Integrative meta-analysis of multiple gene expression profiles in acquired gemcitabine-resistant cancer cell lines to identify novel therapeutic biomarkers

Identification of Pathogenic Genes and Transcription Factors in Osteosarcoma

Osteosarcoma (OS) is an aggressive malignant tumor of the bones. Our study intended to identify and analyze potential pathogenic genes and upstream regulators for OS. We performed an integrated analysis to identify candidate pathogenic genes of OS by using three Gene Expression Omnibus (GEO) databases (GSE66673, GSE49003 and GSE37552). GO and KEGG enrichment analysis were utilized to predict the functional annotation and potential pathways of differentially expressed genes (DEGs). The OS-specific transcriptional regulatory network was established to study the crucial transcriptional factors (TFs) which target the DEGs in OS. From the three GEO datasets, we identified 759 DEGs between metastasis OS samples and non-metastasis OS samples. After GO and KEGG analysis, 'cell adhesion' (FDR = 1.27E-08), 'protein binding' (FDR = 1.13E-22), 'cytoplasm' (FDR = 5.63E-32) and 'osteoclast differentiation' (FDR = 0.000992221) were significantly enriched pathways for DEGs. HSP90AA1 exhibited a highest degree (degree = 32) and was enriched in 'pathways in cancer' and 'signal transduction'. BMP6, regulated by Pax-6, was enriched in the 'TGF-beta signaling pathway'. We indicated that BMP6 may be downregulated by Pax-6 in the non-metastasis OS samples. The up-regulated HSP90AA1 and down-regulated BMP6 and 'pathways in cancer' and 'signal transduction' were deduced to be involved in the pathogenesis of OS. The identified biomarkers and biological process in OS may provide foundation for further study.

Genome-wide profiling of mRNA and lncRNA expression in dengue fever and dengue hemorrhagic fever

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are recurrent diseases that are widespread in the tropics. Here, we identified candidate genes associated with these diseases by performing integrated analyses of DF (GSE51808) and DHF (GSE18090) microarray datasets in the Gene Expression Omnibus (GEO). In all, we identified 7635 differentially expressed genes (DEGs) in DF and 8147 DEGs in DHF as compared to healthy controls (P < 0.05). In addition, we discovered 215 differentially expressed long non-coding RNAs (DElncRNAs) in DF and 225 DElncRNAs in DHF. There were 1256 common DEGs and eight common DElncRNAs in DHF vs DF, DHF vs normal control, and DF vs normal control groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that signal transduction (false discovery rate = 8.33E-10), 'toxoplasmosis', and 'protein processing in endoplasmic reticulum' were significantly enriched pathways for common DEGs. We conclude that the MAGED1,STAT1, and IL12A genes may play crucial roles in DF and DHF, and suggest that our findings may facilitate the identification of biomarkers and the development of new drug design strategies for DF and DHF treatment.