Expression of the Insulin-Like Growth Factor I Receptor and Urokinase Plasminogen Activator in Breast Cancer Is Associated with Poor Survival
Bibliographic record
Abstract
Urokinase plasminogen activator (uPA) expression in breast cancer is associated with relapse and a reduction in disease-specific survival. Thus, efforts are under way to identify uPA inhibitors. By screening a chemical library of >1000 compounds, 17-allyaminogeldanamycin (17AAG) was identified as a potent inhibitor of uPA by the National Cancer Institute and is now in Phase I clinical trials. At this time, it remains unclear how 17AAG blocks uPA; one possibility is through disruption of the insulin-like growth factor I receptor (IGF-IR) pathway. This would be consistent with studies from our laboratory showing that activation of IGF-IR results in the induction of uPA protein. In the study described herein, we observed that IGF-IR and uPA were highly expressed in 87 and 55% of breast cancer by screening tumor tissue microarrays representing 930 cases. A significant proportion (52.1% = 354 of 680 cases, P < 0.0001) of the patients had tumors expressing both proteins. uPA alone (P = 0.033) or in combination with IGF-IR (P = 0.0104) was indicative of decreased disease-specific survival. Next, we demonstrated that treating MDA-MB-231 cells with increasing concentrations of 17AAG resulted in IGF-IR degradation (IC(50) = 1.0 micro M) and blocked signal transduction through the Akt and mitogen-activated protein kinase pathways. Finally, we found that 17AAG had a robust inhibitory effect on the production of uPA mRNAand protein in the presence of IGF-I. Thus, our study raises the possibility that 17AAG could prove to be an effective therapeutic agent for a large number of breast cancer patients by inhibiting the IGF-IR and ultimately uPA.
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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 | 0.000 | 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 | 0.000 |
| 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".