BSCI-26. COMPARATIVE METHYLATION PROFILING OF EGFR MUTANT LUNG ADENOCARCINOMA AND PAIRED BRAIN METASTASIS
Bibliographic record
Abstract
Abstract BACKGROUND: Adenocarcinomas (ADC) are the most common lung tumours and EGFR-mutant lesions have a higher risk of brain metastasis development, which confers poorer survival. Genetic and epigenetic signatures of brain metastasis have not been comprehensively identified. The aim of this study is to compare the methylome of EGFR-mutant primary lung tumor and matched brain metastasis to identify mechanisms of brain metastasis and new treatment targets. METHOD: Seven matched primary to brain metastasis tumours were profiled using the Illumina Infinium MethylationEPIC BeadChip array. Hierarchical clustering and principal component analyses (PCA) were performed using most variable CpG sites. Supervised analyses were performed between lung and brain tumour samples. Copy number variation (CNV) plots identified alterations between pairs along with Leukocytes unmethylation for purity (LUMP) score and prediction lymphocyte proportion analyses to measure immune infiltration. RESULTS: Unsupervised clustering showed that the fourteen tumours clustered according to patient with similar methylation profiles between each of seven matched pairs. On the supervised analysis using 83K significant CpG sites, the fourteen samples clustered into two groups based on tumour site being lung or brain. Of these 83K CpG sites, 2.4K were either hypermethylated or hypomethylated in all lung samples. One quarter of these 2.4K CpG sites were located in promoter regions. CNV analyses showed losses of FGFR1, C19MC, CDKN2A, PTCH1, and MYCN genes with higher deep deletions in brain versus lung primary samples. Immune infiltration measures were similar between lung and brain metastasis pairs (LUMP-score=0.64) consistent with high immune cell infiltration. CONCLUSION: In this EGFR-mutant lung adenocarcinomas and matched brain metastases, differentially methylated CpG sites and CNV alterations are identified that distinguish lung from brain samples. Further work with additional matched samples may further elucidate signatures specific to brain metastasis and aid in our understanding of the mechanisms of brain metastasis.
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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 | 0.000 |
| 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".