Recent advances in cancer immunotherapy: Modulation of tumor microenvironment by Toll-like receptor ligands
Bibliographic record
Abstract
Immunotherapy is considered a promising approach for cancer treatment. An important strategy for cancer immunotherapy is the use of cancer vaccines, which have been widely used for cancer treatment. Despite the great potential of cancer vaccines for cancer treatment, their therapeutic effects in clinical settings have been limited. The main reason behind the lack of significant therapeutic outcomes for cancer vaccines is believed to be the immunosuppressive tumor microenvironment (TME). The TME counteracts the therapeutic effects of immunotherapy and provides a favorable environment for tumor growth and progression. Therefore, overcoming the immunosuppressive TME can potentially augment the therapeutic effects of cancer immunotherapy in general and therapeutic cancer vaccines in particular. Among the strategies developed for overcoming immunosuppression in TME, the use of toll-like receptor (TLR) agonists has been suggested as a promising approach to reverse immunosuppression. In this paper, we will review the application of the four most widely studied TLR agonists including agonists of TLR3, 4, 7, and 9 in cancer immunotherapy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".