Association between glioma susceptibility loci and tumour pathology defines specific molecular etiologies
Bibliographic record
Abstract
BACKGROUND: Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) at 7 loci influencing glioma risk: rs2736100 (TERT), rs11979158 and rs2252586 (EGFR), rs4295627 (CCDC26), rs4977756 (CDKN2A/CDKN2B), rs498872 (PHLDB1), and rs6010620 (RTEL1). MATERIALS AND METHODS: We studied the relationship among these 7 glioma-risk SNPs and characteristics of tumors from 1374 patients, including grade, IDH (ie IDH1 or IDH2) mutation, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, 9p and 10q loss, and 1p-19q codeletion. RESULTS: rs2736100 (TERT) and rs6010620 (RTEL1) risk alleles were associated with high-grade disease, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, and 9p and 10q deletion; rs4295627 (CCDC26) and rs498872 (PHLDB1) were associated with low-grade disease, IDH mutation, and 1p-19q codeletion. In contrast, rs4977756 (CDKN2A/B), rs11979158 (EGFR), and to a lesser extent, rs2252586 (EGFR) risk alleles were independent of tumor grade and genetic profile. Adjusting for tumor grade showed a significant association between rs2736100 and IDH status (P = .01), 10q loss (P = .02); rs4295627 and 1p-19q codeletion (P = .04), rs498872 and IDH (P = .02), 9p loss (P = .04), and 10q loss (P = .02). Case-control analyses stratified into 4 molecular classes (defined by 1p-19q status, IDH mutation, and EGFR amplification) showed an association of rs4295627 and rs498872 with IDH-mutated gliomas (P < 10(-3)) and rs2736100 and rs6010620 with IDH wild-type gliomas (P < 10(-3) and P = .03). CONCLUSION: The frequency of EGFR and CDKN2A/B risk alleles were largely independent of tumor genetic profile, whereas TERT, RTEL1, CCDC26, and PHLDB1 variants were associated with different genetic profiles that annotate distinct molecular pathways. Our findings provide further insight into the biological basis of glioma etiology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".