Cannabinoids, Medical Cannabis, and Colorectal Cancer Immunotherapy
Bibliographic record
Abstract
Colorectal cancer is a major public health problem. Unfortunately, currently, no effective curative option exists for this type of malignancy. The most promising cancer treatment nowadays is immunotherapy which is also called biological or targeted therapy. This type of therapy boosts the patient's immune system ability to fight the malignant tumor. However, cancer cells may become resistant to immunotherapy and escape immune surveillance by obtaining genetic alterations. Therefore, new treatment strategies are required. In the recent decade, several reports suggest the effectiveness of cannabinoids and Cannabis sativa extracts for inhibiting cancer proliferation in vitro and in vivo , including intestinal malignancies. Cannabinoids were shown to modulate the pathways involved in cell proliferation, angiogenesis, programmed cell death and metastasis. Because of that, they are proposed as adjunct therapy for many malignancies. By far less information exists on the potential of the use of cannabis in combination with immunotherapy. Here, we explore the possibility of the use of cannabinoids for modulation of immunotherapy of colon cancer and discuss possible advantages and limitations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".