In‐depth molecular profiling of the biphasic components of uterine carcinosarcomas
Bibliographic record
Abstract
Uterine carcinosarcoma is a clinically aggressive malignancy composed of a mix of carcinomatous and sarcomatous elements. We performed targeted next-generation sequencing of 27 uterine cancer and sarcoma genes together with immunohistochemical analyses of selected proteins in 30 uterine carcinosarcomas. This included 13 cases in which the distinct carcinoma and sarcoma components were sequenced separately and 10 cases where the metastatic tumours were analysed in addition to the primary tumours. We identified non-synonymous somatic mutations in 90% of the cases, with 27 of 30 cases (90%) harbouring TP53 alterations. The PI3K pathway was the most commonly mutated signalling pathway with mutations identified in PIK3CA, PTEN, PIK3R1, and/or PIK3R2 in two-thirds of the cases. Mutations in FBXW7, PPP2R1A, ARID1A and KRAS were demonstrated in a minority of cases. In cases where the carcinomatous and sarcomatous components were separately analysed, most of the mutations identified were present in both components, indicating a common origin for the two components. Furthermore, the same TP53 alterations and/or PI3K pathway mutations seen in the primary tumours were also identified in the metastatic sites. Overall, carcinosarcomas exhibited heterogeneous molecular features that resemble the heterogeneity seen in endometrial carcinomas, with some showing endometrioid carcinoma-like and others showing serous carcinoma-like mutation profiles. While patients with serous-like tumours presented more frequently with advanced-stage disease compared to patients with endometrioid-like tumours, there was no statistical difference in outcome between the two groups. Our results provide insights into the oncogenesis of uterine carcinosarcoma and identify targetable mutations that represent early oncogenic events. The findings of the different molecular types of uterine carcinosarcoma that parallel the different molecular types in endometrial carcinoma may have future treatment implications with targeted therapies.
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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 | 0.002 | 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".