No evidence for the presence of Epstein-Barr virus in squamous cell carcinoma of the mobile tongue
Bibliographic record
Abstract
Squamous cell carcinoma of the head and neck (SCCHN) comprises a large group of cancers in the oral cavity and nasopharyngeal area that typically arise in older males in association with alcohol/tobacco usage. Within the oral cavity, the mobile tongue is the most common site for tumour development. The incidence of tongue squamous cell carcinoma (TSCC) is increasing in younger people, which has been suggested to associate with a viral aetiology. Two common human oncogenic viruses, human papilloma virus (HPV) and Epstein-Barr virus (EBV) are known causes of certain types of SCCHN, namely the oropharynx and nasopharynx, respectively. EBV infects most adults worldwide through oral transmission and establishes a latent infection, with sporadic productive viral replication and release of virus in the oral cavity throughout life. In view of the prevalence of EBV in the oral cavity and recent data indicating that it infects tongue epithelial cells and establishes latency, we examined 98 cases of primary squamous cell carcinoma of the mobile tongue and 15 cases of tonsillar squamous cell carcinoma for the presence of EBV-encoded RNAs (EBERs), EBV DNA and an EBV-encoded protein, EBNA-1. A commercially available in situ hybridisation kit targeting EBER transcripts (EBER-ISH) showed a positive signal in the cytoplasm and/or nuclei of tumour cells in 43% of TSCCs. However, application of control probes and RNase A digestion using in-house developed EBER-ISH showed identical EBER staining patterns, indicating non-specific signals. PCR analysis of the BamH1 W repeat sequences did not identify EBV genomes in tumour samples. Immunohistochemistry for EBNA-1 was also negative. These data exclude EBV as a potential player in TSCC in both old and young patients and highlight the importance of appropriate controls for EBER-ISH in investigating EBV in human diseases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".