PATH-25. SURVIVAL STRATIFICATION OF IDH MUTANT GLIOMA USING METHYLATION AND mRNA ANALYSIS OF HOX GENES
Bibliographic record
Abstract
Diffuse gliomas are separated based on IDH mutation (mut) status. However, IDH-mut gliomas manifest wide range of clinical outcome that are not explained by the current genomic classification. We aim to identify clinically and biologically relevant subgroups within IDH-mut low grade gliomas to gain a deeper insight and improve classification. We used 412 IDH-mut gliomas profiled by The Cancer Genome Atlas (TCGA) Network, utilising methylation, mRNA and mutation datasets to identify unique molecular signatures. We found that IDH-mut gliomas further subdivide into 2 groups based on mutational rate. High mutation load predicts poor survival in IDH-mut glioma. Analysis of differentially expressed genes in high versus low-mutational rate showed significant enrichment of HOX genes, 24/40 HOX genes were up regulated in this group. Interestingly, both overexpression and hyper-methylation of specific HOX genes were associated with worse survival. We further show that 7 of these HOX genes (HOXA4, HOXA7, HOXA10, HOXA13, HOXD3, HOXD9, and HOXD10) are the most significant in determining survival. Signed average of 7 Hox genes significantly improved survival and hazard ratio (HR) based on high versus low methylation (HR=4.3, p<0.0001) and high versus low mRNA expression (HR=2.8, p=0.00095). Similarly, effect on survival based on high expression and hyper-methylation of HOX genes was not only observed in IDH-mut 1p/19q-codeleted and non-codeleted groups independently, but also in IDH-wild-type low grade glioma. Multivariate analysis adjusted for confounding factors (grade, age and codeletion status) showed prognostic factors associated with survival in high versus low methylated group (HR=3.2, p=0.0036). Interestingly, only the same direction (high-high and low-low groups) of both mRNA and methylation showed significance and increased HR, which challenges the current understanding of methylation of genes and gene expression. We show that IDH-mut gliomas can further be stratified into clinically relevant categories based on high mRNA expression and hyper-methylation of Hox genes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".