Type I Insulin-like Growth Factor Receptor Induces Pulmonary Tumorigenesis
Bibliographic record
Abstract
Despite the type I insulin-like growth factor receptor (IGF-IR) being highly expressed in more than 80% of human lung tumors, a transgenic model of IGF-IR overexpression in the lung has not been created. We produced two novel transgenic mouse models in which IGF-IR is overexpressed in either lung type II alveolar cells (surfactant protein C [SPC]-IGFIR) or Clara cells (CCSP-IGFIR) in a doxycycline-inducible manner. Overexpression of IGF-IR in either cell type caused multifocal adenomatous alveolar hyperplasia with papillary and solid adenomas. These tumors expressed thyroid transcription factor 1 and Kruppel-like factor 5 in most tumor cells. Similar to our previous work with lung tumors that developed in the mouse mammary tumor virus-IGF-II transgenic mice, the lung tumors that develop in the SPC-IGFIR and CCSP-IGFIR transgenic mice expressed high levels of the cyclic adenosine monophosphate response element binding protein that was localized primarily to the nucleus. Although elevated IGF-IR expression can initiate lung tumor development, tumors can become independent of IGF-IR signaling as IGF-IR down-regulation in established tumors produced tumor regression in some, but not all, of the tumors. These findings implicate IGF-IR as an important initiator of lung tumorigenesis and suggest that the SPC-IGFIR and CCSP-IGFIR transgenic mice can be used to further our understanding of human lung cancer and the role IGF-IR plays in this disease.
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 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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".