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Background NHS-IL12 is a first-in-class, recombinant fusion protein composed of the human monoclonal antibody NHS76 (binds exposed DNA/histones at sites of intratumoral necrosis) fused to 2 IL-12 heterodimers. The maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of NHS-IL12 monotherapy given subcutaneously (SC) every 4 weeks was previously reported. The study was expanded to include a high-exposure cohort with NHS-IL12 SC every 2 weeks (q2w). Methods This single-arm, phase I trial evaluated NHS-IL12 12 µg/kg SC q2w or 16.8µg/kg SC q2w in patients with metastatic solid tumors. The primary endpoint was safety. Results Using a 3+3 design, 13 patients with advanced cancer were enrolled and 12 were dose-limiting toxicity (DLT) evaluable. There was 1 DLT (Grade 3 aspartate transaminase/alanine transaminase [AST/ALT] elevation). Other grade 3 toxicities included: flu-like symptoms 1/13 (8%), decreased absolute lymphocyte count (ALC) 1/13 (8%), decreased white blood cell count (WBC) 1/13 (8%), but most adverse events reported were low grade and self-limiting grade. Fifty percent of evaluable patients (6/12) experienced stable disease (SD) with 42% (5/12) developing progressive disease (PD) at the first restaging. Conclusion Biweekly NHS-IL12 was well tolerated in this small phase I study. Additional studies incorporating NHS-IL12 with other immunomodulating agents are underway. (ClinicalTrials.gov Identifier: NCT01417546).

Chimeric antigen receptor T cells (CAR-Ts) targeted against CD19 have shown impressive activity in patients with B-cell leukemias and lymphomas. This has revolutionized the treatment landscape for patients with relapsed or refractory (r/r) disease, providing hope for a possible curative approach for those who previously had limited available treatment options. The success of this approach has prompted interest in studying CAR-Ts for other hematologic malignancies and the development of CARs specific for other antigens. In this review, we discuss recent developments in CAR-Ts in multiple myeloma (MM), Hodgkin lymphoma (HL), T-cell malignancies, and acute myelogenous leukemia (AML; Fig 1).

Genetically engineered medicines such as chimeric antigen receptor (CAR) T cells have great potential to be the next pillar of medical therapy beyond chemo- and traditional biologic therapies. To develop genetic medicines, new methods to understand their pharmacokinetics (PK) in humans are crucial. It is not feasible to perform traditional PK analysis for “living drugs”, because the genes themselves (in the form of DNA or RNA), are not typically responsible for the therapeutic effect. Rather, the protein products of the genes or the cells harboring the engineered genes are the actuators, and thus cannot be measured using standard HPLC or ligand binding immunoassays for PK analysis. We used a positron emission tomography (PET) reporter gene or “imaging tag” based on the intracellular bacterial enzyme dihydrofolate reductase (eDHFR) that can be paired with radiolabeled versions of trimethoprim (TMP). In this work, we evaluate the potential for immunogenicity using primary human cells and assays geared to assess low affinity and rare T cell clones that may react to eDHFR. We used overlapping pools of 15-mer eDHFR peptides and found that across 9 patients, there was little reactivity compared to EBV and CMV peptide controls. Further, the relative strength of reactivity to the eDHFR peptides was less than that of the viral peptides. Next, we showed that eDHFR iTag harboring CAR T cells were functionally comparable to unlabeled CAR T cells in vitro, and demonstrated strong, selective [18F]-TMP uptake in the eDHFR-expressing CAR T cells. Finally, using a glypican 3 (GPC3) CAR T rodent model, we performed a feasibility study to non-invasively track proliferation in antigen-harboring xenograft tumors over time with ex vivo correlation to anti-CD3 immunohistochemistry. These data demonstrate the potential for non-invasive monitoring of CAR T cells using PET imaging and translational applicability of DHFR/TMP radiotracers. Citation Format: Mark A Sellmyer, Iris K Lee, Kyle Kuszpit, Jyoti Roy, Alex Alfaro, Virginie Ory, Lily Cheng, Daniel Sutton, Emily Bosco, Christine Fazenbaker, Shabazz Novarra, Ryan Gilbreth, Nick Tschernia, Deborah Berry, Xiaoru Chen, Yuling Wu, Ryan Wong. Evaluation of eDHFR/iTag PET reporter gene immunogenicity and application in GPC3 CAR T cells [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr A37.

Programmed death 1 (PD-1) is an integral component of acute myelogenous leukemia (AML) immune evasion, chemotherapy resistance, and disease progression. PD-1 inhibitors are being investigated as treatment for AML in combination with hypomethylating agents and cytotoxic chemotherapy with encouraging findings. Although allogeneic stem cell transplantation (alloSCT) remains the most established curative treatment for patients with relapsed and refractory AML in complete remission, there are limited data on the clinical outcomes and safety of immune checkpoint inhibitors (ICIs) prior to alloSCT in AML. In the present study, we compared clinical outcomes of 9 patients with AML receiving high-dose cytarabine followed by pembrolizumab in a phase II clinical trial (NCT02768792) prior to alloSCT versus a historical control group of 18 AML patients who underwent alloSCT without prior ICI exposure. The nonparametric Jonckheere-Terpstra test was used to test for a difference in the ordered severity categories of acute graft-versus-host disease (GVHD) within 100 days of transplantation. Time-to-event estimates for overall survival and relapse-free survival were calculated using the Kaplan-Meier method and compared using a log-rank test. One-year survival was not significantly different between the treatment groups (67% versus 78%; P = .34). 100-day mortality was 0% in the ICI group versus 17% in the control group, and there was no increase in grade III-IV acute GVHD in patients treated with pembrolizumab prior to alloSCT. No chronic GVHD was seen in patients treated with pembrolizumab prior to alloSCT and who received post-transplantation cyclophosphamide (PTCy) as part of their conditioning regimen. These findings reinforce the safety and feasibility of ICI therapy prior to alloSCT in patients with AML, and suggest that PTCy may abrogate GVHD risk and severity in patients who receive ICI prior to undergoing alloSCT for AML.

Background Multiple genomics-based biomarkers of response to immune checkpoint inhibition have been reported or proposed, including tumor mutation/neoantigen frequency, PD-L1 expression, T cell receptor repertoire clonality, interferon gene signature expression, HLA expression, and others.1 Although genomics associations of response have been reported, the primary studies have used a variety of data generation and processing techniques. There is a need for data harmonization and assessment of generalizability of potential biomarkers across multiple datasets. Methods We acquired patient-level RNA sequencing FASTQ data files from 10 data sets reported in seven pan-cancer PD-1 and CTLA-4 immune checkpoint inhibition trials with matched clinical annotations.2–7 We applied a common bioinformatics workflow for quality control, mapping to reference (STAR), generating gene expression matrices (SALMON), T cell receptor repertoire inference (MiXCR), extraction of immune gene signatures and immune subtypes,8 and differential gene expression analysis (DESeq2). We analyzed i) immunogenomics features proposed as biomarkers, and ii) gene expression signatures built from each trial for association with overall survival across the set of trials using univariable Cox proportional hazards regression. In all, we assessed 9 total immunogenomics features/signatures. P-values were adjusted for multiple testing using the Benjamini-Hochberg method. Results Of the 9 immunogenomics features assessed, cytolytic activity score and expression of the Follicular Dendritic Cell Secreted Protein gene (FDCSP) were associated with survival in two of seven studies, respectively (adjusted p Conclusions No proposed biomarkers were highly generalizable across studies. We expect that integrated modeling incorporating multiple immunogenomics features will be required to build a robust and generalizable biomarker for ICI response. Further work is needed to analyze determinants of response and clinical benefit. Acknowledgements We would like to thank SITC for funding for this work as part of the Sparkathon TimIOS collaborative project. References Zappasodi R, Wolchok JD, Merghoub T. Strategies for Predicting Response to Checkpoint Inhibitors. Curr Hematol Malig Rep 2018;13(5):383–95. Liu D, Schilling B, Liu D, Sucker A, Livingstone E, Jerby-Arnon L, Zimmer L, Gutzmer R, Satzger I, Loquai C, Grabbe S, Vokes N, Margolis CA, Conway J, He MX, Elmarakeby H, Dietlein F, Miao D, Tracy A, Gogas H, Goldinger SM, Utikal J, Blank CU, Rauschenberg R, von Bubnoff D, Krackhardt A, Weide B, Haferkamp S, Kiecker F, Izar B, Garraway L, Regev A, Flaherty K, Paschen A, Van Allen EM, Schadendorf D. Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma. Nat Med 2019;25(12):1916–27. Gide TN, Quek C, Menzies AM, Tasker AT, Shang P, Holst J, Madore J, Lim SY, Velickovic R, Wongchenko M, Yan Y, Lo S, Carlino MS, Guminski A, Saw RPM, Pang A, McGuire HM, Palendira U, Thompson JF, Rizos H, Silva IPD, Batten M, Scolyer RA, Long GV, Wilmott JS. distinct immune cell populations define response to anti-pd-1 monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy. Cancer Cell 2019;35(2):238–55 e6. Cloughesy TF, Mochizuki AY, Orpilla JR, Hugo W, Lee AH, Davidson TB, Wang AC, Ellingson BM, Rytlewski JA, Sanders CM, Kawaguchi ES, Du L, Li G, Yong WH, Gaffey SC, Cohen AL, Mellinghoff IK, Lee EQ, Reardon DA, O’Brien BJ, Butowski NA, Nghiemphu PL, Clarke JL, Arrillaga-Romany IC, Colman H, Kaley TJ, de Groot JF, Liau LM, Wen PY, Prins RM. Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma. Nat Med. 2019;25(3):477–86. Riaz N, Havel JJ, Makarov V, Desrichard A, Urba WJ, Sims JS, Hodi FS, Martin-Algarra S, Mandal R, Sharfman WH, Bhatia S, Hwu WJ, Gajewski TF, Slingluff CL, Jr., Chowell D, Kendall SM, Chang H, Shah R, Kuo F, Morris LGT, Sidhom JW, Schneck JP, Horak CE, Weinhold N, Chan TA. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell 2017;171(4):934–49 e16. Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, Berent-Maoz B, Pang J, Chmielowski B, Cherry G, Seja E, Lomeli S, Kong X, Kelley MC, Sosman JA, Johnson DB, Ribas A, Lo RS. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 2016;165(1):35–44. Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, Dawson N, O’Donnell PH, Balmanoukian A, Loriot Y, Srinivas S, Retz MM, Grivas P, Joseph RW, Galsky MD, Fleming MT, Petrylak DP, Perez-Gracia JL, Burris HA, Castellano D, Canil C, Bellmunt J, Bajorin D, Nickles D, Bourgon R, Frampton GM, Cui N, Mariathasan S, Abidoye O, Fine GD, Dreicer R. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet. 2016;387(10031):1909–20. Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Ou Yang TH, Porta-Pardo E, Gao GF, Plaisier CL, Eddy JA, Ziv E, Culhane AC, Paull EO, Sivakumar IKA, Gentles AJ, Malhotra R, Farshidfar F, Colaprico A, Parker JS, Mose LE, Vo NS, Liu J, Liu Y, Rader J, Dhankani V, Reynolds SM, Bowlby R, Califano A, Cherniack AD, Anastassiou D, Bedognetti D, Mokrab Y, Newman AM, Rao A, Chen K, Krasnitz A, Hu H, Malta TM, Noushmehr H, Pedamallu CS, Bullman S, Ojesina AI, Lamb A, Zhou W, Shen H, Choueiri TK, Weinstein JN, Guinney J, Saltz J, Holt RA, Rabkin CS, Cancer Genome Atlas Research N, Lazar AJ, Serody JS, Demicco EG, Disis ML, Vincent BG, Shmulevich I. The Immune Landscape of Cancer. Immunity 2018;48(4):812–30e14.

Oncology is in the midst of a therapeutic renaissance. The realization of immunotherapy as an efficacious and expanding treatment option has empowered physicians and patients alike. However, despite these remarkable advances, we have only just broached the potential immunotherapy has to offer and have yet to successfully expand these novel modalities to the field of neuro-oncology. In recent years, exciting results in preclinical studies of immune adjuvants, oncolytic viruses, or cell therapy have been met with only fleeting signs of response when taken to early phase trials. Although many have speculated why these innovative approaches result in impaired outcomes, we are left empty-handed in a field plagued by a drought of new therapies. Herein, we will review the recent advances across cellular therapy for primary malignant brain tumors, an approach that lends itself to overcoming the inherent resistance mechanisms which have impeded the success of prior treatment attempts.

The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I—conceptual challenges and Volume II—practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting.

The development of strongly predictive validated biomarkers is essential for the field of immuno-oncology (IO) to advance. The highly complex, multifactorial data sets required to develop these biomarkers necessitate effective, responsible data-sharing efforts in order to maximize the scientific knowledge and utility gained from their collection. While the sharing of clinical- and safety-related trial data has already been streamlined to a large extent, the sharing of biomarker-aimed clinical trial derived data and data sets has been met with a number of hurdles that have impaired the progression of biomarkers from hypothesis to clinical use. These hurdles include technical challenges associated with the infrastructure, technology, workforce, and sustainability required for clinical biomarker data sharing. To provide guidance and assist in the navigation of these challenges, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to outline the challenges that researchers currently face, both at the conceptual level (Volume I) and at the technical level (Volume II). The committee also suggests possible solutions to these problems in the form of professional standards and harmonized requirements for data sharing, assisting in continued progress toward effective, clinically relevant biomarkers in the IO setting.

Background Immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, long-term benefits are only achieved in a small fraction of patients. Understanding the mechanisms underlying ICB activity is key to improving the efficacy of immunotherapy. A major limitation to uncovering these mechanisms is the limited number of responders within each ICB trial. Integrating data from multiple studies of ICB would help overcome this issue and more reliably define the immune landscape of durable responses. Towards this goal, we formed the TimIOs consortium, comprising researchers from the Society for Immunotherapy of Cancer Sparkathon TimIOs Initiative, the Parker Institute of Cancer Immunotherapy, the University of North Carolina-Chapel Hill, and the Institute for Systems Biology. Together, we aim to improve the understanding of the molecular mechanisms associated with defined outcomes to ICB, by building on our joint and multifaceted expertise in the field of immuno-oncology. To determine the feasibility and relevance of our approach, we have assembled a compendium of publicly available gene expression datasets from clinical trials of ICB. We plan to analyze this data using a previously reported pipeline that successfully determined main cancer immune-subtypes associated with survival across multiple cancer types in TCGA.1 Methods RNA sequencing data from 1092 patients were uniformly reprocessed harmonized, and annotated with predefined clinical parameters. We defined a comprehensive set of immunogenomics features, including immune gene expression signatures associated with treatment outcome,1,2 estimates of immune cell proportions, metabolic profiles, and T and B cell receptor repertoire, and scored all compendium samples for these features. Elastic net regression models with parameter optimization done via Monte Carlo cross-validation and leave-one-out cross-validation were used to analyze the capacity of an integrated immunogenomics model to predict durable clinical benefit following ICB treatment. Results Our preliminary analyses confirmed an association between the expression of an IFN-gamma signature in tumor (1) and better outcomes of ICB, highlighting the feasibility of our approach. Conclusions In line with analysis of pan-cancer TCGA datasets using this strategy (1), we expect to identify analogous immune subtypes characterizing baseline tumors from patients responding to ICB. Furthermore, we expect to find that these immune subtypes will have different importance in the model predicting response and survival. Results of this study will be incorporated into the Cancer Research Institute iAtlas Portal, to facilitate interactive exploration and hypothesis testing. References Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Yang T-H O, Porta-Pardo E. Gao GF, Plaisier CL, Eddy JA, et al. The Immune Landscape of Cancer. Immunity 2018; 48(4): 812–830.e14. https://doi.org/10.1016/j.immuni.2018.03.023. Auslander N, Zhang G, Lee JS, Frederick DT, Miao B, Moll T, Tian T, Wei Z, Madan S, Sullivan RJ, et al. Robust Prediction of Response to Immune Checkpoint Blockade Therapy in Metastatic Melanoma. Nat. Med 2018; 24(10): 1545. https://doi.org/10.1038/s41591-018-0157-9.

Family and migration studies suggest a genetic risk of developing chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). We hypothesized that CLL patients have an increased risk of additional clonally unrelated B-cell malignancies. To test this, we studied 467 CLL patients (2743 person-years (PYs)) at a single institution over 17 years. The incidence rate (IR) of any additional B-cell lymphoid malignancy was 10.9 per 1000 PYs (

Background: Patients with TP53 MUT MDS/AML experience poor clinical outcomes with high rates of disease recurrence and short overall survival (OS). Characterization of these individuals' post-HCT mortality is uniquely challenging due to competing risks from disease relapse and treatment toxicity. Transplant registries contain high-level outcomes data, however, there is a lack of detailed data in molecularly defined subsets of diease. This analysis was undertaken to bridge this gap. Methods: Allogeneic HCT recipients between 1/2014 and 12/2018 were retrospectively studied. Key inclusion criteria were TP53 MUT by NGS or deletion of chromosome 17/17p by FISH/cytogenetics. The primary outcome of non-relapse mortality (NRM) was defined as death from any cause other than disease with relapse as competing risk. Secondary outcomes for this analysis were OS, cumulative incidence of relapse (CIR), and relapse free survival (RFS). Relapse was defined as relapse/progression with NRM as competing risk. Results: 384 TP53 MUT MDS/AML patients were analyzed. 55% of patients were transplanted for AML, 41% received myeloablative conditioning (MAC), 39% had secondary MDS/AML, and 26% received prior chemo and/or radiation therapy (XRT). Median time from HCT to last follow-up was 321 days (range 8-2,385 days). Mutational data was available in 264 patients and cytogenetic data was available in 368 patients; 78% of patients had a complex karyotype (CK), 82% had TP53 missense mutations, and 74% had bi-allelic targeting of the TP53 gene. The incidence of all-grade acute and chronic GVHD (cGVHD) was 52% and 31%, respectively. One and 2 year OS was 48.5% and 30.9%, respectively. Estimated CIR at 1 and 2 years was 49% and 54.9%, respectively. The 1 year NRM was 13.7% and 2 year NRM was 18.1%. In multivariate analysis (MVA), there was no association between NRM and the clinical, molecular, or genetic features of TP53 MUT MDS/AML. HCT diagnosis of MDS (HR: 0.67, 95% CI: 0.46-0.97, p: 0.036), mono-allelic TP53 MUT (HR: 0.6, 95% CI: 0.39-0.94, p: 0.023), achievement of full donor PB chimerism (HR: 0.33, 95% CI: 0.14-0.85, p: 0.022), BM chimerism (HR: 0.33, 95% CI: 0.18-0.60, p: 0.003), and cGVHD (HR: 0.35, 95% CI: 0.23-0.51, p: In subgroup analysis, history of chemo and/or XRT increased NRM in AML (HR: 4.24, 95% CI: 1.35-13.39, p: 0.014). Pre-HCT TP53 MUT persistence by NGS (HR: 3.59, 95% CI: 1.43-9, p: 0.007) predicted for post-HCT relapse whereas pre-HCT CR (HR: 2.93, 95% CI: 1.54-5.59, p: 0.001) and full donor BM chimerism (HR: 0.14, 95% CI: 0.05-0.38, p: No significant NRM associations were identified in MDS. CK (HR: 5.04, 95% CI: 1.95-13.01, p: Conclusions: From this large multi-institutional cohort of TP53 MUT myeloid neoplasms, we report a low NRM rate, likely due to high rates of post-HCT relapse/progression. These data demonstrate associations between bi-allelic TP53m/CK and post-HCT outcomes. Our work highlights the importance donor chimerism after HCT and provides new understanding of the importance of chronic GVHD in TP53 MUT MDS/AML. Figure 1 Figure 1. Disclosures Byrne: Karyopharm: Research Funding. Logan: Amgen, Pfizer, AbbVie: Consultancy; Pharmacyclics, Astellas, Jazz, Kite, Kadmon, Autolus, Amphivena: Research Funding. Lee: CareDx: Membership on an entity's Board of Directors or advisory committees; Kadmon: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Fresensius Kabi: Consultancy; Jazz,: Consultancy; Incyte: Research Funding. Goodman: Seattle Genetics: Consultancy, Speakers Bureau; EUSA Pharma: Consultancy, Honoraria. Gill: Interius Biotherapeutics: Current holder of stock options in a privately-held company, Research Funding; Novartis: Other: licensed intellectual property, Research Funding; Carisma Therapeutics: Current holder of stock options in a privately-held company, Research Funding. Jimenez: Takeda: Research Funding; AbbVie: Research Funding. Metheny: Pharmacosmos: Honoraria; Incyte: Speakers Bureau. Bhatnagar: Pfizer: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Astellas: Honoraria; Cell Therapeutics: Honoraria, Research Funding; Kite: Honoraria; Karyopharm: Honoraria, Research Funding; Sumitomo Dainippon Pharma: Research Funding. Hamilton: Syndax: Membership on an entity's Board of Directors or advisory committees; Equilium: Membership on an entity's Board of Directors or advisory committees. Mishra: Novartis: Research Funding. Savona: BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding.

Introduction Up-regulation of inhibitory receptors, such as programmed death-1 (PD-1), is an integral component of acute myeloid leukemia (AML) immune evasion, chemotherapy resistance, and disease progression. Early phase clinical trials investigating immune checkpoint inhibitors (ICIs) in patients with AML have demonstrated promising findings. We previously reported that pembrolizumab administration on day 14 after high-dose cytarabine (HiDAC) salvage chemotherapy in patients with relapsed/refractory (R/R) AML was safe, feasible, and associated with encouraging clinical outcomes. PD-1 blockade prior to allogeneic stem cell transplant (alloSCT) has been associated with increased risks of alloSCT-related toxicity in lymphoma. AlloSCT remains the most established treatment paradigm for curative intent in AML patients who achieve a complete response (CR); however, there are limited data on the clinical outcomes and safety of ICI prior to alloSCT in AML. We set out to compare clinical outcomes of AML patients receiving pembrolizumab prior to alloSCT versus a control group of AML patients receiving alloSCT without prior ICI exposure. Methods We assessed clinical outcomes of patients who enrolled on a phase II clinical trial of HiDAC followed by pembrolizumab 200 mg IV on day 14 (NCT02768792) for R/R AML and subsequently underwent an alloSCT. Date of alloSCT was required to be >30 days from last dose of pembrolizumab. We matched each trial participant who underwent an alloSCT in a 1:2 ratio with controls who received alloSCT at our institution since 2016. Patients were matched on age, sex, age-adjusted hematopoietic cell transplantation-comorbidity index (HCT-CI), donor type, and conditioning intensity. The nonparametric Jonckheere-Terpstra test was used to test for a difference in the ordered severity categories of acute graft versus host disease (aGVHD) within 100 days of transplant. The time-to-event estimates for overall survival (OS) and relapse-free survival (RFS, event is either death or relapse) were calculated using the Kaplan-Meier method and compared using a log rank test. Results Nine out of 37 (24.3%) R/R AML patients treated with HiDAC followed by pembrolizumab received an alloSCT. Baseline characteristics of the R/R AML patients who received pembrolizumab versus R/R AML controls who underwent alloSCT are described in Table 1. One patient in each cohort received an alloSCT with evidence of active disease by flow cytometry (>5% blasts) or hematopathology IHC evaluation, whereas all other patients in both arms were in CR/CRi or MLFS at the time of alloSCT. The pattern of aGVHD severity was similar with the exception of 3 control patients (3/18 or 17%) having grade III-IV aGVHD versus 0/9 pembrolizumab patients (p = 0.92). Notably, 7/9 (78%) patients in the pembrolizumab cohort had no evidence of chronic GVHD. There was a nonsignificant increase in relapses (6/9: 67% vs. 6/18: 33%; p = 0.22) and deaths (6/9: 67% vs. 8/18: 44%, p = 0.42) in pembrolizumab versus control patients, respectively. The median follow-up for survivors was 23 months. Median OS was 21 months for pembrolizumab cohort versus 25 months for control patients. One-year OS was 67% (95% CI, 28%-87%) for pembrolizumab patients versus 78% (95% CI, 51%-91%) for control patients, p = 0.34. One-year RFS was 44% (95% CI, 14%-72%) for pembrolizumab patients versus 67% (95% CI, 40%-83%) for control patients, p = 0.14. Conclusion Treatment with ICI represents a promising therapeutic strategy for AML. Among a cohort of patients treated with HiDAC followed by pembrolizumab for R/R AML, alloSCT appeared to be feasible without increased risk of GVHD or early mortality. Although a small number of patients received alloSCT after pembrolizumab, OS appeared comparable to R/R AML controls who did not receive ICI. The increase in relapse rates seen in the pembrolizumab cohort may have been impacted by the higher proportion of patients with measurable residual disease (MRD) prior to alloSCT (78% vs. 39%, respectively). These data warrant further investigation of ICI prior to and after alloSCT in high-risk AML patients. Disclosures Tschernia: AstraZeneca: Research Funding. Vincent:GeneCentric Therapeutics: Consultancy. Coombs:Abbvie: Consultancy, Honoraria; Genentech: Honoraria; AstraZeneca: Honoraria; MEI Pharma: Honoraria; LOXO Oncology: Honoraria; Octapharma: Honoraria; Novartis: Honoraria. DeZern:MEI: Consultancy; Celgene: Consultancy, Honoraria; Abbvie: Consultancy; Astex: Research Funding. Luznik:WindMil Therapeutics: Patents & Royalties: Patent holder; Genentech: Research Funding; AbbVie: Consultancy; Merck: Research Funding, Speakers Bureau. Riches:Biointelect: Consultancy. Gojo:BMS: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Merck: Research Funding; Amphivena: Research Funding; Genentech: Research Funding. Zeidner:AbbVie: Honoraria, Other: Independent Review Committee; Agios: Honoraria; Daiichi Sankyo: Honoraria; Genentech: Honoraria; Pfizer: Honoraria; Takeda: Consultancy, Honoraria, Other: Travel Reimbursement, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; AsystBio Laboratories: Consultancy; AROG: Research Funding; Forty-Seven: Other: Travel Reimbursement, Research Funding; Merck: Research Funding; Sumitomo Dainippon Pharma Oncology, Inc.: Research Funding.