Hypoxia‐inducible factor‐1α (HIF‐1α) gene polymorphisms, circulating insulin‐like growth factor binding protein (IGFBP)‐3 levels and prostate cancer
Bibliographic record
Abstract
Abstract BACKGROUND The Hypoxia‐inducible factor‐1 (HIF‐1) plays an important role in regulating angiogenesis in response to hypoxia. Two non‐synonymous polymorphisms (P582S C→T and A588T G→A) in the coding region of the subunit 1α (HIF‐1α) gene have been associated with enhanced stability of the protein and androgen‐independent prostate cancer (CaP). Insulin‐like growth factor binding protein (IGFBP)‐3 mRNA is more abundantly expressed in hypoxia‐related inflammatory angiogenesis and recent in vivo data suggest that IGFBP‐3 has direct, IGF‐independent inhibitory effects on angiogenesis. METHODS We examined the association of these polymorphisms with CaP among 1,072 incident cases and 1,271 controls, and further explored their joint associations with various prediagnostic plasma vascular endothelial growth factor (VEGF), IGF‐I, and IGFBP‐3 levels. RESULTS Neither the P582S nor the A588T polymorphism was associated with risk of overall or metastatic/fatal CaP. However, we found that, among men with the homozygous CC wild‐type (but not CT/TT) of the HIF‐1α P582S, higher IGFBP‐3 levels (≥ vs. interaction = 0.01) lower risk of overall CaP and a 53% (0.25–0.88; Pinteraction = 0.11) lower risk of metastatic and fatal CaP. The A588T polymorphism was too rare to assess interactions. CONCLUSIONS The two HIF‐1α gene polymorphisms were not directly associated with CaP, but the interaction between the P582S polymorphism and IGFBP‐3 merits further evaluation in mechanistic studies. Prostate 67: 1354–1361, 2007. © 2007 Wiley‐Liss, Inc.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".