BIOM-02. IDENTIFYING MGMT ALTERATIONS AS BIOMARKERS OF SURVIVAL IN LUNG ADENOCARCINOMA WITH BRAIN METASTASES
Bibliographic record
Abstract
Abstract EGFR-mutant lung adenocarcinomas (EGFRm-LUAD) have a higher risk of developing brain metastases (BM) compared to non-EGFR-mutant tumors. BM development has significant prognostic impact and leads to poorer patient survival. MGMT promoter methylation is known to determine response to therapy in other cancer types including intracranial gliomas but has not been investigated in EGFRm-LUAD BM. This work aims to assess whether MGMT promoter methylation predicts patient survival or BM development in EGFRm-LUAD patients. A large cohort of 90 primary EGFRm-LUAD tumors, of which 33 (37%) developed BM, were profiled using the Illumina Infinium MethylationEPIC Bead chip. Using the previously reported MGMT-STP27 approach that uses two CpG sites to predict MGMT methylation status, Cox modeling was performed to assess whether MGMT methylation status correlates with overall survival independent of other clinical factors. MGMT methylation significantly predicted poorer survival in EGFRm-LUAD patients that developed BM (p=0.0003) and did not develop BM (p=0.003). A multivariate cox analysis, adjusting for cancer stage and smoking status as potential confounders, showed that MGMT methylation (HR=6.2, 95%CI:2.2–17.4, p=0.0005) and BM development (HR=2.6, 95%CI:1.3–5.3, p=0.007) were both independently predictive of worse overall survival in EGFRm-LUAD patients. This finding of poorer survival in MGMT methylated EGFRm-LUAD is validated in an independent LUAD patient cohort. Total mutation burden, calculated by the number of mutations per megabase of DNA, was substantially higher in MGMT methylated tumours with an interquartile range (IQR) of 58 (30–71) compared to MGMT unmethylated tumours with the IQR of 5.5 (4.3–6.1) resulting p-value of 0.01 for this comparison. Overall, this work shows that MGMT promoter methylation status is an important prognostic biomarker in LUAD patients. MGMT promoter methylation status in EGFRm–LUAD patients with BM may be used to guide patient treatment with potentially a greater extent of treatment for high-risk patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".