ZEB2 drives intra-tumor heterogeneity and skin squamous cell carcinoma formation with distinct EMP transition states
Bibliographic record
Abstract
About 5% of patients with cutaneous squamous cell carcinoma (cSCC) have a poor prognosis which is associated with a loss of tumor differentiation, invasion and metastasis, all of which are linked to the process of epithelial-to-mesenchymal plasticity (EMP). Here, we showed that the EMP-associated transcription factor ZEB2 drives cSCC heterogeneity which resembles biphasic carcinosarcoma-like tumors. Single cell RNA sequencing revealed distinct subpopulations ranging from fully epithelial (E) to intermediate (EM) to fully mesenchymal (M), associated with the gradual loss of cell surface markers EPCAM, CDH1, ITGB4, and CD200. Mesenchymal features were associated with a higher metastatic capacity and anoikis resistance, yet this comes with a sensitivity toward TNF-induced cell death. Altogether we provide insights in cSCC heterogeneity and modes to target mesenchymal-metastasis inducing cells.
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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) | 0.001 | 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".