Journal: Cell & Bioscience

Article Title: Hsa_circ_0051079 functions as an oncogene by regulating miR-26a-5p/TGF-β1 in osteosarcoma

doi: 10.1186/s13578-019-0355-2

Figure Lengend Snippet: Deregulated circRNAs in osteosarcoma tumor tissues. a The heat map of significant circRNAs in osteosarcoma tissues and the matched non-tumor tissues. circRNAs were analyzed by circRNAs Arraystar Chip. The samples were from 5 osteosarcoma patients. b – e Relative expression of the four circRNAs from 45 osteosarcoma tumor tissues and adjacent non-tumor tissues listed in ( a ) measured by RT-qPCR. **p < 0.01

Article Snippet: Fig. 1 Deregulated circRNAs in osteosarcoma tumor tissues. a The heat map of significant circRNAs in osteosarcoma tissues and the matched non-tumor tissues. circRNAs were analyzed by circRNAs Arraystar Chip.

Techniques: Expressing, Quantitative RT-PCR

Journal: FEBS Open Bio

Article Title: Circular RNA expression profiles in extracellular vesicles from the plasma of patients with pancreatic ductal adenocarcinoma

doi: 10.1002/2211-5463.12741

Figure Lengend Snippet: Primers used for quantitative real‐time PCR analysis of circRNA levels. F, forward; PS, product size; R, reverse.

Article Snippet: RNA library construction and circRNA sequencing (circRNA‐seq) were performed by CloudSeq Biotech Inc. (Shanghai, China).

Techniques: Real-time Polymerase Chain Reaction, Sequencing

Journal: FEBS Open Bio

Article Title: Circular RNA expression profiles in extracellular vesicles from the plasma of patients with pancreatic ductal adenocarcinoma

doi: 10.1002/2211-5463.12741

Figure Lengend Snippet: Differential expression of circRNAs in EVs between patients with PDAC and healthy volunteers. (A) Heatmap for the 453 significant differentially expressed circRNAs between EVs of PDAC and normal control. C1–C8 represent samples from patients with PDAC, and H1–H8 represent samples from healthy controls. Each row represents a circRNA, and each column represents a sample. Hierarchical clustering analysis of the samples was shown. (B) The scatterplot showed the EVs circRNA expression variation between patients with PDAC and healthy control subjects. The values of the x and y axes in the scatterplot are the averaged normalized signal values of groups of samples (log2 scaled). The oblique lines are fold change lines. The circRNAs above the top oblique line and below the bottom oblique line indicated more than 2‐fold change of circRNAs between the two groups of samples. (C) Volcano plot of the differentially expressed circRNAs. The vertical lines demark the fold change values, whereas the green horizontal line marks a P ‐value of 0.05. The red squares in the plot represent the differentially expressed circRNAs in patients with PDAC compared with the control subjects ( P < 0.05), corresponding to 2‐fold up and down, respectively. (D, E) Classification of the dysregulated circRNAs by a pie chart.

Article Snippet: RNA library construction and circRNA sequencing (circRNA‐seq) were performed by CloudSeq Biotech Inc. (Shanghai, China).

Techniques: Quantitative Proteomics, Control, Expressing

Journal: FEBS Open Bio

Article Title: Circular RNA expression profiles in extracellular vesicles from the plasma of patients with pancreatic ductal adenocarcinoma

doi: 10.1002/2211-5463.12741

Figure Lengend Snippet: (A) Validation of the differentially expressed circRNAs obtained from circRNA‐seq data. The expression of the top eight up‐regulated and top five down‐regulated circRNAs obtained from RNA‐seq was validated by quantitative real‐time PCR analysis using EVs of 14 patients with PDAC and healthy control subjects. (B) Expression levels of four up‐regulated circRNAs were detected in four kinds of human pancreatic cancer cell lines. The y axis of the columns is the log2‐transformed median fold changes in expression, and data were presented as the mean and standard deviation values. These experiments were repeated three times.

Article Snippet: RNA library construction and circRNA sequencing (circRNA‐seq) were performed by CloudSeq Biotech Inc. (Shanghai, China).

Techniques: Biomarker Discovery, Expressing, RNA Sequencing, Real-time Polymerase Chain Reaction, Control, Transformation Assay, Standard Deviation

Journal: FEBS Open Bio

Article Title: Circular RNA expression profiles in extracellular vesicles from the plasma of patients with pancreatic ductal adenocarcinoma

doi: 10.1002/2211-5463.12741

Figure Lengend Snippet: Predicted circRNA‐miRNA interaction network of the 13 selected differentially expressed circRNAs. Yellow cycles represent circRNAs, and green arrows represent miRNAs.

Article Snippet: RNA library construction and circRNA sequencing (circRNA‐seq) were performed by CloudSeq Biotech Inc. (Shanghai, China).

Techniques:

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: Differential expression of circRNAs in IA tissues. (A) The constituent of upregulated circRNAs. (B) The constituent of downregulated circRNAs. (C) The scatterplot is used for assessing the circRNA expression variation between the two compared samples or two compared groups of samples. The values of X and Y axes in the scatterplot are the normalized signal values of the samples (log 2 scaled) or the averaged normalized signal values of groups of samples (log 2 scaled). The green lines are Fold Change Lines. The circRNAs above the top green line and below the bottom green line indicate more than 1.5-fold change of circRNAs between the two compared samples. (D) Volcano Plots are used for visualizing differential expression between two different conditions. The vertical lines correspond to 1.5-fold up and down, respectively, and the horizontal line represents a p -value of 0.05. So the red point in the plot represents the differentially expressed circRNAs with statistical significance. Group A represented STA samples; group B represented IA samples. (E) The hierarchical clustering of differentially expressed circRNAs. “Red” indicates high relative expression, and “green” indicates low relative expression. Group A represented STA samples; group B represented IA samples. (F) Validation of the differential expression of five upregulated circRNAs. (G) Validation of the differential expression of hsa_circRNA_101833 in another five coupled groups. STA, superficial temporal arteries; IA, IA.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques: Expressing

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: Schematic diagram of hsa_circRNA_101833. The light green bar represents the open reading frame, the blue bar represents proteins binding with hsa_circRNA_101833, and the red bar represents the microRNA binding sites.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques: Binding Assay

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: Open reading frames detected from hsa_circRNA_101833.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques: Sequencing

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: miRNAs that connected with hsa_circRNA_101833.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques:

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: Proteins that bind with hsa_circRNA_101833.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques:

Journal: Frontiers in Aging Neuroscience

Article Title: Circular RNA circDUS2 Is a Potential Biomarker for Intracranial Aneurysm

doi: 10.3389/fnagi.2021.632448

Figure Lengend Snippet: GO and KEGG analysis results. (A) GO annotations of target genes of microRNAs binding on hsa_circRNA_101833 with top 10 enrichment score encompassing the domains of physiological processes. (B) Dotplot of KEGG pathway analysis; the size of the circle represents the count of genes, and the color represents the p -values of pathways. (C) The visualization of signaling pathways regulating the pluripotency of stem cells and the FoxO signaling pathway conducted by Pathview.

Article Snippet: We detected hundreds of differentially expressed circRNAs using the Arraystar human circRNA Microarray; 456 (83.82%) of the upregulated circRNAs and 349 (87.69%) of the downregulated circRNAs belong to the exonic type.

Techniques: Binding Assay

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: Hierarchical clustering of the circRNA expression data based on ‘All Targets Value’–which arranges the samples into groups based on their expression levels–revealed a distinguishable circRNA expression profiling among samples.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques: Expressing

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: Scatter plots used to identify differentially-expressed circRNAs in (A) PTC tumors versus normal thyroid tissue and (B) PTC tumors versus benign thyroid lesions. The axis represent the mean normalized circRNA signal values for each comparator group (log 2 scaled). The green fold-change lines represent 2.0× fold-changes, so the circRNAs lying above and below these green lines displayed greater than a 2.0-fold upregulation or downregulation. Volcano plots used to identify differentially-expressed circRNAs in (C) PTC tumors versus normal thyroid tissue and (D) PTC tumors versus benign thyroid lesions. The x -axis represents fold-change values (log 2 scaled), while the y -axis represents p -values (-log 10 scaled). The green vertical lines correspond to 2.0× upregulation and downregulation, respectively, while the green horizontal line corresponds to a p -value of 0.05. On this basis, the red rectangles represent the differentially-expressed circRNAs of statistical significance.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques:

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: Significantly upregulated circRNAs in PTC tumors versus benign thyroid tissue.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques:

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: Significantly downregulated circRNAs in PTC tumors versus benign thyroid tissue.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques:

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: The network map consists of the previously identified 12 significantly upregulated circRNAs (represented by red nodes) and four significantly downregulated circRNAs (represented by yellow nodes) along with their 56 target miRNAs (represented by blue nodes). The numerical rank of each circRNA fold-change has been annotated next to each circRNA node.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques:

Journal: PLoS ONE

Article Title: Microarray profiling of circular RNAs in human papillary thyroid carcinoma

doi: 10.1371/journal.pone.0170287

Figure Lengend Snippet: (A) The targeted pathway heatmap analysis revealed significant correlations (depicted in red) between cancer-related pathways and two miRNA clusters: the miR-141-3p/miR-15a-5p/miR-23b-3p cluster and the miR-200a-3p/miR-214-3p cluster. The color-coded legend depicts the associated log-scaled p -values. (B) Based on the Arraystar-derived network map of circRNA-miRNA interactions, the candidate circRNA hsa_circRNA_100395 was predicted to interact with the two cancer-related miRNAs: hsa-miR-141-3p and hsa-miR-200a-3p. (C) Seed sequence matching predicts the direct interaction of hsa_circRNA_100395 with miR-141-3p and miR-200a-3p.

Article Snippet: Based on our Arraystar's circRNA target prediction analysis, we constructed a network map of circRNA-miRNA interactions for the sixteen significantly differentiated circRNAs in PTC tumors.

Techniques: Derivative Assay, Sequencing