Role of IGF-1R in Mediating Breast Cancer Invasion and Metastasis
Why this work is in the frame
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Bibliographic record
Abstract
In this review we bring forward what is currently known about the role of type I insulin-like growth factor receptor (IGF-1R) in mediating breast cancer invasion and metastasis. We begin by addressing how activated IGF-1R could allow pre-cancerous cells to become invasive. To this effect, we discuss clinical reports suggesting that activation of IGF-1R could stimulate ductal carcinoma in situs to become invasive. In the same light, we review basic research from our laboratory showing that IGF-1R differentially regulates the expression of breast cancer progression genes when pre-malignant breast epithelial cells were stimulated with insulin-like growth factor-I (IGF-I) over time. The discussion then turns toward the ability of IGF-1R to stimulate invasion of breast cancer cells that have acquired a malignant phenotype. At this stage of breast cancer, it appears that IGF-I stimulates cells to invade in part by inducing urokinase plasminogen activator. Finally, we consider the potential role of IGF-1R in regulating breast cancer metastases by facilitating angiogenesis and lymphangiogenesis. In support of this idea, there is evidence for IGF-1R in both of these processes through the induction of vascular endothelial growth factors (VEGF(165) and VEGF(121)). Thus, IGF-1R affords breast cancer cells many opportunities to become invasive and eventually metastatic. We conclude that disrupting IGF-1R signaling has many important implications in the treatment and management of breast cancer.
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.
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 it