Next Article in Journal
Reirradiation of Local Recurrences of Prostate Cancer: PROSTARE (PROstate Cancer STereotActic REirradiation) Early Safety Analysis of a Phase 2 Study with a Limited Cohort
Previous Article in Journal
Prognostic Value of the CALLY Index in Diffuse Large B-Cell Lymphoma: Linking Inflammation, Nutrition, and Tumor Biology
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 18
Issue 5
10.3390/cancers18050847
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Modulation of Leukemic Blasts into Dendritic Cells (DCleu) and Their Role in Predicting Survival in Patients with AML and MDS

by
Daniel Christoph Amberger
1,2,*,†,
Zuzana Fischer
1,3,†,
Diana Deen
1,3,
Anika Hirn-Lopez
1,3,
Caroline Plett
1,3,
Alexander Rabe
1,3,
Christoph Schwepcke
1,3,
Selda Ugur
1,3,
Lara Kristina Klauer
1,3,
Christian Ansprenger
1,3,
Anja Liepert
1,3,
Markus Freudenreich
1,3,
Christoph Schmid
3,4 and
Helga Maria Schmetzer
1,3,*
1
Department of Medicine III, University Hospital of Ludwig-Maximilian-University Munich, 81377 Munich, Germany
2
First Department of Medicine, Paracelsus Medical University, 5020 Salzburg, Austria
3
Bavarian Cancer Research Center (BZKF), 80539 Munich, Germany
4
Department of Haematology and Oncology, University Hospital of Augsburg, 86156 Augsburg, Germany
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2026, 18(5), 847; https://doi.org/10.3390/cancers18050847
Submission received: 18 January 2026 / Revised: 27 February 2026 / Accepted: 3 March 2026 / Published: 6 March 2026
(This article belongs to the Special Issue Advances in Immunotherapy for Acute Myeloid Leukemia)
Browse Figures
Versions Notes

Simple Summary

Ex vivo-generated dendritic cells (DC/DCleu) from leukemic whole blood or isolated PBMNCs effectively activate immune effector cells and enhance anti-leukemic cytotoxicity. Higher frequencies of DC/DCleu and distinct cytokine secretion patterns are associated with improved blast lysis and improved immune responses in vivo. These functional immune parameters correlate with overall survival of patients, underscoring the prognostic relevance of generated DC/DCleu. Thus, monitoring DC/DCleu generation and immune activation may provide valuable guidance for individualized immunotherapeutic strategies and improved treatment stratification in AML patients.

Abstract

Background/Objectives: Acute myeloid leukemia (AML) is characterized by impaired anti-leukemic immune responses, and the ex vivo or in vivo generation of dendritic cells (DCs), including leukemic dendritic cells (DCleu), represents a promising strategy to stimulate immune cells and improve anti-leukemic activity. Methods: This study examined the generation, phenotype and functional relevance of DCs and DCleu produced ex vivo from blast-containing PBMNCs and whole blood (WB) in AML. Using both standard DC/DCleu-generating protocols and available Kits. Results: We show that DC/DCleu can be reliably generated with both methods. Generated DC/DCleu effectively activated T cells during mixed lymphocyte cultures (MLCs), resulting in enhanced anti-leukemic cytotoxicity. Improved blast lysis correlated with specific immunological features, including higher frequencies of generated DCleu and mature DC subsets, as well as a certain cytokine pattern after DC/DCleu cultures or MLC. In addition, the frequencies of proliferating T cells after MLC strongly correlated with the degree of achieved blast lysis, underscoring the importance of efficient DC/DCleu-mediated T cell stimulation. Both the frequencies of generated DC/DCleu and the resulting blast lytic activity were linked to overall survival (OS) in AML patients. Individuals who failed to demonstrate improved blast lysis exhibited significantly reduced OS, suggesting inadequate immune responsiveness of patients in vivo. Conclusions: These findings identify phenotypic and functional immune parameters as predictors of clinical outcome and highlight the prognostic relevance of ex vivo immune profiling. This approach may help to optimize and personalize future immunotherapeutic strategies in AML.

1. Introduction

Acute myeloid leukemia (AML) is a clonal disorder of genetically altered hematopoietic stem cells, marked by uncontrolled proliferation of immature myeloid blast cells, impairing normal haematopoiesis [1,2].
The diagnosis of AML is based on cellular, cytogenetic and molecular characterization of leukemic cells in the peripheral blood and bone marrow [3]. Induction chemotherapy, using an anthracycline–cytarabine combination followed by consolidation chemotherapy, remains the standard treatment for fit patients with AML [4]. In recent years, novel agents such as Midostaurin (a multitarget tyrosine kinase inhibitor for AML with FLT3 mutations) and Venetoclax (a B-cell lymphoma-2 inhibitor) for elderly or multi-comorbid AML patients unfit for intensive chemotherapy have been incorporated into treatment regimens, improving clinical response [5,6,7]. Hematopoietic stem cell transplantation (HSCT), based on the graft-versus-leukemia effect, remains a potentially curative post-remission therapy for AML [8,9,10]. The prognosis in AML largely depends on chromosomal abnormalities and clinical factors such as age, performance status and previous cytotoxic treatments. Unfortunately, the prognosis remains poor, with a 5-year overall survival rate of 30%, highlighting the need for durable treatment options [11,12].
Advancements in the molecular pathophysiology of AML have led to the development of various heterogeneous immunotherapies. These include antibody-based therapies targeting antigens expressed on leukemic (stem) cells (e.g., CD33, CLEC12A), immunoconjugates, bispecific T-cell engagers (BiTEs), dual-affinity retargeting antibodies (DARTs) and immune checkpoint inhibitors [13,14,15,16,17]. Additionally, adoptive immunotherapy has emerged, including genetically engineered T cells expressing chimeric antigen receptors (CARs) and T-cell receptor (TCR)-modified T cells, which are designed to reactivate effector cells against leukemic blasts [18,19]. Moreover, strategies targeting specific antigens, such as Wilms tumor 1 (WT1), have also been developed [20,21].
Dendritic cells (DCs), as major antigen-presenting cells (APCs), are a promising target for adjuvant treatment in relapsed/refractory AML or to stabilize remissions [22]. Potentially, two main sources of DCs are used or could be used in AML immunotherapy clinical trials: CD14+ monocyte-derived DCs (mo-DCs) and leukemia-derived DCs (DCleu). Mo-DCs can be generated ex vivo under Good Manufacturing Practice (GMP) conditions from peripheral blood mononuclear cells (PBMNCs) or isolated monocytes and loaded with defined leukemia-associated antigens (LAAs) using electroporation of messenger RNA (mRNA) or by peptide pulsing [23,24]. Several strategies are known to produce (mature) DCleu from PBMNCs. After pulsing or ex vivo generation, those DC/DCleu can be adoptively administered as a vaccine [25,26,27,28]. Alternatively, DC/DCleu can be generated from (blast-containing) leukemic whole blood (WB) without induction of blast proliferation ex vivo in the presence of immunomodulators using standard DC/DCleu-generating protocols (e.g., MCM, Ca, PICI, INTRON), as listed in Table 1 [29]. WB-based DC/DCleu generation models most closely simulate physiological conditions and the tumor microenvironment of AML patients, as they include all patient-specific cellular and soluble components and thus closely reflect the physiological (potentially inhibitory or activating) tumor microenvironment in AML. We have developed ten different Kits (Kit A, C, D, E, F, G, H, I, K, M), which combine two or three clinically approved immune-modulatory compounds and enable the generation of mature DCleu directly from leukemic blasts [30,31] (Table 1).
PBMNC- and DC/DCleu-generating protocols/Kits combine cytokines such as granulocyte-macrophage colony-stimulating factor (GM-CSF), Interleukin 4 (IL-4) or FLT3 ligand (FL) for the induction of myeloid differentiation; danger signals (e.g., Picibanil or nucleic acids); and maturation/danger signaling factors such as tumor necrosis factor-α (TNF-α), prostaglandin E1 (PGE1) or prostaglandin E2 (PGE2) to promote DC/DCleu differentiation and maturation. Importantly, these combinations support differentiation without triggering blast proliferation [33].
DC/DCleu produced with DC/DCleu-generating protocols or Kits have been shown to activate (adaptive and innate) immune cells after T cell-enriched immunoreactive cells in Mixed Lymphocyte Cultures (MLC): they promote T cell proliferation and induce effective anti-leukemic responses [33]. The activation of immune cells is monitored through flow cytometry, tracking up/downregulation of different cell subtypes, leukemic blasts, and chemokines [33]. To optimize our WB model, we ranked the Kits based on their ability to generate DC/DCleu and initiate anti-leukemic cytotoxicity in T cell-enriched immunoreactive cells. The top-performing Kits — Kit I (GM-CSF + Picibanil), Kit K (GM-CSF + PGE2) and Kit M (GM-CSF + PGE1)—were selected as the most promising combinations of clinically approved immune-response modifiers [31]. Correlation analyses showed positive correlations between the quantity of DC/DCleu generated with Kit I and Kit M (vs. controls) and induced anti-leukemic effects after MLC [33]. These (ex vivo) anti-leukemic effects induced after MLC of Kit M-pretreated WB were independent of patients’ response to induction chemotherapy, disease stage, French–American–British (FAB) classification, European LeukemiaNet (ELN) risk stratification, platelet/white blood/red blood cell counts, age and sex [34].
These data obtained with DC/DCleu-generating protocols show that those cells could be prepared and adoptively transferred to patients. Moreover, a Kit-based immunotherapy (treating patients directly with Kits) could lead in vivo to induced DC/DCleu, followed by DC/DCleu-activated immune cells that could contribute directly to induced/sustained remissions in AML patients, independent of clinical prognostic and diagnostic criteria.
In this study, we further investigated the quantity and quality of DC/DCleu generated from both AML-blast-containing PBMNCs and WB and assessed their ability to activate immunoreactive cells after T cell-enriched MLC, correlating the frequencies of DC/DCleu (generated from leukemic WB with various DC/DCleu-generating protocols or Kits) with cytokines released into culture supernatants and with induced anti-leukemic activity. We also correlated various clinical parameters (e.g., stage of disease, response to induction therapy) with the quality and quantity of DC/DCleu subtypes to predict AML patients’ overall survival (OS) and to contribute to identifying Kits with potential to improve anti-leukemic responses in vivo.

2. Material and Methods

2.1. Sample Collection and Preparation

Samples were obtained from randomly selected patients with AML (n = 76) or high-grade myelodysplastic syndrome (n = 3) in active stages of the disease after written informed consent was obtained in accordance with the local Ethics Committee (Pettenkoferstraße 8a, 80336 Munich, Ludwig Maximilians University Hospital; Vote No. 19-034). Samples were provided by the University Hospitals of Tuebingen, Düsseldorf, Munich, Oldenburg, and Augsburg. Anticoagulation was performed using lithium-heparin tubes (7.5 mL, Sarstedt, Nürnberg, Germany) containing standardized concentrations of heparin. PBMNCs were isolated from blood samples by density gradient centrifugation using Ficoll-Hypaque (density of separating solution 1.077 g/mL, Biochrom KG, Berlin, Germany). T cells were positively selected from PBMNCs via magnetic beads using CD3+ microbeads and column-based immunomagnetic cell separation technology (Miltenyi Biotec, Bergisch Gladbach, Germany). Cell counts were determined using Neubauer counting chambers. PBMNCs and T cells were frozen until use at −80 °C using Dimethysulfoxide or in liquid nitrogen according to standardized procedures.

2.2. Patients’ Characteristics and Definitions

Blood samples were collected from patients with AML (with an average age of 52.3 years, range 5–85 years and a female-to-male ratio of 1:1) and classified according to the French–American–British classification (FAB) (M0–M7), aetiology of AML (primary, secondary) and stage of the disease (diagnosis = dgn., persistence = pers., relapse = rel. and relapse after HSCT = rel.a.HSCT) [35]. AML patients at diagnosis were classified as favorable (n = 5), intermediate (n = 15) or adverse (n = 13) risk groups according to ELN criteria [4]. AML patients’ response to therapy was determined by achieving or not achieving complete remission (defined as <5% blasts in bone marrow and no blasts in peripheral blood 30 days after therapy start). An overview of patients’ characteristics is given in Table 2.
The cellular composition of blood samples used for subsequent experiments was 59 ± 31% leukemic blasts, 4 ± 18% CD19+ B cells, 11 ± 7% CD3+ T cells, 2 ± 13 CD56+ NK cells and 4 ± 23% CD14+ monocytes as detected by Fluorescence-activated Cell Sorting (FACS). In cases with aberrant expression of T, B, NK or monocytoid antigens on blasts, frequencies were not included in the analysis.

2.3. Flow Cytometry

Flow cytometry using a panel of mouse monoclonal antibodies (mAbs) directly conjugated with fluorescein isothiocyanate (FITC) (a), phycoerythrin (PE) (b), tandem Cy7-PE (PC7) (c) or allophycocyanin (APC) (d) was used to analyse frequencies and subtypes of cells before and after cultures. Antibodies were obtained from Becton Dickinson (Heidelberg, Germany) (CD1ab, CD1ba, CD14c, CD15d, CD71c, CD206d, 7AADc, CCR7c), Beckman Coulter (Krefeld, Germany) (CD1ab, CD3a, CD19c, CD33d, CD56b, CD80b, CD117b,d, CD206b, CD34a,c, CD65a, CD83a) and Thermo Fisher Scientific (Darmstadt, Germany) (CD1ab, CD13c, CD34d and CD86a).
For the flow cytometric analyses, samples were suspended in PBS with 5–20% fetal calf serum (FCS, Biochrom, Berlin, Germany), incubated with mAbs for 15 min, washed, centrifuged and resuspended in 100–200 µL PBS. WB samples were additionally treated with lysing buffer (Becton Dickinson, Heidelberg, Germany) according to manufacturer’s instructions. Isotype controls were used according to manufacturer’s instructions.
Flow cytometric analyses were performed with FACS Calibur Flow Cytometer (Becton Dickinson, Heidelberg, Germany) and analysed with CellQuest (Software version 5.2.1) data acquisition and analysis software (Becton Dickinson, Heidelberg, Germany).
Frequencies of mature DC/DCleu subtypes and T cells were quantified by flow cytometry [29]. An overview of quantified cells is given in Table 3.

2.4. Cell Culture Experiments

All cell culture experiments, including DC/DCleu cultures, MLCs and a cytotoxicity fluorolysis assay, were set up under standard laboratory conditions (37 °C, 21% O2 and 5% CO2).

2.5. Dendritic Cell Culture from PBMNCs and WB

DC/DCleu were generated from 3–4 × 106 isolated leukemic PBMNCs with the DC/DCleu-generating protocols MCM-Mimic (MCM), Calcium ionophore (Ca), Picibanil (Pici) and Interferon (INTRON) [29,32]. Cells were pipetted into 12-multiwell tissue culture plates (ThermoFisher Scientific, Darmstadt, Germany) and diluted in 2 mL serum-free X-Vivo-15 medium (Lonza, Basel, Switzerland). Cytokines were added, as described in Table 1. Half-medium exchange was carried out after 3–4 cell culture days. A culture without added response modifiers served as a control.
DC/DCleu were generated from leukemic WB (presenting the physiological cellular and soluble composition of the individual samples) with Kits A, C, D, E, F, I, K and M [31]. Then, 500 μL of WB was pipetted in 12-multiwell-plates and diluted 1:2 in X-Vivo-15 medium (Lonza, Basel, Switzerland) to imitate physiological conditions. Response modifiers and immune-modulating factors were added to cultures as described in Table 1. A culture without added response modifiers served as a control.

2.6. Mixed Lymphocyte Cultures (MLC)

First, 1 × 106 thawed patients’ CD3+ T cells were co-cultured with IL-2 and a stimulator cell suspension containing approximately 2.5 × 105 generated DC/DCleu, which were generated with the DC/DCleu-generating protocol or Kits from leukemic PBMNCs or WB (MLCPBMNC DC; MLCWB DC). MLCs of T cell-enriched immunoreactive cells with a stimulator cell suspension without pretreatment with DC/DCleu-generating protocol or Kits (MLCPBMNC; MLCWB) served as a control, as previously described [36]. Next, the cells were harvested after 6–7 days, and the subtypes were quantified by flow cytometry and subsequently used for a cytotoxicity fluorolysis assay.

2.7. Cytotoxicity Fluorolysis Assay

The blast lytic activity of DC/DCleu-stimulated T cell-enriched immunoreactive cells in MLC from PBMNC and WB cultures (containing effector cells) was analyzed in a Cytotoxicity Fluorolysis Assay (CTX), as previously described [31,34].
The lytic activity of effector cells was defined as the percentual difference between the frequencies of viable blast target cells before and after T effector cell contact (achieved lysis). To assess the lytic activity of effector cells in more detail, we defined the percentual difference between the achieved lysis of standard DC/DCleu protocol/Kit-pretreated PBMNC/WB vs. untreated PBMNC/WB in every given case (improved lysis).

2.8. Enzyme-Linked Immunosorbent Assay (ELISA)

Secretion of Interleukin 10 (IL-10), Interleukin 17 (IL-17) and Monocyte Chemoattractant Protein-1 (MCP-1) was analyzed in cell culture supernatants (stored at −80°C until the day of analysis) collected from DC/DCleu cultures generated from WB (IL-10DC, IL-17DC, MCP-1DC) as well as from MLCs (IL-10MLC, IL-17MLC, MCP-1MLC) using Sandwich ELISA immunoassay Kits (R&D Systems, Abingdon, UK). Detection limits of the sandwich ELISA immunoassay Kits were set by the manufacturer (R&D Systems) as follows: IL-10: 11 pg/mL; IL-17: 0.5 pg/mL; and MCP-1: 15 pg/mL. The samples were evaluated with a Tristar LB941 ELISA reader (Berthold company, Bad Wildbach, Germany) using a standard curve according to the manufacturer’s instructions.

2.9. Statistical Methods

We evaluated descriptive statistics (average, median, standard deviation) and conducted paired and unpaired t-tests, Mann–Whitney U test, Chi-squared Test, Pearson correlation coefficients and Kaplan–Meier analyses. Statistical analysis and figures were implemented with SPSS Statistics 28 (IBM Software, New York, NY, USA) and GraphPad Prism 8 (GraphPad Software, CA, USA). Differences were considered ‘not significant’ (n.s.) with p values > 0.10, as ‘borderline significant’ with p values from 0.10 to 0.05, and as ‘significant’ with p values < 0.05. Correlation was defined as ‘no correlation’ in cases with r values between 0 and 0.1, as ‘low’ in cases with r values between 0.2 and 0.4, as ‘medium’ in cases with r values between 0.5 and 0.7, and as ‘high’ in cases with r values > 0.7.

3. Results

It is well known that DC/DCleu can be generated from leukemic blasts in PBMNCs as well as WB, which present the physical, cellular and soluble components of each individual patient. These generated DC/DCleu can specifically activate immune cells against leukemic blasts after MLC, resulting in effective anti-leukemic activity against leukemic blasts.
1. 
Blasts are regularly converted to DC/DCleu in the presence of standard DC/DCleu-generating protocols and Kits, leading to activated ne cells, after stimulation in T cell-enriched MLC
Pooling all data obtained with standard DC/DCleu-generating protocols from PBMNCs (compared to MCM alone) and all data with Kits from WB (compared to Kit I alone), comparable frequencies of DCleu/cells, DCleu/bla+, DCleu/DC+ and DCmat/DC+ were found after DC/DCleu cultures. Frequencies of generated DCleu and subsets increased significantly using DC/DCleu-generating protocols and Kits compared to control without added response modifiers (Supplementary Materials Figure S1(A1,A2)), thereby confirming data previously shown [29,31]. No increase in proliferating blasts was found before vs. after Kit treatment. Analysis of T cell subsets before and after T cell-enriched MLC with DC/DCleu-containing PBMNCs or WB showed consistent results, confirming a shift toward higher T cell activation. This effect was independent of whether DC/DCleu were generated using standard protocols from PBMNCs or with Kits from WB.
Furthermore, we analyzed the concentrations of IL-10, IL-17 and MCP-1 in DC/DCleu culture supernatants after cultures with Kits (pooling all data with all Kits compared to Kit I pretreated samples alone) (Supplementary Materials Figure S1(B1,C1,D1)) or from supernatants collected after MLC (pooling all data with all Kit-pretreated samples (compared to Kit I pretreated samples alone)) (Supplementary Materials Figure S1(B2,C2,D2)). We found no differences in cytokine levels when pooling all data from WB cultures pretreated with Kits vs. Kit I alone. However, we found higher levels of all cytokines compared to control supernatants without added Kits, as has been previously described [36].
In summary, our data support previously published findings that DC/DCleu subtypes can be reliably generated from blast-containing PBMNCs using standard protocols, as well as from whole blood using Kits. Additionally, these cells are capable of stimulating T cells to a more activated state during MLC and to an increased release of chemokines and cytokines to DC/DCleu or MLC culture supernatants.
2. 
Functional analyses
We evaluated the potential of DC/DCleu to induce and improve T cells’ anti-leukemic activity after MLC: We analysed blast lytic activity of T cells stimulated with generated DC/DCleu from PBMNCs and WB (MLCDCPBMNC and MLCDCWB) as well as their respective controls (T cells stimulated with leukemic PBMNCs and WB without previous stimulation with generated DC/DCleu (MLCPBMNC and MLCWB)) in a cytotoxicity assay. The lytic activity of effector cells (MLCDCPBMNC, MLCDCWB) versus their respective controls (MLCPBMNC, MLCWB) was analyzed after different coculture durations with blast target cells: at 3 h, at 24 h and additionally by selecting the ‘best lytic result per case’ from either the 3 or 24 h time points in cases where both measurements were available.
  • 2.1 
    Higher probability of achieving blast lysis after DC/DCleu stimulated T cell enriched MLC
First, we examined the anti-leukemic potential of DC/DCleu-stimulated effector cells after MLC to lyse blasts. We found more cases with achieved blast lysis after T cell stimulation with DC/DCleu (MLCDCPBMNC) vs. control (MLCPBMNC) after MLC with DC/DCleu generated with standard DC/DCleu methods (Supplementary Materials Figure S2(A1)). In all conditions, effector cells lysed more blasts than in the control group (Supplementary Materials Figure S2(A2)). These stimulations enhanced blast lysis across all DC/DCleu-generating methods (Supplementary Materials Figure S2(B1)), with up to a 100% increase in blast lysis observed after MCM pretreatment (Supplementary Materials Figure S2(B2)) compared to controls.
Pooling all data on effector cell cytotoxicity after MLC with DC/DCleu generated using Kits (MLCDCWB) compared to MLC with blast-containing WB (MLCWB), we also found in all cohorts more cases with achieved blast lysis after T cell stimulation with DC/DCleu (MLCDCWB)-containing cells (Supplementary Materials Figure S2(C1)). In all settings, more blasts were lysed compared to control (Supplementary Materials Figure S2(C2)). These stimulations resulted in up to 100% of cases compared to control, depending on the Kits used (Supplementary Materials Figure S2(D1)).
In summary, stimulation of T cells with generated DC/DCleu from PBMNC and WB leads to an increase in blast lysis compared to control.
3. 
DC/DCleu, blast, T cell and cytokine profiles in correlation with anti-leukemic activity after MLC
To evaluate the predictive role of DC/DCleu, T cell and cytokine values and their subtypes for the mediation or improvement of anti-leukemic reactions (vs. controls), we correlated frequencies/concentrations of cellular/soluble compositions of the samples with their anti-leukemic potential. In the first step, we present pooled results obtained with all standard DC/DCleu-generating methods/Kits; in the second step, we present results obtained with single standard DC/DCleu-generating methods/Kits: The role of cellular/soluble composition on achieved blast lysis (vs. no lysis) or improved (vs. not improved) blast lysis as compared to controls was evaluated.
Pooling all data obtained with standard DC/DCleu-generating methods and analysing DC/DCleu subsets after culture of PBMNCs with standard DC/DCleu-generating methods showed increased frequencies of DC+/cells, DCleu/cells, DCleu/bla+ and DCmat/DC+ in samples with achieved (vs. not achieved) lysis after 3 h or 24 h, as well as when selecting the best result after 3 or 24 h (e.g., %DCleu/bla+: 32 ± 25 vs. 24 ± 15). When analysing T cell populations after MLC with DC/DCleu generated with standard DC/DCleu methods, a significantly increased frequency of Tprol was found in samples with achieved (vs. not achieved) lysis when selecting the best result after 3 or 24 h (%Tprol/CD3+: 42 ± 40 vs. 11 ± 9%, p = 0.005). When analysing data obtained with single standard DC/DCleu methods, MCM (n = 44), Ca (n = 16) and PICI (n = 16) yielded comparable results. All in all, we confirmed previous data that (mature) DC/DCleu subtypes are increased under the influence of standard DC/DCleu-generating methods leading to activated T cells and improved blast lysis.
Pooling all data obtained with Kits (n = 20) and analysing DC/DCleu subsets after culture of WB with Kits showed increased frequencies of DCleu/DC+ in samples with achieved (vs. not achieved) lysis after 3 h or 24 h, as well as when selecting the best result after 3 or 24 h. Increased frequencies were found for %DCleu/bla+ (37 ± 23 vs. 27 ± 15%, p = 0.029). When analysing T cell populations, significantly increased frequencies of CD8+ T cells were found after MLC with DC/DCleu generated with Kits in samples with achieved (vs. not achieved) lysis (e.g., %TCD8+/CD3+: 51 ± 16 vs. 40 ± 18, p = 0.079).
Analysing cytokine release in DC/DCleu culture supernatants showed increased concentrations of IL-10 (Ø of IL-10DC: 0.77 ± 2.15 vs. 0.0 ± 0.0 pg/mL), decreased concentrations of MCP-1 (Ø of MCP-1DC: 679 ± 580 vs. 1212 ± 41 pg/mL) and comparable concentrations of IL-17 in supernatants of samples with achieved (vs. not achieved) lysis after 3 h, as well as when selecting the best result after 3 or 24 h of co-incubation of target with effector cells. Analysing cytokine release in MLC supernatants showed higher concentrations of IL-10 (Ø of IL-10MLC: 332 ± 441 vs. 203 ± 145 pg/mL), lower concentrations of IL-17 and MCP (Ø of IL-17MLC: 106 ± 81 vs. 166 ± 46 pg/mL; Ø of MCP-1MLC: 434 ± 493 vs. 911 ± 494) in supernatants of samples with achieved (vs. not achieved) lysis after 3 h, as well as when selecting the best result after 3 or 24 h of co-incubation of target with effector cells.
To correlate achieved anti-leukemic effects with DC/DCleu and T cell subsets, we grouped cases according to ‘best achieved anti-leukemic activity’ after Kit pretreatment of patients’ WB. Only cases were included in which DC/DCleu subsets were available with these Kits and where cytotoxicity results after 3 h and 24 h of co-incubation of target with effector cells were available. We separated cases into two groups, characterized by ‘best achieved lysis’ of cells after T cell-enriched MLC with Kit-pretreated WB (group 1 Kits: Kit pretreatment with D, E, I, M (pooled results), Figure 1A, left side), compared to cases with inferior anti-leukemic efficacy (group 2 Kits: Kit pretreatment with Kits C, F, K (pooled results), Figure 1B, right side).
Correlation analyses showed that superior anti-leukemic activity of group 1 Kits correlated with higher frequencies of DC/DCleu subtypes (after Kit culture) and proliferating T cells after MLC compared to group 2 Kits characterized by inferior achieved blast lysis; this pooled cohort correlated with lower frequencies of DC/DCleu subtypes and proliferating T cells after MLC (Figure 1(A2), right side).
4. 
Frequencies of generated DC/DCleu and resulting blast lytic activity as predictors for response to induction therapy and for overall survival in AML patients
As shown in Figure 2 (left side), we could demonstrate that frequencies of DC/DCleu subtypes (especially of %DCleu/Bla+ and DCmat/DC+, generated with group 1 Kits (Kit D, E, I or M, pooled data)) were higher in patients at first diagnosis who had responded vs. not responded to induction therapy. These differences were even more pronounced when only selecting for patients in whom DC/DCleu were generated with Kit I (Figure 2, right side).
Moreover, we correlated the long-term vs. short-term survival of patients (defined as survival longer or shorter than the median survival of the cohort) and found that, in all comparisons, patients with longer vs. shorter survival were characterized by significantly higher frequencies of DCleu/Bla+ in all stages of the disease, at diagnosis and at relapse after HSCT, using all Kits pooled, group 1 Kits and Kit I alone (Figure 3). In summary, this indicates that longer median survival is associated with higher generated DCleu counts.
Furthermore, we could show that frequencies of ex vivo-generated DC and DCleu, including their subgroups, are predictive for overall survival (OS) in 24 AML patients: Survival rates were higher in patients where more than 10% DC+/WB and more than 5% DCleu/DC+ could be generated with group 1 Kits (Kits D, E, I or M in DC/DCleu cultures (data pooled)) (Figure 4,f left side). These findings were consistent both when pooling data from all Kits and when analyzing data from Kit I alone (Figure 4, right side), but not for patients whose blood was treated with group 2 kits (Kits C, F, K). Additionally, as shown in Figure 5, increased blast lytic activity was also associated with improved overall survival. In cases with non-improved blast lysis after MLC, the overall survival was reduced compared to cases with improved blast lysis.

4. Discussion

This study provides a comprehensive analysis of the generation and functional relevance of DC/DCleu derived from blast-containing PBMNCs and WB using both established laboratory DC/DCleu-generating protocols and available Kits. The DC/DCleu-generating Kits used in this study are distinct combinations of clinically approved immune-modulatory compounds that directly influence DC/DCleu differentiation, maturation, and functional capacity. Defining the relevance of each Kit allows interpretation of differences in DC/DCleu quantity, quality, and induced anti-leukemic activity, defining protocols with the greatest translational potential for in vivo application.

4.1. Generation of DC/DCleu and T Cell Activation

Our results confirm that leukemic blasts can consistently be differentiated into functionally competent DC/DCleu using both standard DC/DCleu-generating protocols and Kits [29,31,37] (Supplementary Materials Figure S1). These generated cells exhibited robust expression of key dendritic cell markers and were capable of inducing T cell activation during MLC. Importantly, this activation translated into enhanced anti-leukemic responses in vitro, supporting earlier studies and further validating the immunogenic potential of DC/DCleu [34]. Similar efficacy across PBMNCs and WB underscores their flexibility and practical relevance, particularly for clinical settings where sample availability may vary.

4.2. Cytokine Modulation by Kit Pretreatment

Cytokines in AML—both pro-inflammatory (e.g., IL-1β, IL-6, TNF-α, IL-17) and anti-inflammatory (e.g., IL-10)—regulate leukemic cell growth, survival, immune evasion, and chemoresistance, shaping disease progression and patient outcomes [38]. We could show that treating WB with Kits did not noticeably change the levels of major pro-inflammatory cytokines like IL-17. However, it did cause a small but consistent rise in IL-10 and MCP-1 (Supplementary Materials Figure S1). This suggests that the Kits might have mild immune-modifying effects—potentially contributing to attracting immune cells (through MCP-1) [39,40] or to promoting regulatory responses (through IL-10) [41]. While the variability in MCP-1 release was not statistically significant, it points to compositional differences between Kits that may influence the cytokine milieu and T cell dynamics. Although IL-10 is classically defined as an immunosuppressive cytokine, elevated IL-10 levels in samples with effective blast lysis may reflect strong preceding immune activation rather than a direct inhibitory effect on cytotoxicity. This observation may be explained by the fact that effector T cells, including Th1 cells, can produce IL-10 as part of an intrinsic negative feedback mechanism to limit excessive inflammation. In addition, IL-10 can exert context-dependent immunostimulatory effects. In tumor models, IL-10 has been shown to enhance CD8+ T-cell infiltration, increase IFN-γ expression, and support cytotoxic function, thereby promoting effective immune surveillance under specific inflammatory conditions [42,43,44]. Furthermore, lower MCP-1 levels in samples with effective blast lysis may reflect reduced recruitment of immunosuppressive monocytes and myeloid cells, promoting a microenvironment more permissive for T-cell-mediated cytotoxicity [45,46].

4.3. Improved Anti-Leukemic Activity Following DC/DCleu Stimulation

Functionally, T cells stimulated with DC/DCleu demonstrated superior anti-leukemic activity compared to those co-cultured with leukemic blasts alone. This enhanced cytotoxicity was consistently observed across both 3 h and 24 h co-culture durations. Here we could confirm previously published data from our working group [29,30,34] (Supplementary Materials Figure S2). The different results after 3 or 24 h of co-culture might be the result of different killing mechanisms or, at least, a variation of this process (e.g., the slow pathway of Fas/FasL- or the fast pathway of perforin–granzyme-mediated killing). These effects might act synergistically or independently [47,48].

4.4. Correlation Analyses

Our results demonstrate a clear correlation between the cellular and soluble composition of generated DC/DCleu, T cell activation, cytokine profiles and the anti-leukemic activity of T cells after MLC. When pooling data from all standard DC/DCleu-generating methods, increased frequencies of mature DC/DCleu subtypes (e.g., DCleu/bla+, DCmat/DC+) were consistently associated with effective blast lysis, indicating that the quality and maturation state of generated DC/DCleu are key determinants of T cell-mediated cytotoxicity [34]. The expression of CCR7 on mature DCs is crucial for the migratory capacity of DCs and DCleu to the lymph node, where they activate T cells and other immunoreactive cells and induce anti-leukemic activity [49,50,51]. Correspondingly, MLC analyses showed significantly higher frequencies of proliferating T cells in samples with achieved lysis, supporting the role of DC/DCleu-induced T cell activation in mediating anti-leukemic effects. Single-method analyses (MCM, Ca, PICI) confirmed these observations, highlighting the robustness of standard DC/DCleu generation in promoting functional immune responses [26].
When evaluating Kit-based DC/DCleu generation, similar trends were observed. Samples with superior anti-leukemic activity displayed higher frequencies of DCleu/DC+ and CD8+ T cells, although statistical significance was marginal for some comparisons. Cytokine profiling revealed that increased IL-10 and IFN-γ concentrations in DC/DCleu cultures, together with reduced MCP-1 levels, were associated with effective blast lysis, suggesting that a cytokine milieu combining immune activation (IFN-γ) and regulatory balance (IL-10) may optimize T cell function while limiting excessive inflammation [52]. In MLC supernatants, higher IL-10 and lower IL-17 and MCP-1 levels further supported a regulatory environment conducive to sustained T cell-mediated cytotoxicity [53].
Grouping cases by best achieved anti-leukemic activity after Kit pretreatment revealed that superior cytotoxic responses correlated with higher frequencies of DC/DCleu subsets and proliferating T cells, whereas inferior responses were associated with lower frequencies of these key populations (Figure 1 and Figure 2). These findings collectively underscore that both the cellular composition (mature DC/DCleu, proliferating T cells) and the cytokine environment (IL-10, IFN-γ, MCP-1, IL-17) critically influence the efficacy of anti-leukemic T cell responses. The data support the predictive value of DC/DCleu and T cell profiling for assessing and potentially enhancing the anti-leukemic capacity of immunotherapeutic strategies [25].

4.5. Frequencies of Generated DC/DCleu and Achieved Blast Lytic Activity Can Predict Overall Survival

Our data demonstrate that longer vs. shorter survival compared to the median survival of patients studied in various stages of the disease is associated with significantly increased DCleu values (Figure 3) and, vice versa, that cases with increased DC/DCleu generation exhibited improved survival outcomes (Figure 4 and Figure 5). These results were consistent across pooled data from multiple Kits as well as in the subset of patients treated with Kit I alone, indicating the robustness and reproducibility of this immune signature.
In addition to phenotypic markers, functional immune activity—specifically, the ex vivo blast lytic capacity—was also predictive of clinical outcomes. Increased blast lysis in MLC following stimulation with Kit-pretreated samples was associated with better overall survival. Conversely, in cases where blast lysis was not improved after MLC, overall survival was markedly reduced. This suggests that a lack of functional anti-leukemic immune response reflects an impaired immune system, which may compromise the patient’s ability to control disease progression or respond to immunotherapeutic interventions. Kits may become valuable tools for treating patients with AML in the future, as they have the potential to enhance anti-leukemic activity in vivo. This approach could reduce the need for expensive and complicated vaccinations with ex vivo generated and manipulated (leukemic antigen-loaded) mo-DC and may ultimately improve the prognosis and relapse-free survival of patients with AML.

5. Conclusions

This study demonstrates that both the cellular composition and cytokine environment of generated DC/DCleu critically shape T cell activation and anti-leukemic ex vivo activity. Mature DC/DCleu subsets, together with proliferating and cytotoxic T cells and a certain cytokine milieu, consistently correlated with effective blast lysis with standard DC/DCleu-generating protocols and Kits. Importantly, higher DC/DCleu frequencies and stronger ex vivo anti-leukemic cytotoxicity were associated with improved overall survival for the patients, underscoring their value as predictive biomarkers. All in all, this study highlights DC/DCleu-based immune profiling as a promising tool to refine and enhance immunotherapeutic strategies in AML. The results support further exploration of DC/DCleu as components of personalized immunotherapy and emphasize the importance of immune competence in therapeutic response. As a next step to translate ex vivo findings from bench to bedside, the efficacy and safety of the Kit treatment have to be evaluated in appropriate preclinical in vivo models, such as AML animal models, to confirm immunogenicity and anti-leukemic activity under physiological conditions. We have already treated leukemic rats (compared to rats without treatment) as well as three patients with refractory AML with Kit M. The treatment was very well tolerated. We observed immune activation with increased leukemia-specific responses and memory cell formation. In addition, leukemic blast counts were stabilized and, in some cases, even reduced [54,55]. We are currently performing studies in leukemic mice using a different mouse model, which contributes to a clinical trial. Based on these results, prospective clinical trials would be required to assess safety, feasibility, and clinical benefit in vivo.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers18050847/s1, Figure S1: DC/DCleu can be generated with standard DC/DCleu-generating protocols from blast containing PBMNCs (A1) and with Kits from blast containing WB (A2). Increased concentrations of IL-10, IL-17 and MCP-1 found in DC/DCleu-cultures supernatants (B1,C1,D1) as well as MLC supernatants (B2,C2,D2) after incubation with Kits compared to control. Figure S2: Achieved and improved anti-leukemic activity of immunoreactive cells after MLC with PBMNC pre-treated with standard-DC/DCleu-protocols or Kits as measured by Cytotoxicity Assay.

Author Contributions

D.C.A., Z.F., D.D., A.H.-L., C.P., A.R., C.S. (Christoph Schwepcke), S.U., L.K.K., C.A., A.L. and M.F. conducted the DC/DCleu, MLC and CTX experiments, including flow cytometry analyses. Z.F. contributed data analyses and statistical analyses as well as correlation analyses. C.S. (Christoph Schmid) provided the leukemic whole blood samples and corresponding diagnostic reports. D.C.A., Z.F. and H.M.S. drafted the manuscript. H.M.S. designed the study and is the head of the research group; therefore, she is responsible for the content of this manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

Intramural funding from the University Hospital of Munich and the University Hospital of Augsburg.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the local Ethics Committee (Pettenkoferstraße 8a, 80336 Munich, Ludwig Maximilians University Hospital in Munich; Vote No 19-034, 21 February 2019).

Informed Consent Statement

Written informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data published in this study are openly available in a public repository with a permanent identifier, such as a DOI.

Acknowledgments

The authors thank the patients, nurses and physicians on the wards for their support, the diagnostic laboratories, as well as the treating institutions for the patients’ diagnostic reports.

Conflicts of Interest

Modiblast Pharma GmbH (Oberhaching, Germany) holds the European Patent 15 801 987.7-1118 and US Patent 15-517627 ‘Use of immunomodulatory effective compositions for the immunotherapeutic treatment of patients suffering from myeloid leukemias’, in which H.M.S. is involved.

References

  1. Shimony, S.; Stahl, M.; Stone, R.M. Acute myeloid leukemia: 2023 update on diagnosis, risk-stratification, and management. Am. J. Hematol. 2023, 98, 502–526. [Google Scholar] [CrossRef]
  2. Wachter, F.; Pikman, Y. Pathophysiology of Acute Myeloid Leukemia. Acta Haematol. 2024, 147, 229–246. [Google Scholar] [CrossRef]
  3. Heuser, M.; Ofran, Y.; Boissel, N.; Brunet Mauri, S.; Craddock, C.; Janssen, J.; Wierzbowska, A.; Buske, C. Acute myeloid leukaemia in adult patients: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2020, 31, 697–712. [Google Scholar] [CrossRef]
  4. Dohner, H.; Wei, A.H.; Appelbaum, F.R.; Craddock, C.; DiNardo, C.D.; Dombret, H.; Ebert, B.L.; Fenaux, P.; Godley, L.A.; Hasserjian, R.P.; et al. Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood 2022, 140, 1345–1377. [Google Scholar] [CrossRef]
  5. Stone, R.M.; Mandrekar, S.J.; Sanford, B.L.; Laumann, K.; Geyer, S.; Bloomfield, C.D.; Thiede, C.; Prior, T.W.; Dohner, K.; Marcucci, G.; et al. Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation. N. Engl. J. Med. 2017, 377, 454–464. [Google Scholar] [CrossRef] [PubMed]
  6. DiNardo, C.D.; Pratz, K.; Pullarkat, V.; Jonas, B.A.; Arellano, M.; Becker, P.S.; Frankfurt, O.; Konopleva, M.; Wei, A.H.; Kantarjian, H.M.; et al. Venetoclax combined with decitabine or azacitidine in treatment-naive, elderly patients with acute myeloid leukemia. Blood 2019, 133, 7–17. [Google Scholar] [CrossRef] [PubMed]
  7. Short, N.J.; Daver, N.; Dinardo, C.D.; Kadia, T.; Nasr, L.F.; Macaron, W.; Yilmaz, M.; Borthakur, G.; Montalban-Bravo, G.; Garcia-Manero, G.; et al. Azacitidine, Venetoclax, and Gilteritinib in Newly Diagnosed and Relapsed or Refractory FLT3-Mutated AML. J. Clin. Oncol. 2024, 42, 1499–1508. [Google Scholar] [CrossRef]
  8. Rambaldi, B.; Rizzuto, G.; Rambaldi, A.; Introna, M. Genetically modified and unmodified cellular approaches to enhance graft versus leukemia effect, without increasing graft versus host disease: The use of allogeneic cytokine-induced killer cells. Front. Immunol. 2024, 15, 1459175. [Google Scholar] [CrossRef] [PubMed]
  9. Socie, G.; Galimard, J.E.; Raffoux, E.; Itzykson, R.; Debureaux, P.E.; Michonneau, D.; Lengline, E.; Robin, M.; De Fontbrune, F.S.; Sebert, M.; et al. Allogeneic transplantation in acute myelogenous leukemia: A comprehensive single institution’s experience. Haematologica 2023, 108, 2369–2379. [Google Scholar] [CrossRef]
  10. Sweeney, C.; Vyas, P. The Graft-Versus-Leukemia Effect in AML. Front. Oncol. 2019, 9, 1217. [Google Scholar] [CrossRef] [PubMed]
  11. Boscaro, E.; Urbino, I.; Catania, F.M.; Arrigo, G.; Secreto, C.; Olivi, M.; D’Ardia, S.; Frairia, C.; Giai, V.; Freilone, R.; et al. Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors. Cancers 2023, 15, 3512. [Google Scholar] [CrossRef]
  12. Li, Y.; Zhou, F. Efficacy of bone marrow transplantation in treating acute myeloid leukemia: A systematic review and meta-analysis. Am. J. Transl. Res. 2023, 15, 1–12. [Google Scholar]
  13. Gomez-Llobell, M.; Peleteiro Raindo, A.; Climent Medina, J.; Gomez Centurion, I.; Mosquera Orgueira, A. Immune Checkpoint Inhibitors in Acute Myeloid Leukemia: A Meta-Analysis. Front. Oncol. 2022, 12, 882531. [Google Scholar] [CrossRef]
  14. Khaldoyanidi, S.; Nagorsen, D.; Stein, A.; Ossenkoppele, G.; Subklewe, M. Immune Biology of Acute Myeloid Leukemia: Implications for Immunotherapy. J. Clin. Oncol. 2021, 39, 419–432. [Google Scholar] [CrossRef]
  15. Isidori, A.; Cerchione, C.; Daver, N.; DiNardo, C.; Garcia-Manero, G.; Konopleva, M.; Jabbour, E.; Ravandi, F.; Kadia, T.; Burguera, A.F.; et al. Immunotherapy in Acute Myeloid Leukemia: Where We Stand. Front. Oncol. 2021, 11, 656218. [Google Scholar] [CrossRef]
  16. Tabata, R.; Chi, S.; Yuda, J.; Minami, Y. Emerging Immunotherapy for Acute Myeloid Leukemia. Int. J. Mol. Sci. 2021, 22, 1944. [Google Scholar] [CrossRef] [PubMed]
  17. Venugopal, S.; Daver, N.; Ravandi, F. An Update on the Clinical Evaluation of Antibody-Based Therapeutics in Acute Myeloid Leukemia. Curr. Hematol. Malig. Rep. 2021, 16, 89–96. [Google Scholar] [CrossRef] [PubMed]
  18. Mardiana, S.; Gill, S. CAR T Cells for Acute Myeloid Leukemia: State of the Art and Future Directions. Front. Oncol. 2020, 10, 697. [Google Scholar] [CrossRef] [PubMed]
  19. Hu, Y.; Zhou, Y.; Zhang, M.; Zhao, H.; Wei, G.; Ge, W.; Cui, Q.; Mu, Q.; Chen, G.; Han, L.; et al. Genetically modified CD7-targeting allogeneic CAR-T cell therapy with enhanced efficacy for relapsed/refractory CD7-positive hematological malignancies: A phase I clinical study. Cell Res. 2022, 32, 995–1007. [Google Scholar] [CrossRef]
  20. Goel, H.; Rahul, E.; Gupta, A.K.; Meena, J.P.; Chopra, A.; Ranjan, A.; Hussain, S.; Rath, G.K.; Tanwar, P. Molecular update on biology of Wilms Tumor 1 gene and its applications in acute myeloid leukemia. Am. J. Blood Res. 2020, 10, 151–160. [Google Scholar]
  21. Guarnera, L.; Bravo-Perez, C.; Visconte, V. Immunotherapy in Acute Myeloid Leukemia: A Literature Review of Emerging Strategies. Bioengineering 2023, 10, 1228. [Google Scholar] [CrossRef]
  22. Motallebzadeh Khanmiri, J.; Alizadeh, M.; Esmaeili, S.; Gholami, Z.; Safarzadeh, A.; Khani-Eshratabadi, M.; Baghbanzadeh, A.; Alizadeh, N.; Baradaran, B. Dendritic cell vaccination strategy for the treatment of acute myeloid leukemia: A systematic review. Cytotherapy 2024, 26, 427–435. [Google Scholar] [CrossRef]
  23. Weinstock, M.; Rosenblatt, J.; Avigan, D. Dendritic Cell Therapies for Hematologic Malignancies. Mol. Ther. Methods Clin. Dev. 2017, 5, 66–75. [Google Scholar] [CrossRef] [PubMed]
  24. Anguille, S.; Willemen, Y.; Lion, E.; Smits, E.L.; Berneman, Z.N. Dendritic cell vaccination in acute myeloid leukemia. Cytotherapy 2012, 14, 647–656. [Google Scholar] [CrossRef]
  25. Van Acker, H.H.; Versteven, M.; Lichtenegger, F.S.; Roex, G.; Campillo-Davo, D.; Lion, E.; Subklewe, M.; Van Tendeloo, V.F.; Berneman, Z.N.; Anguille, S. Dendritic Cell-Based Immunotherapy of Acute Myeloid Leukemia. J. Clin. Med. 2019, 8, 579. [Google Scholar] [CrossRef] [PubMed]
  26. Palomares, F.; Pina, A.; Dakhaoui, H.; Leiva-Castro, C.; Munera-Rodriguez, A.M.; Cejudo-Guillen, M.; Granados, B.; Alba, G.; Santa-Maria, C.; Sobrino, F.; et al. Dendritic Cells as a Therapeutic Strategy in Acute Myeloid Leukemia: Vaccines. Vaccines 2024, 12, 165. [Google Scholar] [CrossRef]
  27. Van de Velde, A.L.; Berneman, Z.N.; Van Tendeloo, V.F. Immunotherapy of hematological malignancies using dendritic cells. Bull. Cancer 2008, 95, 320–326. [Google Scholar] [CrossRef]
  28. Subklewe, M.; Geiger, C.; Lichtenegger, F.S.; Javorovic, M.; Kvalheim, G.; Schendel, D.J.; Bigalke, I. New generation dendritic cell vaccine for immunotherapy of acute myeloid leukemia. Cancer Immunol. Immunother. 2014, 63, 1093–1103. [Google Scholar] [CrossRef] [PubMed]
  29. Kremser, A.; Dressig, J.; Grabrucker, C.; Liepert, A.; Kroell, T.; Scholl, N.; Schmid, C.; Tischer, J.; Kufner, S.; Salih, H.; et al. Dendritic cells (DCs) can be successfully generated from leukemic blasts in individual patients with AML or MDS: An evaluation of different methods. J. Immunother. 2010, 33, 185–199. [Google Scholar] [CrossRef]
  30. Amberger, D.C.; Doraneh-Gard, F.; Gunsilius, C.; Weinmann, M.; Mobius, S.; Kugler, C.; Rogers, N.; Bock, C.; Kodel, U.; Werner, J.O.; et al. PGE(1)-Containing Protocols Generate Mature (Leukemia-Derived) Dendritic Cells Directly from Leukemic Whole Blood. Int. J. Mol. Sci. 2019, 20, 4590. [Google Scholar] [CrossRef] [PubMed]
  31. Schwepcke, C.; Klauer, L.K.; Deen, D.; Amberger, D.C.; Fischer, Z.; Doraneh-Gard, F.; Gunsilius, C.; Hirn-Lopez, A.; Kroell, T.; Tischer, J.; et al. Generation of Leukaemia-Derived Dendritic Cells (DC(leu)) to Improve Anti-Leukaemic Activity in AML: Selection of the Most Efficient Response Modifier Combinations. Int. J. Mol. Sci. 2022, 23, 8333. [Google Scholar] [CrossRef]
  32. Sato, M.; Takayama, T.; Tanaka, H.; Konishi, J.; Suzuki, T.; Kaiga, T.; Tahara, H. Generation of mature dendritic cells fully capable of T helper type 1 polarization using OK-432 combined with prostaglandin E(2). Cancer Sci. 2003, 94, 1091–1098. [Google Scholar] [CrossRef] [PubMed]
  33. Klauer, L.K.; Schutti, O.; Ugur, S.; Doraneh-Gard, F.; Amberger, D.C.; Rogers, N.; Kramer, D.; Rank, A.; Schmid, C.; Eiz-Vesper, B.; et al. Interferon Gamma Secretion of Adaptive and Innate Immune Cells as a Parameter to Describe Leukaemia-Derived Dendritic-Cell-Mediated Immune Responses in Acute Myeloid Leukaemia in vitro. Transfus. Med. Hemotherapy 2022, 49, 44–61. [Google Scholar] [CrossRef] [PubMed]
  34. Klauer, L.K.; Rejeski, H.A.; Ugur, S.; Rackl, E.; Abdulmajid, J.; Fischer, Z.; Pepeldjiyska, E.; Frischhut, A.; Schmieder, N.; Volker, A.; et al. Leukemia-Derived Dendritic Cells Induce Anti-Leukemic Effects Ex Vivo in AML Independently of Patients’ Clinical and Biological Features. Int. J. Mol. Sci. 2025, 26, 1700. [Google Scholar] [CrossRef]
  35. Neame, P.B.; Soamboonsrup, P.; Browman, G.P.; Meyer, R.M.; Benger, A.; Wilson, W.E.; Walker, I.R.; Saeed, N.; McBride, J.A. Classifying acute leukemia by immunophenotyping: A combined FAB-immunologic classification of AML. Blood 1986, 68, 1355–1362. [Google Scholar] [CrossRef] [PubMed]
  36. Unterfrauner, M.; Rejeski, H.A.; Hartz, A.; Bohlscheid, S.; Baudrexler, T.; Feng, X.; Rackl, E.; Li, L.; Rank, A.; Filippini Velazquez, G.; et al. Granulocyte-Macrophage-Colony-Stimulating-Factor Combined with Prostaglandin E1 Create Dendritic Cells of Leukemic Origin from AML Patients’ Whole Blood and Whole Bone Marrow That Mediate Antileukemic Processes after Mixed Lymphocyte Culture. Int. J. Mol. Sci. 2023, 24, 17436. [Google Scholar] [CrossRef]
  37. Li, L.; Reinhardt, P.; Schmitt, A.; Barth, T.F.; Greiner, J.; Ringhoffer, M.; Dohner, H.; Wiesneth, M.; Schmitt, M. Dendritic cells generated from acute myeloid leukemia (AML) blasts maintain the expression of immunogenic leukemia associated antigens. Cancer Immunol. Immunother. 2005, 54, 685–693. [Google Scholar] [CrossRef]
  38. Luciano, M.; Krenn, P.W.; Horejs-Hoeck, J. The cytokine network in acute myeloid leukemia. Front. Immunol. 2022, 13, 1000996. [Google Scholar] [CrossRef] [PubMed]
  39. Singh, S.; Anshita, D.; Ravichandiran, V. MCP-1: Function, regulation, and involvement in disease. Int. Immunopharmacol. 2021, 101, 107598. [Google Scholar] [CrossRef]
  40. Lu, B.; Rutledge, B.J.; Gu, L.; Fiorillo, J.; Lukacs, N.W.; Kunkel, S.L.; North, R.; Gerard, C.; Rollins, B.J. Abnormalities in monocyte recruitment and cytokine expression in monocyte chemoattractant protein 1-deficient mice. J. Exp. Med. 1998, 187, 601–608. [Google Scholar] [CrossRef]
  41. Ikeda, T.; Sato, K.; Kuwada, N.; Matsumura, T.; Yamashita, T.; Kimura, F.; Hatake, K.; Ikeda, K.; Motoyoshi, K. Interleukin-10 differently regulates monocyte chemoattractant protein-1 gene expression depending on the environment in a human monoblastic cell line, UG3. J. Leukoc. Biol. 2002, 72, 1198–1205. [Google Scholar] [CrossRef] [PubMed]
  42. Trinchieri, G. Interleukin-10 production by effector T cells: Th1 cells show self control. J. Exp. Med. 2007, 204, 239–243. [Google Scholar] [CrossRef]
  43. Mumm, J.B.; Emmerich, J.; Zhang, X.; Chan, I.; Wu, L.; Mauze, S.; Blaisdell, S.; Basham, B.; Dai, J.; Grein, J.; et al. IL-10 elicits IFNγ-dependent tumor immune surveillance. Cancer Cell 2011, 20, 781–796. [Google Scholar] [CrossRef]
  44. Jankovic, D.; Kugler, D.G.; Sher, A. IL-10 production by CD4+ effector T cells: A mechanism for self-regulation. Mucosal Immunol. 2010, 3, 239–246. [Google Scholar] [CrossRef]
  45. Yoshimura, T. The chemokine MCP-1 (CCL2) in the host interaction with cancer: A foe or ally? Cell. Mol. Immunol. 2018, 15, 335–345. [Google Scholar] [CrossRef]
  46. O’Connor, T.; Heikenwalder, M. CCL2 in the Tumor Microenvironment. Adv. Exp. Med. Biol. 2021, 1302, 1–14. [Google Scholar] [CrossRef] [PubMed]
  47. Hassin, D.; Garber, O.G.; Meiraz, A.; Schiffenbauer, Y.S.; Berke, G. Cytotoxic T lymphocyte perforin and Fas ligand working in concert even when Fas ligand lytic action is still not detectable. Immunology 2011, 133, 190–196. [Google Scholar] [CrossRef]
  48. Rauf, A.; Khatri, M.; Murgia, M.V.; Saif, Y.M. Fas/FasL and perforin-granzyme pathways mediated T cell cytotoxic responses in infectious bursal disease virus infected chickens. Results Immunol. 2012, 2, 112–119. [Google Scholar] [CrossRef] [PubMed]
  49. Burgoyne, P.; Hayes, A.J.; Cooper, R.S.; Le Brocq, M.L.; Hansell, C.A.; Campbell, J.D.; Graham, G.J. CCR7(+) dendritic cells sorted by binding of CCL19 show enhanced Ag-presenting capacity and antitumor potency. J. Leukoc. Biol. 2022, 111, 1243–1251. [Google Scholar] [CrossRef]
  50. Randolph, G.J.; Angeli, V.; Swartz, M.A. Dendritic-cell trafficking to lymph nodes through lymphatic vessels. Nat. Rev. Immunol. 2005, 5, 617–628. [Google Scholar] [CrossRef] [PubMed]
  51. Platt, A.M.; Randolph, G.J. Dendritic cell migration through the lymphatic vasculature to lymph nodes. Adv. Immunol. 2013, 120, 51–68. [Google Scholar] [CrossRef] [PubMed]
  52. Westermann, F.; Kube, D.; Haier, B.; Bohlen, H.; Engert, A.; Zuehlsdorf, M.; Diehl, V.; Tesch, H. Interleukin 10 inhibits cytokine production of human AML cells. Ann. Oncol. 1996, 7, 397–404. [Google Scholar] [CrossRef] [PubMed]
  53. Sanchez-Correa, B.; Bergua, J.M.; Campos, C.; Gayoso, I.; Arcos, M.J.; Banas, H.; Morgado, S.; Casado, J.G.; Solana, R.; Tarazona, R. Cytokine profiles in acute myeloid leukemia patients at diagnosis: Survival is inversely correlated with IL-6 and directly correlated with IL-10 levels. Cytokine 2013, 61, 885–891. [Google Scholar] [CrossRef] [PubMed]
  54. Atzler, M.; Baudrexler, T.; Amberger, D.C.; Rogers, N.; Rabe, A.; Schmohl, J.; Wang, R.; Rank, A.; Schutti, O.; Hirschbuhl, K.; et al. In Vivo Induction of Leukemia-Specific Adaptive and Innate Immune Cells by Treatment of AML-Diseased Rats and Therapy-Refractory AML Patients with Blast Modulating Response Modifiers. Int. J. Mol. Sci. 2024, 25, 13469. [Google Scholar] [CrossRef] [PubMed]
  55. Filippini Velazquez, G.; Anand, P.; Abdulmajid, J.; Feng, X.; Weller, J.F.; Hirschbuhl, K.; Schmetzer, H.; Schmid, C. Clinical stabilization of a highly refractory acute myeloid leukaemia under individualized treatment with immune response modifying drugs by in vivo generation of dendritic cells of leukaemic origin (DCleu) and modulation of effector cells and immune escape mechanisms. Biomark. Res. 2025, 13, 104. [Google Scholar] [CrossRef]
Cancers 18 00847 g001
Figure 1. Correlation analyses (pair-wise Pearson correlation) of best achieved blast cytotoxic activity (as measured by Cytotoxicity Assay after T cell-enriched MLC with Kit-pretreated WB) with DC/DCleu and T cell subtypes. Frequencies of DC/DCleu and T cell subtypes in correlation with cases with superior blast lysis (group 1 Kits, samples pretreated with Kit D, Kit E, Kit I or Kit M (pooled data)) shown in (A) or with cases with inferior blast lysis (group 2 Kits (samples pretreated with Kit C, Kit F or Kit K (pooled data))) schown in (B) in AML patients at diagnosis, persistence or relapse (‘All Stages’) and at diagnosis (‘Dgn.’) are given. Pair-wise Pearson correlation was used.
Figure 1. Correlation analyses (pair-wise Pearson correlation) of best achieved blast cytotoxic activity (as measured by Cytotoxicity Assay after T cell-enriched MLC with Kit-pretreated WB) with DC/DCleu and T cell subtypes. Frequencies of DC/DCleu and T cell subtypes in correlation with cases with superior blast lysis (group 1 Kits, samples pretreated with Kit D, Kit E, Kit I or Kit M (pooled data)) shown in (A) or with cases with inferior blast lysis (group 2 Kits (samples pretreated with Kit C, Kit F or Kit K (pooled data))) schown in (B) in AML patients at diagnosis, persistence or relapse (‘All Stages’) and at diagnosis (‘Dgn.’) are given. Pair-wise Pearson correlation was used.
Cancers 18 00847 g001
Cancers 18 00847 g002
Figure 2. DC/DCleu subtypes in AML patients according to their response to induction therapy in corresponding WB samples pretreated with group 1 Kits (Kit D, Kit E, Kit I or Kit M (pooled data, (A)) and with single Kit I (B). The average frequencies of generated DC/DCleu subsets using group 1 Kits (including Kit D, Kit E, Kit I and Kit M) are presented in relation to response or non-response to induction therapy. (A) shows pooled data for all group 1 Kits, while (B) displays data for Kit I alone. Response to induction therapy was defined as <5% blasts in bone marrow and no blasts in peripheral blood 30 days after therapy start.
Figure 2. DC/DCleu subtypes in AML patients according to their response to induction therapy in corresponding WB samples pretreated with group 1 Kits (Kit D, Kit E, Kit I or Kit M (pooled data, (A)) and with single Kit I (B). The average frequencies of generated DC/DCleu subsets using group 1 Kits (including Kit D, Kit E, Kit I and Kit M) are presented in relation to response or non-response to induction therapy. (A) shows pooled data for all group 1 Kits, while (B) displays data for Kit I alone. Response to induction therapy was defined as <5% blasts in bone marrow and no blasts in peripheral blood 30 days after therapy start.
Cancers 18 00847 g002
Cancers 18 00847 g003
Figure 3. Frequencies of DC/DCleu subtypes in patients with long compared to short overall survival (OS). Significantly higher frequencies of DC/DCleu subtypes could be generated in patients with longer overall survival (OS) compared to patients with shorter OS than the median survival of the cohort. Figure 3 shows comparisons of generated DC/DCleu subsets with OS of patients at all stages (first row, A1, A2, A3), only samples studied at first diagnosis (second row, B1, B2, B3) or at relapse after HSCT (last row, C1, C2, C3). Comparable results were seen, including all pooled Kits (first column, A1, B1, C2), only samples cultured with group 1 Kits (second column, A2, B2, C2) or only samples cultured in the presence of Kit I (last column, A3, B3, C3). We present frequencies of DC/DCleu subtypes as mean ± SD in patients with OS longer (compared to shorter) than the median OS of the cohort.
Figure 3. Frequencies of DC/DCleu subtypes in patients with long compared to short overall survival (OS). Significantly higher frequencies of DC/DCleu subtypes could be generated in patients with longer overall survival (OS) compared to patients with shorter OS than the median survival of the cohort. Figure 3 shows comparisons of generated DC/DCleu subsets with OS of patients at all stages (first row, A1, A2, A3), only samples studied at first diagnosis (second row, B1, B2, B3) or at relapse after HSCT (last row, C1, C2, C3). Comparable results were seen, including all pooled Kits (first column, A1, B1, C2), only samples cultured with group 1 Kits (second column, A2, B2, C2) or only samples cultured in the presence of Kit I (last column, A3, B3, C3). We present frequencies of DC/DCleu subtypes as mean ± SD in patients with OS longer (compared to shorter) than the median OS of the cohort.
Cancers 18 00847 g003
Cancers 18 00847 g004aCancers 18 00847 g004b
Figure 4. Predictivity of DC/DCleu subtype frequencies for patients’ overall survival (OS). AML patients in whom higher frequencies of DC+/WB, DCleu/WB and DCleu/DC+ could be generated ex vivo were characterized by a (not significant) higher probability of overall survival. We present pooled data for group 1 Kits (including Kit D, Kit E, Kit I or Kit M) (A1,B1,C1) and for single Kit I (A2,B2,C2).
Figure 4. Predictivity of DC/DCleu subtype frequencies for patients’ overall survival (OS). AML patients in whom higher frequencies of DC+/WB, DCleu/WB and DCleu/DC+ could be generated ex vivo were characterized by a (not significant) higher probability of overall survival. We present pooled data for group 1 Kits (including Kit D, Kit E, Kit I or Kit M) (A1,B1,C1) and for single Kit I (A2,B2,C2).
Cancers 18 00847 g004aCancers 18 00847 g004b
Cancers 18 00847 g005
Figure 5. Predictivity of ex vivo anti-leukemic activity of immunoreactive cells after 3 or 24 h of stimulation with AML-blast-containing WB pretreated with Kits for patients’ overall survival (OS). AML patients in whom lysis was improved vs. untreated control were characterized by a higher probability of overall survival(OS) using pooled data for group 1 Kits (including Kit D, Kit E, Kit I and Kit M) (A1) and for Kit I (A2). AML patients in whom more than 20% of blasts were lysed were characterized by a higher probability of overall survival using group 1 Kits (including Kit D, Kit E, Kit I and Kit M) (B1) and for Kit I (B2).
Figure 5. Predictivity of ex vivo anti-leukemic activity of immunoreactive cells after 3 or 24 h of stimulation with AML-blast-containing WB pretreated with Kits for patients’ overall survival (OS). AML patients in whom lysis was improved vs. untreated control were characterized by a higher probability of overall survival(OS) using pooled data for group 1 Kits (including Kit D, Kit E, Kit I and Kit M) (A1) and for Kit I (A2). AML patients in whom more than 20% of blasts were lysed were characterized by a higher probability of overall survival using group 1 Kits (including Kit D, Kit E, Kit I and Kit M) (B1) and for Kit I (B2).
Cancers 18 00847 g005
Table 1. DC/DCleu-generating protocols and Kits used for the generation of DC/DCleu from leukemic PBMNCs and WB.
Table 1. DC/DCleu-generating protocols and Kits used for the generation of DC/DCleu from leukemic PBMNCs and WB.
Standard DC/DCleu-Generating Protocols Used for the Generation of DC/DCleu from PBMNCs
CompositionMode of ActionCulture Time (d)References
MCM Mimic (MCM)GM-CSF
IL-4
FL
IL-6
IL-1ß
PGE2		Cytokine-driven DC/DCleu
differentiation;
PGE2 increases the frequencies of matured DC/DCleu
(expressing CCR7+)		10–14[29]
Calcium ionophore (Ca)A23187DC/DCleu differentiation
bypassing the standard
DC/DCleu generation;
A23187 induces maturation		3–4[29]
Picibanil
(Pici)		GM-CSF
IL-4
Picibanil (OK-432)
PGE2		Cytokine-driven DC/DCleu
differentiation including ‘danger signaling’: lysis products from
Streptococcus pyogenes and PGE2 stimulate
DC/DCleu differentiation and maturation		9–11[29,32]
Interferon
(INTRON)		GM-CSF
Picibanil (OK-432)
PGE2
TNF-α
IFN-α		Cytokine-driven DC/DCleu differentiation10–12[29]
Kits used for the generation of DC/DCleu from WB
Kit AGM-CSF
TNF-α		 7–10[31]
Kit CGM-CSF
PGE2		 7–10[31]
Kit DGM-CSF
Picibanil (OK-432)
PGE2		 7–10[31]
Kit E GM-CSF
IFN-α		 7–10[31]
Kit FGM-CSF
A23187		 7–10[31]
Kit IGM-CSF
Picibanil (OK-432)		 7–10[31]
Kit KGM-CSF
PGE2		 7–10[30,31]
Kit MGM-CSF
PGE1		 7–10[30,31]
DC, dendritic cells; DCleu, leukemic-derived dendritic cells; PBMNCs, peripheral mononuclear cells; WB, whole blood; GM-CSF, granulocyte-macrophage colony-stimulating factor; IL-4, Interleukin 4; FL, FLT3 ligand; IL-6, Interleukin 6; IL-1ß, Interleukin 1 beta; PGE1/PGE2, prostaglandin E1/E2; TNF-α, tumor necrosis factor alpha; IFN-α, interferon alpha.
Table 2. Patient characteristics.
Table 2. Patient characteristics.
Pat.Age at Dgn./SexFAB
Type		Blast Phenotype (CD)IC-Blasts, %ELN-RiskT Cell SourceResponse to Therapy
Patients at First Diagnosis (n = 32)
40772/mAML M565, 13, 3370IntAutologousNR
43667/fAML M434, 56, 33, 13, 15, 6545IntAutologousNR
51855/mAML M234, 117, 1386IntAutologousR
54639/mAML M234, 117, 65, 1550FavAutologousR
56143/mAML M2117, 65, 1565AdvAutologousR
61865/mMDS RAEB II117, 3335AdvAutologousR
74866/mAML M234, 117, 3332IntAutologousNR
75763/fAML M434, 117, 3346AdvAutologousR
82048/mAML-M234, 117, 33, 1353IntAutologousR
82470/mAML M1/M234, 7, 1368AdvAutologousR
83769/mAML M234, 117, 33, 1339IntAutologousR
89847/fAML M1117, 3387IntAutologousR
94842/fAML M515, 65, 4, 3334AdvAutologousR
114432/mAML M134, 117, 56, 33, 13, 1982FavAutologousR
119472/mn.d.34, 117, 3330AdvAutologousR
119639/fsMDS RAEB117, 338IntAutologousR
120160/fAML-M515, 64, 65, 13, 14, 4, 5641FavAutologousR
122669/mn.d.117, 34, 3365AdvAutologousNR
124548/fAML M515, 56, 65, 3312AdvAutologousR
125182/mAML M4/564, 13, 33, 65, 56, 467n.d.AutologousNR
125558/mAML M434, 56, 117, 3315IntAutologousR
128027/mAML M034, 117, 3388AdvAutologousR
128556/fAML M434, 117, 33, 13, 6540n.d.AutologousR
129244/fAML M234, 117, 33, 1370FavAutologousR
130024/fAML M134, 117, 13, 33, 6564IntAutologousR
130642/mMDS RAEB234, 117, 3311FavAutologousNR
133145/fAML M134, 13, 33, 4, 760IntAutologousR
133576/fn.d.34, 117, 3386IntAutologousNR
134585/mAML M1117, 33, 1396IntAutologousn.d.
135075/mn.d.34, 33, 11717AdvAutologousNR
135370/mAML M234, 117, 33, 1363AdvAutologousNR
135626/mAML/ALL34, 19, 6580AdvAutologousNR
Patients with persisting disease (n = 3)
50241/mAML M4eo34, 117, 65, 33, 13, 1566AdvAutologousR
102439/mAML M234, 117, 3330IntAutologousR
116559/mn.d.34, 117, 33, 1346IntAutologousR
Patients at relapse (n = 19)
45850/fAML M434, 38, 117, 33, 14, 6438 AutologousR
48166/fAML M4–M534, 117, 33, 13, 15, 56, 1993 AutologousR
54544/fAML M1117, 34, 3387 AutologousNR
58451/fAML M1117, 13, 3391 AutologousR
65266/mAML M134, 33, 1388 AutologousNR
65565/fAML M234, 117, 3320 AutologousR
91469/mAML M434, 33, 13, 15, 64, 1443 AutologousNR
98463/mAML M234, 117, 13, 3342 AutologousNR
99867/mAML M5117, 34, 64, 491 AutologousR
101157/fAML M1117, 34, 33, 461 AutologousR
101769/mAML M434, 117, 3344 AutologousR
120673/fAML M2117, 33, 15, 6442 AutologousNR
123146/fAML M1117, 56, 3355 AutologousR
124335/mAML M234, 117, 33, 13, 233 AutologousR
130364/fAML M456, 33, 14, 65, 479 AutologousR
133073/fAML M434, 3392 AutologousNR
137653/fAML M234, 117, 3361 AutologousNR
138658/mn.d.34, 117, 65, 33, 1380 AutologousNR
138840/fAML M334/117, 33, 1347 AutologousNR
Patients atrelapse after HSCT (n = 25)
41968/fAML M134, 117, 33, 1594 After HSCTR
42859/fAML M434, 117, 3335 After HSCTNR
45359/fAML M134, 117, 33, 1381 After HSCTNR
46036/mAML M056, 13, 33, 65, 15, 760 After HSCTNR
46661/fAML M634, 117, 65, 33, 1352 After HSCTNR
47825/fAML M034, 117, 56, 33, 1333 After HSCTR
48333/mAML M134, 117, 65, 33, 1588 After HSCTNR
53812/mAML M034, 65, 3390 After HSCTNR
56568/fAML M534, 65, 33, 13, 1529 After HSCTNR
6105/fAML M134, 117, 4, 3380 After HSCTNR
76339/fAML M034, 117, 65, 3352 After HSCTR
76758/fAML M134, 117, 65, 33, 1395 After HSCTNR
81840/fAML M034, 117, 65, 3391 After HSCTNR
85334/mAML M034, 117, 33, 7189 After HSCTNR
88027/mAML M434, 117, 33, 1595 After HSCTR
93859/fAML M434, 117, 33, 1534 After HSCTNR
98040/fAML M034, 33, 1382 After HSCTR
100160/fAML M434, 117, 3335 After HSCTNR
114360/fn.d.117, 34, 3, 1924 After HSCTNR
122241/mAML M133, 34, 117, 5660 After HSCTNR
128627/mAML M534, 117, 3323 After HSCTNR
130754/mn.d.34, 33, 13, 65, 15, 1948 After HSCTNR
136927/mAML M034, 117, 3370 After HSCTNR
137547/fAML M534, 15, 33, 11770 After HSCTNR
138773/mAML M4117, 33, 1385 After HSCTn.d.
AML, acute myeloid leukemia; MDS, myelodysplastic syndrome; CD, Cluster of differentiation; ELN-Risk, European LeukemiaNet Classification 2022; f, female; m, male; FAB, French–American–British classification; IC-Blasts, immune cytologically detected blasts; n.d., no data; NR, no response to induction therapy; R, response to induction therapy; HSCT, relapse after hematopoietic stem cell transplantation.
Table 3. Evaluation of cellular composition and cell subtypes by flow cytometry.
Table 3. Evaluation of cellular composition and cell subtypes by flow cytometry.
Subtypes of DC/DCleu
Name of SubgroupReferred toSurface MarkerAbbreviationReference
Leukemic blastsWB/PBMNCBla+
(CD34, CD117, CD65, CD15)		Bla+/WB
Bla+/PBMNC		[29]
Dendritic cellsWB/PBMNCDC+
(CD1b, CD40, CD80, CD83, CD86, CD206)		DC+/WB
DC+/PBMNC		[29]
Leukemia-derived DCWB/PBMNCDC+Bla+DCleu/WB
DCleu/PBMNC		[29]
DCleu in DC fractionDC+DC+Bla+DCleu/DC+[29]
DCleu in leukemic blast fraction (converted DCleu)Bla+DC+Bla+DCleu/Bla+[29]
Mature DCDC+DC+CD197+DCmat/DC+[29]
Viable DC after cultusDC+7AAD−DC+DCvia/DC+[29]
Proliferating leukemic blastsBla+Bla+DC−CD71+Blaprol-CD71/Bla[33]
Proliferating leukemic blastsBla+Bla+DC−ipo38+Blaprol-ipo38/Bla[33]
Subtypes of immune reactive cells for MLC
CD3+ pan-T cellsWBCD3+T cells[34]
CD4+ T cellsCD3+CD4+CD3+CD4+ T cells[34]
CD8+ TellsCD3+CD8+CD3+CD8+ T cells[34]
Early proliferating T cellsCD3+CD69+CD3+Tprol-early[34]
Late proliferating T cellsCD3+CD71+CD3+Tprol-late[34]
PBMNCs, peripheral blood mononuclear cells; WB, whole blood; CD, cluster of differentiation; DC, dendritic cells; DCleu, dendritic cells of leukemic origin; Bla, leukemic blasts; MLC, mixed lymphocyte culture.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Amberger, D.C.; Fischer, Z.; Deen, D.; Hirn-Lopez, A.; Plett, C.; Rabe, A.; Schwepcke, C.; Ugur, S.; Klauer, L.K.; Ansprenger, C.; et al. Modulation of Leukemic Blasts into Dendritic Cells (DCleu) and Their Role in Predicting Survival in Patients with AML and MDS. Cancers 2026, 18, 847. https://doi.org/10.3390/cancers18050847

AMA Style

Amberger DC, Fischer Z, Deen D, Hirn-Lopez A, Plett C, Rabe A, Schwepcke C, Ugur S, Klauer LK, Ansprenger C, et al. Modulation of Leukemic Blasts into Dendritic Cells (DCleu) and Their Role in Predicting Survival in Patients with AML and MDS. Cancers. 2026; 18(5):847. https://doi.org/10.3390/cancers18050847

Chicago/Turabian Style

Amberger, Daniel Christoph, Zuzana Fischer, Diana Deen, Anika Hirn-Lopez, Caroline Plett, Alexander Rabe, Christoph Schwepcke, Selda Ugur, Lara Kristina Klauer, Christian Ansprenger, and et al. 2026. "Modulation of Leukemic Blasts into Dendritic Cells (DCleu) and Their Role in Predicting Survival in Patients with AML and MDS" Cancers 18, no. 5: 847. https://doi.org/10.3390/cancers18050847

APA Style

Amberger, D. C., Fischer, Z., Deen, D., Hirn-Lopez, A., Plett, C., Rabe, A., Schwepcke, C., Ugur, S., Klauer, L. K., Ansprenger, C., Liepert, A., Freudenreich, M., Schmid, C., & Schmetzer, H. M. (2026). Modulation of Leukemic Blasts into Dendritic Cells (DCleu) and Their Role in Predicting Survival in Patients with AML and MDS. Cancers, 18(5), 847. https://doi.org/10.3390/cancers18050847

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop