The tumor immune microenvironments of <scp>HPV</scp><sup>+</sup> and <scp>HPV</scp><sup>−</sup> head and neck cancers
Bibliographic record
Abstract
Abstract Human papillomaviruses (HPVs) are the etiological agent of a significant, and increasing, fraction of head and neck squamous cell carcinomas (HNSCC)—a heterogenous group of malignancies in the head and neck region. HPV infection accounts for approximately 25% of all cases, with the remainder typically caused by smoking and excessive alcohol consumption. These distinct etiologies lead to profound clinical and immunological differences between HPV‐positive (HPV+) and HPV‐negative (HPV−) HNSCC, likely related to the expression of exogenous viral antigens in the HPV+ subtype. Specifically, HPV+ HNSCC patients generally exhibit better treatment response compared to those with HPV− disease, leading to a more favorable prognosis, with lower recurrence rate, and longer overall survival time. Importantly, a plethora of studies have illustrated that the tumor immune microenvironment (TIME) of HPV+ HNSCC has a strikingly distinct immune composition to that of its HPV− counterpart. The HPV+ TIME is characterized as being immunologically “hot,” with more immune infiltration, higher levels of T‐cell activation, and higher levels of immunoregulation compared to the more immunologically “cold” HPV− TIME. In general, cancers with an immune “hot” TIME exhibit better treatment response and superior clinical outcomes in comparison to their immune “cold” counterparts. Indeed, this phenomenon has also been observed in HPV+ HNSCC patients, highlighting the critical role of the TIME in influencing prognosis, and further validating the use of cancer therapies that capitalize on the mobilization and/or modulation of the TIME. This article is categorized under: Cancer > Molecular and Cellular Physiology Infectious Diseases > Molecular and Cellular Physiology
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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 | 0.000 |
| 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 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".