LINE-1 hypermethylation in peripheral blood of cutaneous melanoma patients is associated with metastasis
Bibliographic record
Abstract
Aberrant DNA methylation pattern is a well-known epigenetic marker of cancer cells. Recently, aberrant methylation was also reported in the peripheral blood of cancer patients and it could potentially serve as a biomarker for cancer risk. We investigated the methylation pattern of LINE-1 and other repetitive DNA elements in peripheral blood of cutaneous melanoma patients in order to search for an association with clinical characteristics. The patient cohort was composed by 69 unrelated melanoma patients, 28 of whom were hereditary cases (with or without CDKN2A mutations) and 41 were isolated (sporadic) melanoma cases. Methylation of LINE-1 was evaluated by pyrosequencing, whereas additional repetitive DNA sequences were assessed using Illumina 450K methylation microarray. Melanoma patients exhibited a higher, albeit heterogeneous, LINE-1 methylation level compared with controls. Hereditary melanoma patients carrying CDKN2A mutations showed a hypermethylated pattern of both LINE-1 and repetitive DNA elements compared with other patients. In particular, the methylation level at one specific CpG of LINE-1 was found to be correlated with the occurrence of metastasis. Our data suggest that LINE-1 hypermethylation in peripheral blood of melanoma patients is a potential epigenetic biomarker for metastasis occurrence.
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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) | 0.002 | 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".