A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study
Language English Country United States Media print-electronic
Document type Multicenter Study, Journal Article, Research Support, Non-U.S. Gov't
PubMed
37263306
DOI
10.1053/j.gastro.2023.05.037
PII: S0016-5085(23)00811-9
Knihovny.cz E-resources
- Keywords
- Colorectal Cancer, Machine Learning, Noninvasive Diagnosis, Precancerous Lesions, Small RNA Sequencing, Stool MicroRNAs,
- MeSH
- Adenoma * diagnosis genetics MeSH
- Colorectal Neoplasms * diagnosis genetics MeSH
- Humans MeSH
- MicroRNAs * analysis MeSH
- Biomarkers, Tumor analysis MeSH
- Cross-Sectional Studies MeSH
- Sequence Analysis, RNA MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- MicroRNAs * MeSH
- MIRN149 microRNA, human MeSH Browser
- Biomarkers, Tumor MeSH
BACKGROUND & AIMS: Fecal tests currently used for colorectal cancer (CRC) screening show limited accuracy in detecting early tumors or precancerous lesions. In this respect, we comprehensively evaluated stool microRNA (miRNA) profiles as biomarkers for noninvasive CRC diagnosis. METHODS: A total of 1273 small RNA sequencing experiments were performed in multiple biospecimens. In a cross-sectional study, miRNA profiles were investigated in fecal samples from an Italian and a Czech cohort (155 CRCs, 87 adenomas, 96 other intestinal diseases, 141 colonoscopy-negative controls). A predictive miRNA signature for cancer detection was defined by a machine learning strategy and tested in additional fecal samples from 141 CRC patients and 80 healthy volunteers. miRNA profiles were compared with those of 132 tumors/adenomas paired with adjacent mucosa, 210 plasma extracellular vesicle samples, and 185 fecal immunochemical test leftover samples. RESULTS: Twenty-five miRNAs showed altered levels in the stool of CRC patients in both cohorts (adjusted P < .05). A 5-miRNA signature, including miR-149-3p, miR-607-5p, miR-1246, miR-4488, and miR-6777-5p, distinguished patients from control individuals (area under the curve [AUC], 0.86; 95% confidence interval [CI], 0.79-0.94) and was validated in an independent cohort (AUC, 0.96; 95% CI, 0.92-1.00). The signature classified control individuals from patients with low-/high-stage tumors and advanced adenomas (AUC, 0.82; 95% CI, 0.71-0.97). Tissue miRNA profiles mirrored those of stool samples, and fecal profiles of different gastrointestinal diseases highlighted miRNAs specifically dysregulated in CRC. miRNA profiles in fecal immunochemical test leftover samples showed good correlation with those of stool collected in preservative buffer, and their alterations could be detected in adenoma or CRC patients. CONCLUSIONS: Our comprehensive fecal miRNome analysis identified a signature accurately discriminating cancer aimed at improving noninvasive diagnosis and screening strategies.
Department of Colorectal Surgery Clinica S Rita Vercelli Italy
Department of Computer Science University of Turin Turin Italy
Italian Institute for Genomic Medicine Turin Italy
Italian Institute for Genomic Medicine Turin Italy; Candiolo Cancer Institute FPO IRCCS Turin Italy
LILT associazione provinciale di Biella Biella Italy
RECETOX Faculty of Science Masaryk University Brno Czech Republic
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