Tumor Cholesterol Synthesis, Statin Use, and Lethal Prostate Cancer
Bibliographic record
Abstract
Prostate tumor cells produce cholesterol de novo, and statin therapy targets the initial rate-limiting enzyme in this process, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR). The extent to which the expression of HMGCR in prostate tumors could influence progression and predict the potential antineoplastic effects of statins remains unclear. In a prospective cohort study of 1,098 men diagnosed with primary prostate cancer from 1982 to 2009 in the Health Professionals Follow-up Study and Physicians' Health Study, 16% of prostate tumors showed strong HMGCR staining intensity, and 31% showed no staining. HMGCR expression was higher in tumors with PTEN loss but did not differ by statin use or long-term dietary cholesterol or saturated fat intake. Participants were followed for lethal events (distant metastases or prostate cancer-related death) over up to 32 years, and 96 lethal events occurred in those without metastases at diagnosis. Strong HMGCR expression was associated with higher rates of lethal prostate cancer (HR, 2.2; 95% confidence interval, 1.3-3.7), adjusting for age at diagnosis and Gleason score but without a linear dose response. In vitro, in the LNCaP human prostate cancer cell line, atorvastatin affected tumor cell viability in cells with experimentally lowered HMGCR expression. This study corroborates that high cholesterol synthesis in prostate tumor cells is associated with PTEN loss, aggressive tumor characteristics, and a greater risk of lethality. IMPLICATIONS: High expression of HMGCR, the first rate-limiting enzyme of cholesterol synthesis, is a feature of prostate tumors that are more likely to progress to metastatic disease or death from 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 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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".