IQGAP1 Stimulates Proliferation and Enhances Tumorigenesis of Human Breast Epithelial Cells
Bibliographic record
Abstract
The scaffold protein IQGAP1 integrates signaling pathways and participates in diverse cellular activities. IQGAP1 is overexpressed in a number of human solid neoplasms, but its functional role in tumorigenesis has not been previously evaluated. Here we report that IQGAP1 contributes to neoplastic transformation of human breast epithelial cells. The amount of IQGAP1 in breast carcinoma is greater than that in normal tissue, with highly metastatic breast epithelial cells expressing the highest levels. Overexpression of IQGAP1 enhances proliferation of MCF-7 breast epithelial cells. Reduction of endogenous IQGAP1 by RNA interference impairs both serum-dependent and anchorage-independent growth of MCF-7 cells. Consistent with these in vitro observations, immortalized MCF-7 cells overexpressing IQGAP1 form invasive tumors in immunocompromised mice, whereas tumors derived from MCF-7 cells with stable knockdown of IQGAP1 are smaller and less invasive. In vitro analysis with selected IQGAP1 mutant constructs and a chemical inhibitor suggests that actin, Cdc42/Rac1, and the mitogen-activated protein kinase pathway contribute to the mechanism by which IQGAP1 increases cell invasion. Collectively, our data reveal that IQGAP1 enhances mammary tumorigenesis, suggesting that it may be a target for therapeutic intervention.
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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) | 0.002 | 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".