Journal: Molecular & Cellular Proteomics : MCP

Article Title: Secretomic Analysis Identifies Alpha-1 Antitrypsin (A1AT) as a Required Protein in Cancer Cell Migration, Invasion, and Pericellular Fibronectin Assembly for Facilitating Lung Colonization of Lung Adenocarcinoma Cells *

doi: 10.1074/mcp.M112.017384

Figure Lengend Snippet: A1AT triggers the assembly of pericellular polyFN on lung adenocarcinoma cells to promote lung colonization. A, CL1-0 and CL1-5 cells were trypsinized and placed in a suspension culture for 2 h, stained with rabbit anti-FN antibodies followed by a GFP-conjugated donkey anti-rabbit IgG secondary antibody, observed under a fluorescent microscope, and detected using flow cytometry. Both IF and flow cytometry was used to demonstrate the different levels of FN1 assembly on the cell surfaces of CL1-0 and CL1-5 cells. The assembly levels of pericellular polyFN of CL1-5 cells were higher than those of CL1-0. The Olympus FB1000 microscope was used, and the fluorescent filter set for 488 excitation at 600× magnification. B, Evaluation of polyFN1 assembly on the cell surface after scrambled siRNA control and A1AT siRNA transfection was performed using IF and flow cytometry. The pericellular polyFN assembly of CL1-5 cells was inhibited when the expression of A1AT was reduced by transfecting siRNA. C, In the nude mice model, a tail vein injection was performed using the CL1-5 cells treated with the scrambled siRNA control and A1AT siRNA or CL1-0 cells, using five mice for each treatment. After 8 weeks, the mice were sacrificed and the tumor nodules of their lungs were measured. A tumor size of 0.5 mm in diameter was counted as one nodule. A significant inhibition of lung experimental metastasis was observed in mice that were injected with A1AT siRNA CL1-5 cells. Three of five lungs are shown in (D). E, Represented tumor sections of these three groups were stained with H&E. F, CL1-5 cells were incubated in suspension for 2 h in 20% FBS media. The cells were subsequently treated with myelin basic protein (MBP) and soluble, truncated dipeptidyl peptidase IV (DPP IV) for 20 min. The five mice in each group were sacrificed after 8 weeks, and the lungs were removed and fixed in a 3.7% formalin fixative. On injection of the soluble, truncated DPP IV-treated CL1-5 cells, lung colonization among the nude mice was completely inhibited. There are three representative lungs shown in each group.

Article Snippet: To predict the relationship between PKCε and A1AT in the regulation of polyFN assembly in lung colonization, Metacore interactome prediction software (GeneGo, Joseph, MI, USA) was used ( C ).

Techniques: Suspension, Staining, Microscopy, Flow Cytometry, Control, Transfection, Expressing, Injection, Inhibition, Incubation

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

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: As circRNAs interact with miRNAs via miRNA response elements (MREs), we searched for putative MREs through Arraystar's circRNA target prediction software.

Techniques: Derivative Assay, Sequencing

Journal: BMC Genomics

Article Title: Identification and characterization of microRNAs in the flag leaf and developing seed of wheat ( Triticum aestivum L.)

doi: 10.1186/1471-2164-15-289

Figure Lengend Snippet: Known miRNAs identified in the five wheat sRNA libraries or tissues

Article Snippet: The EST sequences or the contigs from the wheat genome shotgun-sequence assemblies that matched to the sRNA reads were extracted from the databases and analyzed for the existence of pre-miRNA sequences that can form a hairpin secondary structure using miRNA prediction software MIREAP ( http://sourceforge.net/projects/mireap/ ), the potential new miRNAs predicted meeting the common criteria (see details in Methods).

Techniques:

Journal: BMC Genomics

Article Title: Identification and characterization of microRNAs in the flag leaf and developing seed of wheat ( Triticum aestivum L.)

doi: 10.1186/1471-2164-15-289

Figure Lengend Snippet: Summary of newly identified 55 novel miRNAs in the five wheat libraries or tissues

Article Snippet: The EST sequences or the contigs from the wheat genome shotgun-sequence assemblies that matched to the sRNA reads were extracted from the databases and analyzed for the existence of pre-miRNA sequences that can form a hairpin secondary structure using miRNA prediction software MIREAP ( http://sourceforge.net/projects/mireap/ ), the potential new miRNAs predicted meeting the common criteria (see details in Methods).

Techniques: Sequencing

Journal: BMC Genomics

Article Title: Identification and characterization of microRNAs in the flag leaf and developing seed of wheat ( Triticum aestivum L.)

doi: 10.1186/1471-2164-15-289

Figure Lengend Snippet: Comparison of the miRNA expression profiles determined by quantitative real-time RT-PCR (qPCR) and deep sequencing. a , known miRNAs; b , novel miRNAs and candidate miRNAs. In qPCR, UBQ was used as the internal reference gene, and the relative expression of each miRNA was calculated using a comparative C T (ΔΔC T ) method. The miRNA sample with the lowest C T value that corresponds to the highest expression level was selected as the calibrator, in which the expression level was set as 1.0. The relative expression levels of the same miRNA in the other four samples were then normalised by comparing with the highest one in the tested tissues. Three independent biological replicates were performed in this experiment. For each sample, qPCR was performed in triplicate. Each column represents the mean of three samples, and error bars represent the standard deviation. In deep sequencing technology, read counts for each miRNA in one sample were normalised to reads per million of total miRNA reads (RPM). The relative expression of each miRNA was calculated by setting the highest RPM of each miRNA across the five samples as 1.0, and the relative expression of the same miRNA in the other four samples was its RPM divided by the highest RPM.

Article Snippet: The EST sequences or the contigs from the wheat genome shotgun-sequence assemblies that matched to the sRNA reads were extracted from the databases and analyzed for the existence of pre-miRNA sequences that can form a hairpin secondary structure using miRNA prediction software MIREAP ( http://sourceforge.net/projects/mireap/ ), the potential new miRNAs predicted meeting the common criteria (see details in Methods).

Techniques: Comparison, Expressing, Quantitative RT-PCR, Sequencing, Standard Deviation

Journal: BMC Genomics

Article Title: Identification and characterization of microRNAs in the flag leaf and developing seed of wheat ( Triticum aestivum L.)

doi: 10.1186/1471-2164-15-289

Figure Lengend Snippet: Expression patterns of the known and the novel miRNAs based on deep-sequencing datasets. a , Known miRNAs; b , Novel miRNAs. The bars represent the scale of the relative expression levels of miRNAs (MEAN centred).

Article Snippet: The EST sequences or the contigs from the wheat genome shotgun-sequence assemblies that matched to the sRNA reads were extracted from the databases and analyzed for the existence of pre-miRNA sequences that can form a hairpin secondary structure using miRNA prediction software MIREAP ( http://sourceforge.net/projects/mireap/ ), the potential new miRNAs predicted meeting the common criteria (see details in Methods).

Techniques: Expressing, Sequencing