Tumors, spleen, and mesenteric lymph nodes of RIP-Tag2 mice in three treatment groups (vehicle, N = 5 mice; VV-A34/IL2v, N = 5 mice; and VV-GMCSF, N = 4 mice) were removed at 5 days, frozen, and homogenized. RNA was purified and hybridized (25–100ng RNA). Gene expression was measured with the NanoString Immune Profiling Panel for mice (nCounter PanCancer IO 360™) and analyzed using nSolver software 4.0 (NanoString Technologies, Seattle, WA). Of the 770 genes in the panel, genes in four NanoString Functional Annotation Categories relevant to the immunohistochemical readouts were analyzed in detail after removal of duplicates: Apoptosis (39 genes) and Cytotoxicity (42 genes), Cytokine and Chemokine Signaling (94 genes), and Immune Cell Adhesion and Migration subdivided into endothelial cell adhesion (28 genes) and immune cell adhesion (52 genes). Genes in each category were ranked from greatest to least ratio of VV-A34/IL2v group value to vehicle group value and displayed as rank order plots. Genes in VV-GMCSF group tumors were then ranked in the same order as for VV-A34/IL2v group tumors. Tumor genes were also ranked and displayed from greatest to least ratio of VV-GMCSF group value to vehicle group value. Additional genes related to B-cells, T-cells, Tregs, NK cells, or neutrophils were also examined (details in Supplementary Methods ).
Nsolver software 4
Manufactured by NanoString
Sourced in United States
NSolver software 4.0 is a data analysis software for NanoString's nCounter Analysis System. It provides tools for processing, normalizing, and analyzing data generated from nCounter gene expression assays.
Automatically generated - may contain errors
Lab products found in correlation
Ncounter digital analyzer, by NanoString (2 mentions)
Ncounter pancancer io 360, by NanoString (1 mentions)
Ncounter gene expression platform, by NanoString (1 mentions)
Ncounter advanced analysis 2, by NanoString (1 mentions)
Ncounter myeloid innate immunity panel, by NanoString (1 mentions)
Spss statistics version 28, by IBM (1 mentions)
Nanodrop 1000 spectrophotometer, by Thermo Fisher Scientific (1 mentions)
11 protocols using nsolver software 4
1
Transcriptomic Analysis of Tumor Immunity in RIP-Tag2 Mice
2
Evaluating FGFR2 and HER2 Expression
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Although to the small number of cases in our collective, we performed a statistical analysis for different data sets. To evaluate the statistical significance of immunohistochemical staining intensity for FGFR2 and HER2 expression between Becker groups we using the t test with Welch's correction (two-tailed) for unpaired comparisons. A p value less than 0.05 were considered as significant.
The Nanostring RNA expression data set was used with nSolver Software 4.0 using the Advanced Analysis Version 2.0.115 provided by NanoString. To calculate differential expression patterns, the samples were grouped according to their Becker scores (fringe groups: Becker-1 vs. Becker-3). The p value calculation was performed without adjustment and statistical significance was accepted at p < 0.01.
To determine differences within the total number of detected SNV (TST170 Data set), we performed in addition a Kruskal–Wallis test (Kruskal and Wallis 1952 ). It has to be noted that p value adjustment by false discovery rate procedure of Benjamini and Yekutieli was renounced, because of the small number of samples within this collective.
The Nanostring RNA expression data set was used with nSolver Software 4.0 using the Advanced Analysis Version 2.0.115 provided by NanoString. To calculate differential expression patterns, the samples were grouped according to their Becker scores (fringe groups: Becker-1 vs. Becker-3). The p value calculation was performed without adjustment and statistical significance was accepted at p < 0.01.
To determine differences within the total number of detected SNV (TST170 Data set), we performed in addition a Kruskal–Wallis test (Kruskal and Wallis 1952 ). It has to be noted that p value adjustment by false discovery rate procedure of Benjamini and Yekutieli was renounced, because of the small number of samples within this collective.
3
Inflammatory Gene Expression Analysis in Enteroids
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Expression in monolayer-derived enteroids of 250 inflammation-related genes included in the nCounter human inflammation panel 1 (NanoString Technologies, Seattle, WA, USA) was analyzed using the NanoString nCounter gene expression platform (NanoString Technologies) according to the manufacturer’s protocol. Briefly, 50 ng of total RNA was mixed with a color-coded reporter and a capture probe with target-specific sequences, hybridized overnight at 65°C, and scanned on the nCounter GEN2 digital analyzer. Normalization of raw data and data analysis were performed using the nSolver software 4.0 and nCounter Advanced Analysis 2.0 software (NanoString Technologies).
4
NanoString nCounter RNA Quantification
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The NanoString nCounter dataset used in this study was created, validated and described in detail in a previous publication [24 (link)]. Briefly, total RNA was extracted, and cDNA was synthesised from a pool of regenerating arms as described before [24 (link),25 (link)]. The samples were processed in the Nanostring facility at UCL using 100 ng of total RNA/sample and with the nCounter (NanoString Technologies, Seattle, WA, USA) according to manufacturer’s instructions. The results were analysed using the nSolver software 4.0 (NanoString) and quantified as described previously [24 (link)].
5
Differential Gene Expression Analysis
6
Immunotherapeutic Profiling in RIP-Tag2 Mice
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Tumors, spleen, and mesenteric lymph nodes of RIP-Tag2 mice in three treatment groups (vehicle, N = 5 mice; VV-A34/IL2v, N = 5 mice; and VV-GMCSF, N = 4 mice) were removed at 5 days, frozen, and homogenized. RNA was purified and hybridized (25–100 ng RNA). Gene expression was measured with the NanoString Immune Profiling Panel for mice (nCounter PanCancer IO 360) and analyzed using nSolver software 4.0 (NanoString Technologies). Of the 770 genes in the panel, genes in four NanoString Functional Annotation Categories relevant to the IHC readouts were analyzed in detail after removal of duplicates: Apoptosis (39 genes) and Cytotoxicity (42 genes), Cytokine and Chemokine Signaling (94 genes), and Immune Cell Adhesion and Migration subdivided into endothelial cell adhesion (28 genes) and immune cell adhesion (52 genes). Genes in each category were ranked from the greatest to least ratio of VV-A34/IL2v group value to vehicle group value and displayed as rank order plots. Genes in VV-GMCSF group tumors were then ranked in the same order as for VV-A34/IL2v group tumors. Tumor genes were also ranked and displayed from greatest to least ratio of VV-GMCSF group value to vehicle group value. Additional genes related to B cells, T cells, Tregs, NK cells, or neutrophils were also examined (details in Supplementary Methods).
7
Immune-Related mRNA Expression Analysis
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Expression levels of 770 immune-related mRNAs were assessed by human nCounter Myeloid Innate Immunity Panel and custom 30 gene Panel Plus (NanoString Technologies). Hybridization of human samples were performed using 75-100 ng of RNA. Hybridization of mouse samples were performed using 20 ng of RNA. Gene expression was analyzed with nSolver software 4.0 (NanoString Technologies). The expression levels of each gene were normalized to those of control genes. Heat maps and unsupervised hierarchical clustering were generated in nSolver with agglomerative cluster analysis using average Euclidean distance.
8
Differential microRNA Expression Analysis
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Significance of differential miR expression was determined using the nSolver Software 4.0 (Nanostring) applying a paired, two-tailed Student's t-test. Statistical analyses concerning OS and clinical data were performed using SPSS Statistics version 28 (IBM) using the Kaplan-Meier method. Significance was assumed for P≤0.05.
9
Differential Gene Expression Analysis
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Differentially expressed gene analyses were performed in nSolver software 4.0 (NanoString Technologies) using the Differential Expression Call Error Model. Outliers were identified by Grubbs’ test with a false discovery rate (q) = 0.05. All results are expressed as means ± SD. Data were analyzed using t-test, one- or two-way ANOVA as specified. Differences were considered significant at p < 0.05. Figures denote statistical significance of p < 0.05 as *, p < 0.01 as **, p < 0.001 as ***, and p < 0.0001 as ****.
10
Comprehensive Immune Signature Analysis
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Expression of genes belonging to several immune-related signatures was assessed by a custom-designed NanoString nCounter multiplex CodeSet enabling the determination of 364 genes. The gene signatures were selected for providing information on B-cell content and differentiation, TLS formation, follicular T helper cells, TEX subsets, tumor-associated endothelial cells, ICB response, and guadecitabine-specific gene upregulation. For NanoString experiments, panel probes (capture and report) and 200 ng of RNA were hybridized overnight at 65 °C for 16 h. Samples were scanned at maximum scan resolution capabilities (555 FOV) using the nCounter Digital Analyzer. Quality control of samples, data normalization, and data analysis were performed using nSolver software 4.0 (NanoString Technologies).
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