DNA methylation markers have universal prognostic value for anal cancer risk in HIV‐negative and HIV‐positive individuals
Bibliographic record
Abstract
Anal cancer has increasing incidence and is preceded by high-grade anal intraepithelial neoplasia (HGAIN; AIN2-3). Previously, we identified and validated several methylation markers for accurate detection of anal cancer and HGAIN with cancer risk in HIV-positive (HIV+) men who have sex with men (MSM). This study aimed to evaluate these markers in HIV-negative risk groups. A cross-sectional series of 176 tissue samples of anal cancer, AIN3, AIN2, AIN1 and control biopsies obtained in HIV-negative women and men was tested for six methylation markers (ASCL1, LHX8, SST, WDR17, ZIC1 and ZNF582). Accuracy for detection of AIN3 and cancer (AIN3+) was determined by univariable and multivariable mixed-effect ordinal logistic regression. Methylation levels of all markers increased with increasing severity of disease (P < 0.0001) and were comparable to results in HIV+ MSM. All markers showed high accuracy for AIN3+ detection [area under the curve (AUC): 0.83-0.86]. The optimal marker panel (ASCL1 and ZIC1; AUC = 0.85 for AIN3+) detected 98% of cancers at 79% specificity. In conclusion, DNA methylation markers show a high diagnostic performance for AIN3+ detection in HIV+ and HIV-negative risk groups, justifying broad application of methylation analysis for anal cancer prevention programmes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".