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Record W2921549208 · doi:10.1093/jcag/gwz006.274

A275 COMPREHENSIVE GENOMIC ANALYSIS RESULT IN EARLY DETECTION AND IMPLEMENTATION OF IMMUNE CHECK POINT THERAPY TO IMPROVE SURVIVAL FOR PATIENTS WITH INHERITED REPLICATION REPAIR DEFICIENCY GASTROINTESTINAL CANCERS:REPORT FROM THE INTERNATIONAL REPLICATION REPAIR CONSORTIUM

2019· article· en· W2921549208 on OpenAlexaff
Carol Durno, Melyssa Aronson, Melissa Edwards, E Boufett, Uri Tabori

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMicrosatellite instabilityDNA mismatch repairLynch syndromeColorectal cancerCancerMedicineGermline mutationOncologyInternal medicineCancer researchMutationBiologyGeneGeneticsMicrosatellite

Abstract

fetched live from OpenAlex

Understanding tumor biology in patients with gastrointestinal cancers has implications for treatment. Replication repair deficiency (RRD) is a major contributor to carcinogenesis and is enriched in gastrointestinal (GI) malignancies. Germline mutations in the mismatch repair and DNA polymerase genes result in early onset RRD gastrointestinal cancers. In order to better understand RRD tumor biology, develop diagnostic tools, surveillance protocols and novel therapies, an international RRD consortium was established. The aim of the study is to explore diagnostic testing of GI tumors with replication deficiencies and impact clinical outcome. Patients referred to the International RRD Consortium undergo genetic testing to confirm Lynch Syndrome, Constitutional mismatch repair deficiency syndrome (CMMRD) or germline POLE mutations. Tumor analysis include Immunohistochemistry, microsatellite analysis and next generation sequencing. Clinical data are collected as part of the clinical surveillance protocol. Immune Check Point therapy (ICI) is offered to patients with recurrent metastatic tumors. One hundred and forty-nine patients with RRD are registered in the consortium from 40 countries. These patients developed 225 malignancies. Fifty-seven GI cancers were diagnosed in 41 patients (79% colorectal cancer/20.5% small bowel/0.5% gastric cancer). Mean age at first GI cancer was 18.4 years (8.1 - 40.0 years). MSI testing are informative in 23% of patients with CMMRD and POLE mutations. IHC revealed lack of staining in 92% of the corresponding gene (p<0.0001). Tumor mutational burden revealed hypermutation in all cancers. Higher in tumors with both MMRD/POLE mutations. The addition of mutational signatures resulted in 100% sensitivity in detection of germline RRD. Surveillance protocol implemented in 65 individuals detected twenty-one gastrointestinal cancers. All patients are currently alive. Of 45 RRD patients treated with ICI, 9 had gastrointestinal cancers, most with relapsed metastatic disease. Overall survival at 2 years is 89%+/-10% which compared favorably with historical controls. Cancers are common in children and young adults with RRD. Tumor genomic analysis revealed hypermutation and unique tumor signatures which can identify patients who may benefit from targeted therapy with immune check point therapy. MSI testing, the hallmark of Lynch cancers was not sensitive or specific in all RRD tumors. Surveillance protocol and ICI therapy directed to gastrointestinal RRD result in improved survival. It is important to identify patients with inherited GI cancer predisposition syndromes as novel targeted therapy is available. The Zane Cohen Center,

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.260
Teacher spread0.250 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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