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Record W4229874701 · doi:10.1093/jcag/gwz006.007

A8 THE ROLE OF CYCLOOXYGENASE IN COLITIS-ASSOCIATED CANCER

2019· article· en· W4229874701 on OpenAlexaffabout
Hayley Good, Alice E. Shin, L Zhang, Elena N. Fazio, David Meriwether, Srivinasa T. Reddy, Timothy C. Wang, Samuel Asfaha

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsAzoxymethaneCelecoxibMedicineColorectal cancerColitisCancerRofecoxibCancer researchMouse model of colorectal and intestinal cancerCyclooxygenaseSulindacCarcinogenesisInflammatory bowel diseaseInflammationPharmacologyImmunologyInternal medicineDiseaseBiologyEnzyme

Abstract

fetched live from OpenAlex

Colorectal cancer (CRC) is the 2nd leading cause of cancer death in Canada. Inflammatory bowel disease (IBD), a chronic state of colonic inflammation, is a major risk factor for CRC. Despite the clear link between inflammation and cancer, the mechanism by which colitis leads to cancer is unknown. Doublecortin-like kinase-1 (Dclk1) is a marker of tuft cells, a rare and ill-defined cell type of the colon. We previously showed that Dclk1+ cells are quiescent, long-lived, and remain resistant to proliferation even upon mutation of the tumor suppressor APC. However, APC-mutated tuft cells become powerful cancer-initiating cells upon exposure to inflammation, but the mechanism by which this occurs remains unknown. Interestingly, Dclk1+ tuft cells express high levels of cyclooxygenase (COX)-1 and -2, the direct enzyme target of non-steroidal anti-inflammatory drugs (NSAIDs) which are known chemopreventative drugs in CRC. In the present study, we aim to determine the effects of COX inhibition by NSAIDs on colitis-associated colorectal cancer. Dclk1CreERT2/APCfl/fl mice were administered tamoxifen to induce an APC mutation in Dclk1-expressing cells. Mice were then exposed to the colitis-inducing agent dextran sodium sulfate (DSS), followed by daily treatment with Aspirin (non-selective COX inhibitor), celecoxib or rofecoxib (COX-2 inhibitors), SC-560 (COX-1 inhibitor), or vehicle, for the experiment duration. As a comparison, we followed a similar experimental protocol in the commonly used AOM/DSS model of CAC. The carcinogen azoxymethane (AOM) followed by DSS were administered to induce tumorigenesis. Sixteen weeks post-tamoxifen or AOM, colonic tumor number and size were examined to determine the effect of NSAIDs on tumor initiation and growth, respectively. Extent of inflammation was assessed by myeloperoxidase (MPO) activity and histology. Colonic tissue was taken for measurement of inflammatory mediators by qRT-PCR and of inflammatory eicosanoids by LC-MS. Treatment with Aspirin, but surprisingly, none of the COX-specific inhibitors, significantly reduced the number of both Dclk1+ cell-derived and AOM DSS-derived colonic tumors. There was no significant difference in tumor size or degree of colitis, as assessed by MPO activity and histology, between vehicle and NSAID-treated groups. Interestingly, LC-MS revelated that in DSS-colitis, the production of COX-mediated prostaglandins was significantly inhibited in Aspirin- and SC-560-treated mice, but not in mice treated with celecoxib. Aspirin was also associated with a significant reduction in Dclk1+ cells. These findings suggest a role for cyclooxygenase in colitis-associated cancer. Our results suggest that Aspirin is chemopreventative in CAC, potentially through inhibition of COX-1-mediated prostaglandins that may be critical for Dclk1+ cell survival. CIHR

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.004
GPT teacher head0.229
Teacher spread0.226 · 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 routes2
Has abstractyes

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Same venueJournal of the Canadian Association of GastroenterologySame topicCancer Research and TreatmentsFrench-language works237,207