Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The experimental scheme of the study. The discovery cohort was composed of two TB patients and two age- and gender-matched healthy controls: one young male case-control pair and one senior female case-control pair. PBMC circRNA expression in the discovery cohort was profiled by both rRNA-depleted RNA-seq and a circRNA expression microarray. We aggregated circRNAs into pathway-level mechanisms using KEGG pathway definitions. Pathways with significant circRNA dysregulation were prioritized by performing a paired Wilcoxon signed-rank test between paired control and TB samples. A molecular signature was developed based on the dysregulated circRNAs within the prioritized pathways. This circRNA signature was further validated by qRT-PCR in a validation cohort with 11 healthy controls and 10 TB patients.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Control, Expressing, RNA Sequencing, Microarray, Quantitative RT-PCR, Biomarker Discovery

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: Landscape of PBMC circRNA expression. (a) A Venn diagram of the parental genes with circRNA transcripts among PBMCs, platelets, RBCs, and whole blood. (b) Distribution of log 2 -transformed TPM values of circular transcripts in PBMCs, platelets, RBCs, and whole blood. (c) The fraction of RNA-seq reads from coding linear, non-coding linear, and circular transcripts. (d) The cumulative distribution of TPM values of circular transcripts. A significantly increased circRNA TPM was observed in the TB patients compared with the healthy controls. The P -values were computed by the Kolmogorov-Smirnov test.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Expressing, Transformation Assay, RNA Sequencing

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The KEGG pathways enriched by upregulated circRNAs. A paired Wilcoxon test was applied to identify the KEGG pathways enriched by dysregulated circRNAs in young and senior TB patients. (a) The correlation in Z -scores (computed by a paired Wilcoxon test) between young and senior case-control pairs. Each dot represents one KEGG pathway. The red points stand for the pathways with circular transcripts commonly upregulated in both young and senior TB patients. (b) Paired comparison of circRNA expression in the five prioritized KEGG pathways. (c) Comparison of the fraction of circRNA reads in the five pathways between healthy controls and TB patients.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Control, Comparison, Expressing

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: Technical validation of the five prioritized KEGG pathways using a circRNA expression microarray. Total RNA was treated with RNase R to remove linear transcripts and then subject to microarray hybridization.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Biomarker Discovery, Expressing, Microarray, Hybridization

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The 7-circRNA signature.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques:

Journal: EBioMedicine

Article Title: Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

doi: 10.1016/j.ebiom.2017.12.007

Figure Lengend Snippet: The 7-circRNA signature. (a) Expression heatmap of the circRNAs within the 7-circRNA signature in the discovery cohort. The expression measured by both RNA-seq and circRNA microarray is displayed. (b) Comparison of the expression levels of the 7-circRNA signature between the healthy controls and TB patients in the validation cohort. The error bars represent the standard error of the mean. (c) Principal component analysis of the 7-circRNA signature. PC1: the first principal component; PC2: the second principal component. (d) Comparison of the circRNA-based TB index between the healthy controls and TB patients in the validation cohort. (e) The ROC curve of the TB index in distinguishing TB patients from healthy controls. The light blue area indicates the confidence interval of the ROC curve.

Article Snippet: The CapitalBio Technology Human CircRNA Array v2 (4 × 180K) was used to quantify circRNA expression.

Techniques: Expressing, RNA Sequencing, Microarray, Comparison, Biomarker Discovery

Journal: Cell & Bioscience

Article Title: Circular RNA expression profile in blood according to ischemic stroke etiology

doi: 10.1186/s13578-020-00394-3

Figure Lengend Snippet: Distribution by chromosomes ( a ) and chromosome’s region ( b ). Differentially expressed circRNA distribution in chromosomes and chromosome´s region (exonic, intronic, antisense, sense overlapping and intergenic) for each comparison

Article Snippet: To this end, we used Arraystar Human circRNA Array (8 × 15 K, Arraystar), which surveys up to 13,617 probes to identify human circRNAs, in 30 acute stroke patients with different etiologies by TOAST classification [ ].

Techniques:

Journal: Cell & Bioscience

Article Title: Circular RNA expression profile in blood according to ischemic stroke etiology

doi: 10.1186/s13578-020-00394-3

Figure Lengend Snippet: Deregulated circRNA chosen for qPCR validation

Article Snippet: To this end, we used Arraystar Human circRNA Array (8 × 15 K, Arraystar), which surveys up to 13,617 probes to identify human circRNAs, in 30 acute stroke patients with different etiologies by TOAST classification [ ].

Techniques:

Journal: Cell & Bioscience

Article Title: Circular RNA expression profile in blood according to ischemic stroke etiology

doi: 10.1186/s13578-020-00394-3

Figure Lengend Snippet: RT-qPCR validation of hsa_circRNA_102488. a Schematic representation of the UBA52 gene, origin of hsa_circRNA_102488. The graph shows the map of hsa_circRNA_102488 which is originated from exons 2 and 3 of its host mRNA (NCBI RefSeq track shown in the UCSC Genome Browser). b hsa_circRNA_102488 backsplicing. The Sanger-Sequencing electropherogram specifies the sequence of the backspliced junction that results in the circRNA formation. c – e hsa_circRNA_102488 and UBA52 mRNA expression levels between atherotrombotic vs cardioembolic samples. Percentage of hsa_circRNA_102488 expression relative to GAPDH mRNA ( c ) or UBA52 mRNA ( d ) is decreased in atherotrombotic with respect to cardioembolic stroke patients. However, we found similar expression levels of UBA52 mRNA in atherotrombotic and cardioembolic samples groups ( e ). Error bars: 95% CI. **p-value < 0.01; ***p-value < 0.001

Article Snippet: To this end, we used Arraystar Human circRNA Array (8 × 15 K, Arraystar), which surveys up to 13,617 probes to identify human circRNAs, in 30 acute stroke patients with different etiologies by TOAST classification [ ].

Techniques: Quantitative RT-PCR, Sequencing, Expressing

Journal: Cell & Bioscience

Article Title: Circular RNA expression profile in blood according to ischemic stroke etiology

doi: 10.1186/s13578-020-00394-3

Figure Lengend Snippet: GO analysis by mirPath v.3. The image shows the heatmaps corresponding to the analysis performed with the overrepresented miRNAs in the three comparisons (atherotrombotic-cardioembolic-undetermined) by TargetScan ( a ) and the analysis involving the target miRNAs for hsa_circRNA_102488 in accordance with molecular function ( b , by Tarbase) or biological process ( c , by microT-CDS)

Article Snippet: To this end, we used Arraystar Human circRNA Array (8 × 15 K, Arraystar), which surveys up to 13,617 probes to identify human circRNAs, in 30 acute stroke patients with different etiologies by TOAST classification [ ].

Techniques:

Journal: Cell & Bioscience

Article Title: Circular RNA expression profile in blood according to ischemic stroke etiology

doi: 10.1186/s13578-020-00394-3

Figure Lengend Snippet: hsa_circRNA_102488 impact pathways. The cartoon shows miRNAs (in blue) sharing a target site with hsa_circRNA_102488 (in black) and the pathways in which they converge (in dark orange), within those associated with the overrepresented miRNAs in the three comparisons (in light orange). RBPs sites matching to hsa_circRNA_102488 clustered around AGO2 (in dark green) and RBPs sites that matched to its flanking regions clustered around FUS (in light green). ARVC: Arrhythmogenic Right Ventricular Cardiomyopathy; HCM: Hypertrophic Cardiomyopathy

Article Snippet: To this end, we used Arraystar Human circRNA Array (8 × 15 K, Arraystar), which surveys up to 13,617 probes to identify human circRNAs, in 30 acute stroke patients with different etiologies by TOAST classification [ ].

Techniques:

Journal: BMC Cardiovascular Disorders

Article Title: Circular RNA expression profile and its potential regulative role in human abdominal aortic aneurysm

doi: 10.1186/s12872-020-01374-8

Figure Lengend Snippet: circRNAs expression profiles detected by microarray in the AAA group and control group. a The box plot shows the nearly identical distributions of normalized intensity values from the aortic samples of the AAA and control group. b The scatter plot is built to assess the expression variation of circRNAs between the two groups. The X and Y axes indicate the normalized intensity values of each circRNAs from the AAA and control group. The dots above the upper green line and below the lower green line represent the dysregulated circRNAs with a fold change (FC) > 2.0 between the two groups. c The volcano plot presents differentially expressed circRNAs in AAA. The vertical lines correspond to 2-fold upregulation and downregulation, the horizontal line indicates P value of 0.05. The red dots represent the differentially expressed circRNAs (FC > 2.0 and P value < 0.05). d Hierarchical clustering analysis reveals a distinguishable expression profile of circRNAs between the AAA and control group. Each column indicates an aortic sample, each row represents a circRNA. The red and green color indicate high and low expression level, respectively. e Chromosomal distribution of the differentially expressed circRNAs between the two groups

Article Snippet: The fragmented labeled cRNAs were hybridized onto the circRNA expression microarray slide (Arraystar Human circRNA Array V2).

Techniques: Expressing, Microarray, Control

Journal: BMC Cardiovascular Disorders

Article Title: Circular RNA expression profile and its potential regulative role in human abdominal aortic aneurysm

doi: 10.1186/s12872-020-01374-8

Figure Lengend Snippet: Validation of six randomly selected dysregulated circRNAs by qRT-PCR. Each circRNA was evaluated at least three times and compared with the results of microarray. The Y axis indicates the fold change of AAA vs control of each circRNA

Article Snippet: The fragmented labeled cRNAs were hybridized onto the circRNA expression microarray slide (Arraystar Human circRNA Array V2).

Techniques: Biomarker Discovery, Quantitative RT-PCR, Microarray, Control

Journal: BMC Cardiovascular Disorders

Article Title: Circular RNA expression profile and its potential regulative role in human abdominal aortic aneurysm

doi: 10.1186/s12872-020-01374-8

Figure Lengend Snippet: The predicted circRNA/miRNA interaction networks for six randomly selected circRNAs. a , b The red nodes indicate upregulated circRNAs. c - f The blue nodes represent downregulated circRNAs. The green nodes are five complementary binding miRNAs of each circRNA

Article Snippet: The fragmented labeled cRNAs were hybridized onto the circRNA expression microarray slide (Arraystar Human circRNA Array V2).

Techniques: Binding Assay

Journal: Frontiers in Oncology

Article Title: CircHADHA-augmented autophagy suppresses tumor growth of colon cancer by regulating autophagy-related gene via miR-361

doi: 10.3389/fonc.2022.937209

Figure Lengend Snippet: Plasma circRNA expression pattern in healthy individuals and colon polyp and colon cancer patients. (A) The endoscopic diagnosis of healthy individuals (left panel) and colon polyp (central panel) and colon cancer (right panel) patients. (B) The schematic diagram of Arraystar assay performance in plasma circRNAs. (C) The differential expression of plasma circRNAs in polyp patients ( N = 5) and healthy individuals ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between polyp patients and healthy individuals (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between polyp patients and healthy individuals (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (D) The differential expression of plasma circRNAs in colon cancer ( N = 5) and colon polyp patients ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between colon cancer and colon polyp patients (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between colon cancer and colon polyp patients (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (E) The differential expression of plasma circRNAs in colon cancer patients ( N = 5) and healthy individuals ( N = 5). The expression variation of circRNAs was assessed by the scatter plot between colon cancer patients and healthy individuals (left panel). The green lines represented fold change lines. The circRNAs above the top green line and below the bottom green line indicated more than 1.5-fold change of circRNAs between the two compared samples. The differential expression of circRNAs was analyzed by volcano plots between cancer patients and healthy individuals (right panel). Red points represented the differentially expressed circRNAs with statistical significance (1.5-fold upregulation and downregulation, P < 0.05). (F–H) The composition of types in detectable circRNAs. (F) The composition of circRNA types in polyp and colon cancer patients. (I) The Venn analysis between upregulated circRNAs from colon cancer patients compared with colon polyp patients and downregulated circRNAs from colon polyp patients compared with healthy individuals. (J) The Venn analysis between downregulated circRNAs from colon cancer patients compared with colon polyp patients and upregulated circRNAs from colon polyp patients compared with healthy individuals. (K) The potential circRNA candidates were validated by performing real-time PCR in plasma from healthy individuals ( N = 15) and colon polyp ( N = 15) and colon cancer ( N = 15) patients. (L) The schematic diagram of circHADHA dynamic alteration in healthy individuals and colon polyp and colon cancer patients. **** P < 0.0001; ns, no significant difference.

Article Snippet: We collected plasma from healthy individuals and colon polyp and colon cancer patients confirmed by endoscopic diagnosis ( ) and analyzed 2,162 human circRNAs by Arraystar ( ).

Techniques: Clinical Proteomics, Expressing, Biomarker Discovery, Quantitative Proteomics, Real-time Polymerase Chain Reaction

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: The expression of circRNA SCARB1, mature miR-497 and miR-497 precursor was altered in HCC. HCC and paired non-tumor tissues were collected from the 64 HCC patients included in this study, and the expression of circRNA SCARB1 ( A ), mature miR-497 ( B ) and miR-497 precursor ( C ) in these tissue samples was determined by RT-qPCR. Average values of three technical replicates were used to express gene expression data in paired HCC and non-tumor tissues, ** p < 0.01.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Expressing, Quantitative RT-PCR, Gene Expression

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: The Correlations Between Clinicopathological Variables and the Expression of circRNA SCARB1 in HCC

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Expressing, Infection

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: CircRNA SCARB1 and mature miR-497 were inversely correlated across HCC samples. Pearson’s correlation coefficient analysis was used to analyze the correlations between circRNA SCARB1 and mature miR-497 ( A ) or miR-497 precursor ( B ) across HCC tissue samples.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques:

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 downregulated mature miR-497 in HCC cells. To explore the effects of overexpression of circRNA SCARB1 on the maturation of miR-497, SNU-423 and SNU-387 cells were transfected with either circRNA SCARB1 expression vector or miR-497 mimic, followed by the confirmation of transfections at 48 h post-transfection by RT-qPCR ( A ). The effects of overexpression of circRNA SCARB1 of the expression of mature miR-497 ( B ) and miR-497 precursor ( C ), as well as the effects of the transfection of miR-497 mimic on circRNA SCARB1 expression ( D ) were also analyzed by RT-qPCR. Mean ± SD values were used to express data of 3 biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, Transfection, Expressing, Plasmid Preparation, Quantitative RT-PCR, In Vitro

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 increased HCC cell proliferation through miR-497. CCK-8 assay was performed to analyze the effects of overexpression of circRNA SCARB1 and miR-497 on the proliferation of SNU-423 ( A ) and SNU-387 cells ( B ). Mean ± SD values were used to express data of three biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, CCK-8 Assay, In Vitro

Journal: Cancer Management and Research

Article Title: The Maturation of Tumor Suppressor miR-497 in Hepatocellular Carcinoma is Inhibited by Oncogenic circRNA SCARB1

doi: 10.2147/CMAR.S304125

Figure Lengend Snippet: Overexpression of circRNA SCARB1 increased HCC cell migration through miR-497. Transwell assay was conducted to analyze the effects of overexpression of circRNA SCARB1 and miR-497 on the migration of SNU-423 ( A and C ) and SNU-387 cells ( B and D ). Mean ± SD values were used to express data of three biological replicates of in vitro cell experiments. * p < 0.05.

Article Snippet: To overexpress circRNA SCARB1, pcDNA3.1(+) CircRNA Mini Vector (Addgene) was used as the backbone to construct the expression vector of circRNA SCARB1.

Techniques: Over Expression, Migration, Transwell Assay, In Vitro