Modeling Developmental and Tumorigenic Aspects of Trilateral Retinoblastoma via Human Embryonic Stem Cells
Bibliographic record
Abstract
Human embryonic stem cells (hESCs) provide a platform for studying human development and understanding mechanisms underlying diseases. Retinoblastoma-1 ( RB1 ) is a key regulator of cell cycling, of which biallelic inactivation initiates retinoblastoma, the most common congenital intraocular malignancy. We developed a model to study the role of RB1 in early development and tumor formation by generating RB1 -null hESCs using CRISPR/Cas9. RB1 −/− hESCs initiated extremely large teratomas, with neural expansions similar to those of trilateral retinoblastoma tumors, in which retinoblastoma is accompanied by intracranial neural tumors. Teratoma analysis further revealed a role for the transcription factor ZEB1 in RB1-mediated ectoderm differentiation. Furthermore, RB1 −/− cells displayed mitochondrial dysfunction similar to poorly differentiated retinoblastomas. Screening more than 100 chemotherapies revealed an RB1 –/– -specific cell sensitivity to carboplatin, exploiting their mitochondrial dysfunction. Together, our work provides a human pluripotent cell model for retinoblastoma and sheds light on developmental and tumorigenic roles of RB1 .
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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".