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Record W2314787270 · doi:10.1097/pas.0000000000000298

The Histomorphology of Lynch Syndrome–associated Ovarian Carcinomas

2014· article· en· W2314787270 on OpenAlexaff
M. Herman Chui, Paul M. Ryan, Jordan Radigan, Sarah E. Ferguson, Aaron Pollett, Melyssa Aronson, Kara Semotiuk, Spring Holter, Keiyan Sy, Janice S. Kwon, Anita Soma, Naveena Singh, Steven Gallinger, Patricia Shaw, Jocelyne Arseneau, William D. Foulkes, C. Blake Gilks, Blaise Clarke

Bibliographic record

VenueThe American Journal of Surgical Pathology · 2014
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill University Health CentreUniversity of British ColumbiaUniversity Health NetworkBC Cancer AgencyUniversity of Toronto
Fundersnot available
KeywordsMicrosatellite instabilitySerous carcinomaLynch syndromeSerous fluidMedicinePathologyClear cell carcinomaImmunohistochemistryCarcinomaH&E stainOvarian cancerDNA mismatch repairGermline mutationAnatomical pathologyClear cellOvarian carcinomaCancerOncologyInternal medicineBiologyMutationColorectal cancerMicrosatelliteGenetics

Abstract

fetched live from OpenAlex

Women with Lynch syndrome (LS) are at increased risk for the development of epithelial ovarian cancer (OC). Analogous to previous studies on BRCA1/2 mutation carriers, there is evidence to suggest a histotype-specific association in LS-associated OCs (LS-OC). Whereas the diagnosis of high-grade serous carcinoma is an indication for BRCA1/2 germline testing, in contrast, there are no screening guidelines in place for triaging OC patients for LS testing based on histotype. We performed a centralized pathology review of tumor subtype on 20 germline mutation-confirmed LS-OCs, on the basis of morphologic assessment of hematoxylin and eosin-stained slides, with confirmation by immunohistochemistry when necessary. Results from mismatch-repair immunohistochemistry (MMR-IHC) and microsatellite instability (MSI) phenotype status were documented, and detailed pedigrees were analyzed to determine whether previously proposed clinical criteria would have selected these patients for genetic testing. Review of pathology revealed all LS-OCs to be either pure endometrioid carcinoma (14 cases), mixed carcinoma with an endometrioid component (4 cases), or clear cell carcinoma (2 cases). No high-grade or low-grade serous carcinomas or mucinous carcinomas of intestinal type were identified. Tumor-infiltrating lymphocytes were prominent (≥40 per 10 high-powered fields) in 2 cases only. With the exception of 1 case, all tumors tested for MMR-IHC or MSI had an MMR-deficient phenotype. Within this cohort, 50%, 55%, 65%, and 85% of patients would have been selected for genetic workup by Amsterdam II, revised Bethesda Guidelines, SGO 10% to 25%, and SGO 5% to 10% criteria, respectively, with <60% of index or sentinel cases detected by any of these schemas. To further support a subtype-driven screening strategy, MMR-IHC reflex testing was performed on all consecutive non-serous OCs diagnosed at 1 academic hospital over a 2-year period; MMR deficiency was identified in 10/48 (21%) cases, all with endometrioid or clear cell histology. We conclude that there is a strong association between endometrioid and clear cell ovarian carcinomas and hereditary predisposition due to MMR gene mutation. These findings have implications for the role of tumor subtype in screening patients with OC for further genetic testing and support reflex MMR-IHC and/or MSI testing for newly diagnosed cases of endometrioid or clear cell ovarian carcinoma.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.012
GPT teacher head0.256
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations121
Published2014
Admission routes1
Has abstractyes

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