MGMT Promoter Methylation Predicts Survival in Lung Adenocarcinoma
Bibliographic record
Abstract
Lung cancer is the third most common cause of cancer death worldwide. Lung adenocarcinoma (LUAD), its predominant subtype, is particularly lethal due to the delayed diagnosis, variability, and complexity of precision medicine. Although MGMT promoter methylation predicts overall survival in some cancers, it remains unexamined in LUAD. This study assessed whether MGMT promoter methylation predicts survival in LUAD patients. We analyzed 415 primary LUAD samples with the Illumina Infinium Methylation 450K BeadChip. MGMT promoter methylation status was determined using the MGMT-STP27 approach, which relies on two CpG sites. Gene expression data underwent supervised analysis with a limma-based Bioconductor model. Copy number variations (CNVs) were generated via the CONUMEE Bioconductor package for further CNV analysis. The results of all stages showed that MGMT methylated patients' OS after diagnosis (4 years) was significantly shorter than MGMT unmethylated patients' OS (7 years) (p=0.034). The Boxplot result indicated that the MGMT methylated LUAD patient group has a significantly higher aneuploidy score than the unmethylated group (p=0.01). Furthermore, the Kaplan-Meier diagram for the survival probability of the MGMT unaltered group had a longer OS (7 years) than the MGMT altered group (3 years) of LUAD patients for stage 1 to 4 (p=00045). MGMT promoter status is a key prognostic biomarker in LUAD, indicating poorer survival and potentially guiding more aggressive treatment strategies 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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".