MétaCan
Menu
Back to cohort
Record W2089762788 · doi:10.1158/0008-5472.can-05-3343

Epidermal Growth Factor Receptor Signaling Is Required for Microadenoma Formation in the Mouse Azoxymethane Model of Colonic Carcinogenesis

2007· article· en· W2089762788 on OpenAlexaff
Alessandro Fichera, Nathaniel Little, Sujatha Jagadeeswaran, Urszula Dougherty, Amikar Sehdev, Reba Mustafi, Sandra Cerda, Weihua Yuan, Sharad Khare, Maria Tretiakova, Can Gong, Michael Tallerico, Greg Cohen, Loren Joseph, John Hart, Jerrold R. Turner, Marc Bissonnette

Bibliographic record

VenueCancer Research · 2007
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsImmunovaccine (Canada)
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteUniversity of Chicago
KeywordsAzoxymethaneGefitinibEpidermal growth factor receptorAberrant crypt fociEndocrinologyInternal medicineCancer researchGrowth factor receptorEpidermal growth factorCarcinogenesisBiologyMedicineColorectal cancerCancerReceptor

Abstract

fetched live from OpenAlex

Colonic carcinogenesis involves the progressive dysregulation of homeostatic mechanisms that control growth. The epidermal growth factor (EGF) receptor (EGFR) regulates colonocyte growth and differentiation and is overexpressed in many human colon cancers. A requirement for EGFR in colonic premalignancy, however, has not been shown. In the current study, we used a specific EGFR antagonist, gefitinib, to investigate this role of the receptor in azoxymethane colonic premalignancy. The azoxymethane model shares many clinical, histologic, and molecular features of human colon cancer. Mice received azoxymethane i.p. (5 mg/kg/wk) or saline for 6 weeks. Animals were also gavaged with gefitinib (10 mg/kg body weight) or vehicle (DMSO) thrice weekly for 18 weeks, a dose schedule that inhibited normal receptor activation by exogenous EGF. Compared with control colonocytes [bromodeoxyuridine (BrdUrd), 2.2+/-1.2%], azoxymethane significantly increased proliferation (BrdUrd, 12.6+/-2.8%), whereas gefitinib inhibited this hyperproliferation (BrdUrd, 6.2+/-4.0%; <0.005). Azoxymethane significantly induced pro-transforming growth factor-alpha (6.4+/-1.3-fold) and increased phospho-(active) EGFR (5.9+/-1.1-fold), phospho-(active) ErbB2 (2.3+/-0.2-fold), and phospho-(active) extracellular signal-regulated kinase (3.3+/-0.4-fold) in premalignant colonocytes. Gefitinib inhibited activations of these kinases by >75% (P<0.05). Gefitinib also significantly reduced the number of large aberrant crypt foci and decreased the incidence of colonic microadenomas from 75% to 33% (P<0.05). Gefitinib concomitantly decreased cell cycle-regulating cyclin D1 and prostanoid biosynthetic enzyme cyclooxygenase-2 in microadenomas, suggesting that these regulators are key targets of EGFR in colonic carcinogenesis. These results show for the first time that EGFR signaling is required for early stages of colonic carcinogenesis. Our findings suggest, moreover, that inhibitors of EGFR might be useful in chemopreventive strategies in individuals at increased risk for colonic malignancies.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.175
GPT teacher head0.418
Teacher spread0.243 · 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

Citations53
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicColorectal Cancer Treatments and StudiesFrench-language works237,207