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Record W3133776625 · doi:10.1093/jcag/gwab002.000

A1 F4/80+LY6CHI MACROPHAGES ARE KEY TO CANCER INITIATION IN COLITIS

2021· article· en· W3133776625 on OpenAlexaff
Alice E. Shin, Hayley Good, Yodit Tesfagiorgis, L Zhang, Steven M. Kerfoot, Philip M. Sherman, T C Wang, Chris Howlett, Samuel Asfaha

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsLondon Health Sciences CentreSickKids FoundationWestern University
Fundersnot available
KeywordsColitisAzoxymethaneInflammatory bowel diseaseInflammationMedicineImmune systemCarcinogenesisColorectal cancerCancer researchMyeloperoxidaseCancerImmunologyCitrobacter rodentiumInternal medicineDisease

Abstract

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Abstract Background Colorectal cancer (CRC) is the third leading cause of cancer death, with a major risk factor being chronic inflammation. Thus, patients with inflammatory bowel disease (IBD) are at an increased risk of CRC. Despite the clear association between inflammation and cancer, the mechanism by which colitis leads to CRC is still not well understood. Aims In this study, we aim to explore the mechanism by which inflammation contributes to the initiation of colitis-associated cancer (CAC). We hypothesize that dextran sodium sulfate (DSS)-induced colitis leads to the infiltration of a specific immune cell type associated with tumorigenesis. Methods Following an injection of azoxymethane (AOM), mice were treated with the colitis-inducing agents DSS, trinitrobenzene sulfonic acid (TNBS), oxazolone (oxa), Citrobacter rodentium, or Doxorubicin (Doxo). The tumor studies were repeated using our published Cre-dependent murine model of CAC. To generate tamoxifen-inducible Cre transgenic mice that allow for Dclk1+ cell lineage tracing and cell-specific knock-out of the tumor suppressor adenomatous polyposis coli (APC), we crossed our Dclk1CreERT2 mice to both ROSA26tdTomato and APCfl/fl mice (Dclk1/APCfl/fl). Results Treatment with DSS, TNBS, oxa, C. rodentium, or Doxo induced colonic inflammation as detected by increased myeloperoxidase (MPO) activity and histologic analysis. DSS administration led to colonic tumors, whereas TNBS, oxa, C. rodentium, or Doxo did not lead to tumorigenesis up to 52 weeks following colitis induction. Upon flow cytometric analysis of several types of immune cells in the colonic tissue, we observed no difference in the number of T and B cells between mice treated with various colitis inducing agents. We did, however, detect significantly increased levels of Ly6G+ neutrophils and F4/80+Ly6Chi macrophages in the DSS-treated mice when compared to mice in the other models of colitis. mRNA and protein array analyses of the colonic tissue, as well as analysis of the RNA-seq data from 206 UC patients (GSE109142), revealed upregulated expression of genes associated with macrophages and neutrophils. Addition of macrophage-produced cytokines, such as IL-1β, TNF-α, or IL-6, induced lineage tracing of Dclk1+ tuft cells in intestinal organoids. Clodronate liposome-mediated depletion of F4/80+Ly6Chi macrophages significantly reduced the number of colonic tumors but did not affect tumor size in Dclk1/APCfl/fl mice. Conclusions Our data suggest that infiltration of F4/80+Ly6Chi macrophages, unique to DSS-induced colitis, leads to colonic tumor formation. This demonstrates that specific immune cell types, rather than the presence of colonic inflammation, plays an important role in the initiation of CAC. Funding Agencies CAG, 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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