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Record W4295577585 · doi:10.3389/fnmol.2022.928355

The impact of heme biosynthesis regulation on glioma aggressiveness: Correlations with diagnostic molecular markers

2022· article· en· W4295577585 on OpenAlexaff
Mario Mischkulnig, Barbara Kiesel, Thomas Rötzer-Pejrimovsky, Martin Borkovec, Alexandra Lang, Matthias Millesi, Lisa I. Wadiura, Shawn L. Hervey‐Jumper, Josef Penninger, Mitchel S. Berger, Georg Widhalm, Friedrich Erhart

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2022
Typearticle
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsUniversity of British Columbia
FundersMemorial Sloan-Kettering Cancer Center
KeywordsGliomaBiologyHemeCDKN2ACancer researchCancerGeneticsBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Background The prognosis of diffusely infiltrating glioma patients is dismal but varies greatly between individuals. While characterization of gliomas primarily relied on histopathological features, molecular markers increasingly gained importance and play a key role in the recently published 5 th edition of the World Health Organization (WHO) classification. Heme biosynthesis represents a crucial pathway due to its paramount importance in oxygen transport, energy production and drug metabolism. Recently, we described a “heme biosynthesis mRNA expression signature” that correlates with histopathological glioma grade and survival. The aim of the current study was to correlate this heme biosynthesis mRNA expression signature with diagnostic molecular markers and investigate its continued prognostic relevance. Materials and methods In this study, patient data were derived from the “The Cancer Genome Atlas” (TCGA) lower-grade glioma and glioblastoma cohorts. We identified diffusely infiltrating gliomas correlating molecular tumor diagnosis according to the most recent WHO classification with heme biosynthesis mRNA expression. The following molecular markers were analyzed: EGFR amplification, TERT promoter mutation, CDKN2A/B homozygous loss, chromosome 7 + /10- aneuploidy, MGMT methylation, IDH mutation, ATRX loss, p53 mutation and 1p19q codeletion. Subsequently, we calculated the heme biosynthesis mRNA expression signature for correlation with distinct molecular glioma markers/molecular subgroups and performed survival analyses. Results A total of 649 patients with available data on up-to-date molecular markers and heme biosynthesis mRNA expression were included. According to analysis of individual molecular markers, we found a significantly higher heme biosynthesis mRNA expression signature in gliomas with IDH wildtype ( p < 0.0005), without 1p19q codeletion ( p < 0.0005), with homozygous CDKN2A/B loss ( p < 0.0005) and with EGFR amplification ( p = 0.001 ). Furthermore, we observed that the heme biosynthesis mRNA expression signature increased with molecular subgroup aggressiveness ( p < 0.0005 ), being lowest in WHO grade 2 oligodendrogliomas and highest in WHO grade 4 glioblastomas. Finally, the heme biosynthesis mRNA expression signature was a statistically significant survival predictor after multivariate correction for all molecular markers ( p < 0.0005). Conclusion Our data demonstrate a significant correlation between heme biosynthesis regulation and diagnostic molecular markers and a prognostic relevance independent of these established markers. Consequently, heme biosynthesis expression is a promising biomarker for glioma aggressiveness and might constitute a potential target for novel therapeutic approaches.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.248
Teacher spread0.241 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

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