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Stimulation of Precursor-B Acute Lymphoblastic Leukemia Cells with Toll-Like Receptor Ligands Alters Their Immunogenicity.

2004· article· en· W2557385370 on OpenAlexaff
Gregor S. D. Reid, Kristin Wynne, Kevin She, Darko Curman, Kristy Garbutt, Heather Wildgrove, Joan Mathers

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsImmune systemTLR2ImmunologyImmunogenicityToll-like receptorAntigenTLR3BiologyB cellT cellTLR9Cancer researchTLR4Innate immune systemAntibodyDNA methylation

Abstract

fetched live from OpenAlex

Abstract Pediatric pre-B acute lymphoblastic leukemia is the most common childhood cancer. Although current therapies achieve a high rate of remission, relapse of pre-B ALL remains a significant clinical challenge and new forms of therapy are needed. The graft-vs-leukemia (GVL) effect after bone marrow transplantation has shown that the immune system is capable of producing an effective anti-tumor response, which suggests that immune-mediated therapies may provide a complementary treatment strategy. Toll-like receptors (TLR), found on many immune cells, including B cells, have been shown to be important molecules in both innate and adaptive immune responses. Ligation of TLRs with their respective ligands results in an increase in the immunogenicity of antigen presenting cells (APC), through upregulation of MHC antigens and costimulatory molecules and production of cytokines and chemokines. We have previously reported that stimulation of pre-B ALL cells with the TLR9 ligand, CpG DNA, enhances the induction of Th1 immune responses by allogeneic T cells. In this study we examined the expression profile of TLRs 1-8 in precursor-B ALL cells and the effects of TLR ligation on the immune stimulatory capacity of precursor-B ALL cell lines. Eight precursor-B ALL cell lines were used in this study (Nalm6, REH, Sup-B15, KOPN-57bi, 380, 697, OP-1 and RS4:11). Standard RT-PCR analysis was used to examine the expression of TLRs 1-8 by the cell lines. The cell lines were stimulated with ligands for TLR2 (peptidoglycan), TLR3 (poly I:C) and TLR4 (LPS) and evaluated for changes in costimulatory molecule expression and allogeneic T cell stimulation. Non-quantatative PCR detected each TLR, with the exception of TLR8, in the majority of the cell lines. TLR8 was only detected, at low level, in RS4:11 cells. Despite the broad expression profile of the TLRs, significant differences in the effect of TLR ligation were observed between cell lines. In general, only modest increases in CD40 and CD86 expression were observed on responsive cell lines, with the majority of the lines showing no significant changes in response to TLR2, 3 or 4 ligation, despite receptor detection by PCR. Changes in allogeneic T cell proliferation in response to TLR stimulated ALL cell lines were observed, with the largest increases occurring with peptidoglycan and LPS. As was the case with costimulatory molecule expression, no T cell proliferative response change was common to all cell lines. However, analysis of cytokine production by T cells revealed a consistent increase in IFN-gamma and reduction in IL-5 levels in response to peptidoglycan stimulated ALL cells. The results reported in this study indicate that precursor-B ALL cell lines express several TLR molecules and that TLR ligation alters the immunogenicity of the majority of these lines. Interestingly, ligation of TLR2 with peptidoglycan induced a profound shift towards Th1 cytokine production. These observatios suggest that TLR ligation, most notably TLR2 ligation, may provide a strategy to influence anti-ALL immune responses and enhance immune mediated control of this disease.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.194
Teacher spread0.189 · 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
Published2004
Admission routes1
Has abstractyes

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