Abstract 3455: Comparison of expression profiles of pediatric high and low grade brainstem gliomas to pediatric supratentorial high grade astrocytomas
Bibliographic record
Abstract
Abstract Diffuse intrinsic pontine gliomas (DIPG) are one of the most devastating pediatric malignancies and currently the number one cause of brain tumor related death in children with a 10-12 month median survival. Despite this very little is understood about the biology of these tumors. We have already shown potential novel therapeutic targets for DIPG using high-resolution SNP-based analysis. We performed high resolution genetic analysis using whole-genome single-nucleotide polymorphism (SNP) arrays (Affymetrix 500K and 6.0) on post mortem tumor with matched normal brain samples (n=9) and surgical samples (n=2) for a series of DIPG patients as well as pediatric supratentorial high grade astrocytomas (sHGA, n=20). Here we extend our initial study to include expression array analysis, amalgamating the datasets to generate a more complete understanding of the genetic alterations underlying brainstem gliomas. Expression profiling using Illumina HumanHT-12 arrays was conducted on 26 high grade brainstem gliomas, including 23 DIPGs, 51 low grade brainstem gliomas and 30 supratentorial high grade astrocytomas. Expression profiles highlighted the distinctiveness of DIPGs when compared to high grade supratentorial astrocytomas. Analysis resulted in two groups of DIPGs when clustering based on most significant differentially expressed genes (p < 0.005) with one group being more similar to pediatric low grade brainstem gliomas and the other distinct from both the supratentorial high grade tumors and other brainstem gliomas. This data will increase our understanding of brainstem glioma biology, information crucial to the development of agents targeted more specifically towards this devastating disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3455. doi:10.1158/1538-7445.AM2011-3455
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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 | 0.001 |
| 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) | 0.002 | 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".