Functional Redundancy between β1 and β3 Integrin in Activating the IR/Akt/mTORC1 Signaling Axis to Promote ErbB2-Driven Breast Cancer
Bibliographic record
Abstract
Integrin receptors coordinate cell adhesion to the extracellular matrix (ECM) to facilitate many cellular processes during malignant transformation. Despite their pro-tumorigenic roles, therapies targeting integrins remain limited. Here, we provide genetic evidence supporting a functional redundancy between β1 and β3 integrin during breast cancer progression. Although ablation of β1 or β3 integrin alone has limited effects on ErbB2-driven mammary tumorigenesis, deletion of both receptors resulted in a significant delay in tumor onset with a corresponding impairment in lung metastasis. Mechanistically, stiff ECM cooperates with integrin receptors to recruit insulin receptors (IRs) to focal adhesion through the formation of integrin/IR complexes, thereby preventing their lysosomal degradation. β1/β3 integrin-deficient tumors that eventually emerged exhibit impaired Akt/mTORC1 activity. Murine and human breast cancers exhibiting enhanced integrin-dependent activity also display elevated IR/Akt/mTORC1 signaling activity. Together, these observations argue that integrin/IR crosstalk transduces mechanical cues from the tumor microenvironment to promote ErbB2-dependent breast cancer 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".