Epigenetic Silencing of Novel Tumour Suppressor Genes in Medulloblastoma
Bibliographic record
Abstract
Medulloblastomas (MB) are the most common pediatric nervous system malignancy. Known mutations account for only a subset of MB cases. We hypothesized that CpG island methylation-mediated tumour suppressor gene (TSG) silencing contributes to MB pathogenesis, either alone, or in combination with genetic events such as loss of heterozygosity (LOH). We performed a microarray-based genome-wide screen of MB cell lines treated with 5-aza-2’deoxycytidine, identifying genes exhibiting increased expression following treatment. Using this strategy, we identified inhibitors of WNT signalling (SFRP1, SFRP2, and SFRP3) and an inhibitor of the HGF/MET signalling pathway (SPINT2) as putative TSGs silenced by promoter region methylation in MB. \nMethylation of the WNT signalling inhibitors SFRP1, SFRP2, and SFRP3 was identified using bisulfite sequencing and methylation-specific PCR (MSP). Stable re-expression of SFRP1, SFRP2, and SFRP3 reduced proliferation, impaired anchorage-independent growth, and limited WNT signalling activity. SFRP1 re-expression reduced tumour growth in vivo in xenograft models. Aberrant WNT signalling plays a role in the pathogenesis of a subset of sporadic human MB, as well as MB in cases of Turcot syndrome with germline mutations of APC. Activating mutations of β-catenin are also implicated in a subset of MB. We have identified for the first time an additional mechanism – loss of normal pathway inhibition by SFRP gene silencing – that contributes to MB pathogenesis.\nSPINT2 methylation was confirmed with bisulfite sequencing and MSP. Stable re-expression of SPINT2 reduced proliferation, impaired cell migratory ability, and decreased the capacity for anchorage-independent growth. In vivo, re-expression of SPINT2 reduced tumour formation in xenograft models. This study identified for the first time SPINT2 as a putative TSG in human MB, and further implicated aberrant HGF/MET oncogenic signalling in the pathogenesis of this disease.\nThe efficacy of targeting the HGF/MET pathway as a novel therapeutic strategy was tested in vitro using the small molecule MET kinase inhibitor PHA665752. Treatment of MB cell lines with PHA665752 reduced cell proliferation, anchorage-independent growth, migration, and limited downstream signalling via the MAPK and PI3K/AKT pathways.
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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".