mab against dsg2 (R&D Systems)
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Mab Against Dsg2, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 7 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/mab against dsg2/product/R&D Systems
Average 94 stars, based on 7 article reviews
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1) Product Images from "Desmoglein-2 expression is an independent predictor of poor prognosis patients with multiple myeloma."
Article Title: Desmoglein-2 expression is an independent predictor of poor prognosis patients with multiple myeloma.
Journal: Molecular oncology
doi: 10.1002/1878-0261.13055
Figure Legend Snippet: Fig. 1. DSG2 is expressed by MM PC at the gene and protein level in a distinct subset of MM patients. (A, B) In silico analysis of publicly available microarray datasets E-MTAB-363 (A) and E-GEOD-16122 (B) was performed. In these studies, RNA was extracted from CD138+
Techniques Used: In Silico, Microarray
Figure Legend Snippet: Fig. 2. DSG2 expression in a subset of MM cell lines. (A) DSG2 gene expression values for 65 human MM cell lines were extracted from a publicly available RNAseq dataset as described in Materials and methods. Cell lines were ranked according to level of DSG2 gene expression for simplicity of visualization. (B, C) For nine of the cell lines shown in A, surface expression of DSG2 protein was assessed by flow cytometry. Examples of negative, low and high expression are shown in (B), while the relationship between gene and surface protein for all cell lines analysed is shown in C (Spearman’s correlation coefficient r = 0.65).
Techniques Used: Expressing, Gene Expression, Cytometry
Figure Legend Snippet: Fig. 3. DSG2 expression in MM is strongly associated with reduced survival, independent of NSD2. (A) Microarray dataset GSE4581 was analysed for expression of DSG2 using probe set 1553105. Visual inspection of the data spread revealed a cluster of samples with elevated DSG2 expression. A 70/30 percentile split was applied to the data, which cleanly separated these DSG2-low and DSG2-high populations, as shown, for further analysis. (B) Overall survival was compared between the DSG2-low (lower 70%, n = 289) and DSG2-high (upper 30%, n = 125) subsets using Kaplan–Meier analysis. P < 0.01 (C) Expression of DSG2 was compared between patients grouped into disease subtypes according to gene expression signatures. DSG2 expression was significantly greater in the MS subset compared to all others (Kruskal–Wallis test). (D, E) Scatterplots comparing expression of DSG2 and NSD2 genes in all samples (D) or non-MS samples only (E). Dotted lines indicate thresholds for expression based on 70th percentile (DSG2) or 80th percentile (NSD2). Values represent the number of samples in each quadrant. (F) The non-MS patient cohort was stratified into DSG2-low and DSG2-high subsets and overall patient survival compared using Kaplan–Meier analysis.
Techniques Used: Expressing, Microarray, Gene Expression
Figure Legend Snippet: Fig. 4. Differential gene expression analysis comparing DSG2-low and DSG2-high subsets. Dataset GSE4581 was stratified into DSG2-low (blue bar) and DSG2-high (red bar) patient subsets as per Fig. 3, and genes differentially expressed between the two groups were identified and displayed in heatmaps. Clustering of genes displayed in the heatmap was unsupervised and shown as analyses of the entire patient cohort (A), or only the subgroup of patients lacking MMSET expression (MS-neg; B).
Techniques Used: Gene Expression, Expressing



