Insulin-Like Growth Factor (IGF) Binding Protein-3 Attenuates Prostate Tumor Growth by IGF-Dependent and IGF-Independent Mechanisms
Bibliographic record
Abstract
IGF binding protein (IGFBP)-3 inhibits cell growth and promotes apoptosis by sequestering free IGFs. In addition IGFBP-3 has IGF-independent, proapoptotic, antiproliferative effects on prostate cancer cells in vitro. Expression of the large T-antigen (Tag) under the long probasin promoter (LPB) in LPB-Tag mice results in prostate tumorigenesis. To investigate the IGF-dependent and IGF-independent effects of IGFBP-3 on prostate tumor growth, we crossed LPB-Tag mice with cytomegalovirus (CMVBP-3) and phosphoglycerate kinase (PGKBP-3) mice that overexpress IGFBP-3 under the cytomegalovirus promoter and the phosphoglycerate kinase promoter, respectively, and also I56G/L80G/L81G-mutant IGFBP-3 (PGKmBP-3) mice that express I56G/L80G/L81G-IGFBP-3, a mutant, that does not bind IGF-I but retains IGF-independent proapoptotic effects in vitro. Prostate tumor size and the steady-state level of p53 were attenuated in LPB-Tag/CMVBP-3 and LPB-Tag/PGKBP-3 mice, compared with LPB-Tag/wild-type (Wt) mice. A more marked effect was observed in LPB-Tag/CMVBP-3, compared with LPB-Tag/PGKBP-3, reflecting increased levels of transgene expression in CMVBP-3 prostate tissue. No attenuation of tumor growth was observed in LPB-Tag/PGKmBP-3 mice during the early tumor development, indicating that the inhibitory effects of IGFBP-3 were most likely IGF dependent during the initiation of tumorigenesis. At 15 wk of age, epidermal growth factor receptor expression was increased in LPB-Tag/Wt and LPB-Tag/PGKmBP-3 tissue, compared with LPB-Tag/PGKBP-3. IGF receptor was increased in all transgenic mice, but pAkt expression, a marker of downstream IGF-I action, was increased only in LPB-Tag/Wt and LPB-Tag/PGKmBP-3. After 15 wk of age, a marked reduction in tumor growth was apparent in LPB-Tag/PGKmBP-3 mice, indicating that the IGF-independent effects of IGFBP-3 may be important in inhibiting tumor progression.
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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) | 0.001 | 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) | 0.001 | 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".