AKT-mediated phosphorylation of Sox9 induces Sox10 transcription in a murine model of HER2-positive breast cancer.
Bibliographic record
Abstract
Abstract Background: Approximately 5-10% of HER2-positive breast cancers can be defined by low expression of the Ste20-like kinase, SLK, and high expression of SOX10. Our lab has observed that genetic deletion of SLK results in the induction of Sox10 and significantly accelerates tumor initiation in a HER2-induced mammary tumor model. However, the mechanism responsible for the induction of SOX10 gene expression in this context remains unknown. Methods: Using tumor derived cell lines from MMTV-Neu mice lacking SLK and biochemical approaches, we have characterized the signaling mechanisms and relevant DNA elements driving Sox10 expression. Results: Biochemical and genetic analyses of the SOX10 regulatory region in SLK-deficient mammary tumor cells show that Sox10 expression is dependent on a novel -7kb enhancer that harbors three SoxE binding sites. ChIP analyses demonstrate that Sox9 is bound to those elements in vivo . Our data show that AKT can directly phosphorylate Sox9 in vitro at serine 181 and that AKT inhibition blocks Sox9 phosphorylation and Sox10 expression in SLK(-/-) tumor cells. AKT-mediated Sox9 phosphorylation increases its transcriptional activity on the Sox10 -7kb enhancer without altering its DNA binding activity. Interestingly, analysis of murine and human mammary tumors reveals a direct correlation between the levels of active phospho-Sox9 S181 and Sox10 expression. Conclusions: Our results have identified a novel Sox10 enhancer and validated Sox9 as direct target for AKT. As Sox10 is a biomarker for triple negative breast cancers (TNBC), these findings might have major implications in the targeting and treatment of those 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| 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 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".