ArticleJournal of veterinary internal medicine2022
Association of fecal and serum microRNA profiles with gastrointestinal cancer and chronic inflammatory enteropathy in dogs.
Article in Journal of veterinary internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- ACVIM-endorsed statement: consensus statement and systematic review on guidelines for the diagnosis and treatment of chronic inflammatory enteropathy in dogs.Journal of veterinary internal medicine · 2026Pooled it
- Evaluation of normalisation strategies for qPCR data obtained from canine gastrointestinal tissues with different pathologies.Scientific reports · 2025Article
- Stability of microRNAs in Canine Serum-A Prerequisite for Use as Biomarkers in Tumour Diagnostics.Veterinary sciences · 2025Article
- MiR-451 in Inflammatory Diseases: Molecular Mechanisms, Biomarkers, and Therapeutic Applications-A Comprehensive Review Beyond Oncology.Current issues in molecular biology · 2025Review
- Review of Molecular Technologies for Investigating Canine Cancer.Animals : an open access journal from MDPI · 2024Review
- miRNA Profiles of Canine Intestinal Carcinomas, Lymphomas and Enteritis Analysed by Digital Droplet PCR from FFPE Material.Veterinary sciences · 2023Article
- Association of fecal and serum microRNA profiles with gastrointestinal cancer and chronic inflammatory enteropathy in dogs.Journal of veterinary internal medicine · 2022Article
- Association of serum and fecal microRNA profiles in cats with gastrointestinal cancer and chronic inflammatory enteropathy.Journal of veterinary internal medicineArticle
Corrections and comments
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Authors and funding
14 authors at 7 institutions in 7 countries.
Funding
Abstract
backgroundReliable biomarkers to differentiate gastrointestinal cancer (GIC) from chronic inflammatory enteropathy (CIE) in dogs are needed. Fecal and serum microRNAs (miRNAs) have been proposed as diagnostic and prognostic markers of GI disease in humans and dogs. HYPOTHESIS/
objectivesDogs with GIC have fecal and serum miRNA profiles that differ from those of dogs with CIE.
aims(a) identify miRNAs that differentiate GIC from CIE, (b) use high-throughput reverse transcription quantitative real-time PCR (RT-qPCR) to establish fecal and serum miRNA panels to distinguish GIC from CIE in dogs. ANIMALS: Twenty-four dogs with GIC, 10 dogs with CIE, and 10 healthy dogs, all client-owned.
methodsAn international multicenter observational prospective case-control study. Small RNA sequencing was used to identify fecal and serum miRNAs, and RT-qPCR was used to establish fecal and serum miRNA panels with the potential to distinguish GIC from CIE.
resultsThe best diagnostic performance for distinguishing GIC from CIE was fecal miR-451 (AUC: 0.955, sensitivity: 86.4%, specificity: 100%), miR-223 (AUC: 0.918, sensitivity: 90.9%, specificity: 80%), and miR-27a (AUC: 0.868, sensitivity: 81.8%, specificity: 90%) and serum miR-20b (AUC: 0.905, sensitivity: 90.5%, specificity: 90%), miR-148a-3p (AUC: 0.924, sensitivity: 85.7%, specificity: 90%), and miR-652 (AUC: 0.943, sensitivity: 90.5%, specificity: 90%). Slightly improved diagnostic performance was achieved when combining fecal miR-451 and miR-223 (AUC: 0.973, sensitivity: 95.5%, specificity: 90%). CONCLUSIONS AND CLINICAL IMPORTANCE: When used as part of a diagnostic RT-qPCR panel, the abovementioned miRNAs have the potential to function as noninvasive biomarkers for the differentiation of GIC and CIE in dogs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.