Morphologic Reproducibility, Genotyping, and Immunohistochemical Profiling Do Not Support a Category of Seromucinous Carcinoma of the Ovary
Bibliographic record
Abstract
The 2014 World Health Organization Classification of Tumors of Female Reproductive Organs endorsed the new category of seromucinous carcinoma, a neoplasm that exhibits morphologic and immunophenotypic overlap with other histotypes of ovarian carcinoma. The goal of this study was to determine whether seromucinous carcinoma was a distinct histotype by assessing its diagnostic reproducibility and comparing its molecular composition to the 5 major histotypes of ovarian carcinoma. Thirty-two tumors diagnosed as seromucinous carcinomas from 2 centers were studied. Eighteen cases were randomly selected for a review set comprising a total of 50 ovarian carcinomas of various histotypes. Morphologic histotype was independently assessed by 4 pathologists. For the 32 seromucinous carcinomas, a histotype-specific immunophenotype was assigned using a diagnostic immunohistochemical panel. Histotype-specific genotype was assigned using a combination of immunohistochemistry and targeted next-generation sequencing for somatic mutations, including genes recurrently mutated in ovarian carcinomas. There was low to modest agreement between pathologists with the reference diagnosis of seromucinous carcinoma, ranging from 39% to 56% for the 4 observers. The immunophenotype was not unique but overlapped predominantly with endometrioid and to a lesser extent with mucinous and low-grade serous carcinoma. Genomic and immunohistochemical alterations were detected in a number of target genes, including KRAS (70%), PIK3CA (37%), PTEN (19%), and ARID1A (16%); no CTNNB1 mutations were identified. Nine cases (30%) harbored concurrent KRAS/PIK3CA mutations. An endometrioid genotype was assigned to 19 cases, a low-grade serous genotype to 9, and a mucinous genotype to 1 and 3 cases were uninformative. Integrating morphology, immunophenotype, and genotyping resulted in reclassifying the seromucinous carcinomas to endometrioid 23/32 (72%), low-grade serous 8/32 (25%), and mucinous 1/32 (3%). The morphologic diagnosis of seromucinous carcinomas is not very reliable and it does not exhibit a distinct immunophenotype or genotype. The molecular features overlap mostly with endometrioid and low-grade serous carcinomas. Our data suggest the category of seromucinous carcinoma be discontinued as ancillary molecular tests can assign cases to one of the major histotypes.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".