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Multicenter Study
. 2023 Sep;165(3):582-599.e8.
doi: 10.1053/j.gastro.2023.05.037. Epub 2023 May 30.

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

Barbara Pardini  1 , Giulio Ferrero  2 , Sonia Tarallo  3 , Gaetano Gallo  4 , Antonio Francavilla  5 , Nicola Licheri  6 , Mario Trompetto  7 , Giuseppe Clerico  7 , Carlo Senore  8 , Sergio Peyre  9 , Veronika Vymetalkova  10 , Ludmila Vodickova  10 , Vaclav Liska  11 , Ondrej Vycital  11 , Miroslav Levy  12 , Peter Macinga  13 , Tomas Hucl  13 , Eva Budinska  14 , Pavel Vodicka  10 , Francesca Cordero  6 , Alessio Naccarati  15
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Free article
Multicenter Study

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

Barbara Pardini et al. Gastroenterology. 2023 Sep.
Free article

Abstract

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.

Keywords: Colorectal Cancer; Machine Learning; Noninvasive Diagnosis; Precancerous Lesions; Small RNA Sequencing; Stool MicroRNAs.

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