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Record W4404238114 · doi:10.1093/neuonc/noae165.1159

TMET-21. METABOLIC PROFILING OF MENINGIOMA REVEALS NOVEL SUBGROUP-SPECIFIC BIOLOGIC INSIGHTS AND OUTCOME DEPENDENCIES

2024· article· en· W4404238114 on OpenAlexaff
Alexander Landry, Justin Wang, Jeff Liu, Vikas Patil, Wenjiang Zhang, Yosef Ellenbogen, Chloe Gui, Andrew Ajisebutu, Thomas Kislinger, Eric X. Chen, Farshad Nassiri, Gelareh Zadeh

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProfiling (computer programming)Computational biologyMedicineBiologyComputer scienceProgramming language

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Prior studies have elucidated the presence of four consensus molecular groups (MGs) of meningioma, with unique underlying biology and outcomes. The hyperactivation of metabolic pathways may be associated with tumour growth in so-called hypermetabolic (MG3) tumours, and there is a need to better understand the metabolic profiles of these tumours. This study is the first to study the global metabolon of meningioma in the context of modern molecular subgroups. METHODS We performed untargeted metabolic profiling of 53 meningiomas representing each MG and WHO grade. Prognostic biochemicals were identified using Cox regression and further investigated using RNA and protein-based pathway analyses. A larger cohort with available RNA sequencing (n=121) was used to further explore the prognostic influence of relevant pathways, and biochemicals of interest were validated on a subset of these samples (n=35) using targeted high performance liquid chromatography (HPLC). RESULTS Our untargeted approach identified 560 unique biochemicals for downstream analysis. The abundance of N6-trimethyllysine was associated with significantly earlier time to recurrence highly prognostic on our whole cohort (HR [95%CI] = 3.18 [1.45-26.23], p = 0.004) and within hypermetabolic (MG3) tumours (HR [95%CI] = 6.73 [1.72-6.97], p = 0.006); pyruvate was with worse outcomes in proliferative (MG4) tumours specifically (HR [95%CI] = 5.65 [1.073-29.71], p = 0.041). Analysis of implicated gene pathways demonstrated that upregulation of the oxidative phosphorylation pathway portends worse outcomes in the hypermetabolic subgroup but better outcomes in the proliferative subgroup. By contrast, upregulated lactate transporters were associated with worse outcomes in proliferative, but not hypermetabolic, meningiomas. CONCLUSIONS This is the first study to demonstrate a subgroup-specific prognostic role of N6-trimethyllysine and pyruvate in meningioma, offering increasingly granular outcome predictions using a widely accessible technique (HPLC). In addition, we demonstrated key differences in energy utilization between hypermetabolic and proliferative tumours suggesting fundamental differences in preferred energy utilization and reinforcing a need for subgroup-specific therapies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.354
Teacher spread0.270 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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 routes1
Has abstractyes

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