Colorectal cancer (CRC) molecular subtypes have been recently identified by gene expression profiling. To search for microRNAs potentially driving the subtypes, we designed an analytical pipeline, microRNA Master Regulator Analysis (MMRA). As input, MMRA requires a paired microRNA/mRNA expression dataset, with samples subdivided in two or more subgroups, and gene expression signatures specific for each subgroup. MMRA then identifies candidate regulator microRNAs by assessing their subtype-specific expression, target gene enrichment in subtype signatures and network analysis-based contribution to subtype gene expression. MMRA was applied to a CRC dataset of 450 samples, assigned to various subtypes by three different transcriptional classifiers. In total, 24 microRNA were associated to subtypes, in most cases negatively contributing to the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirmed downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, and highlighted shared target genes and pathways mediating this effect.
MicroRNA/mRNA interactions underlying colorectal cancer molecular subtypes / Cantini, Laura; Isella, Claudio; Petti, Consalvo; Picco, Gabriele; Chiola, Simone; Ficarra, Elisa; Caselle, Michele; Medico, Enzo. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 6:8878(2015), pp. 1-12. [10.1038/ncomms9878]
MicroRNA/mRNA interactions underlying colorectal cancer molecular subtypes
FICARRA, ELISA;
2015
Abstract
Colorectal cancer (CRC) molecular subtypes have been recently identified by gene expression profiling. To search for microRNAs potentially driving the subtypes, we designed an analytical pipeline, microRNA Master Regulator Analysis (MMRA). As input, MMRA requires a paired microRNA/mRNA expression dataset, with samples subdivided in two or more subgroups, and gene expression signatures specific for each subgroup. MMRA then identifies candidate regulator microRNAs by assessing their subtype-specific expression, target gene enrichment in subtype signatures and network analysis-based contribution to subtype gene expression. MMRA was applied to a CRC dataset of 450 samples, assigned to various subtypes by three different transcriptional classifiers. In total, 24 microRNA were associated to subtypes, in most cases negatively contributing to the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirmed downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, and highlighted shared target genes and pathways mediating this effect.File | Dimensione | Formato | |
---|---|---|---|
ncomms9878.pdf
Open access
Tipologia:
Versione pubblicata dall'editore
Dimensione
1.7 MB
Formato
Adobe PDF
|
1.7 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris