Monitoring mouse papillomavirus-associated cancer development using longitudinal Pap smear screening
Bibliographic record
Abstract
A substantial percentage of the population remains at risk for cervical cancer due to pre-existing human papillomavirus (HPV) infections, despite prophylactic vaccines. Early diagnosis and treatment are crucial for better disease outcomes. The development of new treatments heavily relies on suitable preclinical model systems. Recently, we established a mouse papillomavirus (MmuPV1) model that is relevant to HPV genital pathogenesis. In the current study, we validated the use of Papanicolaou (Pap) smears, a valuable early diagnostic tool for detecting HPV cervical cancer, to monitor disease progression in the MmuPV1 mouse model. Biweekly cervicovaginal swabs were collected from the MmuPV1-infected mice for viral DNA quantitation and cytology assessment. The Pap smear slides were evaluated for signs of epithelial cell abnormalities using the 2014 Bethesda system criteria. Tissues from the infected mice were harvested at various times post-viral infection for additional histological and virological assays. Over time, increased viral replication was consistent with higher levels of viral DNA, and it coincided with an uptick in epithelial cell abnormalities with higher severity scores noted as early as 10 weeks after viral infection. The cytological results also correlated with the histological evaluation of tissues harvested simultaneously. Both immunocompromised and immunocompetent mice with squamous cell carcinoma (SCC) cytology also developed vaginal SCCs. Notably, samples from the MmuPV1-infected mice exhibited similar cellular abnormalities compared to the corresponding human samples at similar disease stages. Hence, Pap smear screening proves to be an effective tool for the longitudinal monitoring of disease progression in the MmuPV1 mouse model. IMPORTANCE: Papanicolaou (Pap) smear has saved millions of women's lives as a valuable early screening tool for detecting human papillomavirus (HPV) cervical precancers and cancer. However, more than 200,000 women in the United States alone remain at risk for cervical cancer due to pre-existing HPV infection-induced precancers, as there are currently no effective treatments for HPV-associated precancers and cancers other than invasive procedures including a loop electrosurgical excision procedure (LEEP) to remove abnormal tissues. In the current study, we validated the use of Pap smears to monitor disease progression in our recently established mouse papillomavirus model. To the best of our knowledge, this is the first study that provides compelling evidence of applying Pap smears from cervicovaginal swabs to monitor disease progression in mice. This HPV-relevant cytology assay will enable us to develop and test novel antiviral and anti-tumor therapies using this model to eliminate HPV-associated diseases and cancers.
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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 | 0.000 |
| 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) | 0.001 | 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 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".