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Record W4392642735 · doi:10.1038/s41698-024-00537-6

Biallelic EPCAM deletions induce tissue-specific DNA repair deficiency and cancer predisposition

2024· article· en· W4392642735 on OpenAlexafffund
Victoria J. Forster, Melyssa Aronson, C. Zhang, Jiil Chung, Sumedha Sudhaman, Melissa A. Galati, Jacalyn Kelly, Logine Negm, Ayse B. Ercan, Lucie Stengs, Carol Durno, Melissa Edwards, Martin Komosa, Leslie E. Oldfield, Nuno M. Nunes, Stephanie Pedersen, Johanna Wellum, Iram Siddiqui, Vanessa Bianchi, Brent R. Weil, Victor L. Fox, Trevor J. Pugh, Junne Kamihara, Uri Tabori

Bibliographic record

Venuenpj Precision Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity Health NetworkUniversity of TorontoSickKids FoundationSinai Health SystemHospital for Sick Children
FundersStand Up To CancerCIHR Skin Research Training CentreCanadian Institutes of Health ResearchHospital for Sick ChildrenGovernment of Canada
KeywordsOrganoidMSH2CarcinogenesisBiologyCancer researchDNA mismatch repairCell biologyHaploinsufficiencyMolecular biologyCancerGeneticsPhenotypeColorectal cancerGene

Abstract

fetched live from OpenAlex

Abstract We report a case of Mismatch Repair Deficiency (MMRD) caused by germline homozygous EPCAM deletion leading to tissue-specific loss of MSH2. Through the use of patient-derived cells and organoid technologies, we performed stepwise in vitro differentiation of colonic and brain organoids from reprogrammed EPCAMdel iPSC derived from patient fibroblasts. Differentiation of iPSC to epithelial-colonic organoids exhibited continuous increased EPCAM expression and hypermethylation of the MSH2 promoter. This was associated with loss of MSH2 expression, increased mutational burden, MMRD signatures and MS-indel accumulation, the hallmarks of MMRD. In contrast, maturation into brain organoids and examination of blood and fibroblasts failed to show similar processes, preserving MMR proficiency. The combined use of iPSC, organoid technologies and functional genomics analyses highlights the potential of cutting-edge cellular and molecular analysis techniques to define processes controlling tumorigenesis and uncovers a new paradigm of tissue-specific MMRD, which affects the clinical management of these patients.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.362
Teacher spread0.324 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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Same venuenpj Precision OncologySame topicGenetic factors in colorectal cancerFrench-language works237,207