A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu multicentrická studie, časopisecké články, práce podpořená grantem
PubMed
37263306
DOI
10.1053/j.gastro.2023.05.037
PII: S0016-5085(23)00811-9
Knihovny.cz E-zdroje
- Klíčová slova
- Colorectal Cancer, Machine Learning, Noninvasive Diagnosis, Precancerous Lesions, Small RNA Sequencing, Stool MicroRNAs,
- MeSH
- adenom * diagnóza genetika MeSH
- kolorektální nádory * diagnóza genetika MeSH
- lidé MeSH
- mikro RNA * analýza MeSH
- nádorové biomarkery analýza MeSH
- průřezové studie MeSH
- sekvenční analýza RNA MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
- Názvy látek
- mikro RNA * MeSH
- MIRN149 microRNA, human MeSH Prohlížeč
- nádorové biomarkery 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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