Computational identification and analysis of early diagnostic biomarkers for kidney cancer.

Renal cell carcinoma is one of the most common urinary system tumors in adults, it is usually asymptomatic in its early stage and the patients are often diagnosed late. MicroRNA has a higher diagnostic accuracy than traditional markers and may become a new type of early diagnostic biomarker for kidney cancer. Three computational methods and several bioinformatic methods including PPI network, overall survival analysis and enrichment analysis were used to identify the significant differentially expressed miRNAs. Thirteen miRNAs that were significantly differentially expressed in RCC patients were identified, 10 of them have been proved to be associated with kidney cancer in other studies, miR-576, miR-616 and miR-133a-2 are three newly discovered biomarkers of RCC in this study. We found that the target genes of miR-576 (CUL3 and RAC1) are involved in the regulation of multiple cancer-related biological pathways, and the target gene of miR-616 (ASB13 and FBXW2) has been reported to be associated with the development of other cancers. Our findings may have guiding significance for the early diagnosis of renal cell carcinoma.

Integrating microRNA expression, miRNA-mRNA regulation network and signal pathway: a novel strategy for lung cancer biomarker discovery.

BACKGROUND: Since there are inextricably connections among molecules in the biological networks, it would be a more efficient and accurate research strategy to screen microRNA (miRNA) markers combining with miRNA-mRNA regulatory networks. The independent regulation mode is more "fragile" and "influential" than the co-regulation mode. miRNAs can be used as biomarkers if they can independently regulate hub genes with important roles in the PPI network, simultaneously the expression products of the regulated hub genes play important roles in the signaling pathways of related tissue diseases. METHODS: We collected miRNA expression of non-small cell lung cancer (NSCLC) from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Volcano plot and signal-to-noise ratio (SNR) methods were used to obtain significant differentially expressed (SDE) miRNAs from the TCGA database and GEO database, respectively. A human miRNA-mRNA regulatory network was constructed and the number of genes uniquely targeted (NOG) by a certain miRNA was calculated. The area under the curve (AUC) values were used to screen for clinical sensitivity and specificity. The candidate markers were obtained using the criteria of the top five maximum AUC values and NOG ≥ 3. The protein-protein interaction (PPI) network was constructed and independently regulated hub genes were obtained. Gene Ontology (GO) analysis and KEGG pathway analysis were used to identify genes involved in cancer-related pathways. Finally, the miRNA which can independently regulate a hub gene and the hub gene can participate in an important cancer-related pathway was considered as a biomarker. The AUC values and gene expression profile analysis from two external GEO datasets as well as literature validation were used to verify the screening capability and reliability of this marker. RESULTS: Fifteen SDE miRNAs in lung cancer were obtained from the intersection of volcano plot and SNR based on the GEO database and the TCGA database. Five miRNAs with the top five maximum AUC values and NOG ≥ 3 were screened out. A total of 61 hub genes were obtained from the PPI network. It was found that the hub gene GTF2F2 was independently regulated by miR-708-5p. Further pathway analysis indicated that GTF2F2 participates in protein expression by binding with polymerase II, and it can regulate transcription and accelerate tumor growth. Hence, miR-708-5p could be used as a biomarker. The good screening capability and reliability of miR-708-5p as a lung cancer marker were confirmed by AUC values and gene expression profiling of external datasets, and experimental literature. The potential mechanism of miR-708-5p was proposed. CONCLUSIONS: This study proposes a new idea for lung cancer marker screening by integrating microRNA expression, regulation network and signal pathway. miR-708-5p was identified as a biomarker using this novel strategy. This study may provide some help for cancer marker screening.