Comparative analysis of murine marrow–derived dendritic cells generated by Flt3L or GM-CSF/IL-4 and matured with immune stimulatory agents on the in vivo induction of antileukemia responses
Bibliographic record
Abstract
Bone marrow (BM)-derived dendritic cells (DCs) cultured in granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin 4 (IL-4) have been used to generate antitumor immune responses. The cytokine Flt3 ligand (Flt3L) also has been shown to generate BM DCs. We sought to determine if DCs generated by using Flt3L then matured with lipopolysaccharide (LPS) could lead to DCs with in vivo anti-acute myelogenous leukemia (anti-AML) activity. LPS and tumor necrosis factor alpha (TNF-alpha) are effective agents for maturing DCs; however, they have potential in vivo toxicities. Cytosine-phosphorothioate-guanine oligodeoxynucleotides (CpGs) are considered relatively nontoxic, potent activators of DC function and maturation in vitro and in vivo. We investigated whether CpGs would be comparable to TNF-alpha or LPS for the maturation of GM-CSF/IL-4-generated DCs. DCs cultured with GM-CSF/IL-4 and matured with TNF-alpha, LPS, or CpG produced a greater allogeneic T-cell response compared with Flt3L/LPS-generated DCs. All 4 distinct DC types were pulsed with AML-lysate and administered before tumor challenge produced an increase in the total number of splenic anti-AML-specific cytotoxic T-lymphocyte precursors and led to significantly (P < or =.0001) improved survival compared with nonvaccinated controls. GM-CSF/IL-4/LPS was superior to Flt3L/LPS for generating anti-AML effects in vivo. Whereas TNF-alpha was comparable to LPS in conferring on GM-CSF/IL-4 DCs anti-AML effects in vivo, CpGs were superior to LPS. These data have important clinical implications and are the first to show that Flt3L-generated DCs can provide antitumor protection and that nontoxic agents such as CpGs and Flt3L may be useful in the clinical development of DC vaccines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".