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Record W2006306117 · doi:10.1093/neuonc/nov061.97

MB-21 * INTEGRATED GENOMICS ELUCIDATES RELATIVE SPATIAL HOMOGENEITY OF EMBRYONAL BRAIN TUMORS

2015· article· en· W2006306117 on OpenAlexaff
Marc Remke, Florence M.G. Cavalli, A. S. Morrissy, V. Ramaswamy, David Jones, Roger J. Packer, Éric Bouffet, Gary D. Bader, Stefan M. Pfister, Nada Jabado, Marco A. Marra, Michael D. Taylor

Bibliographic record

VenueNeuro-Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreBC Cancer AgencyUniversity of TorontoCanada's Michael Smith Genome Sciences CentreHospital for Sick Children
Fundersnot available
KeywordsHomogeneity (statistics)GenomicsComputational biologyBiologyEvolutionary biologyGeneticsGenomeComputer scienceGeneMachine learning

Abstract

fetched live from OpenAlex

INTRODUCTION: Comprehensive, genome-wide profiling and next-generation based sequencing studies have dramatically improved our understanding of pediatric brain tumor biology in the recent years. However, the vast majority of theses studies are based on the assumption that single biopsies are representative for the entire primary tumor. Intratumor heterogeneity constitutes a common phenomenon previously described in renal cell carcinoma (RCC), breast cancer, and high-grade glioma (HGG). Highly disparate molecular profiles of spatially separated tumor areas within the same tumor may preclude development of personalized, molecularly targeted therapies based on single tumor biopsies. MATERIAL AND METHODS: To address this issue, we conducted multiregion whole exome sequencing, high-resolution DNA copy number analysis (Cytoscan HD), and transcriptional profiling on 39 distinct pediatric and adult tumors with a median of six spatially distant biopsies per tumor (range 4-11). Histological entities included AT/RT (n = 2), HGG (n = 17), medulloblastoma (n = 9), medulloepithelioma (n = 1), and RCC (n = 10). We assessed the degree of intratumor heterogeneity and subgroup affiliation using integrated genomics and unsupervised hierarchical clustering algorithms. RESULTS: Embryonal brain tumors demonstrated highly spatially homogenous transcriptomes. In contrast to adult glioblastoma, we showed that subgroup affiliation was stable in multiregion biopsies from the same medulloblastoma patient. Furthermore, embryonal brain tumors displayed highly similar focal and broad DNA copy number alterations compared to HGG and RCC. Multiregion sequencing further reinforced the relatively higher degree of intratumor homogeneity in embryonal brain tumors. Compared to HGG or RCC, somatic mutations in embryonal tumors were much more likely to be ubiquitous throughout the tumor. CONCLUSIONS: The relative spatial homogeneity of embryonal brain tumors suggests that limited biopsies are representative of the tumor genomics landscape, which has important implications for biological classification and development of targeted therapies for these tumors.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.301
Teacher spread0.269 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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