Rearrangements of viral and human genomes at human papillomavirus integration events and their allele-specific impacts on cancer genome regulation
Bibliographic record
Abstract
Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer. To resolve genome dysregulation associated with HPV integration, we performed Oxford Nanopore Technologies long-read sequencing on 72 cervical cancer genomes from a Ugandan data set that was previously characterized using short-read sequencing. We find recurrent structural rearrangement patterns at HPV integration events, which we categorize as del(etion)-like, dup(lication)-like, translocation, multi-breakpoint, or repeat region integrations. Integrations involving amplified HPV-human concatemers, particularly multi-breakpoint events, frequently harbor heterogeneous forms and copy numbers of the viral genome. Transcriptionally active integrants are characterized by unmethylated regions in both the viral and human genomes downstream from the viral transcription start site, resulting in HPV-human fusion transcripts. In contrast, integrants without evidence of expression lack consistent methylation patterns. Furthermore, whereas transcriptional dysregulation is limited to genes within 200 kb of an HPV integrant, dysregulation of the human epigenome in the form of allelic differentially methylated regions affects megabase expanses of the genome, irrespective of the integrant's transcriptional status. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.
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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 | 0.001 |
| 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".