Query a miRNA
Users can query a miRNA of interest by typing the miRNA accession number, miRNA ID of miRBase release 22.1  or previous miRNA IDs in
the 'Search a miRNA' field and selecting this miRNA from the dropdown
list. In addition to the general information including IDs and sequence
of the queried miRNA, links to five miRNA-target databases including
ENCORI , miRDB , miTarBase , TargetScan , and
Diana-TarBase  are also provided.
A suite of advanced analyses can be interactively performed
for a selected miRNA of interest (Figure 1), including:
(1) Pan-cancer differential expression (DE) analysis,receiver operating characteristic (ROC) analysis
and Kaplan Meier (KM) survival analysis in TCGA;
(2) DE analysis, ROC analysis, and KM survival analysis in a selected TCGA project;
(3) miRNA-target correlation analysis;
(4) Functional enrichment analysis of miRNA targets;
(4) Functional enrichment analysis of miRNA targets;
(5) Circulating miRNA expression analysis
Figure 1. Query a miRNA of interest
2. TCGA Pan-cancer Analysis
Pan-cancer DE analysis and ROC analysis of a miRNA
between tumor and normal samples can be performed
in 33 cancer types from TCGA (Figure 2).
(1) Wilcoxon rank sum test is used for DE analysis.
The expression levels and statistical significances
of the miRNA in all the TCGA projects can be visualized
in a box plot.
(2) ROC analysis is performed to measure the diagnostic ability of the
miRNA in classifying tumor and normal samples.
A forest plot with the number of tumor and normal samples,
area under the curve (AUC), and 95% confidence interval (CI)
of the AUC for each TCGA project is used to visualize the result.
(3) Prognostic ability of a miRNA can be evaluated by performing KM survival analysis of overall survival (OS) between tumor
samples with high and low expression of the miRNA of interest
defined by its median expression value.
A forest plot displaying the number of tumor samples, hazard ratio (HR),
95% CI of the HR, and p value for each cancer type in TCGA is used to
visualize the result of pan-cancer survival analysis.
Figure 2. Pan-cancer DE analysis, ROC analysis, and KM survival analysis for the selected miRNA
3. miRNA Analysis in individual TCGA projects
CancerMIRNome provides functions to focus the DE analysis,
ROC analysis, and KM survival analysis for the miRNA of
interest in a selected TCGA project.
When a TCGA project is selected from the dropdown list,
(1) A box plot with miRNA expression and p value of wilcoxon rank-sum
test between tumor and normal samples, (2) an ROC curve, and (3) a KM
survival curve for the selected project will be displayed (Figure 3).
Figure 3. miRNA analysis in a selected TCGA project
4. miRNA-Target Correlation Analysis
Pearson correlation between a miRNA and its targets in tumor and normal
tissues of TCGA projects can be queried in CancerMIRNome.
The miRNA-target interactions are based on miRTarBase 2020 ,
an experimentally validated miRNA-target interactions database.
The expression correlations between a miRNA and all of its targets in
a selected TCGA project are listed in an interactive data table.
Users can select an interested interaction between miRNA and mRNA target
in the data table to visualize a scatter plot showing their expression
pattern and correlation metrics.
An interactive heatmap is also available to visualize and
compare such miRNA-target correlations across all TCGA projects.
Figure 4. miRNA-target correlation analysis
5. Functional Enrichment Analysis of miRNA Targets
Functional enrichment analysis of the target genes for a miRNA
can be performed using clusterProfiler  in CancerMIRNome.
CancerMIRNome supports functional enrichment analysis with many
pathway/ontology knowledgebases including:
(1) KEGG: Kyoto Encyclopedia of Genes and Genomes
(3) DO: Disease Ontology
(4) NCG: Network of Cancer Gene
(6) GO-BP: Gene Ontology (Biological Process)
(7) GO-CC: Gene Ontology (Cellular Component)
(8) GO-MF: Gene Ontology (Molecular Function)
(9) MSigDB-H: Molecular Signatures Database (Hallmark)
(10) MSigDB-C4: Molecular Signatures Database (CGN: Cancer Gene Neighborhoods)
(11) MSigDB-C4: Molecular Signatures Database (CM: Cancer Modules)
(12) MSigDB-C6: Molecular Signatures Database (C6: Oncogenic Signature Gene Sets)
A data table is produced to summarize the significantly enriched
pathways/ontologies in descending order based on their significance
levels, as well as the number and proportion of enriched genes and the
gene symbols in each pathway/ontology term. The top enriched pathways/ontologies
are visualized using both bar plot and bubble plot.
Figure 5. Functional enrichment analysis of miRNA targets
6. Circulating miRNA Expression Profiles of Cancer
Expression of the interested miRNA in whole blood, serum, plasma,
extracellular vesicles, or exosomes in both healthy and different cancer
types can be conveniently explored in CancerMIRNome on the basis of 40
circulating miRNome datasets. Users can select one or more datasets
for an analysis, through which violin plots are displayed for visualization
and comparison of circulating miRNA expression between samples or datasets.
Figure 6. Expression of circulating miRNAs in cancer
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