Identification of molecular targets specific to pediatric astrocytomas
Bibliographic record
Abstract
Brain tumours are currently the leading cause of cancer related mortality and morbidity in the pediatric years and astrocytomas are the most common type of central nervous system tumours.High grade astrocytomas in children are rare; however, they have a high rate of morbidity and mortality.Our first focus was to identify gene expression profiles specific to grade IV pediatric astrocytomas also known as glioblastomas (GBM).We demonstrated that pGBM is distinct from adult GBM in their gene expression profile and also showed that there are at least two subsets of pGBM that can be distinguished based on their association or lack of association with an aberrantly active Ras and Akt pathway in a sample.These results were further confirmed using an independent data set consisting of formalin-fixed paraffin embedded (FFPE) pGBM samples.We further aimed to characterize whether grade III and IV pediatric astrocytomas had distinct gene expression profiles.Our results indicate that Grade III astrocytomas have unique gene expression signatures when compared to pGBM, including upregulation of the mTOR pathway, which was found to be the most differentially regulated between the two tumour grades.Analysis of our microarray results to identify genes differentially regulated specifically in pGBM and accounting for gliomagenesis led us to focus on sorting nexin 3 (SNX3), a protein involved in endosomal trafficking, based on its role in modulating EGFR, Ras and PI3K/Akt activation; which are major targets and signaling pathways in GBM.We showed that SNX3 is upregulated specifically in primary GBM tumours, and that this upregulation correlates with increased EGFR and MET expression in samples.Overexpression of SNX3 in pGBM cell lines, delayed EGFR degradation, sustained EGFR and MET signaling, increased cell proliferation, and induced tumorigenesis in vivo.Our work indicate that there are specific targets in gliomagenesis in children and identify the mTOR pathway and deregulation of endosomal recycling as potential drivers of gliomagenesis in respectively pediatric grade III and IV astrocytomas.committee members, Dr.
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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 | 0.001 | 0.001 |
| 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".