In search of a targetable immune profile for acute myeloid leukemia.

Cohabitation as a determinant of adaptive and innate immune cell profiles: Findings from the Health and Retirement Study

Immune Gene Expression Profiling in Children and Adults with Acute Myeloid Leukemia Identifies Distinct Phenotypic Patterns

Parallel Detection of Single-Cells and Extracellular Vesicles from Bone Marrow and Peripheral Blood Reveals Asymmetric Immunometabolic Profile in Acute Myeloid Leukemia

Tumor phenotypes are dictated not only by the neoplastic cell component, but also by the tumor microenvironment (TME), which includes immune and inflammatory cells. Acute myeloid leukemia (AML) is the second most common leukemia of childhood. Although intensive multi-agent chemotherapy in conjunction with improved supportive care has increased survival rates to 70%, 30-40% of children with AML relapse and only one-third of them will survive to adulthood. Investigation of new therapeutic strategies for high-risk AML, including immunotherapy, remains a priority and is being actively pursued. Importantly, AML-induced immune suppression poses a fundamental barrier to successful immune-based interventions. We previously showed that in vitro treatment of primary AML cells with interferon (IFN)-γ induces functional indoleamine 2,3-dioxygenase-1 (IDO1), a molecule with potent immunosuppressive properties, in 50% of unselected cases (IFN-γ responders). With a median follow-up of 8 years, IFN-γ responders experienced a significantly shorter event-free survival and overall survival (OS). Herein, we aimed to get insights into the immune landscape of childhood AML using multi-scale immune profiling strategies with the aim to identify molecular circuits that can be targeted to revert leukemia-induced immune dysfunction and improve clinical outcome. We employed a novel high-throughput digital platform, the nCounter system (nanoString Technologies, Seattle, USA), and Optimized Multi-color Immuno-phenotyping Panels (OMIPs) to comprehensively characterize the bone marrow immune infiltrate in 34 children diagnosed with non-promyelocytic AML (17 males, 17 females; median age at diagnosis=10 years; 28 de novo AML, 4 infant leukemia, 1 secondary AML, 1 congenital leukemia; 7 patients with favorable-risk cytogenetics, 21 patients with intermediate-risk cytogenetics and 6 patients with unfavorable-risk cytogenetics). The RNA Pan-Cancer Immune Profiling Panel, which includes 109 cell surface markers for 24 immune cell types, 30 cancer testis antigens, and >500 immune response genes, allowed us to measure immune gene expression levels on the clinic-ready nCounter® FLEX platform (nanoString Technologies). Transcriptomic data were normalized and analyzed using the nSolver software package. Relapse-free survival (RFS) and OS were selected as covariates. For immune phenotyping studies, viable bone marrow mononuclear cells were labeled with fluorochrome-conjugated antibodies and then analyzed on a 10-color Gallios flow cytometer (Beckman Coulter Life Sciences, Buckinghamshire, UK) with standard settings. Hierarchical clustering of immune gene expression data highlighted patient subgroups with heightened expression of T-cell and natural killer (NK)-cell function genes, as well as Toll-like receptor (TLR) genes, interleukin genes and tumor necrosis factor (TNF) family genes. Patients with high levels of CD8A mRNA also expressed IFNG, CXCL9, CXCL10, FOXP3 and negative checkpoints, including LAG3, CTLA4, IDO1 and CD279 (PD-L1), consistent with T-cell inflamed phenotypes that might underpin the establishment of adaptive immune resistance mechanisms of immune escape. In-depth phenotyping studies showed higher percentages of bone marrow-resident naïve B cells, plasmablasts, intermediate and non-conventional monocytes, plasmacytoid dendritic cells (DCs) and CXCR3-expressing Th1 cells at diagnosis compared with complete remission (CR). By contrast, both type 1 and type 2 myeloid DCs were more represented in the TME of patients with AML in CR. The frequencies of innate lymphoid cells (ILCs) and Vγ9+Vδ2+ T cells were not significantly different when comparing diagnosis and CR samples. Relapses occurred in 71.4% of children with “inflamed” AML compared with 28.6% of patients with “non-inflamed” AML (p=0.012; two-sided Fisher’s exact test). Importantly, RFS was remarkably shorter in patients with inflamed compared with non-inflamed AML (median RFS=394 days vs. undefined; hazard ratio = 0.266; 95% CI=0.11-0.64; p=0.0039, log-rank test). A non-significant association with OS was also observed. In conclusion, inflamed or “hot” AMLs are associated with shorter RFS and might be amenable to immunotherapy approaches tailored to the bone marrow TME, including PD-1/PD-L1 blockade and/or small-molecule IDO1 inhibitors. Grant support: Roger Counter Foundation, Dorset, UK and Qatar National Research Fund (grant #NPRP8-2297-3-494). Citation Format: Jayakumar Vadakekolathu, Gemma A. Foulds, Tasleema Patel, Stephen Reeder, Alan Graham Pockley, Sarah K. Tasian, Sergio Rutella. Immune gene expression profiling identifies predictors of relapse in childhood acute myeloid leukemia [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr B62.

Immunogenomic Exploration of the Acute Myeloid Leukemia Microenvironment Identifies Determinants of T-Cell Fitness

Integrative analysis of the interplay between peripheral immune landscape and leukemic blast adaptation in Acute Myeloid Leukemia

T/NK Cell-Associated Transcriptomic Profile Informs Response to FLT3 Inhibitors in Acute Myeloid Leukemia

P0156 Plasma immune protein profiles in therapy-naïve ulcerative colitis relate to extent of affected tissue and density of intestinal infiltration, differentiating patients with discreet disease courses

Background: Acute myeloid leukemia (AML) is characterized by clonal expansion of poorly differentiated myeloid precursors, resulting in impaired hematopoiesis and often bone marrow (BM) failure. The general therapeutic approach in patients with AML has not changed substantially in more than 30 years. Investigation of new strategies, including immunotherapy, remains a priority. Tumor phenotypes are dictated not only by major oncogene drivers, but also by the tumor immunologic microenvironment (TIME) which is inherently immunosuppressive, is equipped to hamper effector T-cell function and includes immune and inflammatory cells, soluble mediators such as interferon (IFN)-gamma and extracellular matrix components. Herein, we profiled the TIME of AML to identify gene signatures that are reflective of general immune status and predictive of antileukemia immune potential. Methods: We used the hybridization-based nCounter® system (NanoString Technologies®, Seattle, WA) and the RNA Pan-Cancer Immune Profiling PanelTM to analyze BM aspirates from 290 adults and 40 children with newly diagnosed, nonpromyelocytic AML. Data were normalized to a set of reference genes and log2-transformed for bioinformatics analysis. The clinical relevance of the association between immune gene signatures and patient outcome was further validated in silico using publicly available cancer transcriptomic datasets (The Cancer Genome Atlas; TCGA). Results: We identified distinct sets of co-expressed genes corresponding to innate immunity, adaptive immunity and IFN-gamma signaling. BM samples with IFN-gamma-dominant gene expression profiles showed up-regulation of actionable immune checkpoints, such as B7-H3, PD-L1 and CTLA-4. A set of 4 differentially expressed immune genes between children and adults with AML (FDR<0.005) was associated with adverse cytogenetic features, leukemia relapse and shorter patient survival, and also stratified survival in the TCGA cohort of adult patients with AML. Finally, all four genes were amplified, deleted or mutated in 7% of 51,175 TCGA solid tumors, with the highest frequency of mutations being detected in primary CNS lymphoma (40%) and diffuse large B-cell lymphoma (25%). Conclusions: Our study identified distinct immune gene programs in the TIME of patients with newly diagnosed AML. From a translational standpoint, immune-enriched and IFN-gamma-dominant AMLs may benefit from immune checkpoint blockade and from new immunotherapy approaches, including dual-affinity T-cell redirecting antibodies targeting CD123. Grant support: John and Lucille van Geest Foundation, UK; Roger Counter Foundation, UK; Qatar National Research Fund (#NPRP8-2297-3-494). Citation Format: Sergio Rutella, Jayakumar Vadakekolathu, Tressa Hood, Stephen Reeder, Sarah E. Warren, Patrick Danaher, Jan Davidson-Moncada, Alessandra Cesano, Joseph M. Beechem, Sarah K. Tasian, Mark D. Minden. Immune gene expression profiling of acute myeloid leukemia identifies predictors of survival and actionable targets for treatment [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B63.

Background: Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous disease. TP53 mutations and 17p (TP53) deletions occur in 37-46% of AML cases with adverse risk cytogenetics and are associated with primary induction failure (PIF), high risk of relapse and dismal prognosis. Herein, we aimed to determine whether TP53 abnormalities identify a patient subgroup that may benefit from immunotherapy approaches. Patients and Methods: We used the following transcriptomic data sets and patient cohorts (C) for in silico and wet-lab analyses: 1) The Cancer Genome Atlas (TCGA; 162 adult AML patients, 13 with TP53 mutations); 2) Beat AML Master Trial (281 adult AML patients, 17 with TP53 mutations); 3) HOVON (618 adult AML patients, 14 with TP53 mutations); 4) 24 diagnostic bone marrow (BM) samples from patients with TP53-wild-type AML (Bologna series); 5) 36 diagnostic BM samples from patients with TP53-mutated AML (Studien Allianz Leukämie [SAL] series); 6) 30 BM samples from patients with relapsed/refractory (R/R) AML (10 cases with TP53 mutations and/or 17p deletion) that received immunotherapy with flotetuzumab, a CD123×CD3 bispecific DART molecule (NCT02152956). Microenvironmental immune gene expression profiles (wet-lab cohorts, C4 and C5) were analyzed using the Pan-Cancer IO 360 Panel (NanoString Technologies, Seattle, WA). Immune cell type-specific and biological activity signature scores were computed as recently published (JITC 2017; 5: 18). Results: Compared with TCGA-AML cases (C1) with favorable-risk and intermediate-risk molecular features, all patients with TP53 mutations showed high levels of immune infiltration, including genes associated with adaptive immune responses and an interferon (IFN)-γ-dominant tumor microenvironment (TME), and a higher tumor mutational burden (14 versus 10 mutations on average in patients with TP53-mutated and TP53-wild-type AML, respectively; p=0.02). Similarly, 16 out of 17 (94%) TP53-mutated Beat AML cases (C2) expressed high levels of IFN signaling molecules, CD8 and markers of cytotoxicity (GZMB). Compared with patients with TP53-wild-type AML (C4), primary BM samples from patients with TP53-mutated AML (C5) showed higher levels of CD8A, markers of cellular senescence (EOMES, KLRD1, HRAS), IFN-γ-inducible genes (IRF1) and negative immune checkpoints including LAG3, IDO1, PDL1 and VSIR (VISTA). Interestingly, 10 patients with R/R AML (C6) had TP53 abnormalities and 5 of 6 patients evaluated for immune gene profiles had an immune-infiltrated TME. In patients with TP53 abnormalities, the overall response rate (ORR) was 40% to flotetuzumab (2 patients with CR, 1 patient with CRh, and 1 patient with morphologic leukemia-free state). The overall decrease of BM blasts averaged 42%. Stable disease was observed in 3 patients. Median overall survival (OS) was 3.5 months (range 1.25-21.25), which favorably compares with survival estimates for TP53-mutated cases with PIF in large AML series, such as HOVON (C3; median OS=1.16 months). Conclusions: This study provides evidence for a correlation between IFN-γ-dominant immune subtypes of AML and TP53 abnormalities. The ORR seen in this patient subgroup encourages further study of this immunotherapeutic approach. Citation Format: Jayakumar Vadakekolathu, Catherine Lai, Stephen Reeder, Sarah E. Church, Tressa Hood, John Muth, Heidi Altmann, Marilena Ciciarello, Antonio Curti, Peter J. Valk, Bob Löwenberg, Martin Bornhäuser, John F. DiPersio, Jan K. Davidson-Moncada, Sergio Rutella. TP53 abnormalities correlate with immune infiltration and are associated with response to flotetuzumab, an investigational immunotherapy, in acute myeloid leukemia [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT035.

Background: Abemaciclib is a selective CDK4 and CDK6 inhibitor with demonstrated efficacy in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer. The most common adverse event across previous trials was early-onset diarrhea, affecting the patients’ quality of life and necessitating dose reductions. However, the exact mechanism for the lower rate of diarrhea in the other CDK4 and CDK6 inhibitors compared with abemaciclib is unknown. Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with the anti-tumor response; however, reported microbial signatures associated with adverse events by anti-cancer agent are inconsistent. To determine the underlying mechanism, we evaluated the correlation between diarrhea with abemaciclib and microbiota signatures in a metastatic breast cancer cohort. Methods: The KBCRN-A002 study is a multicenter, prospective cohort study, which aims to evaluate the association between gut microbiota signatures and abemaciclib-induced diarrhea in breast cancer patients. Patients with metastatic breast cancer who were receiving abemaciclib were eligible. The primary objective of this study is the correlation between diarrhea and the microbiota signatures and immune profile. Incidence and severity of diarrhea were evaluated by the Bristol stool scale at baseline, from day 1 to day 14, and at day 90 of treatment. Stool samples were collected at baseline and at day 90 after the start of abemaciclib treatment. The gut microbiota signature was evaluated by 16S rRNA analysis. Blood samples were collected at baseline and at days 14 and 90 after starting abemaciclib to evaluate the correlation between the gut microbiota signatures and the systemic immune profile in peripheral blood mononuclear cells (PBMCs). The immune profile was evaluated by mass cytometry, multi-plex cytokines assay, and RNA-sequencing of bulk PBMCs. We characterized the gut microbiota signatures, immune cell composition, immune cell signature, comprehensive cytokines, and severity of diarrhea in all patients. Results: We analyzed 39 patients, 77 stool samples, and 117 blood samples. In the preplanned interim analysis, among the 39 patients, 90% experienced diarrhea. Depleted gut microbiome α-diversity was positively associated with abemaciclib treatment and the severity of diarrhea. The relative abundances of 10 intestinal bacteria species increased and those of 18 intestinal bacteria decreased significantly after abemaciclib treatment, including bacteria known to be involved in diarrhea severity and anti-tumor immunity, such as Faecalibacterium (Table). The immune cell and cytokine profiles in PBMCs were also associated with the gut microbiota signatures. Conclusions: Gut microbiota signatures are associated with abemaciclib-induced diarrhea and the immune profile in metastatic breast cancer patients. These findings can help to elucidate the mechanism of diarrhea caused by abemaciclib and offer strategies for its management and prevention. Intestinal Microbiota Altered by Abemaciclib Citation Format: Kosuke Kawaguchi, Yurina Maeshima, Hiroshi Ishiguro, Kazuhiko Yamagami, Sachiko Takahara, Hirofumi Suwa, Masae Torii, Shigenori Nagai, Yasuaki Sagara, Wakako Tsuji, Hiroyasu Yamashiro, Takeshi Kotake, Shinji Fukuda, Kuniaki Saito, Yasuko Yamamoto, Masako Kataoka, Yuki Himoto, Atsushi Yonezawa, Yukiko Fukui, Yuki Nakamura, Wei Li, Sunao Tanaka, Satoshi Morita, Masakazu Toi. Alteration of gut microbiota signatures and its association with diarrhea during abemaciclib treatment: A multicenter prospective cohort study (KBCRN-A002 study) [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-26-07.

BackgroundVaccines have the ability to induce a range of immune responses under different conditions, for example stimulating the production of neutralizing antibodies to block pathogen entry or activating cytotoxic T-cells to eliminate infected cells. Many such immune responses have not been thoroughly examined and classified. The Vaccine Ontology (VO) is a community-based ontology in the domain of vaccinology. We here describe how VO is used to represent the variety of immune responses associated with vaccines, together with associated biomarkers and profiles.ResultsThe VO differentiates ‘vaccination’ and ‘vaccine immunization.’ The former is a process of administering a vaccine in vivo; the latter is the outcome of vaccine induction of immune response. This distinction is critical for understanding both the procedure of vaccination and the resulting immune effects. VO also models and represents various vaccine-induced responses at multiple biological levels, including population, organism, organ/tissue, cell, and gene/protein levels. Such an approach captures the complexity of vaccine-induced immunity, from population-wide trend (for example: herd immunity) to molecular mechanisms. VO defines immune biomarkers as material entities such as neutralizing antibodies that signify humoral immune response, and IFN-gamma that is indicative of cell-mediated responses. Such biomarkers provide measurable indicators of the immune system’s functional state post vaccination, enabling robust evaluation of vaccine efficacy. VO classifies ‘immune response profile’ and ‘correlated profile (or correlate) of immune protection’ as ‘process profiles,’ a class in the Basic Formal Ontology (BFO 2.0). Immune response profiles, such as ‘Th1 (or Th2)-biased profile,’ can be induced by various vaccines and vaccine adjuvants. Different types of ‘correlated profile of immune protection’ are also identified, such as mechanistic and non-mechanistic correlates of immune protection. Such distinctions help us to quickly identify biomarkers and associated prediction and measurement of different kinds of vaccine protection.ConclusionThe important immune-related terms for immune biomarkers, profiles, and responses are modeled ontologically in VO together with their interrelations. The results support enhanced classification and analysis of vaccine-induced immune responses and related biomarkers and immune profiles, leading to further understanding of the vaccine immune mechanisms and enhanced vaccine research and development.

Quantitative Multiplex Immunohistochemistry Identifies Immunosuppression in the AML Bone Marrow and NK-Cells As Prognostic Biomarker in Intermediate-Risk Patients

P106 INFLAMMATORY BOWEL DISEASE CHARACTERIZATION OF SHARED AND UNIQUE ALTERATIONS IN IMMUNE CELLS, MOLECULAR PATHWAYS, AND TRANSCRIPTS

Inflammatory Bowel Disease (IBD), characterized by chronic inflammation of the intestine, is propelled by alterations in the immune profile and inflammatory mediators within affected tissue. However, as IBD pathobiology is heterogeneous in nature, a more comprehensive understanding of common and distinct variations within individuals is required for more precise diagnostic methods and tailored therapeutic regimens. Using publicly available IBD transcriptomes from American and European patient cohorts, we aimed to elucidate alterations, both similar and distinct, in the immune profile, molecular pathways, and transcripts in affected tissue. Whole transcriptomes from healthy controls, active or non-active IBD cohorts were utilized (~500 patient endoscopic biopsies, NCBI GEO). Immune profiles were assessed by the core LM22 signature (CIBERSORT) (p<0.05). Pathway analysis was performed using Ingenuity Pathway Analysis (IPA, Qiagen) (p<0.05). In healthy human colon, immune cell profiling revealed a consistent abundance of B cells (plasma), T cells (CD4 memory resting), mast cells (resting) and macrophages (M2). In active-IBD involved tissue, we observed substantial alterations in the immune landscape including increased neutrophils, T CD4 memory activated cells, active dendritic cells, M0/M1 macrophages, and B naïve cells, as well as noticeably reduced T CD8 cells, Tregs, B memory cells, dendritic resting cells, and M2 macrophages (Fig 1). This immune signature was similarly observed across IBD cohorts with the exception of eosinophils, T CD4 resting cells, and Tγδ cells. In uninvolved tissue from active-IBD, the immune cell composition was similar to healthy control with the exception of elevated T CD4 memory activated cells and reduced Tregs (Fig 1). Next, relative to healthy control, IPA of differentially expressed transcripts from IBD cohorts revealed similarly altered pathways linked to bacterial signaling (TLR, LPS/IL-1, fMLP), inflammation (Th1/2 responses, chemokine and cytokine), inflammasome activation, and activated cell signaling (NFkB, ERK/MAPK, p38, iNOS, PI3K). However, pathways that differed among IBD cohorts included select signaling linked to inflammation (IL17A, OX40), growth (TGFb, PTEN, p53), and metabolic (PPARa, leptin) functions. At the individual transcript level, we found several novel transcripts consistently altered in IBD affected tissues among cohorts including KYNU, LPCAT1, CLDN8 as well as those differentially altered including MASPIN, FGFR2, AGRP, INSR. We determined the global immune cell landscape and molecular pathways that were similarly and differentially altered, highlighting the complex, heterogeneic nature of IBD pathobiology. Further utilization of this approach may provide clues for development of precise diagnostic and personalized therapeutic intervention for IBD patients. Figure 1. Alterations in the immune cell landscape in healthy control, active-IBD-involved, and active-IBD-noninvolved tissue samples. Graphs represent changes in relative abundances of subsets of B cells, T cells, dendritic cells, macrophages, mast cells, and neutrophils (GSE38713, *,#p<0.05, *compared to healthy control, #compared to active-IBD-involved) (CIBERSORT, cibersort.stanford.edu).