Original Article
Identification of potential gene and microRNA biomarkers for colon cancer by an integrated bioinformatical approach
Abstract
Background: A unique resource for genomic studies is the NCI-60 cancer cell line panel, which provides various publicly available datasets, including gene and microRNA (miRNA) transcripts, whole-exome sequencing, DNA copy number, and protein levels against 59 cancer cell lines. In this study, we aimed to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) for colon cancers by analyzing NCI-60 gene and miRNA expression profiles.
Methods: The real-time quantitative RT-PCR (qRT-PCR) was used to validate the identified candidate genes and miRNAs. The functional enrichment analysis and pathway analysis were performed for DEGs and the network analysis was performed for predicted miRNA targets of DEMs.
Results: Finally, we integrated DEGs and DEMs and constructed a network, revealing the relationship for 5 miRNAs and 104 gene probes. The identified specific genes, miRNAs and integrated network for colon might provide new clues on possible mechanisms for colon cancer.
Conclusions: In conclusion, integrated bioinformatics approaches on publicly available datasets play critical roles for finding candidate biomarkers and potential mechanisms for cancers.
Methods: The real-time quantitative RT-PCR (qRT-PCR) was used to validate the identified candidate genes and miRNAs. The functional enrichment analysis and pathway analysis were performed for DEGs and the network analysis was performed for predicted miRNA targets of DEMs.
Results: Finally, we integrated DEGs and DEMs and constructed a network, revealing the relationship for 5 miRNAs and 104 gene probes. The identified specific genes, miRNAs and integrated network for colon might provide new clues on possible mechanisms for colon cancer.
Conclusions: In conclusion, integrated bioinformatics approaches on publicly available datasets play critical roles for finding candidate biomarkers and potential mechanisms for cancers.
