<scp> <i>CDKN2A</i> </scp> deletion in p16‐negative/ <scp>HPV</scp> ‐positive head and neck squamous cell carcinoma: Highlighting the molecular basis behind the limitation of relying on p16 immunohistochemistry as a surrogate marker for <scp>HPV</scp> involvement
Bibliographic record
Abstract
AIMS: Immunohistochemistry (IHC) for p16 is widely used as a surrogate marker for HPV involvement in oropharyngeal squamous cell carcinoma (OPSCC), among other tumours. Confirming HPV status in OPSCC is critical, as HPV-positive tumours have better overall survival and may require de-escalated therapy compared to HPV-independent OPSCC in the future. However, discordance exists between p16 and HPV, and direct HPV testing is occasionally required to ensure an accurate diagnosis. The aim of this study is to highlight the genomic basis behind the limitation of relying on p16 IHC as a surrogate marker for HPV involvement. METHODS AND RESULTS: Through a multi-institutional collaboration, this case series compiled four patients with a 'false' negative p16 staining pattern in HPV-positive non-keratinizing head and neck squamous cell carcinoma. All cases demonstrated minimal to no p16 IHC staining and were positive for HPV by direct RNA in situ hybridization. Through CDKN2A fluorescence in situ hybridization testing, three patients demonstrated a homozygous deletion of CDKN2A and one demonstrated a heterozygous deletion. CONCLUSIONS: This series highlights the genomic basis for the 'false' negative p16 results, raising awareness of a significant diagnostic pitfall while emphasizing the importance of careful consideration of clinicopathologic parameters in the clinical workup of these cases.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".