Coordinated activation of c-Src and FOXM1 drives tumor cell proliferation and breast cancer progression
Bibliographic record
Abstract
Activation of the tyrosine kinase c-Src promotes breast cancer progression and poor outcomes, yet the underlying mechanisms are incompletely understood. Here, we have shown that deletion of c-Src in a genetically engineered model mimicking the luminal B molecular subtype of breast cancer abrogated the activity of forkhead box M1 (FOXM1), a master transcriptional regulator of the cell cycle. We determined that c-Src phosphorylated FOXM1 on 2 tyrosine residues to stimulate its nuclear localization and target gene expression. These included key regulators of G2/M cell-cycle progression as well as c-Src itself, forming a positive feedback loop that drove proliferation in genetically engineered and patient-derived models of luminal B-like breast cancer. Using genetic approaches and small molecules that destabilize the FOXM1 protein, we found that targeting this mechanism induced G2/M cell-cycle arrest and apoptosis, blocked tumor progression, and impaired metastasis. We identified a positive correlation between FOXM1 and c-Src expression in human breast cancer and show that the expression of FOXM1 target genes predicts poor outcomes and associates with the luminal B subtype, which responds poorly to currently approved therapies. These findings revealed a regulatory network centered on c-Src and FOXM1 that is a targetable vulnerability in aggressive luminal breast cancers.
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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 | 0.001 | 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) | 0.000 | 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 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".