Prognostic significance of high-risk human papilloma virus (HPV), p16, and p53 status in women with vulvar squamous cell carcinoma (VSCC).
Bibliographic record
Abstract
5105 Background: The incidence of VSCC is increasing. Studies suggest the presence of two histologically and molecularly distinct subsets of VSCC; one contingent on and another independent of HPV infection. However, it is uncertain if HPV status has prognostic significance. HPV oncoproteins can result in degradation of the tumor suppressor p53, cell cycle deregulation and abnormal expression of cyclin dependant kinase inhibitor p16. The aim of this study was to investigate HPV infection, p16 and p53 in relation to clinical parameters in women with VSCC. Methods: Sequential cases of VSCC from patients (pts) treated at Princess Margaret Hospital (PMH) from 2000 to 2008 were reviewed. HPV infection was evaluated by Roche Linear array. A tissue microarray was constructed. p16 and p53 immunohistochemistry was performed. Clinical data was abstracted from medical records and PMH Cancer Database. Survival analysis was performed using Kaplan-Meier curves and log rank test. Results: We identified124 pts with VSCC. HPV was detected in 43/123 (35%) pts (median age 71 ± 16 yrs). HPV16 was the most common serotype (38/43; 88.4%). p16 was expressed in 30/115 (26%) pts and p53 in 59/117 (50.4%) pts. Median age of pts was not different in relation to HPV, p16 and p53 status. Expression of p16 (p<0.0001) and loss of p53 (p=0.007) were associated with HPV infection. Pts with HPV positive tumors were less likely to recur (recurrence rate at 5 years (RR) 12.5% vs 50.3%, p=0.009). HPV positive VSCC were not associated with better 5 yr disease free survival (DFS), 58% vs 31%; p=0.15, or overall survival (OS), 61% vs 61% ; p=0.94. p16 positive tumors had a lower RR at 5 yrs, 23.8% vs 59%, p=0.006 and better 5yr DFS (61% vs 27% ; p=0.009) but not significant for OS (65% vs 59%; p=0.94). Among pts with HPV positive VSCC, OS and DFS were not different between p16 positive and negative VSCC. In the 46 pts treated with radiotherapy, HPV and p16 positive tumors were associated with a lower RR (p=0.004 and 0.005). p53 expression was not prognostic in any pt group. Conclusions: Women with HPV-positiveVSCC have a lower risk of disease recurrence. p16-expressing VSCC are associated with reduced disease recurrence and improved DFS.
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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 | 0.001 |
| 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 | 0.000 |
| 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".