HIF-2α maintains an undifferentiated state in neural crest-like human neuroblastoma tumor-initiating cells
Bibliographic record
Abstract
High hypoxia-inducible factor-2alpha (HIF-2alpha) protein levels predict poor outcome in neuroblastoma, and hypoxia dedifferentiates cultured neuroblastoma cells toward a neural crest-like phenotype. Here, we identify HIF-2alpha as a marker of normoxic neural crest-like neuroblastoma tumor-initiating/stem cells (TICs) isolated from patient bone marrows. Knockdown of HIF-2alpha reduced VEGF expression and induced partial sympathetic neuronal differentiation when these TICs were grown in vitro under stem cell-promoting conditions. Xenograft tumors of HIF-2alpha-silenced cells were widely necrotic, poorly vascularized, and resembled the bulk of tumor cells in clinical neuroblastomas by expressing additional sympathetic neuronal markers, whereas control tumors were immature, well-vascularized, and stroma-rich. Thus, HIF-2alpha maintains an undifferentiated state of neuroblastoma TICs. Because low differentiation is associated with poor outcome and angiogenesis is crucial for tumor growth, HIF-2alpha is an attractive target for neuroblastoma therapy.
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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) | 0.000 | 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".