Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet: AGAP2 mRNA and protein levels discrepancies (A) AGAP2 mRNA basal levels were measured in prostate cancer (PC) cell lines (DU145, PC3, LNCaP) and chronic myeloid leukemia (CML) cell lines (KU812, TCC-S, KCL-22) by RT-qPCR. The values presented were normalized against the levels of the housekeeping gene HPRT and shown relative to the prostate cancer cell line DU145. Statistical analyses were carried out by one-way ANOVA[F (5, 12) = 21.23, p < 0.0001)] with post-hoc Sidak’s multiple comparison tests. (B) Representative image of AGAP2 protein levels detected by immunoblotting in CML and PC cell lines. β-Actin was used a loading control. Densitometry values for the relative protein expression are represented below the blots. Differences were analyzed using Kruskal-Wallis [H (5) = 14.71, p = 0.012] followed by uncorrected Dunn’s test. (C) Strong negative correlation between AGAP2 mRNA (x axis) and protein levels (y axis) in PC and CML cell lines (Pearson’s R = −0.89, p = 0.016). The data presented is relative to DU145 (PC cell line). (D and E) AGAP2 relative mRNA levels (D) and protein (E) in different cancer cell lines, assessed as described in (A) and (B). Statistical analyses for mRNA levels in (D) were carried out by one-way ANOVA[F (9, 20) = 41.30, p < 0.001)] with post-hoc Sidak’s multiple comparison tests. (F and G) Western blot analysis for the accumulation of ubiquitinated proteins (as positive control for the proteasomal inhibitors) and AGAP2 levels in CML cell lines treated with proteasomal inhibitors: MG132 [KU812 (5 μM), TCC-S (5 μM), KCL-22 (50 μM) for 4 h] and Bortezomib [KU812 (200 nM), TCC-S (10 nM), KCL-22 (100 nM) for 6 h]. β-Actin levels were used as a loading control. All data shown in the graphs in this figure are the mean ± SD from three independent experiments (performed in triplicate in the case of qPCRs); (∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001).

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Quantitative RT-PCR, Comparison, Western Blot, Control, Expressing, Positive Control

Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet: Alternative TSS usage for AGAP2 in PC and CML cell lines leads to differential 5′ UTR isoforms (A) Image derived from the ZENBU browser ( http://fantom.gsc.riken.jp/zenbu/ ) showing the main TSSs in AGAP2 and its frequency (height of peaks). 5′ RACE was performed according to the manufacturer’s instructions using adenines for the tailing reaction. KU812, a CML cell line, presents with an upstream TSS that produces an AGAP2 mRNA with a slightly longer (35 bp) 5′ UTR than the one found in DU145, a PC cell line. In those extra nucleotides, there is a repetition of guanine residues that fits the pattern predicted for the formation of G quadruplexes. (B) Comparison of the frequency of alternative TSSs used in DU145 (PC) and KU812 (CML) cell lines, mapped by 5′ RLM-RACE. The relative frequencies (in percentages) are shown as bars placed at the nucleotide position upstream from the start codon (n = 10). (C) TSSs for AGAP2 in KU812 obtained by 5′ RLM-RACE is plotted against the TSSs noted by the FANTOM CAGE database. (D) Cartoon representing AGAP2 core promoter and its TSSs. The differential TSS selection creates slight differences in the length of the 5′ UTR, with upstream/earlier TSSs resulting in longer 5′ UTRs. The selection of an earlier TSS in CML KU812 produces an mRNA that encodes extra nucleotides in the 5′ UTR containing the consensus for a G quadruplex structure. (E) Relative levels of the longer AGAP2 5′ UTR containing the G quadruplex consensus sequence in PC and CML cell lines. The data represent the mean ± SD of three independent experiments. Statistical differences were analyzed by one-way ANOVA[F (5, 12) = 29.35, p < 0.0001)] with post-hoc Sidak’s multiple comparison tests, p-values shown. (∗p < 0.05; ∗∗∗p < 0.001).

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Derivative Assay, Comparison, Selection, Sequencing

Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet: The G quadruplex (G4) structure in AGAP2 longer 5′ UTR influences mRNA translation negatively (A) Schematic representation of the fragments cloned into the bicistronic luciferase reporter (pcDNA3 RLUC POLIRES FLUC) plasmid. The AGAP2 5′ UTR fragments (shorter 5′ UTR, longer 5′ UTR with G4 consensus, and longer 5′ UTR with G4 consensus mutated) were inserted at the unique Nhe I restriction site proximal to the Renilla luciferase (Rluc) ORF. The Rluc is driven by cap-dependent mRNA translation through the cloned 5′ UTR. The Firefly luciferase cistron was used as an internal control for normalization. (B) Relative luciferase activity of the AGAP2 5′ UTR constructs measured using an in vitro transcription and translation system. The graph represents the mean of 4 independent experiments +/- standard deviation and data are expressed as the Rluc/Fluc ratio relative to the activity of the shorter 5′ UTR. Differences were analyzed using a Kruskal-Wallis [H (2) = 47.13, p =<0.001] followed by Mann-Whitney U test (∗∗∗p < 0.001). (C) Relative luciferase activity after transfecting the different constructs in DU145 and KU812 cells. The luciferase activity was analyzed 48 h after transfection in DU145 and 6 h after transfection in KU812. The graph represents the mean of three independent experiments performed in duplicate and expressed as relative Rluc/Fluc ratios. Differences between samples were analyzed with a Kruskal Wallis test followed by the Mann-Whitney U test, ∗∗∗p < 0.001. The bars represent the mean ± standard deviation. (D) Lysates for polysome profiling were prepared from KU812 and TCC-S cells and fractionated through a sucrose gradient. The profiles were monitored by measuring the absorbance at 254 nm (A 254 nm ). A representative polysome profile from a KU812 extraction is shown on the left. The relative distribution of the mRNA for AGAP2 longer 5′ UTR isoform (concentrated in the non-polysomal fractions) is shown on the right. The abundance of the RNA detected per fraction is presented as the percentage of the total RNA. mRNA levels were normalized to exogenous spike-in luciferase control mRNA. The graph represents the mean ± SEM of two independent experiments.

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Clone Assay, Luciferase, Plasmid Preparation, Control, Activity Assay, Construct, In Vitro, Standard Deviation, MANN-WHITNEY, Transfection, Extraction

Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet: Identification of potential targets regulated in a similar manner to AGAP2 (A) Workflow diagram used to identify genes whose expression could be regulated by the alternative selection of a TSSs, involving the presence of a G quadruplex (G4). First, the FANTOM database was used to identify all the transcripts that contained a G quadruplex (G4) consensus sequence between alternative TSSs within their defined TSS cluster. The G4 consensus sequences were identified using the pqsfinder package in R. The FANTOM database was also used to detect differential expression in PC (DU145, PC3) and CML (KU812, K562, KCL-22) cell lines for those genes that would encode a G4 consensus between alternative TSSs. Microarray and SWATH-MS data from the NCI-60 database were integrated to characterize genes that demonstrated discrepancies between their mRNA and protein levels (high mRNA and low protein) within those genes showing a differential 5′ UTRs with G4 sequences. (B) Metacore pathway enrichment analysis of mRNAs with alternative 5′ UTRs that contain G4 consensus sequences. The dot plot shows the top 15 enriched pathways with the largest gene ratio. The size of the dots represents the number of genes in each pathway and the color of the dots represents the adjusted p values (BH). (C) Venn diagram illustrating the overlapping genes in the FANTOM and NCI-60 databases showing differential 5′ UTRs with G4 consensus, with differentially expressed mRNA (≥1 log FC), and either no statistically significant differences in protein levels or significantly lower proteins levels in CML cell lines (left) or PC cell lines (right). The differential expression and TSS distribution were computed by linear modeling followed by empirical Bayes statistics.

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Expressing, Selection, Sequencing, Quantitative Proteomics, Microarray, Data-independent acquisition

Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet: HK1 expression is also regulated by an alternative TSSs and mediation of a G4 structure (A) HK1 mRNA basal levels were detected in prostate cancer (PC) cell lines (DU145, PC3, and LNCaP) and chronic myeloid leukemia (CML) cell lines (KU812, TCC-S, and KCL-22) by RT-qPCR. HK1 expression was normalized against levels for the housekeeping gene HPRT and it is shown relative to levels in the PC cell line DU145. The difference in RNA expression was analyzed using one-way ANOVA[F (5, 12) = 22.25, p < 0.001)] with post-hoc Sidak’s multiple comparison tests, P-values shown (∗∗∗p < 0.001). The error bars denote standard deviation. (B) HK I protein levels were detected by western blot. The graph later in discussion shows overall densitometry values relative to those in the DU145 cell line. (C) Relative expression levels for the HK1 isoform with the longer 5′ UTR containing a G4 consensus sequence, detected by RT-qPCR in PC and CML cell lines. The bars represent the mean ± SD of three independent experiments. Statistical differences were analyzed by one-way ANOVA[F (5, 12) = 8.6, p < 0.001)] with post-hoc Sidak’s multiple comparison tests, p-values shown (∗p < 0.05; ∗∗p < 0.01). (D) rG4IP followed by HK1 detection by RT-qPCR. Expression levels were normalized by input control, and the data presented correspond to three independent immunoprecipitations. The error bars denote the standard deviation. Differences between samples were analyzed by unpaired two-tailed t-tests, P-values shown. (E) Polysomal fractionation: relative abundance of the HK1 mRNA with the longer 5′ UTR in polysome fractions in TCC-S cells (left) and KU812 cells (right).

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Expressing, Quantitative RT-PCR, RNA Expression, Comparison, Standard Deviation, Western Blot, Sequencing, Control, Two Tailed Test, Fractionation

Journal: iScience

Article Title: Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression

doi: 10.1016/j.isci.2022.105519

Figure Lengend Snippet:

Article Snippet: KU812 (Human chronic myelogenous leukaemia) , ATCC , Cat#CRL-209; RRID:CVCL_0379.

Techniques: Control, Virus, Recombinant, Protease Inhibitor, Reporter Assay, Plasmid Preparation, TA Cloning, Bicinchoninic Acid Protein Assay, Reverse Transcription, Western Blot, Transfection, Microarray, Data-independent acquisition, Circular Dichroism, Mutagenesis, Software, Sequencing, Membrane, Cell Culture, Modification

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Schematic depicting the composition of circRNA_101237 (encoded by CDK8). circRNA, circular RNA; CDK8, cyclin-dependent kinase 8; chr, chromosome.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques:

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: CircRNA_101237 expression in HCC tissues. (A) Heatmap for differentially expressed circRNAs in HCC tumor tissues and the matched adjacent tissues (n=3). (B) RT-qPCR was performed to determine the expression of circRNA_101237 in tumor tissues (n=100) and adjacent tissues (n=100). (C) RT-qPCR was performed to assess the expression of circRNA_101237 in serum samples from patients with HCC (n=234) and healthy controls (n=120). (D) Kaplan-Meier survival curves were drawn to compare the survival of patients with high circRNA_101237 expression (n=148) and those with low circRNA_101237 expression (n=86). RT-qPCR, reverse transcription-quantitative PCR; HCC, hepatocellular carcinoma; circRNA_101237, circular RNA 101237; hsa, Homo sapiens.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques: Expressing, Quantitative RT-PCR, Real-time Polymerase Chain Reaction

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Clinical association between serum circRNA_101237 levels and clinicopathological characteristics of patients with hepatocellular carcinoma.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques: Expressing

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Univariate analysis of prognostic factors for patients with hepatocellular carcinoma.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques:

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Multivariate analysis of independent prognostic factors for patients with hepatocellular carcinoma.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques:

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Expression of circRNA_101237 is associated with cisplatin resistance. (A) RT-qPCR was performed to assess the expression of circRNA_101237 in serum samples of patients with cisplatin-sensitive HCC (n=50) and those with cisplatin-resistant HCC (n=35). (B) RT-qPCR was performed to determine the expression of circRNA_101237 in liver cancer cells. * P<0.05 vs. HCCLM3 cells; #P<0.05, Huh7/DDP vs. Huh7. Huh/DDP, cisplatin-resistant Huh7 cells; RT-qPCR, reverse transcription-quantitative PCR; HCC, hepatocellular carcinoma; circRNA_101237, circular RNA 101237.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques: Expressing, Quantitative RT-PCR, Real-time Polymerase Chain Reaction

Journal: Experimental and Therapeutic Medicine

Article Title: Cisplatin resistance-associated circRNA_101237 serves as a prognostic biomarker in hepatocellular carcinoma

doi: 10.3892/etm.2020.8526

Figure Lengend Snippet: Changes in circRNA_101237 expression in hepatocellular carcinoma cell lines in response to cisplatin treatment. (A) Cells were treated for 48 h with cisplatin at 0, 0.5, 1 and 2 µg/ml. (B) Cells were treated with cisplatin at 1 µg/ml for 0, 12, 24 or 48 h. Reverse transcription-quantitative PCR was performed to assess the expression of circRNA_101237. *P<0.05 vs. controls. circRNA_101237, circular RNA 101237.

Article Snippet: The circRNA microarray data were analyzed using Arraystar Human circRNA Array V2 analysis (Arraystar) by Kangchen BioTech Inc.

Techniques: Expressing, Real-time Polymerase Chain Reaction

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: Non-coding RNA Research

Article Title: Circular RNAs in intracranial aneurysms: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

doi: 10.1016/j.ncrna.2023.11.012

Figure Lengend Snippet: Schematic illustration of the effect of circular RNAs (circRNAs) on intracranial aneurysm (IA) rupture. Current evidence strongly suggests a central role for endothelial dysfunction in the initiation and progression of IA. Post-subarachnoid hemorrhage (SAH), several early pathophysiological events can be commonly observed in blood-brain barrier (BBB) components, such as the endothelium (endothelial dysfunction). In results, post- SAH injuries can disrupt the integrity and function of the BBB . Both negative (red cross) and positive (green cross) regulation of circRNAs have been observed in this pathological cascade. The role of circRNAs is based on components: 1) strong role in endothelial cells (ECs) homeostasis; 2) regulation of barrier function and vascular tone; 3) associated with SAH and its complications; 4) correlates with clinical outcomes (Glasgow Coma Scale, the volume of SAH, modified Fisher scale, Hunt-Hess levels, and surgical type; 5) regulators of transcription/translation, sequesters of microRNA (miRNA)/RNA-binding proteins (RBPs), and biomarkers of IA.

Article Snippet: Leveraging the power of the Arraystar human circRNAs microarray, differentially expressed circRNAs between patients with UIAs and RIAs were meticulously analyzed.

Techniques: Modification, RNA Binding Assay

Journal: Non-coding RNA Research

Article Title: Circular RNAs in intracranial aneurysms: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

doi: 10.1016/j.ncrna.2023.11.012

Figure Lengend Snippet: Schematic illustration of circular RNAs (circRNAs) regulation mechanisms underlying vascular smooth muscle cells (VSMCs) phenotypic modulation, oxidative stress, and cell death in intracranial aneurysms (IAs). As can be seen from the figure, circRNAs play a role both in the development and progression of IA and in the inhibition of IA through the control of VSMC. However, some of them exhibit a double effect as circ_FOXO3 and circ_0020397.

Article Snippet: Leveraging the power of the Arraystar human circRNAs microarray, differentially expressed circRNAs between patients with UIAs and RIAs were meticulously analyzed.

Techniques: Inhibition

Journal: Non-coding RNA Research

Article Title: Circular RNAs in intracranial aneurysms: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

doi: 10.1016/j.ncrna.2023.11.012

Figure Lengend Snippet: Benefits of using cell free circular RNAs (circRNAs) as biomarkers.

Article Snippet: Leveraging the power of the Arraystar human circRNAs microarray, differentially expressed circRNAs between patients with UIAs and RIAs were meticulously analyzed.

Techniques:

Journal: Non-coding RNA Research

Article Title: Circular RNAs in intracranial aneurysms: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

doi: 10.1016/j.ncrna.2023.11.012

Figure Lengend Snippet: The studied cell free circular RNAs (circRNAs) are presented as non-invasive biomarkers in intracranial aneurysms (IAs).

Article Snippet: Leveraging the power of the Arraystar human circRNAs microarray, differentially expressed circRNAs between patients with UIAs and RIAs were meticulously analyzed.

Techniques:

Journal: Non-coding RNA Research

Article Title: Circular RNAs in intracranial aneurysms: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

doi: 10.1016/j.ncrna.2023.11.012

Figure Lengend Snippet: Summary information on the role of circular RNAs (circRNAs) in the formation and development of intracranial aneurysms (IAs).

Article Snippet: Leveraging the power of the Arraystar human circRNAs microarray, differentially expressed circRNAs between patients with UIAs and RIAs were meticulously analyzed.

Techniques: Migration, Transformation Assay