Metastasis in endometriosis: targeted sequencing suggests non-malignancy associated endometriosis is capable of wide dissemination
Bibliographic record
Abstract
Objective Multiple forms of endometriosis have been shown to harbour somatic cancer-driver alterations. Previous studies have focused on the inter-patient heterogeneity of genetic alterations in endometriosis, analyzing lesions collected from the same anatomical types of endometriosis across different patients. The aim of our study was to explore intra-patient heterogeneity and potential clonal relationships of multiple anatomically separated lesions of distinct types of endometriosis within a given patient. Materials and methods We examined endometriosis lesions of patients with multiple anatomically separated lesions, and each having at least two distinct types of endometriosis. Samples were assayed with a high sensitivity targeted sequencing panel and findings validated with droplet digital PCR and mutation-surrogate immunohistochemistry. Results 73 endometriosis lesions from 27 patients were analyzed. Results found 13/27 patients had informative somatic driver mutation in endometriosis, of these 9/13 had identical mutations across distinct lesions. Endometriomas showed a higher mutational complexity, with functionally redundant driver mutations within the same gene. Conclusions Our data are consistent with clonality across endometriosis lesions regardless of subtype. Further the finding of redundancy in mutations with the same gene and lesions is also consistent with endometriosis representing an oligoclonal disease with dissemination likely to consist of multiple epithelial clones travelling together. This suggests the current anatomically defined classification of endometriosis does not fully recognize the etiology of the disease. A novel classification should consider genomic and other molecular features. These findings could further contribute to the development of a more personalized endometriosis diagnosis and care. Publication History Article published online: 11 October 2022 © 2022. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".