Journal: Journal of Clinical Bioinformatics

Article Title: PROGmiR: a tool for identifying prognostic miRNA biomarkers in multiple cancers using publicly available data

doi: 10.1186/2043-9113-2-23

Figure Lengend Snippet: Description of various data sources included in progmir database

Article Snippet: 7 , Small Cell Lung Cancer , GSE27435 , GEO , Capitalbio mammal microRNA V3.0 , 42 , 1638 , [ ] .

Techniques: Microarray

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: The schematic pipeline for MPCa microRNA biomarker identification. LIMMA linear models for microarray data analysis; eBayes the empirical bayes; adj.p value adjusted p value; FC fold change; DE differentially expressed; MicroRNA-BD microRNA biomarker discovery; NSR number of single-line regulation; TFP transcription factor gene percentage; UTP percentage of transcription factor genes in microRNA unique targets; ROC receiver operating characteristic curve; GO Gene Ontology; MPCa metastatic prostate cancer

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Biomarker Discovery, Microarray

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Summary of the microRNA and mRNA dataset used in this study

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Biomarker Discovery

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Schematic description of microRNA-mRNA regulatory types. Four types were defined here, i.e., TF or non-TF genes regulated by multiple or single microRNAs. For example, G_1 was uniquely regulated by M_1 whereas TF gene G_5 was co-regulated by M_2 and M_3 . The co-regulatory sites are robust since one of the regulations altered can be compensated by others. Here the unique regulatory sites, i.e., single-line regulations, are considered as the vulnerable structure in the network. Meanwhile, microRNAs that target more TF genes seem to be functionally important. M microRNA; G gene; TF transcription factor

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques:

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Topological and functional characterization of reported PCa microRNA biomarkers. a NSR distribution of reported PCa microRNA biomarkers and all microRNAs in human microRNA-mRNA network. b TFP distribution of reported PCa microRNA biomarkers and all microRNAs in human microRNA-mRNA network. The statistical significance was calculated using Kolmogorov–Smirnov test. NSR number of single-line regulation; TFP transcription factor gene percentage; PCa prostate cancer

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Functional Assay

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Details for the identified microRNA biomarkers

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques:

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: ROC analysis for the identified microRNA biomarkers. The AUC distribution in the prediction set GSE21036 and another independent validation set GSE26964 ranged from 0.70 to 0.99 and from 0.71 to 0.93, respectively. Red curve: GSE21036; blue curve: GSE26964. PPCa primary prostate cancer; MPCa metastatic prostate cancer; ROC receiver operating characteristic curve; AUC area under the curve

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Biomarker Discovery

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Identified biomarker microRNAs and their targets in MPCa-specific microRNA-mRNA network. Elliptic, triangular and rectangular nodes represent microRNAs, TF genes and non-TF genes, respectively. Nodes in grey represent genes that are uniquely regulated by single microRNAs in the network. MPCa metastatic prostate cancer; TF transcription factor

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Biomarker Discovery

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Top ten significant GO terms enriched by targets of the identified microRNA biomarkers

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Membrane, Activity Assay, Binding Assay

Journal: Journal of Translational Medicine

Article Title: Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

doi: 10.1186/s12967-018-1506-7

Figure Lengend Snippet: Pathway enrichment analysis for targets of the identified microRNA biomarkers. The statistical significance level (adj. p value) was negative 10-based log transformed. a The top ten significant KEGG terms. b The top ten significant IPA terms. adj.p value adjusted p value; KEGG Kyoto Encyclopedia of Genes and Genomes; IPA ingenuity pathway analysis

Article Snippet: Moreover, another independent dataset GSE26964 [ ] with 6 PPCa and 7 MPCa samples from Capitalbio mammal microRNA V3.0 platform was selected for result validation.

Techniques: Transformation Assay

Journal: Computational and Mathematical Methods in Medicine

Article Title: Integrative Bioinformatics Analysis Reveals That miR-524-5p/MEF2C Regulates Bone Metastasis in Prostate Cancer and Breast Cancer

doi: 10.1155/2022/5211329

Figure Lengend Snippet: Identification of DE-miRNAs and DEGs related to cancer bone metastasis. (a) Clustered heat map of 1555 DEGs in GSE137842. Red: significantly upregulated genes; blue: significantly downregulated genes. (b) Differentially expressed volcano plots in GSE137842. Red dots: significantly upregulated; green dots: significantly downregulated; and black dots: no significant differences. (c) Clustered heat map of 833 DEGs in GSE32269. Red: significantly upregulated genes; blue: significantly downregulated genes. (d) Differentially expressed volcano plots in GSE32269. Red dots: significantly upregulated; green dots: significantly downregulated; and black dots: no significant differences. (e) Clustered heat map of 88 DE-miRNAs in GSE26964. Red: upregulated genes; blue: downregulated genes. (f) Differentially expressed volcano plots in GSE26964. Red dots: significantly upregulated; green dots: significantly downregulated; and black dots: no significant differences. (g) The common DEGs from GSE32269 and GSE137842 involved in prostate cancer bone metastasis and breast cancer bone metastasis by Venny 2.1.0. (h) List of the common DEGs from GSE32269 and GSE137842.

Article Snippet: The miRNA microarray dataset GSE26964 [ ] was composed of 6 primary prostate cancer samples and 7 prostate cancer bone metastatic samples (platform: Capitalbio mammal microRNA V3.0).

Techniques:

Journal: American Journal of Translational Research

Article Title: Angiotensin II type i receptor agonistic autoantibodies induces apoptosis of cardiomyocytes by downregulating miR21 in preeclampsia: a mechanism study

doi:

Figure Lengend Snippet: miRNA expression profiles and detection of miR-21 in the cardiac tissue and neonatal rat cardiomyocytes. A: Microarray chip analysis of miRNA expression in the cardiac tissue of control and model groups. Columns represent cell lines and rows show the relative expression level for individual miRNAs. The red and green colors indicate high of low expression, respectively. B: Scatter plot of signal intensity of gene chip. C, D: miR-21 level in the cardiac tissue and neonatal rat cardiomyocytes by Western Blot and qRT-PCR analysis.

Article Snippet: Total RNA was extracted by routine Trizol method, and the quality was detected by ultraviolet absorption and denaturing agarose gel electrophoresis. miRNA chip V3.0 hybridization was performed using miR crystal core · micro RNA microarray Kit (CapitalBio).

Techniques: Expressing, Microarray, Control, Western Blot, Quantitative RT-PCR