Synergistic antitumor effects of CpG oligodeoxynucleotide and STAT3 inhibitory agent JSI‐124 in a mouse melanoma tumor model
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Bibliographic record
Abstract
One of the major limitations for cancer immunotherapy is related to the frequent existence of an intra-tumoral immunosuppressive environment, to which STAT3 (Signal transducer and activator of transcription-3) activation in tumor and dendritic cells (DCs) are believed to contribute. In this study, we tested the hypothesis that the combination of CpG (a DC activator) and JSI-124 (a STAT3 inhibitor) may generate synergistic antitumor effects compared to CpG or JSI-124 alone. B16-F10, a mouse melanoma cell line that has constitutively active STAT3, was grafted in C57BL/6 mice and then tumor-bearing mice treated intra-tumorally with (a) phosphate buffered saline, (b) 10 microg CpG, (c) 1 mg kg(-1) JSI-124 or (d) 10 microg CpG+1 mg kg(-1) JSI-124. The effects of treatments on tumor growth, survival and antitumor immune responses were evaluated. Although significant antitumor effects were detected with the single-agent treatments, the CpG+JSI-124 treatment resulted in synergistic antitumor effects compared to CpG or JSI-124 alone. Correlating with these findings, the combination therapy resulted in significantly higher intra-tumoral levels of several proinflammatory, TH1-related cytokines (including IL-12, IFN-gamma, TNF-alpha and IL-2), increases in intra-tumoral CD8+ and CD4+ T cells expressing activation/memory markers and NK cells and increases in activated DCs in the tumors and regional lymph nodes (LNs). Concomitantly, the combination therapy led to a significantly decreased level of immunosuppression, as evidenced by lower intra-tumoral level of VEGF and TGF-beta, and decreased number of CD4+CD25+Foxp3+ regulatory T cells in the regional LNs. This study has provided the proof-of-principle for combining CpG and JSI-124 to enhance antitumor immune responses.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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