β1-integrin is dispensable for the induction of ErbB2 mammary tumors but plays a critical role in the metastatic phase of tumor progression
Bibliographic record
Abstract
Cross-talk between integrin receptors and activated growth factor receptors has been hypothesized to play a critical role in the initiation and progression of cancer. Despite in vitro evidence documenting the important role of integrin receptors in the regulation of cancer cell proliferation, the relative contribution of the integrin receptors to the initiation and progression of tumors remains unclear. Previous studies with a polyomavirus middle T mammary tumor model have indicated that targeted disruption of beta1-integrin in the mammary glands of these mice completely blocks tumor induction. To further explore the general significance of these observations, we have crossed these conditional beta1-integrin strains to a strain of mice carrying mouse mammary tumor virus/activated erbB2 (herein referred to as the NIC strain). In contrast to the tumor induction block in the polyomavirus middle T model, tumor onset in the beta1-integrin-deficient NIC mice was delayed by only 30 d and was 100% penetrant. This modest effect on tumor induction was not a result of inefficient excision, as all tumors were confirmed as beta1-integrin-null. Animals bearing beta1-integrin-deficient ErbB2 tumors exhibited significantly reduced tumor volume, which was associated with increased tumor cell apoptosis and a reduction in tumor angiogenesis. In addition, beta1-integrin-deficient tumors were compromised in their capacity to metastasize to the lung, a deficiency associated with abrogation of adhesion signaling. Taken together, these observations suggest that, although beta1-integrin is dispensable for the initiation of ErbB2 tumor induction, it plays a critical role in metastatic phase of tumor progression.
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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 | 0.000 |
| 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".