Integrin-uPAR signaling leads to FRA-1 phosphorylation and enhanced breast cancer invasion
Bibliographic record
Abstract
BACKGROUND: The Fos-related antigen 1 (FRA-1) transcription factor promotes tumor cell growth, invasion and metastasis. Phosphorylation of FRA-1 increases protein stability and function. We identify a novel signaling axis that leads to increased phosphorylation of FRA-1, increased extracellular matrix (ECM)-induced breast cancer cell invasion and is prognostic of poor outcome in patients with breast cancer. METHODS: While characterizing five breast cancer cell lines derived from primary human breast tumors, we identified BRC-31 as a novel basal-like cell model that expresses elevated FRA-1 levels. We interrogated the functional contribution of FRA-1 and an upstream signaling axis in breast cancer cell invasion. We extended this analysis to determine the prognostic significance of this signaling axis in samples derived from patients with breast cancer. RESULTS: and uPAR expression in these cells suggested that integrin receptors might activate this FAK-SRC-ERK2 signaling. Transient knockdown of urokinase/plasminogen activator urokinase receptor (uPAR) in basal-like breast cancer cells grown on vitronectin reduces FRA-1 phosphorylation and stabilization; and uPAR and FRA-1 are required for vitronectin-induced cell invasion. In clinical samples, a molecular component signature consisting of vitronectin-uPAR-uPA-FRA-1 predicts poor overall survival in patients with breast cancer and correlates with an FRA-1 transcriptional signature. CONCLUSIONS: We have identified a novel signaling axis that leads to phosphorylation and enhanced activity of FRA-1, a transcription factor that is emerging as an important modulator of breast cancer progression and metastasis.
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 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) | 0.001 | 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".