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Record W4386317887 · doi:10.1093/dote/doad052.107

268. DEVELOPMENT OF A NOVEL ESOPHAGUS-ON-A-CHIP MODEL: A HIGH-FIDELITY PLATFORM FOR DIRECTING PERSONALIZED THERAPY IN ESOPHAGEAL ADENOCARCINOMA

2023· article· en· W4386317887 on OpenAlexaff
Sanjima Pal, Elee Shimshoni, Salvador Flores-Torres, Julie Bérubé, Mingyang Kong, Betty Giannias, Sean R. R. Hall, Nicholas Bertos, Veena Sangwan, Donald E. Ingber, Lorenzo Ferri

Bibliographic record

VenueDiseases of the Esophagus · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineChemotherapyEsophagusDocetaxelEsophageal cancerPathologyNeoadjuvant therapyAdenocarcinomaCancer researchOncologyInternal medicineCancerBreast cancer

Abstract

fetched live from OpenAlex

Abstract Background 80% of patients diagnosed with esophageal adenocarcinoma (EAC) die of disease. Current standard of care for EAC is systemic cytotoxic, platinum-based neoadjuvant chemotherapy followed by resection and additional rounds of chemotherapy. Locally advanced, resectable patients often fail to respond due to intrinsic and/or acquired chemoresistance. Traditional preclinical models fail to offer alternative salvage options. To our knowledge, this is the first high-fidelity dynamic 3D platform implemented to study esophageal function, pathophysiology, and drug effects. Methods Primary tissues obtained from EAC patients at diagnostic biopsy were propagated into patient-derived organoids (PDOs). The upper (mucosal) channel of the esophagus-chip was designated for PDO-derived epithelial cells, while the lower stromal channel was designated for matched fibroblasts. Autologous cell types were exposed to a physiologically relevant flow of nutrient media and microtissues were formed. Epithelial permeability was determined by cascade blue assay. Using this model, a clinically relevant chemotherapy protocol was administered to study patient-specific tumor response. To determine microtissue development and cellular fate in response to chemotherapy, level of several epithelial/mesenchymal biomarkers were evaluated. Results Study cohort consisted of both chemo-sensitive and -resistant EAC patients. Esophagus-chip models were developed with samples from patient-matched tumor and normal tissue. Chips recapitulated morphological and histological features of their parental tissues. Epithelial barrier integrity was established within 5 days on-chip. Scanning electron microscopy revealed the presence of pleomorphic cells and mature microvilli in EAC-chips. In vitro administration of docetaxel triplet chemotherapy demonstrated efficacy similar to that observed in the clinical setting when assessed directly or indirectly. Confocal imaging revealed treatment-associated differential expression of epithelial (CK7, CK19), and mesenchymal (vimentin) markers. Conclusion 3D-organoids conserve cellular heterogeneity of source patients, whereas esophagus-on-chip expand on this diversity by adding microphysiological relevance, stromal influence & flexible complexity. This high-fidelity biomimetic platform enables clinical mimicry and can predict patient-specific chemosensitivity within a clinically relevant timeframe. This esophagus-chip system is a promising potential replacement for both inefficient preclinical animal models and existing tumor-only avatars lacking stromal and microphysiological context.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.317
Teacher spread0.253 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

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