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Record W2987794972 · doi:10.1053/j.gastro.2019.11.019

Drug Screen Identifies Leflunomide for Treatment of Inflammatory Bowel Disease Caused by TTC7A Deficiency

2019· article· en· W2987794972 on OpenAlexafffund
Sasha Jardine, Sierra Anderson, Stephen Babcock, Gabriella Leung, Jie Pan, Neel Dhingani, Neil Warner, Conghui Guo, Iram Siddiqui, Daniel Kotlarz, James J. Dowling, Roman A. Melnyk, Scott B. Snapper, Christoph Klein, Jay R. Thiagarajah, Aleixo M. Muise

Bibliographic record

VenueGastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicIntestinal Malrotation and Obstruction Disorders
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenSickKids Foundation
FundersCanadian Institutes of Health ResearchAmerican Gastroenterological AssociationLeona M. and Harry B. Helmsley Charitable TrustCanada Research ChairsNational Institute of Diabetes and Digestive and Kidney DiseasesBoston Children's Hospital
KeywordsLeflunomideInflammatory bowel diseaseDrugMedicineDiseaseDrug treatmentGastroenterologyInternal medicinePharmacologyMethotrexate

Abstract

fetched live from OpenAlex

Background & Aims Mutations in the tetratricopeptide repeat domain 7A gene ( TTC7A ) cause intestinal epithelial and immune defects. Patients can become immune deficient and develop apoptotic enterocolitis, multiple intestinal atresia, and recurrent intestinal stenosis. The intestinal disease in patients with TTC7A deficiency is severe and untreatable, and it recurs despite resection or allogeneic hematopoietic stem cell transplant. We screened drugs for those that prevent apoptosis of in cells with TTC7A deficiency and tested their effects in an animal model of the disease. Methods We developed a high-throughput screen to identify compounds approved by the US Food and Drug Administration that reduce activity of caspases 3 and 7 in TTC7A - knockout (TTC7A-KO) HAP1 (human haploid) cells and reduce the susceptibility to apoptosis. We validated the effects of identified agents in HeLa cells that stably express TTC7A with point mutations found in patients. Signaling pathways in cells were analyzed by immunoblots. We tested the effects of identified agents in zebrafish with disruption of ttc7a , which develop intestinal defects, and colonoids derived from biopsy samples of patients with and without mutations in TTC7A . We performed real-time imaging of intestinal peristalsis in zebrafish and histologic analyses of intestinal tissues from patients and zebrafish. Colonoids were analyzed by immunofluorescence and for ion transport. Results TTC7A-KO HAP1 cells have abnormal morphology and undergo apoptosis, due to increased levels of active caspases 3 and 7. We identified drugs that increased cell viability; leflunomide (used to treat patients with inflammatory conditions) reduced caspase 3 and 7 activity in cells by 96%. TTC7A-KO cells contained cleaved caspase 3 and had reduced levels of phosphorylated AKT and X-linked inhibitor of apoptosis (XIAP); incubation of these cells with leflunomide increased levels of phosphorylated AKT and XIAP and reduced levels of cleaved caspase 3. Administration of leflunomide to ttc7a –/– zebrafish increased gut motility, reduced intestinal tract narrowing, increased intestinal cell survival, increased sizes of intestinal luminal spaces, and restored villi and goblet cell morphology. Exposure of patient-derived colonoids to leflunomide increased cell survival, polarity, and transport function. Conclusions In a drug screen, we identified leflunomide as an agent that reduces apoptosis and activates AKT signaling in TTC7A-KO cells. In zebrafish with disruption of ttc7a , leflunomide restores gut motility, reduces intestinal tract narrowing, and increases intestinal cell survival. This drug might be repurposed for treatment of TTC7A deficiency.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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".

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Citations66
Published2019
Admission routes2
Has abstractyes

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