Project description:Cytarabine is the main drug for acute myeloid leukemia (AML) treatment; however, drug resistance hinders the treatment of AML. Although microRNA (miRNA) alteration is one of the well-recognized mechanisms underlying drug resistance in AML, few studies have investigated the role and function of miRNAs in the development of cytarabine resistance. In this study, total RNA was isolated from parental HL60 and cytarabine resistant HL60 (R-HL60) cells. Subsequently, miRNAs and mRNAs were detected using small RNA sequencing and gene expression array, respectively. The miRNAs and genes with ≥ 2-fold difference in expression between HL60 and R-HL60 cells were screened out. Negatively correlated miRNA–mRNA pairs were selected as candidate miRNA–mRNA target pairs by using the miRDB, Targetscan or miRTar databases. Functional enrichment analysis of differentially expressed genes (DEGs) included in the candidate miRNA–mRNA network was performed. The results revealed that CCL2, SOX9, SLC8A1, ICAM1, CXCL10, SIPR2, FGFR1, OVOL2, MITF, and CARD10 were simultaneously involved in seven GO pathways, namely the regulation of cell migration, regulation of locomotion, regulation of cellular component movement, cell migration, locomotion, cell motility, localization of cell. These genes were negatively correlated with the altered miRNAs (miR-1-3p, miR-155-5p, miR-1255b-5p, miR-200c-5p, miR-3609, miR-1285-3p, miR-124-3p, miR-146a-5p, miR-497a-5p, and miR-3150a-5p), suggesting that they are the potential targets of the miRNAs to regulate cell migration behavior or ability. Therefore, our results advance our understanding of the regulatory mechanism underlying cytarabine resistance development, specifically related to miRNAs.
Project description:Cytarabine is the main drug for acute myeloid leukemia (AML) treatment; however, drug resistance hinders the treatment of AML. Although microRNA (miRNA) alteration is one of the well-recognized mechanisms underlying drug resistance in AML, few studies have investigated the role and function of miRNAs in the development of cytarabine resistance. In this study, total RNA was isolated from parental HL60 and cytarabine resistant HL60 (R-HL60) cells. Subsequently, miRNAs and mRNAs were detected using small RNA sequencing and gene expression array, respectively. The miRNAs and genes with ≥ 2-fold difference in expression between HL60 and R-HL60 cells were screened out. Negatively correlated miRNA–mRNA pairs were selected as candidate miRNA–mRNA target pairs by using the miRDB, Targetscan or miRTar databases. Functional enrichment analysis of differentially expressed genes (DEGs) included in the candidate miRNA–mRNA network was performed. The results revealed that CCL2, SOX9, SLC8A1, ICAM1, CXCL10, SIPR2, FGFR1, OVOL2, MITF, and CARD10 were simultaneously involved in seven GO pathways, namely the regulation of cell migration, regulation of locomotion, regulation of cellular component movement, cell migration, locomotion, cell motility, localization of cell. These genes were negatively correlated with the altered miRNAs (miR-1-3p, miR-155-5p, miR-1255b-5p, miR-200c-5p, miR-3609, miR-1285-3p, miR-124-3p, miR-146a-5p, miR-497a-5p, and miR-3150a-5p), suggesting that they are the potential targets of the miRNAs to regulate cell migration behavior or ability. Therefore, our results advance our understanding of the regulatory mechanism underlying cytarabine resistance development, specifically related to miRNAs.
Project description:Parkinson's disease (PD) is a common neurodegenerative disease, and the mechanism underlying PD pathogenesis is not completely understood. Increasing evidence indicates that microRNAs (miRNAs) play a critical regulatory role in the pathogenesis of PD. This study aimed to explore the miRNA-mRNA regulatory network for PD. The differentially expressed miRNAs (DEmis) and genes (DEGs) between PD patients and healthy donors were screened from the miRNA dataset GSE16658 and mRNA dataset GSE100054 downloaded from the Gene Expression Omnibus (GEO) database. Target genes of the DEmis were selected when they were predicted by three or four online databases and overlapped with DEGs from GSE100054. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) and Metascape analytic tools. The correlation between the screened genes and PD was evaluated with the online tool Comparative Toxicogenomics Database (CTD), and protein-protein interaction (PPI) networks were built by the STRING platform. We further investigated the expression of genes in the miRNA-mRNA regulatory network in blood samples collected from PD patients and healthy donors via qRT-PCR. We identified 1505 upregulated and 1302 downregulated DEGs, and 77 upregulated and 112 downregulated DEmis were preliminarily screened from the GEO database. Further functional enrichment analysis identified 10 PD-related hub genes, including RAC1, IRS2, LEPR, PPARGC1A, CAMKK2, RAB10, RAB13, RAB27B, RAB11A, and JAK2, which were mainly involved in Rab protein signaling transduction, AMPK signaling pathway, and signaling by Leptin. A miRNA-mRNA regulatory network was then constructed with 10 hub genes, and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p, and miR-21-5p. Analysis of clinical samples verified significant upregulation of LEPR and downregulation of miR-101-3p and miR-30e-5p in PD patients as compared with healthy donors. Thus, the miRNA-mRNA regulatory network was initially constructed and has the potential to provide novel insights into the pathogenesis and treatment of PD.
Project description:Human Promyelocytic Leukemia Cell Line HL60 has been used extensively as a model for myeloid differentiation and leukemia. HL60-RG cell is its sub-line and shows a higher growth rate. In this study, we carried out a genome scan using SNP 10k mapping array on both cells. Comparative study on chromosomal changes of these cells will give us information on mechanism of tumor progression. Experiment Overall Design: Two samples HL60-NG cell and HL60-RG cel were analyzed by SNP 10k mapping array.
Project description:Background: Hypertrophic cardiomyopathy (HCM) is a myocardial disease with unidentified pathogenesis. Increasing evidence indicated the potential role of microRNA (miRNA)-mRNA regulatory network in disease development. This study aimed to explore the miRNA-mRNA axis in HCM. Methods: The miRNA and mRNA expression profiles obtained from the Gene Expression Omnibus (GEO) database were used to identify differentially expressed miRNAs (DEMs) and genes (DEGs) between HCM and normal samples. Target genes of DEMs were determined by miRTarBase. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to identify biological functions of the DEGs and DEMs. miRNA-mRNA regulatory network was constructed to identify the hub genes and miRNAs. Logistic regression model for HCM prediction was established basing on the network. Results: A total of 224 upregulated and 366 downregulated DEGs and 10 upregulated and 14 downregulated DEMs were determined. We identified 384 DEM-targeted genes, and 20 of them were overlapped with the DEGs. The enriched functions include extracellular structure organization, organ growth, and phagosome and melanoma pathways. The four miRNAs and three mRNAs, including hsa-miR-373, hsa-miR-371-3p, hsa-miR-34b, hsa-miR-452, ARHGDIA, SEC61A1, and MYC, were identified through miRNA-mRNA regulatory network to construct the logistic regression model. The area under curve (AUC) values over 0.9 suggested the good performance of the model. Conclusion: The potential miRNA-mRNA regulatory network and established logistic regression model in our study may provide promising diagnostic methods for HCM.
Project description:Human Promyelocytic Leukemia Cell Line HL60 has been used extensively as a model for myeloid differentiation and leukemia. HL60-RG cell is its sub-line and shows a higher growth rate. In this study, we carried out a genome scan using SNP 10k mapping array on both cells. Comparative study on chromosomal changes of these cells will give us information on mechanism of tumor progression. Keywords: cell type comparison