Unveiling the Therapeutic Potential of Isoliquiritigenin in Prostate Cancer: Insights from a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Prostate cancer is a significant and primary cause of cancer-related mortality among men worldwide with treatment challenges that include resistance to conventional therapies. Isoliquiritigenin (ISL) is a natural compound with anticancer properties which have emerged as a potential alternative. Purpose: This review explores the role of ISL in prostate cancer treatment by analyzing preclinical and clinical studies. Methodology: The relevant studies investigating the anticancer effect of ISL were identified using a systematic literature review across PubMed, Scopus, Web of Science, and Google Scholar. Depending on the inclusion and exclusion criteria, the studies were screened and data was extracted regarding tumor growth inhibition, sample size, molecular pathways, etc. Quality assessment was performed with the Newcastle-Ottawa Scale (NOS), and the pooled data was analyzed using I² statistics to examine the potential of ISL as a treatment for prostate cancer. Results: A sum of 8 studies were included which met the criteria for meta-analysis. It demonstrated the anti-proliferative effects that induce apoptosis via depolarization in the mitochondrial membrane and the activation of caspase-3. The cell cycle halts at the G1 and G2/M phases by influencing p21 and p27. It also serves as a possible chemosensitizing agent. Conclusion: ISL shows anticancer properties through various mechanisms. It is recommended that ISL be used in combination therapies to address drug resistance. Further in vivo and clinical studies are needed to evaluate and assess the drug profile of ISL in human models. Keywords: Isoliquiritigenin, Prostate cancer, Apoptosis, Cell cycle arrest
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".