SCT Promoter Methylation Is a Highly Discriminative Biomarker for Lung and Many Other Cancers
Bibliographic record
Abstract
Aberrant DNA methylation has long been implicated in cancers. In this letter, we present a highly discriminative DNA methylation biomarker for non-small cell lung cancers (NSCLCs) and 14 other cancers. Based on 69 NSCLC cell lines and 257 cancer-free lung tissues, we identified a CpG island in SCT gene promoter, which was verified by qMSP experiment in 15 NSCLC cell lines and three immortalized human respiratory epithelium cells. In addition, we found that the SCT promoter was methylated in 23 cancer cell lines involving >10 cancer types profiled by ENCODE. We found that the SCT promoter is hypermethylated in primary tumors from TCGA lung cancer cohort. In addition, we found that SCT promoter is methylated at high frequencies in 15 malignancies and is not methylated in ~1000 non-cancerous tissues across >30 organ types. This letter indicates that SCT promoter methylation is a highly discriminative biomarker for lung and many other cancers.
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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 | 0.001 | 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) | 0.001 | 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".