c-KIT Analysis and Targeted Molecular Sequencing of Mesonephric Carcinomas of the Female Genital Tract
Bibliographic record
Abstract
Mesonephric carcinoma is a rare malignancy, thought to derive from Wolffian remnants. To date, no targeted molecular therapeutic options have been identified. On the basis of limited case reports, c-KIT immunohistochemical expression has been reported in female adnexal tumors of Wolffian origin, and targeted therapy with Imatinib has been attempted with mixed success. Currently, it is unclear whether c-KIT immunohistochemical expression is seen in mesonephric carcinoma, a tumor that is thought to be related to female adnexal tumors of Wolffian origin, and how this correlates with KIT mutational status. In this study, we assessed the immunohistochemical expression of c-KIT and KIT mutational status, in a series of 13 mesonephric neoplasms (5 cervical [including 2 cervical carcinosarcomas], 3 uterine corpora, 4 ovarian, and 1 vaginal/pelvic). The intensity of staining and proportion of cells showing cytoplasmic/membranous staining for c-KIT were recorded. KIT was sequenced using a next-generation sequencing panel that targeted 120 hotspots and 17 exons in 33 known actionable cancer genes. This panel included KIT exons 9, 11, and 13, and 6 hotspots (T670, D816, D820, N822, Y823, A829). Although c-KIT immunohistochemical expression was observed in the majority of mesonephric carcinomas (10/12 cases; 83%), no KIT mutations were detected. This cautions pathologists against the use of c-KIT immunohistochemistry as a surrogate marker for KIT-activating mutations in this setting. Consistent with previous studies, the majority of mesonephric neoplasms (10/13; 77%) harbored KRAS mutations. Additional mutations were found in CTNNB1 (2/13, 15%), TP53 (2/13, 15%), and PIK3CA (1/13, 8%).
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 | 0.001 |
| 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 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".