IGFBP7 Binds to the IGF-1 Receptor and Blocks Its Activation by Insulin-Like Growth Factors
Bibliographic record
Abstract
Insulin-like growth factor-binding protein 7 (IGFBP7) is a secreted factor that suppresses growth, and the abundance of IGFBP7 inversely correlates with tumor progression. Here, we showed that pretreatment of normal and breast cancer cells with IGFBP7 interfered with the activation and internalization of insulin-like growth factor 1 receptor (IGF1R) in response to insulin-like growth factors 1 and 2 (IGF-1/2), resulting in the accumulation of inactive IGF1R on the cell surface and blockade of downstream phosphatidylinositol 3-kinase (PI3K)-AKT signaling. Binding of IGFBP7 and IGF-1 to IGF1R was mutually exclusive, and the N-terminal 97 amino acids of IGFBP7 were important for binding to the extracellular portion of IGF1R and for preventing its activation. Prolonged exposure to IGFBP7 resulted in activation of the translational repressor 4E-binding protein 1 (4E-BP1) and enhanced sensitivity to apoptosis in IGF1R-positive cells. These results support a model whereby IGFBP7 binds to unoccupied IGF1R and suppresses downstream signaling, thereby inhibiting protein synthesis, cell growth, and survival.
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 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) | 0.002 | 0.001 |
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".