The landscape of N6-methyladenosine in localized primary prostate cancer
Bibliographic record
Abstract
N6-methyladenosine (m6A), the most abundant internal RNA modification in humans, regulates most aspects of RNA processing. Prostate cancer is characterized by widespread transcriptomic dysregulation; therefore, we characterized the m6A landscape of 162 localized prostate tumors with matched DNA, RNA and protein profiling. m6A abundance varied dramatically across tumors, with global patterns emerging via complex germline–somatic cooperative regulation. Individual germline polymorphisms regulated m6A abundance, cooperating with somatic mutation of cancer driver genes and m6A regulators. The resulting complex patterns were associated with prognostic clinical features and established the biomarker potential of global and locus-specific m6A patterns. Tumor hypoxia dysregulates m6A profiles, bridging prior genomic and proteomic observations. Specific m6A sites, such as those in VCAN, drive disease aggression, associating with poor outcomes, tumor growth and metastasis. m6A dysregulation is thus associated with key events in the natural history of prostate cancer: germline risk, microenvironmental dysregulation, somatic mutation and metastasis. Transcriptome-wide m6A RNA methylation profile in 162 primary prostate tumors identifies m6A association with prognostic clinical features and disease aggression.
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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 | 0.000 |
| 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) | 0.002 | 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".