STEM-25. IN VIVO FUNCTIONAL GENOMICS IDENTIFIES ESSENTIALITY OF POTASSIUM HOMEOSTASIS IN MEDULLOBLASTOMA
Bibliographic record
Abstract
Abstract Distinguishing cancer maintenance genes—i.e. genes essential and specific to tumor survival—from initiation, progression, and passenger genes is critical for developing effective cancer therapeutics. We engineered the Lazy Piggy genetic screening system, which uses a Sleeping Beauty / piggyBac hybrid transposon to dysregulate and later restore gene expression. In vivo spatiotemporal control of Lazy Piggy transposon insertion and remobilization depletes insertions that are non-essential for tumor survival while enriching for maintenance driver insertions. Using this functional genomic approach, we identify potassium channels as a regulator for medulloblastoma, the most common pediatric brain malignancy. Loss of potassium channel Kcnb2 diminishes the pool of medulloblastoma-propagating cells by hampering their replication potential, thereby prolonging the survival of tumor-bearing mice. Mechanistically, Kcnb2 governs potassium homeostasis to regulate plasma membrane tension-gated EGFR signaling, which drives the proliferative expansion of medulloblastoma-propagating cells. Our in vivo functional genomics reveals potassium homeostasis as a tumor maintenance essentiality, establishes a link between potassium channel activity and plasma membrane tension, and defines a mechanism by which ion homeostasis integrates biomechanical and biochemical signaling to promote medulloblastoma aggression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".