Abstract LB-177: HPV16 CpG and de novo-cytosine methylation is differentially associated with low-grade versus high-grade anal intraepithelial neoplasia in HIV-infected men
Bibliographic record
Abstract
Abstract Objective: To determine if cytosine methylation in CpG and de novo sites is differentially associated with high- or low-grade anal intraepithelial neoplasias (HG-, LG-AIN), HPV16 DNA from182 clinical specimens. Background: Intra-anal cancer (IAC) is an emerging health crisis for gay, bisexual, transgender and other men who have sex with men (MSM) and rates have risen sharply among HIV-infected MSM despite introduction of HAART. High-risk HPVs are a causal risk factor for IAC and are especially common where MSM show HIV-coinfection. Further, cytosine methylation has been posited as an epigenetic transcription regulator that is poorly described in intra-anal dysplasias and cancers. Methods: HPV16 DNA was extracted from anal swab specimens and tested using bisulfite modification, PCR, cloning and sequencing of ∼10 clones/sample. Cervical cancer cell lines, CaSki and SiHa, and paraffin-embedded anal cancer specimens were similarly characterized as controls. Genomic sequences were evaluated using CLUSTAL and BiQ Sequence Alignment analysis software. Descriptive, tabular and multivariate analyses were performed using SAS (Version 9.2). Graphical representations were compiled using SIGMAPLOT (Version 9.0). Findings: Overall, methylation was relatively low in clinical AIN specimens. For 25,085 cytosines, the mean prevalence of methylation was 2.7% (SEM=0.4%) across 3′ L1 and LCR; the prevalence me-CpG, -CpA, -CpT, and -CpC was 3.2% (0.2%), 2.6% (0.1%), 2.5% (0.1%), and 2.7% (0.1%), respectively. However, some variation in HPV16 genomes was observed across specific functional gene sequences for HG- and LG-AIN specimens. Specifically, LG-AINs showed 1.30–2.62 times greater mean prevalence of methylation when compared to HG-AINs, across 24 of the 31 cytosines between nt7428–7564 (p-values<0.05) in the 5′ LCR and enhancer. In total, across the 148 cytosine positions, 37 sites showed statistically significantly greater prevalence of meC in LG-AINs and none showed higher methylation in HG-AINs, yielding a false discovery rate of 0.2 (7.4/37). The nt7428–7564 contains binding sites for E2–1, TEF-1, NF-1, YY1, OCT-1, GRE and potential deamination targets for ApoBec3G. Analyses are ongoing, nonetheless, multivariate analyses show risk for HG-AIN decreases by 27% for each cumulative increase of 100% cytosine-methylation across nt7220–7558, even after we controlled for age, CD4+ T-lymphocyte count, and repeated measurements. Conclusions: Data suggest the HPV16 5′LCR/enhancer region contains a large concentration of cytosine-containing transcription regulatory elements where binding interference by methylation might alter expression of the p97 promoter. Methylation in the HPV16 5′LCR/enhancer may decrease risk for HG-AIN. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-177. doi:10.1158/1538-7445.AM2011-LB-177
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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 | 0.000 |
| 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) | 0.004 | 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".