BK Polyomavirus Genomic Integration and Large T Antigen Expression: Evolving Paradigms in Human Oncogenesis
Bibliographic record
Abstract
Human polyomaviruses are ubiquitous, with primary infections that typically occur during childhood and subsequent latency that may last a lifetime. Polyomavirus-mediated disease has been described in immunocompromised patients; its relationship to oncogenesis is poorly understood. We present deep sequencing data from a high-grade BK virus-associated tumor expressing large T antigen. The carcinoma arose in a kidney allograft 6 years after transplantation. We identified a novel genotype 1a BK polyomavirus, called Chapel Hill BK polyomavirus 2 (CH-2), that was integrated into the BRE gene in chromosome 2 of tumor cells. At the chromosomal integration site, viral break points were found, disrupting late BK gene sequences encoding capsid proteins VP1 and VP2/3. Immunohistochemistry and in situ hybridization studies demonstrated that the integrated BK virus was replication incompetent. We propose that the BK virus CH-2 was integrated into the human genome as a concatemer, resulting in alterations of feedback loops and overexpression of large T antigen. Collectively, these findings support the emerging understanding that viral integration is a nearly ubiquitous feature in polyomavirus-associated malignancy and that unregulated large T antigen expression drives a proliferative state that is conducive to oncogenesis. Based on the current observations, we present an updated model of polyomavirus-mediated oncogenesis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".