Divergent Therapeutic and Immunologic Effects of Oligodeoxynucleotides with Distinct CpG Motifs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Immune stimulatory oligodeoxynucleotides (ODN) with unmethylated CpG motifs are potent inducers of both innate and adaptive immunity. It initially appeared that a single type of optimal CpG motif would work in all applications. We now report that specific motifs of CpG ODN can vary dramatically in their ability to induce individual immune effects and that these differences impact on their antitumor activity in different tumor models. In particular, a distinct type of CpG motif, which has a chimeric backbone in combination with poly(G) tails, is a potent inducer of NK lytic activity but has little effect on cytokine secretion or B cell proliferation. One such NK-optimized CpG ODN (1585) can induce regression of established melanomas in mice. Surprisingly, no such therapeutic effects were seen with CpG ODN optimized for activation of B cells and Th1-like cytokine expression (ODN 1826). The therapeutic effects of CpG 1585 in melanoma required the presence of NK but not T or B cells and were not associated with the induction of a tumor-specific memory response. In contrast, CpG 1826, but not CpG 1585, was effective at inducing regression of the EL4 murine lymphoma; this rejection was associated with the induction of a memory response and although NK cells were necessary, they were not sufficient. These results demonstrate that selection of optimal CpG ODN for cancer immunotherapy depends upon a careful analysis of the cellular specificities of various CpG motifs and an understanding of the cellular mechanisms responsible for the antitumor activity in a particular tumor.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it