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Record W2907244787 · doi:10.1200/jco.18.00474

Functional Repair Assay for the Diagnosis of Constitutional Mismatch Repair Deficiency From Non-Neoplastic Tissue

2019· article· en· W2907244787 on OpenAlexafffund
Andrew Y. Shuen, Stella Lanni, Gagan B. Panigrahi, Melissa Edwards, Lisa Yu, Brittany Campbell, Ariane Mandel, Cindy Zhang, Nataliya Zhukova, Musa Alharbi, Mark L. Bernstein, Daniel C. Bowers, Sara Carroll, Kristina A. Cole, Shlomi Constantini, Bruce Crooks, Rina Dvir, Roula Farah, Nobuko Hijiya, Ben George, Theodore W. Laetsch, Valérie Larouche, Scott Lindhorst, Rebecca C. Luiten, Vanan Magimairajan, Gary Mason, Warren Mason, Oz Mordechai, Naureen Mushtaq, Garth Nicholas, Michael Oren, Laura Palma, Luis Alberto Pedroza, Jagadeesh Ramdas, David Samuel, Kami Wolfe Schneider, Andrea Seeley, Kara Semotiuk, Ashraf Shamvil, David Sumerauer, Helen Toledano, Patrick Tomboc, Margaret E. Wierman, An Van Damme, Yi‐Yen Lee, Michal Zápotocký, Éric Bouffet, Carol Durno, Melyssa Aronson, Steve Gallinger, William D. Foulkes, David Malkin, Uri Tabori, Christopher E. Pearson

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsPrincess Margaret Cancer CentreMount Sinai HospitalMcGill UniversityMcGill University Health CentreOttawa HospitalUniversity of ManitobaUniversité LavalToronto General HospitalSickKids FoundationUniversity of TorontoDalhousie UniversityHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsPMS2MedicineMSH6DNA mismatch repairLynch syndromeMSH2CancerMLH1Cancer researchInternal medicineColorectal cancer

Abstract

fetched live from OpenAlex

PURPOSE: Constitutional mismatch repair deficiency (CMMRD) is a highly penetrant cancer predisposition syndrome caused by biallelic mutations in mismatch repair (MMR) genes. As several cancer syndromes are clinically similar, accurate diagnosis is critical to cancer screening and treatment. As genetic diagnosis is confounded by 15 or more pseudogenes and variants of uncertain significance, a robust diagnostic assay is urgently needed. We sought to determine whether an assay that directly measures MMR activity could accurately diagnose CMMRD. PATIENTS AND METHODS: In vitro MMR activity was quantified using a 3'-nicked G-T mismatched DNA substrate, which requires MSH2-MSH6 and MLH1-PMS2 for repair. We quantified MMR activity from 20 Epstein-Barr virus-transformed lymphoblastoid cell lines from patients with confirmed CMMRD. We also tested 20 lymphoblastoid cell lines from patients who were suspected for CMMRD. We also characterized MMR activity from patients with neurofibromatosis type 1, Li-Fraumeni syndrome, polymerase proofreading-associated cancer syndrome, and Lynch syndrome. RESULTS: All CMMRD cell lines had low MMR activity (n = 20; mean, 4.14 ± 1.56%) relative to controls (n = 6; mean, 44.00 ± 8.65%; P < .001). Repair was restored by complementation with the missing protein, which confirmed MMR deficiency. All cases of patients with suspected CMMRD were accurately diagnosed. Individuals with Lynch syndrome (n = 28), neurofibromatosis type 1 (n = 5), Li-Fraumeni syndrome (n = 5), and polymerase proofreading-associated cancer syndrome (n = 3) had MMR activity that was comparable to controls. To accelerate testing, we measured MMR activity directly from fresh lymphocytes, which yielded results in 8 days. CONCLUSION: On the basis of the current data set, the in vitro G-T repair assay was able to diagnose CMMRD with 100% specificity and sensitivity. Rapid diagnosis before surgery in non-neoplastic tissues could speed proper therapeutic management.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.420
Teacher spread0.322 · 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 designBench or experimental
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

Citations34
Published2019
Admission routes2
Has abstractyes

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Same venueJournal of Clinical OncologySame topicGenetic factors in colorectal cancerFrench-language works237,207