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Image Search Results
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: Pan-Cancer Analysis of SGO2 Expression ( A ) SGO2 expression profiles across pan-cancers were analyzed using data from the TCGA database. Tumor samples (represented as red boxes) were compared against normal samples (represented as blue boxes) via the Mann-Whitney U test to assess expression differences. ( B ) SGO2 expression patterns across pan-cancers were interrogated utilizing the GEPIA web platform. Tumor samples (depicted as red dots) were contrasted with normal samples (depicted as green dots), with statistical testing following GEPIA’s default analytical pipeline (*p < 0.05, **p < 0.01,***p < 0.001).
Article Snippet:
Techniques: Expressing, MANN-WHITNEY
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: Investigation of SGO2 Expression in LUAD. ( A ) Paired comparison: SGO2 expression in tumor vs. matched adjacent normal tissues from LUAD patients (paired t-test). ( B ) Unpaired comparison: SGO2 expression in tumor vs. normal tissues (unpaired t-test). ( C ) Immunohistochemical validation: Immunohistochemical analysis assessed SGO2 expression in LUAD tumor tissues and adjacent peri-tumor tissues from 21 patients (n = 21). Comparison of relative SGO2 expression levels (top) and positive staining area percentages (bottom) between tumor and peri-tumor tissues used paired t-test. ( D ) Clinical stage-related analysis: Based on the TCGA database, SGO2 expression was analyzed across subgroups of T stage, N stage, M stage, and pathological stage. Statistical method: One-way ANOVA with Bonferroni post-hoc test. (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
Article Snippet:
Techniques: Expressing, Comparison, Immunohistochemical staining, Biomarker Discovery, Staining
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: Elevated SGO2 expression was associated with poor prognosis in LUAD patients. ( A-C ) Kaplan-Meier survival analyses (via log-rank test) from TCGA database comparing LUAD patients with high vs. low SGO2 expression (stratified by median). ( A ) OS: High-expression group (n = 265) showed significantly worse prognosis than low-expression group (n = 265) (HR = 1.64, p < 0.001). ( B ) DSS: High-expression group (n = 247) had poorer outcomes than low-expression group (n = 248) (HR = 1.87, p < 0.001). ( C ) PFS: High-expression group (n = 265) exhibited shorter PFS than low-expression group (n = 265) (HR = 1.47, p = 0.005). ( D-E ) Validation in GEO datasets (log-rank test): ( D ) GSE13213 : High-expression group (n = 75) had significantly reduced survival vs. low-expression group (n = 42) (p < 0.01). ( E ) GSE31210 : High-expression group (n=84) showed worse prognosis compared to low-expression group (n = 120) (p = 0.005). HR: Hazard ratio.
Article Snippet:
Techniques: Expressing, Biomarker Discovery
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: The diagnostic ROC curve for SGO2. ( A ) Receiver operating characteristic (ROC) curve evaluating SGO2 expression as a diagnostic biomarker for LUAD. The area under the curve (AUC) was 0.873 (95% CI: 0.843-0.903), indicating high discriminatory power.
Article Snippet:
Techniques: Diagnostic Assay, Expressing, Biomarker Discovery
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: SGO2 expression in LUAD cell lines relative to normal Beas-2B cells. ( A ) Combined subpanels showing relative SGO2 mRNA expression: ( a-c ) Relative SGO2 mRNA expression in A549 ( a ), H1975( b ) and H1299 ( c ) cells, normalized to Beas-2B. (n = 3, Student’s t-test). ( B-C ) Representative western blot ( B ) and quantitative analysis ( C ) of SGO2 protein expression in the same cell lines. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document} -actin served as the loading control (n = 3, one-way ANOVA with Tukey’s post hoc test). Original blots are shown in Fig. . (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
Article Snippet:
Techniques: Expressing, Western Blot, Control
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: SGO2 knockdown suppressed malignant behaviors in LUAD cells. ( A-B ) Validation of siRNA-mediated SGO2 knockdown efficiency by ( A ) qPCR and ( B ) Western blot. (n = 3, one-way ANOVA with Tukey’s post hoc test). ( C-E ) Proliferation (CCK-8), migration (wound healing), and invasion (Matrigel) assays in SGO2-depleted H1299 cells. (n = 3, Student’s t-test). ( F ) Western blot analysis of EMT markers (N-cadherin, E-cadherin, Vimentin) in SGO2-knockdown H1299 cells with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document} -actin served as loading control. (n = 3, Student’s t-test). Original blots are shown in Fig. . (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
Article Snippet:
Techniques: Knockdown, Biomarker Discovery, Western Blot, CCK-8 Assay, Migration, Control
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: Knockdown of SGO2 affected the cell cycle in LUAD cells. ( A ) Flow cytometry analysis of cell cycle distribution (G1, S, G2/M phases) in si-SGO2 and si-NC groups. (n = 3, two-way ANOVA with Sidak’s test). ( B ) Western blot of cell cycle proteins (Cyclin B1, Cyclin D1). \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document} -actin served as control (n = 3, Student’s t-test). Original blots are shown in Fig. . (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
Article Snippet:
Techniques: Knockdown, Flow Cytometry, Western Blot, Control
Journal: Scientific Reports
Article Title: Elevated SGO2 expression in lung adenocarcinoma promotes migration and invasion via MAD2 and correlates with poor prognosis
doi: 10.1038/s41598-025-10993-0
Figure Lengend Snippet: SGO2 regulated LUAD cell migration and invasion via MAD2. ( A ) GO and KEGG enrichment analysis of genes associated with SGO2. (The use permission from Kanehisa Laboratories has been obtained.) ( B ) Correlation analysis between SGO2 and MAD2 expression (Pearson’s R = 0.62, p < 0.001). ( C-D ) Verification of SGO2 overexpression efficiency using qPCR and Western blot, and analysis of MAD2 expression following SGO2 knockdown or overexpression (n = 3, Student’s t-test). ( E ) Invasion and migration assays of H1299 cells in three groups: SGO2 overexpression (OE-SGO2), control (OE-SGO2-NC), and SGO2-OE with MAD2 inhibitor (OE-M2I-1) (n = 3, one-way ANOVA with Tukey’s post hoc test). Original blots are shown in Fig. . (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).
Article Snippet:
Techniques: Migration, Expressing, Over Expression, Western Blot, Knockdown, Control
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 1. Landscape of expression and genetic variation of GPRASP1 in human cancers. (A): Boxplots showing differential MXD3 expression levels (log2 FPKM + 1) between tumor and adjacent normal tissues across TCGA database. The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001). (B): GPRASP1 mutation frequency in multiple TCGA pan-cancer studies according to the cBioPortal database. (C): Mutation diagram of GPRASP1 in different cancer types across protein domains from the cBioPortal database.
Article Snippet:
Techniques: Expressing, Mutagenesis
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 2. Prognostic value and immunological role of GPRASP1 in human cancers. (A): The prognostic value of GPRASP1 in human cancers. The asterisks indicate a significant statistical p value (*p < 0.05; **p < 0.01; ***p < 0.001). HR (Hazard ratio) and p value were calculated by Cox regression analyse. (B): Correlation of GPRASP1 expression with ESTIMATE (immune score, stromal score, ESTIMATE score, and tumor purity), and stemness indexes (RNAss and DNAss). The asterisks indicate a significant statistical p value (*p < 0.05; **p < 0.01; ***p < 0.001). Correlation coefficient and p value were calculated by Spearman correlation analysis. (C): The radar plot depicted correlation between GPRASP1 expression and TMB. Correlation coefficient and p value were calculated by Spearman correlation analysis. The asterisks indicate a statistically significant p value calculated using the Spearman correlation analysis (*p < 0.05; **p < 0.01; ***p < 0.001). (D): The radar plot depicted correlation between GPRASP1 expression and MSI. Correlation coefficient and p value were calculated by Spearman correlation analysis. The asterisks indicate a statistically significant p value calculated using the Spearman correlation analysis (*p < 0.05; **p < 0.01; ***p < 0.001).
Article Snippet:
Techniques: Expressing
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 3. Identification of GPRASP1 differential expression between tumor and paracancerous tissues in GEO, and TMA datasets. (A): GSE16515 cohorts. (B): GSE28735 cohorts. (C): Tumor cell proportion scores in PC TMA datasets based on IHC. (D): Staining intensity scores in PC TMA datasets based on IHC. (E): IHC scores in PC TMA datasets based on IHC. (F, G): Images of IHC staining for GPRASP1 in adjacent non-tumour tissues. (H, I): Images of IHC staining for GPRASP1 in PC tissues. Scale bars of 40 ×magnifcation, 100 µm. The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001).
Article Snippet:
Techniques: Quantitative Proteomics, Staining, Immunohistochemistry
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 4. Correlation of GPRASP1 expression with clinicopathologic characteristics. The heatmap depicted the distribution of clinical characteristics arranged by the increasing GPRASP1 expression in TCGA datasets (A), and GSE62452 datasets (B). Comparison of the different clinical characteristics between high GPRASP1 and low GPRASP1 subgroups. The asterisks indicate a statistically significant p value calculated using the Chi-square test (*p < 0.05; **p < 0.01; ***p < 0.001). (C-H): Comparison of the GPRASP1 expression in different clinical characteristics in TCGA and GSE62452 datasets. (C): Age in TCGA datasets. (D): T stage in TCGA datasets. (E): N stage in TCGA datasets. (F): TNM stage in TCGA datasets. (G): histologic grade in GSE62452 datasets. (H): TNM stage in GSE62452 datasets. The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001).
Article Snippet:
Techniques: Expressing, Comparison
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 5. The prognostic efficacy and clinical usefulness of GPRASP1 in TCGA and GEO cohorts. (A-C): Kaplan-Meier survival curves with log-rank test for different GPRASP1 expression subgroups to compare the OS differences in TCGA cohorts (A), GSE62452 cohorts (B), and GSE78229 cohorts (C). (D-F): Time-independent ROC curves with AUC values to evaluate predictive efficacy of GPRASP1 in TCGA cohorts (D), GSE62452 cohorts (E), and GSE78229 cohorts (F). (G, H): ROC analysis was performed to compare the prognostic performance of the GPRASP1 against TNM stage and GPRASP1 + TNM stage in TCGA (G) and GSE62452 (H) cohorts. (I, J): Decision curve analysis was applied to evaluate the clinical usefulness of GPRASP1 against TNM stage and GPRASP1 + TNM stage in TCGA (I) and GSE62452 (J) cohorts. The Y-axis represents the net benefit. The black line represents the hypothesis that no patients die. The X-axis represents the threshold probability. The threshold probability is where the expected benefit of treatment is equal to the expected benefit of avoiding treatment.
Article Snippet:
Techniques: Expressing
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 6. The underlying mechanisms for the altered expression of GPRASP1 in PC. (A): The correlation of GPRASP1 expression with GPRASP1 multiple methylation sites. Correlation coefficient and p value were calculated by Spearman correlation analysis. (B): The prognostic value of GPRASP1 multiple methylation sites. The asterisks indicate a significant statistical p value (*p < 0.05; **p < 0.01; ***p < 0.001). HR (Hazard ratio) and p value were calculated by Cox regression analyse. (C): The correlation of GPRASP1 expression with CNV frequency. Correlation coefficient and p value were calculated by Spearman correlation analysis. (D, G, J): The correlation of GPRASP1 expression with cg15579650 (D), cg23571457 (G) and cg25950739 (J) methylation level. Correlation coefficient and p value were calculated by Spearman correlation analysis. (E, H, K): Kaplan-Meier survival curves with log-rank test for different cg15579650 (E), cg23571457 (H) and cg25950739 (K) methylation levels. (F, I, L): Joint survival analysis combined cg15579650 (F), cg23571457 (I), cg25950739 (L) methylation, respectively and expression of GPRASP1 to compare the survival differences.
Article Snippet:
Techniques: Expressing, Methylation
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 7. GPRASP1 biological functions in PC based on different enrichment of MSigDB Collection (GO, KEGG, and Hallmark). (A, B): Gene sets involved Gene Ontology were enriched by differential expression levels of GPRASP1 (upper)(A) and GPRASP1 (lower)(B). (C, D): Gene sets involved Kyoto Encyclopedia of Genes and Genomes were enriched by differential expression levels of GPRASP1 (upper)(C) and GPRASP1 (lower)(D). (E, F): Gene sets involved Hallmark were enriched by differential expression levels of GPRASP1 (upper)(E) and GPRASP1 (lower)(F).
Article Snippet:
Techniques: Quantitative Proteomics
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 8. Analyzing the correlation between GPRASP1 expression and infiltrating immune cells. (A, B) Comparison of infiltrating immune cells between high and low GPRASP1 expression subgroups by CIBERSORTx tool (A), and ssGSEA algorithm(B). p value was calculated using the Wilcoxon test. (C-E): Correlation of GPRASP1 expression with immune cell infiltration by CIBERSORTx tool (C), ssGSEA algorithm (D), and online TIMER tools (E). Correlation coefficient and p value were calculated by Spearman correlation analysis.
Article Snippet:
Techniques: Expressing, Comparison
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 9. Analyzing the correlation between GPRASP1 expression and biological pathways based on Gene set variation analysis (GSVA). (A): Comparison of biological pathways between GPRASP1 different subgroups. The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001). (B): The radar plot depicted correlation between GPRASP1 expression and biological pathways. Correlation coefficient and p value were calculated by Spearman correlation analysis. The asterisks indicate a statistically significant p value calculated using the Spearman correlation analysis (*p < 0.05; **p < 0.01; ***p < 0.001). (C): Differential expression of immune checkpoint inhibitors between different GPRASP1 expression subgroups. p value was calculated using the Wilcoxon test. (D): Correlation between GPRASP1 expression and immune checkpoint inhibitors. Correlation coefficient and p value were calculated by Spearman correlation analysis. (E): Differential expression of HLA-related genes between different GPRASP1 expression subgroups. p value was calculated using the Wilcoxon test. (F): Correlation between GPRASP1 expression and HLA-related genes. Correlation coefficient and p value were calculated by Spearman correlation analysis.
Article Snippet:
Techniques: Expressing, Comparison, Quantitative Proteomics
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 10. Analyzing the correlation between GPRASP1 expression and immunomodulators (chemokines and chemokines receptors). (A): Differential expression of chemokines and chemokines receptors between different GPRASP1 expression subgroups. p value was calculated using the Wilcoxon test. (B): Correlation between GPRASP1 expression and chemokines and chemokines receptors. Correlation coefficient and p value were calculated by Spearman correlation analysis.
Article Snippet:
Techniques: Expressing, Quantitative Proteomics
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 11. Analyzing the correlation between GPRASP1 expression and ESTIMATE, neoantigen, TMB, and MSI. (A-L): Differential analysis of immune score(A), stromal score(B), ESTIMATE score(C), tumor purity(D), the number of clonal(E), the. number of clonal neoantigens(F), the number of subclonal(G), the number of subclonal neoantigens(H), ploidy(I), purity (J), TMB (K), and MSI(L). The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001). (M): Correlation between GPRASP1 expression and ESTIMATE(immune score, stromal score, ESTIMATE score, tumor purity), neoantigen (the number of clonal, the number of clonal neoantigens, the number of subclonal, the number of subclonal neoantigens, ploidy, and purity), TMB, and MSI. Correlation coefficient and p value were calculated by Spearman correla tion analysis.
Article Snippet:
Techniques: Expressing, Immunopeptidomics
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 12. Evaluation of GPRASP1 expression potential in predicting immunotherapeutic response. (A): Comparison of the relative activity of the cycle steps between different GPRASP1 subtypes. p value was calculated using the Wilcoxon test. (B-K): Differential analysis of IPS CTLA4(-) PD1(-) score(B), IPS CTLA4(-) PD1(+) score (C), IPS CTLA4(+) PD1(-) score(D), IPS CTLA4(+) PD1(+) score (E), TIDE score(F), Dysfunction(G), Exclusion(H), MDSC (I), CD8(J), and IFNG (K). The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001). (L): The distribution of immunotherapeutic response in two groups stratified by GPRASP1 expression in TCGA PC cohort based on the TIDE algorithm. A two-sided Chi-square test was used to analyze contingency tables for ICI responders. (M): Comparison of GPRASP1 expression between responder and non-responder groups. The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001).
Article Snippet:
Techniques: Expressing, Comparison, Activity Assay
Journal: Pathology, research and practice
Article Title: Comprehensive pan-cancer analysis of role of GPRASP1, associated with clinical outcomes, immune microenvironment, and immunotherapeutic efficiency in pancreatic cancer.
doi: 10.1016/j.prp.2023.154374
Figure Lengend Snippet: Fig. 13. GPRASP1 expression in pancreatic cancer cells and cancer tissues. (A): GPRASP1 expression in 16 pairs of pancreatic cancer and corresponding adjacent tissues. (B): GPRASP1 expression in pancreatic cancer cells (PANC-1, MIA, PaCa-2, BxPC-3, SW1990, AsPC-1) and normal pancreatic ductal epithelial cells (HPDE). The asterisks indicate a significant statistical p value calculated using the Wilcoxon test (*p < 0.05; **p < 0.01; ***p < 0.001).
Article Snippet:
Techniques: Expressing