| Autor: |
Cantini L; Department of Oncology, Università degli Studi di Torino, S.P. 142, km 3, 95-10060 Candiolo, Italy.; Department of Control and Computer Engineering, Politecnico di Torino, Cso Duca degli Abruzzi 24, 10129 Torino, Italy.; Istituto Nazionale Biostrutture e Biosistemi-Consorzio Interuniversitario, Viale delle Medaglie d'Oro, 305-00136 Roma, Italy., Isella C; Department of Oncology, Università degli Studi di Torino, S.P. 142, km 3, 95-10060 Candiolo, Italy.; Candiolo Cancer Institute, FPO IRCCS, S.P. 142, km 3, 95-10060 Candiolo, Italy., Petti C; Candiolo Cancer Institute, FPO IRCCS, S.P. 142, km 3, 95-10060 Candiolo, Italy., Picco G; Department of Oncology, Università degli Studi di Torino, S.P. 142, km 3, 95-10060 Candiolo, Italy.; Candiolo Cancer Institute, FPO IRCCS, S.P. 142, km 3, 95-10060 Candiolo, Italy., Chiola S; Department of Oncology, Università degli Studi di Torino, S.P. 142, km 3, 95-10060 Candiolo, Italy.; Candiolo Cancer Institute, FPO IRCCS, S.P. 142, km 3, 95-10060 Candiolo, Italy., Ficarra E; Department of Control and Computer Engineering, Politecnico di Torino, Cso Duca degli Abruzzi 24, 10129 Torino, Italy., Caselle M; Department of Physics and INFN, Università degli Studi di Torino, via P.Giuria 1, I-10125 Turin, Italy., Medico E; Department of Oncology, Università degli Studi di Torino, S.P. 142, km 3, 95-10060 Candiolo, Italy.; Candiolo Cancer Institute, FPO IRCCS, S.P. 142, km 3, 95-10060 Candiolo, Italy. |
| Abstrakt: |
Colorectal cancer (CRC) transcriptional subtypes have been recently identified by gene expression profiling. Here we describe an analytical pipeline, microRNA master regulator analysis (MMRA), developed to search for microRNAs potentially driving CRC subtypes. Starting from a microRNA-mRNA tumour expression data set, MMRA identifies candidate regulator microRNAs by assessing their subtype-specific expression, target enrichment in subtype mRNA signatures and network analysis-based contribution to subtype gene expression. When applied to a CRC data set of 450 samples, assigned to subtypes by 3 different transcriptional classifiers, MMRA identifies 24 candidate microRNAs, in most cases downregulated in the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirms downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, which share target genes and pathways mediating this effect. These results show that, by combining statistical tests, target prediction and network analysis, MMRA effectively identifies microRNAs functionally associated to cancer subtypes. |
