Abstract 2129: Pediatric diffuse intrinsic pontine gliomas are genetically distinct from high and low grade astrocytomas
Bibliographic record
Abstract
Abstract Tumors of the central nervous system constitute the most common type of solid pediatric tumors and account for the majority of mortality and morbidity in pediatric oncology. Brainstem glioma (BSG) is a type of brain tumor that arises in the medulla, pons or midbrain and accounts for approximately 10-20% of pediatric brain tumors. Diffuse gliomas of the pontine region, diffuse intrinsic pontine glioma (DIPG) are the most common type of brainstem tumor, accounting for about 58-78% of BSG and the number one cause of brain tumor related death in children with a 1-2 year survival. Despite this very little is understood about the biology of these tumors. To try to address this lack of knowledge we have undertaken genomic analysis of a series of DIPGs and compared their copy number changes to those seen in pediatric supratentorial high grade astrocytomas as well as low grade astrocytomas. Post mortem tumor and matched normal brain samples (n= 9) and surgical samples (n= 4) were collected for a series of DIPG patients. We performed high-resolution genetic analysis using whole-genome single-nucleotide polymorphism (SNP) arrays (Affymetrix 500K and 6.0). Data analysis was conducted using Partek Genome Suite and Copy Number Analysis Tool (Affymetrix). Analysis of copy number alterations returned hits in several cancer related pathways including MAPK, Wnt, prostate cancer and gliomagenesis. DIPG copy number was also compared to that of pediatric high grade (n= 20) and low grade (n= 30) astrocytomas. Unsupervised Pearson's Dissimilarity clustering resulted in 3 distinct groups. One contained 6 DIPGs; the second contained mostly LGA with a few HGA, while the third group contained mostly HGA with the remaining DIPGs clustering with this group. Although there were some similarities, DIPG are genetically distinct from supratentorial high grade and low grade astrocytomas. A better understanding of DIPG biology is needed in order to develop agents targeted more specifically towards this disease particularly given the dismal prognosis and unresponsive nature of these tumors to conventional treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2129.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.004 | 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".