MEDU-46. SONIC HEDGEHOG SPEEDS UP DNA REPLICATION AND CAUSES CANCER-INITIATING MUTATIONS
Bibliographic record
Abstract
Cancer is a multi-stage disease caused by sequential mutations; however, the molecular mechanism that generates cancer-initiating mutations is not well understood. Using the developing cerebellum as a model system, here we show the molecular mechanism of tumor initiation in Sonic hedgehog medulloblastoma (SHH-MB), a common subtype of the most frequent pediatric brain tumor. The most common initiating event of SHH-MB is Ptch1 loss of heterozygosity (LOH), which occurs in cerebellar granule cell progenitors (GCPs) and leads to preneoplasia formation. Since GCPs proliferate in response to Shh, we tested whether the normal proliferative effects of Shh can lead to genomic instability and DNA lesions responsible for Ptch1 LOH in the SHH-MB cell-of-origin. We found that Shh profoundly alters DNA replication dynamics in GCPs, leading to DNA damage, formation of DNA breaks in S-phase and hyper-recombination. Shh led to DNA helicase loading and activation, resulting in high levels of replication origin firing. Shh-dependent origin firing was required for Shh-induced DNA damage and recombination. Moreover, reducing origin firing decreased recombination and tumor initiation in a pre-clinical model of MB. These results show that reduction of Shh-dependent, DNA replication-associated DNA damage in tumor-prone Ptch1+/- GCPs before cancer initiation is capable of preventing MB-initiating mutations. Thus, we demonstrate that a developmental mitogen can cause cancer-initiating mutations through an increase in origin firing, and attenuating origin firing can prevent cancer initiation.
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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".