HPV-Positive and -Negative Cervical Cancers Are Immunologically Distinct
Bibliographic record
Abstract
Although infection with human papillomavirus (HPV) is associated with nearly all cervical cancers (CC), a small proportion are HPV-negative. Recently, it has become clear that HPV-negative CC represent a distinct disease phenotype compared to HPV-positive disease and exhibit increased mortality. In addition, variations between different HPV types associated with CC have been linked to altered molecular pathology and prognosis. We compared the immune microenvironments of CC caused by HPV α9 species (HPV16-like), HPV α7 species (HPV18-like) and HPV-negative disease. HPV-negative CC appeared distinct from other subtypes, with greatly reduced levels of lymphocyte infiltration compared to either HPV α9 or α7 CC. Besides reduced levels of markers indicative of B, T, and NK lymphocytes, the expression of T-cell effector molecules, activation/exhaustion markers, and T-cell receptor diversity were also significantly lower in HPV-negative CC. Interestingly, HPV-negative CC expressed much higher levels of potential neoantigens than HPV-positive CC. These results identify profound differences between the immune landscape of HPV-positive and HPV-negative CC as well as modest differences between HPV α9 and α7 CC. These differences may contribute to altered patient outcomes between HPV-negative and HPV-positive CC and potentially between CC associated with different HPV types.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".