guidelines and/or warning criteria according to 2013 ELN criteria. We computed descriptive statistics for patients at each of the above criteria at the 3 time points. Kaplan-Meier product limit method, was used to estimate the median for overall survival (OS), event-free survival (EFS), failure-free survival (FFS) and transformation-free survival (TFS). Results Of the 730 CML patients evaluated, using the 2009 ELN guidelines, 2%, 3% and 5% of the patients met the 3, 6 and 12 months definition of suboptimal response, respectively. Analysis of baseline characteristics show a median age of 44.1, 42.1 and 44.4 years, respectively for the three time lines with a predominantly male and white population. Using the 2013 guidelines 4%, 10% and 17% of the patients met the 3, 6 and 12 months definition of warning, respectively. Patients were again predominantly male and white with a median age at diagnosis of 41.5, 44.1 and 47 years respectively. With regard to achieving complete cytogenetic response (CCyR), a higher percentage of patients achieved CCyR using the 2013 guidelines (55.2%, 80.8% and 98%, for warning cohorts at 3, 6 and 12 months, respectively) compared to using the 2009 guidelines (35.3%, 56.5% and 81.1%, respectively). Similarly, for best molecular response, a higher percentage of patients achieved MR4.5 using the 2013 guidelines (10.7%, 20.8% and 44.2%, for warning cohorts at 3, 6 and 12 months, respectively) compared to using the 2009 guidelines (13.3%, 4.5% and 24.2%, for suboptimal cohorts respectively). With respect to survival outcomes, patients classified as warning per the 2013 guidelines had better outcomes than those with suboptimal response using the 2009 guidelines. For example, for EFS, median survival was longer for the 2013 warning cohort compared to the 2009 suboptimal cohort (29 months vs. 18 months, by 3 months assessment). For FFS, the median survival was longer for the 2013 warning cohort compared to the 2009 suboptimal cohort (68 months vs. 11 months, by 6 months assessment). Using the 2013 guidelines median survival could not be reached for most of the survival outcomes. Conclusion Our assessment reveal that survival outcomes were better for the warning cohort using the ELN 2013 recommendations compared to the suboptimal cohort of the 2009 recommendations. This represents a stage migration by moving the subset of patients with the worse outcome away from this intermediate category and into the failure. An important, still unanswered question, is the optimal management of patients in this intermediate category or of those that migrate from one category to the next based on a change in definitions. Disclosures Kantarjian: Ariad: Research Funding; Amgen: Honoraria, Research Funding; Immunogen: Research Funding; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Astex: Research Funding; Cyclacel: Research Funding; Pfizer: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Research Funding; BMS: Research Funding; Daiichi-Sankyo: Research Funding; Takeda: Honoraria; Novartis: Research Funding. Borthakur:Eli Lilly and Co.: Research Funding; NKarta: Consultancy; PTC Therapeutics: Consultancy; Cyclacel: Research Funding; Eisai: Research Funding; Janssen: Research Funding; Agensys: Research Funding; Oncoceutics: Research Funding; Tetralogic Pharmaceuticals: Research Funding; Bayer Healthcare AG: Research Funding; BMS: Research Funding; AbbVie: Research Funding; Merck: Research Funding; GSK: Research Funding; Incyte: Research Funding; Arvinas: Research Funding; BioTheryX: Membership on an entity's Board of Directors or advisory committees; Xbiotech USA: Research Funding; Novartis: Research Funding; AstraZeneca: Research Funding; Argenx: Membership on an entity's Board of Directors or advisory committees; Polaris: Research Funding; Cantargia AB: Research Funding; BioLine Rx: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; FTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Oncoceutics, Inc.: Research Funding; Strategia Therapeutics: Research Funding. Verstovsek:Blueprint Medicines Corp: Research Funding; Celgene: Consultancy, Research Funding; Gilead: Research Funding; Promedior: Research Funding; CTI BioPharma Corp: Research Funding; Genetech: Research Funding; Sierra Oncology: Research Funding; Pharma Essentia: Research Funding; Roche: Research Funding; NS Pharma: Research Funding; Incyte: Research Funding; Astrazeneca: Research Funding; Ital Pharma: Research Funding; Protaganist Therapeutics: Research Funding; Constellation: Consultancy; Pragmatist: Consultancy; Novartis: Consultancy, Research Funding. Kadia:BMS: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bioline RX: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding. Pemmaraju:abbvie: Consultancy, Honoraria, Research Funding; samus: Research Funding; celgene: Consultancy, Honoraria; cellectis: Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; novartis: Consultancy, Research Funding; plexxikon: Research Funding; Daiichi-Sankyo: Research Funding; sagerstrong: Research Funding; affymetrix: Research Funding; mustangbio: Consultancy, Research Funding; incyte: Consultancy, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Konopleva:Agios: Research Funding; Ablynx: Research Funding; Astra Zeneca: Research Funding; Kisoji: Consultancy, Honoraria; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ascentage: Research Funding; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Cellectis: Research Funding; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Eli Lilly: Research Funding; Forty-Seven: Consultancy, Honoraria; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Calithera: Research Funding. DiNardo:notable labs: Membership on an entity's Board of Directors or advisory committees; jazz: Honoraria; medimmune: Honoraria; syros: Honoraria; daiichi sankyo: Honoraria; abbvie: Consultancy, Honoraria; celgene: Consultancy, Honoraria; agios: Consultancy, Honoraria. Sasaki:Otsuka: Honoraria; Pfizer: Consultancy. Jabbour:Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Cyclacel LTD: Research Funding. Cortes:Immunogen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Sun Pharma: Research Funding; Biopath Holdings: Consultancy, Honoraria; BiolineRx: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Astellas Pharma: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Merus: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Consultancy, Honoraria, Research Funding.

Abstract: Introduction: The outcomes of patients (pts) with post-MPN AML are poor, and there is no standard treatment. The Janus kinase 1/2 (JAK1/2) inhibitor ruxolitinib (RUX) markedly improves symptoms and splenomegaly and extends overall survival in advanced myelofibrosis (MF). In a phase 2 study of RUX in pts with relapsed/refractory (R/R) leukemias, 3 of 18 pts with post-MPN AML achieved a complete response (CR) with or without sufficient count recovery and RUX was very well tolerated up to 50 mg twice daily (bid, Eghtedar et al. Blood 2012). The hypomethylating agent (HMA) decitabine (DAC) is widely used for the treatment of AML. HMAs have significant activity in post-MPN AML (Thepot et al. Blood 2010, Mascarenhas et al. Leuk Res 2010, Badar et al. Leuk Res 2015). The combination of RUX and DAC provides an opportunity to target post-MPN AML through disparate mechanisms. Methods: All pts with R/R AML were eligible in the phase I portion of this ongoing, phase I/II trial. Pts in the phase II portion must have post-MPN AML. DAC is administered at 20 mg/m2/d x 5 days in each cycle and RUX is administered continuously starting day 1 of DAC. Cycle length is 4-6 weeks. In the phase I portion, the RUX dose was escalated in "3+3" fashion from 10 through 50 mg bid (dose levels 0, 1, 2 and 3 = 10, 15, 25 and 50 mg bid). Dose limiting toxicities (DLTs) were defined in the first cycle. Response assessment is performed according to published criteria for AML (Cheson et al. JCO 2003). Pts may receive up to 24 cycles of therapy and may proceed to allogeneic stem cell transplantation (ASCT) at any time after cycle 1. Measurement of circulating cytokine levels, intracellular signaling proteins and gene methylation assays are to be performed after 1 and 3 cycles and every 3 cycles thereafter. Results: The phase I portion of the study has completed accrual. 14 pts with AML were enrolled, of whom 2 did not complete 1 cycle of treatment and hence were not evaluable for DLT (withdrew consent; not considered further). The median age was 70 (range 32-92) and the median bone marrow blast percentage was 27.5 (range 1-50). All but 2 pts had post-MPN AML. Of these 2 pts, one (with AML arising from myelodysplastic syndrome (MDS)) had a JAK2 V617F mutation. Of the 10 pts with post-MPN AML, 5 had received no prior therapy for their MPN, 3 hydroxyurea (HU) alone, and 2 multiple treatments for MF. The pt with prior MDS was previously untreated, and the pt with AML without an antecedent hematological disorder had received 2 prior cytotoxic chemotherapy regimens (Table 1). 3 pts each received 10, 15, 25 and 50 mg of RUX bid. Most adverse events (AEs) were grades 1 or 2. Grade 3 or 4 AEs included pneumonia, febrile neutropenia, thrombocytopenia, neutropenia, infection, hypotension, fracture, fever, fatigue, anorexia, muscle weakness, confusion, ileus, and transaminitis; of these, only grade 3/4 thrombocytopenia and neutropenia were judged possibly related to the therapy. No DLTs occurred and the recommended phase 2 dose (RP2D) is RUX 50 mg bid with standard dose DAC. 4 of the 12 evaluable pts have died, 2 from pneumonia, 1 from sepsis and 1 from gastric hemorrhage, all considered unrelated to study treatment. 4 pts remain on study; 4 others discontinued due to disease progression. The median number of cycles received is 4 (range 1-7). 1 pt achieved a CR and 1 CR with incomplete platelet recovery (CRp) after 1 and 3 cycles, respectively; both remain on study treatment. These pts (pt 11 and pt 6 in table 1) received RUX at 50 mg bid and 15 mg bid, respectively. Another pt in the RUX 50 mg bid cohort (pt 10 in table 1) with AML with a complex karyotype and mutated TP53 achieved a CR with incomplete count recovery (CRi) after 1 cycle but subsequently relapsed. A fourth pt (pt 2 in table 1) obtained a partial remission after 2 cycles and proceeded to ASCT after 5. The last pt in the RUX 50 mg bid cohort (pt 12 in table 1) has received 1 cycle of treatment and achieved a morphologic leukemia-free state. The overall response rate is 42%. Conclusion: The combination of RUX and DAC is tolerable and shows promising efficacy in post-MPN AML. Up to 24 pts with post-MPN AML will be enrolled in the phase II portion of the study, at the RP2D of 50 mg bid of RUX and 20 mg/m2/d of DAC x 5 days. Disclosures Jain: Celgene: Research Funding; Infinity: Research Funding; Seattle Genetics: Research Funding; BMS: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; ADC Therapeutics: Consultancy, Honoraria, Research Funding; Incyte: Research Funding; Novartis: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria, Research Funding; Abbvie: Research Funding; Novimmune: Consultancy, Honoraria. Jabbour:ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy. DiNardo:Celgene: Research Funding; Novartis: Research Funding; Agios: Research Funding; Abbvie: Research Funding; Daiichi Sankyo: Research Funding. Pemmaraju:Incyte Corporation: Consultancy, Honoraria. Kantarjian:ARIAD: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Research Funding; Pfizer Inc: Research Funding; Delta-Fly Pharma: Research Funding; Novartis: Research Funding.

Abstract: IMA101 is an actively personalized, multi-targeted adoptive cell therapy (ACT), whereby autologous T cells are directed against multiple novel defined peptide-HLA (pHLA) cancer targets. HLA-A*02:01-positive patients with relapsed/refractory solid tumors expressing ≥1 of 8 predefined targets underwent leukapheresis. Endogenous T cells specific for up to 4 targets were primed and expanded in vitro. Patients received lymphodepletion (fludarabine, cyclophosphamide), followed by T-cell infusion and low-dose IL2 (Cohort 1). Patients in Cohort 2 received atezolizumab for up to 1 year (NCT02876510). Overall, 214 patients were screened, 15 received lymphodepletion (13 women, 2 men; median age, 44 years), and 14 were treated with T-cell products. IMA101 treatment was feasible and well tolerated. The most common adverse events were cytokine release syndrome (Grade 1, n = 6; Grade 2, n = 4) and expected cytopenias. No patient died during the first 100 days after T-cell therapy. No neurotoxicity was observed. No objective responses were noted. Prolonged disease stabilization was noted in three patients lasting for 13.7, 12.9, and 7.3 months. High frequencies of target-specific T cells (up to 78.7% of CD8+ cells) were detected in the blood of treated patients, persisted for & gt;1 year, and were detectable in posttreatment tumor tissue. Individual T-cell receptors (TCR) contained in T-cell products exhibited broad variation in TCR avidity, with the majority being low avidity. High-avidity TCRs were identified in some patients’ products. This study demonstrates the feasibility and tolerability of an actively personalized ACT directed to multiple defined pHLA cancer targets. Results warrant further evaluation of multi-target ACT approaches using potent high-avidity TCRs. See related Spotlight by Uslu and June, p. 865

Abstract: Nilotinib is effective frontline treatment for patients with early chronic‐phase chronic myeloid leukemia, resulting in a high rate of deep and sustained molecular responses. The long‐term safety profile remains favorable.