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 non-invasive CRC diagnosis. Methods: A total of 1,273 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 CRC, 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 and 80 healthy volunteers. miRNA profiles were compared with those of 132 tumor/adenoma paired with adjacent mucosa, 210 plasma extracellular vesicles samples, and 185 fecal immunochemical tests (FIT) leftover samples. Results: Twenty-five miRNAs showed altered levels in stool of CRC patients in both cohorts (adj. P<.05). A five-miRNA signature, including miR-149-3p, miR-607-5p, miR-1246, miR-4488, and miR-6777-5p, distinguished patients from controls (AUC=0.86, 95% CI=0.79-0.94) and was validated in an independent cohort (AUC=0.96, 95% CI=0.92-1.00). The signature classified controls from low-/high-stage tumors, and advanced adenomas (AUC=0.82, 95% CI=0.71-0.97). Tissue miRNA profiles mirrored those of stool samples, while fecal profiles of different gastrointestinal diseases highlighted miRNAs specifically dysregulated in CRC. miRNA profiles in FIT leftover samples showed good correlation with those of stool collected in preservative buffer and their alterations can be detected in adenoma or CRC patients. Conclusions: Our comprehensive fecal miRNome analysis identified a signature accurately discriminating cancer aimed at improving a non-invasive diagnosis and screening strategies.

A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study / 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; Budinska, Eva; Vodicka, Pavel; Cordero, Francesca; Naccarati, Alessio. - In: GASTROENTEROLOGY. - ISSN 1528-0012. - (2023). [10.1053/j.gastro.2023.05.037]

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

Gallo, Gaetano;
2023

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 non-invasive CRC diagnosis. Methods: A total of 1,273 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 CRC, 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 and 80 healthy volunteers. miRNA profiles were compared with those of 132 tumor/adenoma paired with adjacent mucosa, 210 plasma extracellular vesicles samples, and 185 fecal immunochemical tests (FIT) leftover samples. Results: Twenty-five miRNAs showed altered levels in stool of CRC patients in both cohorts (adj. P<.05). A five-miRNA signature, including miR-149-3p, miR-607-5p, miR-1246, miR-4488, and miR-6777-5p, distinguished patients from controls (AUC=0.86, 95% CI=0.79-0.94) and was validated in an independent cohort (AUC=0.96, 95% CI=0.92-1.00). The signature classified controls from low-/high-stage tumors, and advanced adenomas (AUC=0.82, 95% CI=0.71-0.97). Tissue miRNA profiles mirrored those of stool samples, while fecal profiles of different gastrointestinal diseases highlighted miRNAs specifically dysregulated in CRC. miRNA profiles in FIT leftover samples showed good correlation with those of stool collected in preservative buffer and their alterations can be detected in adenoma or CRC patients. Conclusions: Our comprehensive fecal miRNome analysis identified a signature accurately discriminating cancer aimed at improving a non-invasive diagnosis and screening strategies.
2023
colorectal cancer; machine learning; non-invasive diagnosis; precancerous lesions; small RNA sequencing; stool microRNAs
01 Pubblicazione su rivista::01l Trial clinico
A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study / 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; Budinska, Eva; Vodicka, Pavel; Cordero, Francesca; Naccarati, Alessio. - In: GASTROENTEROLOGY. - ISSN 1528-0012. - (2023). [10.1053/j.gastro.2023.05.037]
File allegati a questo prodotto
File Dimensione Formato  
Pardini_A-Fecal-MicroRNA_2023.pdf

solo gestori archivio

Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 4.67 MB
Formato Adobe PDF
4.67 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1681685
Citazioni
  • ???jsp.display-item.citation.pmc??? 10
  • Scopus 21
  • ???jsp.display-item.citation.isi??? 19
social impact