Human prostate cancer xenografts in <i>lit/lit</i> mice exhibit reduced growth and androgen‐independent progression
Bibliographic record
Abstract
BACKGROUND: The growth hormone/insulin-like growth factor I (GH/IGF-I) axis has been linked to prostate cancer (PCa) risk. Although previous studies indicate that human breast cancers and a murine PCa model develop more slowly in murine hosts homozygous for a missense mutation in the GH-releasing hormone receptor (lit/lit) whose "little" dwarfed phenotype is caused by suppressed GH and IGF-I production, the role of these two hormones remains controversial. METHODS: To assess how the GH/IGF-I axis influences androgen-responsive, castration-resistant (CR), and androgen-independent (AI) growth of human PCa, we compared xenograft growth of the androgen-responsive human PCa cells, LNCaP, and AI human PCa cells, PC3, in intact and castrate Nod/SCID lit/lit and lit/+ mice, and in vitro growth of these cell lines in lit/lit and lit/+ serum-containing media supplemented with GH or IGF-I. RESULTS: Tumor growth and PSA accumulation rates were suppressed in LNCaP tumor-bearing lit/lit mice pre- and post-castration. Growth of PC3 xenografts in lit/lit mice was also suppressed. In vitro proliferation of LNCaP and PC3 cells cultured in media containing lit/lit mouse serum was decreased as compared to growth in media containing lit/+ serum. Suppressed growth in lit/lit serum could be restored by the addition of IGF-I, and to a lesser extent, GH. Differences in growth correlated with differences in steady-state AKT and ERK1/2 activation. CONCLUSIONS: This study demonstrates that circulating GH and IGF-I can promote androgen-responsive growth, CR progression, and AI expansion of PTEN-deficient human PCa cell xenografts and indicates that IGF-I can promote PCa growth in a suppressed GH environment.
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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 | 0.000 |
| 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) | 0.000 | 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".