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Record W4399785926 · doi:10.1093/neuonc/noae064.426

LGG-34. THE LANDSCAPE OF GLIOMAS IN CHILDREN, ADOLESCENTS AND YOUNG ADULTS REVEALS INSIGHTS ON GLIOMAGENESIS: A CANADIAN ADOLESCENTS AND YOUNG ADULTS NEURO-ONCOLOGY NETWORK (CANON) STUDY

2024· article· en· W4399785926 on OpenAlexaffabout
Julie Bennett, Adrian Levine, Liana Nobre, Logine Negm, Jiil Chung, Karen Fang, Monique Johnson, Martin Komosa, Stacey Krumholtz, Nuno M. Nunes, Mansuba Rana, Scott Ryall, Javal Sheth, Robert Siddaway, Tejus Bale, Éric Bouffet, Michael D. Cusimano, Sunit Das, Jay Detsky, Peter B. Dirks, Matthias A. Karajannis, Paul Kongkham, Alexandra Giantini-Larsen, Bryan Kincheon Li, Mary Jane Lim-Fat, Andrew Lin, Warren Mason, Alexandra Miller, James Perry, Arjun Sahgal, Sameer Farouk Sait, Derek S. Tsang, Gelareh Zadeh, Normand Laperrière, Lananh Nguyen, Andrew Gao, Julia Keith, David G. Muñoz, Uri Tabori, Cynthia Hawkins

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science CentreHospital for Sick ChildrenStollery Children's HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineYoung adultGliomaPediatricsOncologyInternal medicineCancer research

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Gliomas are a heterogenous and common cancer in children, adolescents and young adults (CAYA, ages 0-39 years). Little is known about the biologic and clinical implications of gliomas in AYA limiting our ability to appropriately manage these patients. METHODS We compiled a population-based cohort of patients with glioma aged 0-39 years diagnosed between 2000-2020, performed molecular characterization of the tumors and collected clinical data including therapy and long-term outcome. RESULTS A total of 1456 patients, including 873 AYA patients were included. A pathogenic molecular alteration was found in 98% of AYA samples available. Strikingly, pediatric-type mutations were found in 31% of AYA glioma of which 37% were BRAF V600E and 23% FGFR alterations. Important differences were observed between gliomas in children versus AYAs. First, hemispheric tumors were enriched in AYAs compared to midline tumors in children, especially for RAS/MAPK alterations. Second, increased incidence of high grade tumors in AYA compared to children were observed for BRAF V600E and FGFR mutations (p<0.0001). In contrast, if these alterations were identified in AYA and the tumor was low grade, outcome was improved for BRAF V600E and FGFR mutant tumors in AYAs compared to pediatrics (for BRAF V600E 5 year PFS 55.6% <10 years, 78.1% for 10-20 years and 87.1% for 10-20 years of age, p=0.0002). Third, a specific time window for transformation was observed for each alteration (BRAF, FGFR, IDH). This correlated with different methylation profiles and transcriptional patterns between early midline and late hemispheric tumors. Increased senescence signatures were observed in older patients with low grade RAS/MAPK driven tumors with superior outcome. CONCLUSIONS Different cell of origin and secondary mutations shape tumor behavior and lead to either transformation or senescence during gliomagenesis in CAYA. These can affect early interventions and tailored approaches for gliomas by age and molecular alteration.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.257
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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