Molecular correlates of invasion pattern in HPV‐associated endocervical adenocarcinoma: emergence of two distinct risk‐stratified tiers
Bibliographic record
Abstract
BACKGROUND: The pattern-based (Silva) classification of invasive human papilloma virus (HPV)-associated endocervical adenocarcinomas (HPVA) is an established and reproducible method to predict outcomes for this otherwise stage-dependent group of tumours. Previous studies utilising targeted sequencing have shown a correlation between mutational profiles and an invasive pattern. However, such correlation has not been explored using comprehensive molecular testing. DESIGN: Clinicopathologic data including invasive pattern (Silva groups A, B, and C) was collected for a cohort of invasive HPVA, which previously underwent massive parallel sequencing using a panel covering 447 genes. Pathogenic alterations, molecular signatures, tumour mutational burden (TMB), and copy number alterations (CNA) were correlated with pattern of invasion. RESULTS: Forty five HPVA (11 pattern A, 17 pattern B, and 17 pattern C tumours) were included. Patients with pattern A presented at stage I with no involved lymph nodes or evidence of recurrence (in those with >2 months of follow-up). Patterns B and C patients also mostly presented at stage I with negative lymph nodes, but had a greater frequency of recurrence; 3/17 pattern B and 1/17 pattern C HPVAs harboured lymphovascular space invasion (LVI). An APOBEC mutational signature was detected only in Silva pattern C tumours (5/17), and pathogenic PIK3CA changes were detected only in destructively invasive HPVA (patterns B and C). When cases were grouped as low-risk (pattern A and pattern B without LVI) and high-risk (pattern B with LVI and pattern C), high-risk tumours were enriched in mutations in PIK3CA, ATRX, and ERBB2. There was a statistically significant difference in TMB between low-risk and high-risk pattern tumours (P = 0.006), as well as between Pattern C tumours with and without an APOBEC signature (P = 0.002). CNA burden increased from pattern A to C. CONCLUSION: Our findings further indicate that key molecular events in HPVA correlate with the morphologic invasive properties of the tumour and their aggressiveness. Pattern B tumours with LVI clustered with pattern C tumours, whereas pattern B tumours without LVI approached pattern A genotypically. Our study provides a biologic foundation for consolidating the Silva system into low-risk (pattern A + B without LVI) and high-risk (pattern B with LVI and pattern C) categories.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".