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Record W4417018263 · doi:10.1182/blood-2025-5138

Tumor-induced dendritic cell dysfunction impairs T-cell proliferation and confers poor prognosis in high-risk acute lymphoblastic leukemia

2025· article· en· W4417018263 on OpenAlexaff
Anil Kumar, Kory Hamane, Caroline Duault, João Rodrigues Lima-Júnior, Da Jin Sol Jung, Hanjun Qin, Sheyla Salcido, Min Huang, Xinying Guo, Adeleh Taghi Khani, Ashly Sanchez Ortiz, Lucy Ghoda, Guido Marcucci, Norman J. Lacayo, Kathleen M. Sakamoto, Christian Hurtz, Martin Carroll, Sarah K. Tasian, Huimin Geng, Lingyun Ji, Saro H. Armenian, Shai Izraeli, Holden T. Maecker, Xiwei Wu, Srividya Swaminathan

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsDendritic cellFlow cytometryBone marrowImmune systemMyeloidPeripheral blood mononuclear cellPopulationT cell

Abstract

fetched live from OpenAlex

Abstract Background: Dendritic cells (DCs) are key regulators of long-term anti-leukemia immunity. The functional status of DCs and mechanisms by which they are perturbed in B/T- cell acute lymphoblastic leukemia (ALL) are unknown. We delineated the defects in DC homeostasis in patients with high-risk ALL and assessed the cause and prognostic significance of these defects. Approach: Using high-dimensional flow cytometry and single cell RNA-sequencing (scRNA-seq) respectively, we profiled proteins and mRNA in single myeloid cells including DC subsets in mononuclear cell samples from peripheral blood (PBMC) and bone marrow (BMMC) of 33 high-risk ALL patients and 35 tissue-matched healthy donor (HD) controls. We used co-cultures of DCs with immune effector cells (T or NK) and primary mouse models of B- and T-ALL to determine the cause and consequence of DC dysfunction in ALL. We correlated DC dysfunction with clinical outcome. Results: Monocytes and DCs exhibit functional similarities and phenotypic plasticity. In the non-malignant immune cell fraction, we found significant reduction in CD14+ total monocytes in PBMC and BMMC of ALL patients compared to HD controls. Classical monocytes (CD14HighCD16-) were significantly reduced at the expense of other monocytes subsets (p<0.0001). Frequencies of CD14+CD209+ monocyte-derived DCs, which can impair T-cell surveillance, were aberrantly increased in ALL patients (p<0.001). In non-monocytic, non-B, non-T, HLA-DR+ fraction of ALL patients, CD123LowCD11c- population aberrantly emerged at the expense of CD11c+ conventional DCs (cDC) and CD123HighCD11c- plasmacytoid DCs (pDCs) (p<0.001 PB, p<0.001 BM for all DC subsets). High-dimensional flow cytometry and scRNA-seq found CD141HighCD1c- (cDC1) and CD141Low/-CD1c+ (cDC2-3) to be reduced at the expense of CD141Low/-CD1c- (cDC4-5) in ALL patient PBMC and BMMC compared to healthy counterparts. We identified DC progenitors (DCP), cDC1-5, and pDCs (DC6) in healthy PBMCs, but this distinction was lost in ALL. cDC1-3 showed greatest disruption, with subtype-specific markers being expressed aberrantly in ALL. Computational lineage tracing showed that ALL DCs do not follow the healthy differentiation trajectory; this could be potentially due to below threshold expression levels of transcription factors IRF8 and IRF4, which are essential for the terminal differentiation of DC subsets. Consistent with this, cytokines (e.g., GM-CSF) and receptors (e.g., CD116 and CD117) required for DC maturation and differentiation were significantly reduced in ALL microenvironments compared to healthy controls. Thus, functional specialization of DC subsets is impaired in ALL. Antigen-primed DCs derived from ALL patients, when co-cultured with healthy donor-derived pan-T cells, were unable to induce T-cell proliferation, unlike their healthy donor-derived DC counterpart. Thus, perturbed DC homeostasis in ALL impairs the ability of DCs to induce T-cell mediated immunity. Increased HLA-DR and CD11c mark mature DCs with T-cell priming potential. Consistent with the inability of DCs in ALL patients to induce T-cell proliferation, we found a reduction in CD11cHighHLA-DRHigh and a concomitant increase in CD11cLowHLA-DRLow/-DC fraction in patients with ALL and in two transgenic mouse models that develop high-risk disease. MYC overexpression in leukemia cells drove the reduction in frequencies of CD11cHighHLA-DRHigh DCs. ALL patients with lower than median frequencies of CD11cHighHLA-DRHighDCs had poor overall survival. Finally, using transcriptomic profiles of less mature/dysfunctional and mature/functional DCs, we used CIBERSORT to estimate the relative fractions of dysfunctional and functional DCs in patients with B-ALL enrolled in the Children’s Oncology Group (COG) P9906 trial. Higher proportion of dysfunctional DCs at diagnosis predicted poor clinical outcomes in children with ALL independent of known indicators of poor prognosis including central nervous system involvement of leukemia cells and high white blood cell count at diagnosis (P<0.05). Conclusion: Oncogenic signaling from leukemic cells impairs DC differentiation and function in ALL. The subsequent loss in DC-mediated T-cell priming disrupts anti-leukemic immune surveillance. Level of DC dysfunction in patients with ALL is a reliable predictor of patient prognosis and could inform treatment strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.202
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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