Anne Hartz

Background: Acute myeloid leukemia (AML) is characterized by reduced antileukemic effector cells and increased immunosuppressive cell populations. Leukemia-derived dendritic cells (DC_leu), generated from 18 leukemic whole blood (WB) ex vivo using ‘Kit-M’ (clinically approved: GM-CSF + PGE1), lead to improved cytotoxicity against autologous blasts after mixed lymphocyte culture (MLC) with patients’ T-cells. Methods: We studied Kit-M-mediated effects on frequencies of tolerogenic, immunosuppressive DC (DC_tol) and correlated findings with ex vivo-achieved antileukemic effects (increased intracellular IFNγ production/degranulation, blast lysis) and patients’ clinical characteristics. Results: We show significantly decreased frequencies of DC_tol (and increased frequencies of mature DC_leu) without induced blast proliferation in Kit-M treated vs. untreated WB samples. After T-cell-enriched MLC with Kit-M pretreated vs. not pretreated, WB frequencies of regulatory (CD152+ T-cells) were significantly decreased, while ‘activated’ (IFNγ+, degranulating) non-naive, proliferating, memory, CD154+) T-cells, as well as NK and CIK-cells were (significantly) increased. We found a (significant) positive correlation of achieved improved blast lysis, frequencies of DC_leu and ‘activated’ (IFNγ+/degranulating) T- or NK/CIK cells, and a (significant) negative correlation with frequencies of DC_tol and regulatory (CD152+ T-cells). Kit-M treatment of leukemic WB increases DC_leu and decreases DC_tol, correlating with improved immune reactions/improved cytotoxicity against autologous blasts, and downregulated suppressive T-cells in samples before or after MLC. Conclusions: These findings demonstrate the potential of Kit-M (using clinically approved drug compositions) to treat AML patients to potentially overcome the immunosuppressive tumor microenvironment, leading to improved antileukemic responses—thereby stabilizing remission of the disease in AML patients.

Various AML treatment regimens might trigger different immunological mechanisms against leukemic cells. The role of different immune cell subsets in the mediation of antileukemic processes is not clear. In this study, we longitudinally assessed (leukemia specific) immune subtype compositions in 17 AML patients before stem cell transplantation (SCT) at different timepoints in the course and in different stages of the disease using flow cytometry. Further we correlated immune cell compositions with patients’ response to induction therapy and the median survival (3.8 months in our cohort) of the patients. Finally, we compared immune cell profiles from patients before and after SCT. (1) Patients in CR (compared to dgn and PD) were characterized by higher frequencies of leukemia-derived DC (DCleu), (leukemia-specific—IFNg or TNFα producing or CD107a degranulating) anti-tumor relevant T cells (Tgd, Tβ7), central/effector memory cells (Tcm, Tem), alongside with lower frequencies of (leukemia-specific) regulatory T cells. (2) Patients with higher frequencies of (leukemia-specific) antitumor relevant T cells, (leukemia-specific) memory T cells and NK cells demonstrated a prolonged median survival time and/or responded better to induction (RTI) treatment (3) Comparing patients before and after SCT, only minimal differences were observed. However, patients in CR_preSCT exhibited higher frequencies of DC, Tcm, Tβ7 and leukemia-specific iNKT cells compared to patients in CR_postSCT. (1) Immune monitoring qualifies to quantify (leukemia-specific) immune cells in different stages and under different treatment strategies in the course of AML. (2) Higher frequencies of activating and antitumor relevant leukemia-specific immune cell subtypes found after ‘costimulatory’ (especially KitM induced) treatment’ and in CR. (3) In particular, DC/DCleu, (leukemia-specific) antitumor-relevant T (memory) and NK cells seem to dominate in CR and positively influence RTI and survival. (4) Monitoring of (leukemia-specific) immune cell subtypes contribute to quantify individual AML patients’ antileukemic potential in different stages and treatment groups and also could be used to predict patients’ survival.