RUNX2 Phosphorylation by Tyrosine Kinase ABL Promotes Breast Cancer Invasion
Bibliographic record
Abstract
Activity of transcription factors is normally regulated through interaction with other transcription factors, chromatin remodeling proteins and transcriptional co-activators. In distinction to these well-established transcriptional controls of gene expression, we have uncovered a unique activation model of transcription factors between tyrosine kinase ABL and RUNX2, an osteoblastic master transcription factor, for cancer invasion. We show that ABL directly binds to, phosphorylates, and activates RUNX2 through its SH2 domain in a kinase activity-dependent manner and that the complex formation of these proteins is required for expression of its target gene MMP13. Additionally, we show that the RUNX2 transcriptional activity is dependent on the number of its tyrosine residues that are phosphorylated by ABL. In addition to regulation of RUNX2 activity, we show that ABL transcriptionally enhances RUNX2 expression through activation of the bone morphogenetic protein (BMP)-SMAD pathway. Lastly, we show that ABL expression in highly metastatic breast cancer MDA-MB231 cells is associated with their invasive capacity and that ABL-mediated invasion is abolished by depletion of endogenous RUNX2 or MMP13. Our genetic and biochemical evidence obtained in this study contributes to a mechanistic insight linking ABL-mediated phosphorylation and activation of RUNX2 to induction of MMP13, which underlies a fundamental invasive capacity in cancer and is different from the previously described model of transcriptional activation.
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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 | 0.000 |
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".