<i>In Vitro</i> Anticancer Activity of Plant-Derived Cannabidiol on Prostate Cancer Cell Lines
Bibliographic record
Abstract
Cannabinoids, the active components of Cannabis sativa Linnaeus, have received renewed interest in recent years due to their diverse pharmacologic activities such as cell growth inhibition, anti-inflammatory effects and tumor regression, but their use in chemotherapy is limited by their psychotropic activity. To date, cannabinoids have been successfully used in the treatment of nausea and vomiting, two common side effects that accompany chemotherapy in cancer patients. Most non-THC plant cannabinoids e.g. cannabidiol and cannabigerol, seem to be devoid of psychotropic properties. However, the precise pathways through which these molecules produce an antitumor effect have not yet been fully characterized. We therefore investigated the antitumor and anti-inflammatory activities of cannabidiol (CBD) in human prostate cancer cell lines LNCaP, DU145, PC3, and assessed whether there is any advantage in using cannabis extracts enriched in cannabidiol and low in THC. Results obtained in a panel of prostate cancer cell lines clearly indicate that cannabidiol is a potent inhibitor of cancer cell growth, with significantly lower potency in non-cancer cells. The mRNA expression level of cannabinoid receptors CB1 and CB2, vascular endothelial growth factor (VEGF), PSA (prostate specific antigen) are significantly higher in human prostate cell lines. Treatment with Cannabis extract containing high CBD down regulates CB1, CB2, VEGF, PSA, pro-inflammatory cytokines/chemokine IL-6/IL-8. Our overall findings support the concept that cannabidiol, which lacks psychotropic activity, may possess anti-inflammatory property and down regulates both cannabinoid receptors, PSA, VEGF, IL-6 and IL-8. High CBD cannabis extracts are cytotoxic to androgen responsive LNCaP cells and may effectively inhibit spheroid formation in cancer stem cells. This activity may contribute to its anticancer and chemosensitizing effect against prostate cancer. Cannabidiol and other non-habit forming cannabinoids could be used as novel therapeutic agents for the treatment of prostate cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".