The pioneer factor SOX9 competes for epigenetic factors to switch stem cell fates
Bibliographic record
Abstract
During development, progenitors simultaneously activate one lineage while silencing another, a feature highly regulated in adult stem cells but derailed in cancers. Equipped to bind cognate motifs in closed chromatin, pioneer factors operate at these crossroads, but how they perform fate switching remains elusive. Here we tackle this question with SOX9, a master regulator that diverts embryonic epidermal stem cells (EpdSCs) into becoming hair follicle stem cells. By engineering mice to re-activate SOX9 in adult EpdSCs, we trigger fate switching. Combining epigenetic, proteomic and functional analyses, we interrogate the ensuing chromatin and transcriptional dynamics, slowed temporally by the mature EpdSC niche microenvironment. We show that as SOX9 binds and opens key hair follicle enhancers de novo in EpdSCs, it simultaneously recruits co-factors away from epidermal enhancers, which are silenced. Unhinged from its normal regulation, sustained SOX9 subsequently activates oncogenic transcriptional regulators that chart the path to cancers typified by constitutive SOX9 expression.
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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".