MétaCan
Menu
← Back to cohort

Comprehensive molecular assessment of mismatch repair deficiency in Lynch-associated ovarian cancers using next-generation sequencing (NGS) panel.

2020· article· en· W3030237145 on OpenAlexaffabout
Rachel Soyoun Kim, Leslie E. Oldfield, Alicia Tone, Aaron Pollett, Emily Van de Laar, Stephanie Pedersen, Johanna Wellum, Blaise Clarke, Trevor J. Pugh, Sarah E. Ferguson

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity Health NetworkMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsLynch syndromeMedicineEndometrial cancerSerous fluidEpigeneticsOncologyOvarian cancerGermline mutationCancerDNA mismatch repairGermlineInternal medicineCancer researchMutationGeneticsBiologyGene

Abstract

fetched live from OpenAlex

1523 Background: Abnormalities in mismatch repair (MMR) gene may be the result of pathogenic germline (Lynch syndrome) and somatic mutations as well as epigenetic events. Abnormalities in MMR have been described in non-serous/non-mucinous ovarian cancer (OC) but few studies have examined the causes of these MMR defects (MMRd). To address this, we have completed targeted mutational and methylation sequencing on MMRd OC cases. Methods: Women with newly diagnosed non-serous/mucinous OC (N = 215) were prospectively recruited from three cancer centers in Ontario, Canada between 2015-18. Tumors were reflexively assessed for MMR protein expression by immunohistochemistry. Tumor DNA was extracted from macrodissected MMRd cases and MMR-intact (MMRi) controls following pathology review. Matched tumor-normal samples were run on a custom NGS panel to identify germline and somatic mutations, copy number variants, rearrangements and promoter methylation in MMR and associated genes. Results: Of the 215 women enrolled in our study, 185 (86%) had OC alone and 30 (14%) had synchronous OC and endometrial cancer. Twenty-eight (13%) cases were MMRd, 11 of which were synchronous. The MMRd cohort had median age of 52.5 years, with mostly stage I (N = 14; 50%), grade 1 or 2 disease (N = 18; 64%) with endometrioid histotype (N = 18; 64%). One patient had recurrence after median follow-up of 33.6 months (13.2-93.6). There was no significant difference in overall/progression-free survival between the MMRd and MMRi patients. Using the NGS panel, Lynch syndrome (LS) was detected in 39% of MMRd cases (11/28; 7 OC and 4 synchronous): 7 MSH6, 2 MLH1, 1 PMS2, and 1 MSH2. Clinical germline sequencing was performed on all cases and verified panel findings. An explanation for the observed MMR phenotype was available for 18/20 deficient cases, including 9/10 MLH1−/PMS2− (7 somatic methylation, 1 bi-allelic somatic deletion, 1 germline mutation), 0/1 PMS2−, 6/7 MSH6− (6 germline mutations) and 2/2 MSH2−/MSH6− (1 germline mutation, 1 bi-allelic somatic mutation). Concordance between clinical and research panel sequencing results was 90%. None of the germline mutations were missed by the panel. Conclusions: Use of our custom NGS panel allows for the streamlined assessment of hereditary and somatic causes of MMR deficiency in OC and may be an attractive screening strategy for LS in this population.

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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.443
GPT teacher head0.483
Teacher spread0.040 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicGenetic factors in colorectal cancer→French-language works237,207→