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Record W4389243632 · doi:10.1182/blood-2023-189892

Toll-like Receptor-9 Agonist Reverses T Cell Exhaustion in a Murine Model of Pediatric B-ALL

2023· article· en· W4389243632 on OpenAlexaff
Tanmaya Atre, Gregor S. D. Reid

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsCD8ImmunologyB cellChimeric antigen receptorT cellLeukemiaImmune systemMedicineAntigenCancer researchBiologyAntibody

Abstract

fetched live from OpenAlex

Despite significant treatment advances, the poor long-term prognosis for children with relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL) persists. The application of immune cell-based therapies, such as chimeric antigen receptor-expressing T cells and bispecific T-cell engagers, has improved progression-free survival for many B-ALL patients. However, the majority of these patients still experience disease relapse. An improved understanding of the mechanisms that impair T cell function in B-ALL patients could inform strategies to further improve outcomes. Recent studies have revealed T cell exhaustion, especially as indicated by PD-1 and Tim- 3 expression, to be predictive of disease relapse and overall survival in B-ALL. However, the precise contribution of T cell dysfunction to B-ALL development remains unclear. In this study, we explore the biology that leads to impaired T cell function and investigate potential approaches to restore it using both transgene-driven and syngeneic leukemia cell transplant models of B-ALL. First, we used the Emu-Ret transgenic mouse model of hyperdiploid B-ALL to investigate the induction of exhaustion-associated marker expression (PD-1, CTLA-4 and Tim-3) on CD4 and CD8 T cells. Longitudinal analysis of marker expression in various settings revealed that an upregulation of PD-1 and Tim-3, but not CTLA-4, on T cells occurred only in the presence of leukemia cells, not during the extended, nascent preleukemia phase. This suggests that T cell exhaustion occurs exclusively during the established malignancy phase, highlighting the dynamic nature of T cell responses as disease progresses. Next, B-ALL cells from moribund Emu-Ret mice were transplanted into 4-6-week-old wild type BALB/c mice and markers of T cell exhaustion were measured as disease progressed. Expression of PD-1 and Tim-3 on T cells correlated with disease progression. Notably, a significant increase in these markers was already detectable at low leukemia burden. These results indicate that T cell exhaustion is not simply a reflection of high disease burden and confirm the differing abilities of preleukemic and leukemic cells to affect T cell phenotype. Previously, we have demonstrated the ability of toll-like receptor (TLR) ligands to induce immune control over B-ALL cells. Thus, we investigated the impact of CpG oligodeoxynucleotides (CpG ODN), a ligand for TLR-9, on B-ALL depletion and T cell dysfunction. The treatment of leukemia bearing mice with CpG ODN led to a decrease in PD-1 and Tim-3 expression on T cells, which was also associated with a reduction in leukemia burden. We are currently investigating the functional implications of these expression changes using in vitro assays of T cell proliferation, cytokine production, and cytotoxicity. Additionally, we are also assessing if anti-tumour control by T cells can be revived in vivo, by comparing B-ALL progression and mouse survival after administration of antibodies against exhaustion markers, with or without CpG ODNs as adjuvant therapy. Overall, this study reveals that the functional impact of interactions between B-ALL cells and the immune system evolves during leukemia development. These insights could inform therapeutic strategies to overcome B-ALL immune evasion mechanisms and enhance patient outcomes.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.032
GPT teacher head0.285
Teacher spread0.252 · 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
Published2023
Admission routes1
Has abstractyes

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