Transcriptional repression of <scp>SOX2</scp> by p53 in cancer cells regulates cell identity and migration
Bibliographic record
Abstract
During cancer development and progression, many genetic alterations lead to the acquisition of novel features that confer selective advantage to cancer cells and that resemble developmental programs. SRY-box transcription factor 2 (SOX2) is one of the key pluripotency transcription factors, expressed during embryonic development and active in adult stem cells. In cancer, SOX2 is frequently dysregulated and associated with tumor stemness and poor patient survival. SOX2 expression is suppressed in differentiated cells by tumor suppressor proteins that form a transcriptional repressive complex. We previously identified some of these proteins and found that their absence combined with deficiency in Trp53 leads to maximal dysregulated expression of Sox2. Using cancer cell lines of different origin and with different p53 status, we show here that manipulating TP53 to restore or decrease its activity results in repression or induction of SOX2, respectively. Mechanistically, we observed that the regulation of SOX2 expression by TP53 is transcriptional and identified Trp53 bound to the promoter region and the Sox2 Regulatory Region 2 enhancer of Sox2. Forcing high levels of SOX2 in cancer cells leads to morphological changes that molecularly correspond to the acquisition of a more mesenchymal phenotype, correlating with an increased migratory capacity. Finally, the analysis of human breast cancer samples shows that this correlation between TP53 status, levels of expression of SOX2, and a more metastatic phenotype is also observed in cancer patients. Our results support the notion that lack of TP53 in tumor cells results in deregulated expression of developmental gene SOX2 with phenotypic consequences related to increased malignization.
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 | 0.000 |
| 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".