Molecular Classification of Colorectal Cancer by microRNA Profiling: Correlation with the Consensus Molecular Subtypes (CMS) and Validation of miR-30b Targets

Simple Summary Colorectal cancer is one of the most significant causes of cancer mortality worldwide. Patients stratification is central to improve clinical practice and the Consensus Molecular Subtypes (CMS) have been validated as a useful tool to predict both prognosis and treatment response. This is the first study describing that microRNA profiling can define colorectal cancer CMS subtypes as well as mRNA profiling. MicroRNAs small size facilitates its analysis in serum facilitating a real-time analysis of the disease course. Three microRNA subtypes are identified: miR-LS is associated with the low-stroma/CMS2-subtype; miR-MI with the mucinous-MSI/CMS1-subtype and miR-HS with the high-stroma/CMS4-subtype. MicroRNA novel subtypes and association to the CMS classification were externally validated using TGCA data. Analyzing both mRNAs and miRs in the same population enabled identification of miR target genes and altered biological pathways. A miR-mRNA interaction screening and regulatory network selected major miR targets and was functionally validated for the miR30b/SCL6A4 pair. Colorectal cancer consensus molecular subtypes (CMSs) are widely accepted and constitutes the basis for patient stratification to improve clinical practice. We aimed to find whether miRNAs could reproduce molecular subtypes, and to identify miRNA targets associated to the High-stroma/CMS4 subtype. The expression of 939 miRNAs was analyzed in tumors classified in CMS. TALASSO was used to find gene-miRNA interactions. A miR-mRNA regulatory network was constructed using Cytoscape. Candidate gene-miR interactions were validated in 293T cells. Hierarchical-Clustering identified three miRNA tumor subtypes (miR-LS; miR-MI; and miR-HS) which were significantly associated (p < 0.001) to the reported mRNA subtypes. miR-LS correlated with the low-stroma/CMS2; miR-MI with the mucinous-MSI/CMS1 and miR-HS with high-stroma/CMS4. MicroRNA tumor subtypes and association to CMSs were validated with TCGA datasets. TALASSO identified 1462 interactions (p < 0.05) out of 21,615 found between 176 miRs and 788 genes. Based on the regulatory network, 88 miR-mRNA interactions were selected as candidates. This network was functionally validated for the pair miR-30b/SLC6A6. We found that miR-30b overexpression silenced 3 '-UTR-SLC6A6-driven luciferase expression in 293T-cells; mutation of the target sequence in the 3 '-UTR-SLC6A6 prevented the miR-30b inhibitory effect. In conclusion CRC subtype classification using a miR-signature might facilitate a real-time analysis of the disease course and treatment response.