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mRNA/microRNA gene expression profile in microsatellite unstable colorectal cancer

BACKGROUND: Colorectal cancer develops through two main genetic instability pathways characterized by distinct pathologic features and clinical outcome. RESULTS: We investigated colon cancer samples (23 characterized by microsatellite stability, MSS, and 16 by high microsatellite instability, MSI-H)...

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Detalles Bibliográficos
Autores principales: Lanza, Giovanni, Ferracin, Manuela, Gafà, Roberta, Veronese, Angelo, Spizzo, Riccardo, Pichiorri, Flavia, Liu, Chang-gong, Calin, George A, Croce, Carlo M, Negrini, Massimo
Formato: Texto
Lenguaje:English
Publicado: BioMed Central|1 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2048978/
https://www.ncbi.nlm.nih.gov/pubmed/17716371
http://dx.doi.org/10.1186/1476-4598-6-54
Descripción
Sumario:BACKGROUND: Colorectal cancer develops through two main genetic instability pathways characterized by distinct pathologic features and clinical outcome. RESULTS: We investigated colon cancer samples (23 characterized by microsatellite stability, MSS, and 16 by high microsatellite instability, MSI-H) for genome-wide expression of microRNA (miRNA) and mRNA. Based on combined miRNA and mRNA gene expression, a molecular signature consisting of twenty seven differentially expressed genes, inclusive of 8 miRNAs, could correctly distinguish MSI-H versus MSS colon cancer samples. Among the differentially expressed miRNAs, various members of the oncogenic miR-17-92 family were significantly up-regulated in MSS cancers. The majority of protein coding genes were also up-regulated in MSS cancers. Their functional classification revealed that they were most frequently associated with cell cycle, DNA replication, recombination, repair, gastrointestinal disease and immune response. CONCLUSION: This is the first report that indicates the existence of differences in miRNA expression between MSS versus MSI-H colorectal cancers. In addition, the work suggests that the combination of mRNA/miRNA expression signatures may represent a general approach for improving bio-molecular classification of human cancer.