A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study

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Authors

PARDINI Barbara FERRERO Giulio TARALLO Sonia GALLO Gaetano FRANCAVILLA Antonio LICHERI Nicola TROMPETTO Mario CLERICO Giuseppe SENORE Carlo PEYRE Sergio VYMETALKOVA Veronika VODICKOVA Ludmila LISKA Vaclav VYCITAL Ondrej LEVY Miroslav MACINGA Peter HUCL Tomas BUDINSKÁ Eva VODICKA Pavel CORDERO Francesca NACCARATI Alessio

Year of publication 2023
Type Article in Periodical
Magazine / Source Gastroenterology
MU Faculty or unit

Faculty of Science

Citation
Web https://www.sciencedirect.com/science/article/pii/S0016508523008119?via%3Dihub
Doi http://dx.doi.org/10.1053/j.gastro.2023.05.037
Keywords Stool MicroRNAs; Noninvasive Diagnosis; Small RNA Sequencing; Colorectal Cancer; Precancerous Lesions; Machine Learning
Attached files
Description 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.
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