Epigenetic Disordering Drives Stemness, Senescence Escape and Tumor Heterogeneity
Bibliographic record
Abstract
Tumor heterogeneity is the substrate for tumor evolution and the linchpin of treatment resistance. Cancer cell heterogeneity is largely attributed to distinct genetic changes within each cell population. However, the widespread epigenome repatterning that characterizes most cancers is also highly heterogenous within tumors and could generate cells with diverse identities and malignant features. We show that high levels of the epigenetic regulator and oncogene, UHRF1, in zebrafish hepatocytes rapidly induced methylome disordering, loss of heterochromatin, and DNA damage, resulting in cell cycle arrest, senescence, and acquisition of stemness. Reducing UHRF1 expression transitions these cells from senescent to proliferation-competent. The expansion of these damaged cells results in hepatocellular carcinomas (HCC) that have immature cancer cells intermingled with fibroblasts, immune and senescent cells expressing high UHRF1 levels, which serve as reservoirs for new cancer cells. This defines a distinct and heterogenous HCC subtype resulting from epigenetic changes, stemness and senescence escape.
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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".