Molecular Analysis of Mixed Endometrial Carcinomas Shows Clonality in Most Cases
Bibliographic record
Abstract
Mixed endometrial carcinoma refers to a tumor that comprises 2 or more distinct histotypes. We studied 18 mixed-type endometrial carcinomas-11 mixed serous and low-grade endometrioid carcinomas (SC/EC), 5 mixed clear cell and low-grade ECs (CCC/EC), and 2 mixed CCC and SCs (CCC/SC), using targeted next-generation sequencing and immunohistochemistry to compare the molecular profiles of the different histotypes present in each case. In 16 of 18 cases there was molecular evidence that both components shared a clonal origin. Eight cases (6 EC/SC, 1 EC/CCC, and 1 SC/CCC) showed an SC molecular profile that was the same in both components. Five cases (3 CCC/EC and 2 SC/EC) showed a shared endometrioid molecular profile and identical mismatch-repair protein deficiency in both components. A single SC/EC case harbored the same POLE exonuclease domain mutation in both components. One SC/CCC and 1 EC/CCC case showed both shared and unique molecular features in the 2 histotype components, suggesting early molecular divergence from a common clonal origin. In 2 cases, there were no shared molecular features, and these appear to be biologically unrelated synchronous tumors. Overall, these results show that the different histologic components in mixed endometrial carcinomas typically share the same molecular aberrations. Mixed endometrial carcinomas most commonly occur through morphologic mimicry, whereby tumors with serous-type molecular profile show morphologic features of EC or CCC, or through underlying deficiency in DNA nucleotide repair, with resulting rapid accrual of mutations and intratumoral phenotypic heterogeneity. Less commonly, mixed endometrial carcinomas are the result of early molecular divergence from a common progenitor clone or are synchronous biologically unrelated tumors (collision tumors).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".