Metformin targets c-MYC oncogene to prevent prostate cancer
Bibliographic record
Abstract
UNLABELLED: Prostate cancer (PCa) is the second leading cause of cancer-related death in American men and many PCa patients develop skeletal metastasis. Current treatment modalities for metastatic PCa are mostly palliative with poor prognosis. Epidemiological studies indicated that patients receiving the diabetic drug metformin have lower PCa risk and better prognosis, suggesting that metformin may have antineoplastic effects. The mechanism by which metformin acts as chemopreventive agent to impede PCa initiation and progression is unknown. The amplification of c-MYC oncogene plays a key role in early prostate epithelia cell transformation and PCa growth. The purpose of this study is to investigate the effect of metformin on c-myc expression and PCa progression. Our results demonstrated that (i) in Hi-Myc mice that display murine prostate neoplasia and highly resemble the progression of human prostate tumors, metformin attenuated the development of prostate intraepithelial neoplasia (PIN, the precancerous lesion of prostate) and PCa lesions. (ii) Metformin reduced c-myc protein levels in vivo and in vitro. In Myc-CaP mouse PCa cells, metformin decreased c-myc protein levels by at least 50%. (iii) Metformin selectively inhibited the growth of PCa cells by stimulating cell cycle arrest and apoptosis without affecting the growth of normal prostatic epithelial cells (RWPE-1). (iv) Reduced PIN formation by metformin was associated with reduced levels of androgen receptor and proliferation marker Ki-67 in Hi-Myc mouse prostate glands. Our novel findings suggest that by downregulating c-myc, metformin can act as a chemopreventive agent to restrict prostatic neoplasia initiation and transformation. SUMMARY: Metformin, an old antidiabetes drug, may inhibit prostate intraepithelial neoplasia transforming to cancer lesion via reducing c-MYC, an 'old' overexpressed oncogene. This study explores chemopreventive efficacy of metformin in prostate cancer and its link to cMYC in vitro and in vivo.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".