Journal: iScience

Article Title: Migration of human T cells can be differentially directed by electric fields depending on the extracellular microenvironment

doi: 10.1016/j.isci.2024.109746

Figure Lengend Snippet:

Article Snippet: Anti-human CD3 mouse IgG2aκ - FITC , Miltenyi Biotec , Cat#: 130-113-128 Lot: 520080617.

Techniques: Recombinant, Control, Cell Isolation, Isolation, Software

Journal: PLoS ONE

Article Title: CXCL10/IP-10 Neutralization Can Ameliorate Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome in Rats

doi: 10.1371/journal.pone.0169100

Figure Lengend Snippet: Monoclonal antibodies used for the analysis of inflammatory cells.

Article Snippet: CD3 , PerCP-Vio700 , Miltenyi Biotec , REA223 , 130-103-128 , 1 in 100.

Techniques: Bioprocessing, Control

Journal: Frontiers in Immunology

Article Title: Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging

doi: 10.3389/fimmu.2024.1383932

Figure Lengend Snippet: Immunophenotyping panel for multiplexed tissue imaging of cancer.

Article Snippet: CD3 , REA1151 , 50 , 130-120-267 , FITC (APC) , Miltenyi Biotec.

Techniques: Imaging

Journal: Journal of the American Heart Association

Article Title: Impact of NKG2D Signaling on Natural Killer and T‐Cell Function in Cerebral Ischemia

doi: 10.1161/jaha.122.029529

Figure Lengend Snippet: Figure 5. Distribution of NKG2D-expressing immune cells and their interaction with ligand-expressing brain resident cells in human stroke patients. A, Representative immunofluorescence staining of NKG2D receptor as well as CD3+ T cells, CD4+ and CD8+ T cell subsets, CD56+ NK cells, and CD56+/CD3+ NKT cells in the brain of human patients with stroke and control patients. B, Representative immunofluorescence staining of NKG2D ligands (ULBP1, −3, and − 4) as well as NeuN+ neurons, CX3CR1+ microglia, CD68+ monocytes/microglia, and glial fibrillary acidic protein (GFAP+) astrocytes in control brain tissue and stroke lesions. ULBP: cytomegalovirus UL16-binding protein. NK indicates natural killer cell; and NKT, natural killer T cell.

Article Snippet: In the degranulation assay, the following fluorescently labeled antibodies purchased from Miltenyi Biotec were used: CD3 (17A2, Cat. 130-118-849), CD45 (REA737, Cat. 130-110-803), CD8a (REA601, Cat. 130-120-822), NKG2D (CX5, Cat. 130-102-730), CD107a (REA777, Cat. 130-111-505), CD161 (REA1162, Cat. 130-120-510).

Techniques: Expressing, Immunofluorescence, Staining, Control, Binding Assay

Journal: Cancer Research

Article Title: An In Vivo CRISPR Screen Identifies Stepwise Genetic Dependencies of Metastatic Progression

doi: 10.1158/0008-5472.can-21-3908

Figure Lengend Snippet: Figure 1. Generation and characterization of a CTC-derived xenograft model. A, Schematic of the establishment of human CTC-derived xenografts (CDX) from a patient with breast cancer (BR16). CTCs from BR16 patient blood were isolated, expanded ex vivo, and injected in the mammary fat pad of NSG mice. Upon tumor development, spontaneously formed CTCs seed metastases to defined organs, mirroring the metastatic pattern of the patient-of-origin. B, Representative pictures of primary tumor, single CTCs, and CTC clusters from the BR16-CDX model. The primary tumor was stained for human pan-cytokeratin (hCK; green), laminin (turquoise), CD31 (red), Ki67 (purple), and DAPI (nuclei; white), whereas single CTCs and CTC clusters were live-stained for epithelial cell adhesion molecule (EpCAM), HER2, and EGFR (green) within the microfluidic cassette, directly after capture. C, Representative pictures of spontaneous bone, brain, liver and lymph node metastasis of BR16-CDX mice, stained for hCK (green), laminin (turquoise), glial fibrillary acidic protein (GFAP; turquoise), CD31 (red), Ki67 (purple), and DAPI (white).

Article Snippet: Primary human cytokeratin (hCK; Milteny Biotec, 130–112– 931), laminin (Novus Biologicals, NB300–144), CD31 (R&D Systems, AF3628), Ki67 (Invitrogen, 14–5698–82), glial fibrillary acidic protein (GFAP; Invitrogen, PA1–10019) antibodies and secondary IgG-Cy3 (Jackson ImmunoResearch, 712–165–153), IgG-594 (Invitrogen, SA5–10028), IgG-594 (Invitrogen, SA5–10040), IgG-555 (Invitrogen, A-31572), IgG-647 (Invitrogen, A-21447), and IgG-488 (709–545– 149) antibodies were used.

Techniques: Derivative Assay, Isolation, Ex Vivo, Injection, Staining, Capture-C

Journal: Nature Communications

Article Title: Integrated spatial proteomic analysis of breast cancer heterogeneity unravels cancer cell phenotypic plasticity

doi: 10.1038/s41467-025-65477-6

Figure Lengend Snippet: A Schematic representation of the multiplexed imaging workflow. Consecutive slides were stained with two antibody panels and DAPI. Quantification was composed of two workflows. The first workflow was used for cell quantification and involved cell segmentation, followed by cell classification and quantification. The second workflow, for blood vessel quantification, was pixel-based on and quantified the area of blood vessels in the tumors. B Schematic representation of the analytical pipeline for multilayer proteomics and imaging integration. Scale = 200 µm. C–F Dot plots show the quantification of TME components in whole-slide images: CD3+ T cells percent ( C ), CD68+ macrophages percent ( D ), αSMA+ fibroblasts percent ( E ), and blood vessels (BV) area percent. Each dot represents an individual slide from a patient. Patient identities are color-coded, and the same slide order is maintained across all graphs. Data represent n = 11 patients with a total of 47 slides. G Correlation heatmap of percent CD3+ cells, CD68+ cells, BV, αSMA+ cells, and pan-cytokeratin (panCK+) cancer cells in the whole tissue analysis. Values represent average percentages across multiple FFPE tissue blocks per patient. Colors indicate Spearman’s correlation coefficients, and statistically significant correlations are marked with asterisks: * p < 0.05, ** p < 0.01, *** p < 0.001. The “corrplot” (v0.95) R package was used for visualization. H Boxplots depict the distribution of percent CD3 + T cells and CD68+ macrophages in BV-Low (light pink, n = 61) and BV-High (coral, n = 60) regions. Each box shows the median, interquartile range, and whiskers indicate data variability, with individual data points overlaid as jittered dots. Data represent cell type percentages in P-ROI regions. Statistical comparisons were performed using a two-sided Student’s t -test for CD3 ( t (119) = 2.23, p = 0.028, 95% CI [0.43, 7.18], Cohen’s d = 0.41), and a two-sided Welch’s t -test for CD68 due to unequal variance (Welch’s t (108.89) = 3.53, p = 6 × 10 -4 , 95% CI [1.17, 4.15], Glass’s Δ = 0.78). Linear mixed-effects models (LMMs) accounting for patient as a random effect were also applied to obtain adjusted p -values. I Violin plots combined with boxplots show the distribution of percent CD3+ , CD68+ , and αSMA+ cells in Grade 2 vs. Grade 3 tumors at the whole slide level. Boxplots indicate the median (center line), interquartile range (IQR; box limits), and whiskers extending to 1.5 × IQR; points beyond whiskers represent outliers. Two-sided Student’s t -tests were performed to compare T cells ( t (44) = −3.31, p = 0.002, Cohen’s d = −0.98; Grade 2, n = 20; Grade 3, n = 26), macrophages ( t (44) = −2.41, p = 0.02, Cohen’s d = −0.72; Grade 2, n = 20; Grade 3, n = 26), and fibroblasts ( t (45) = 6.03, p = 2.8 ×10 -7 ,Cohen’s d = 1.77; Grade 2, n = 21; Grade 3, n = 26). Linear mixed model (LMMs) accounting for the patient as a random effect were applied to obtain adjusted p -values. J Violin plots combined with boxplots show the distribution of averaged T-cell, fibroblast, and macrophage percentages per METABRIC patient in the imaging mass cytometry dataset . A minimum threshold of 500 single cells per patient was applied to filter out insignificant observations. Patients with zero values and outliers (defined using the IQR) were excluded. Two-sided Student’s t -tests were used to compare CD3+ T cells ( t (246) = −1.78, p = 0.077, Cohen’s d = −0.23), and αSMA+ fibroblasts ( t (294) = 2.32, p = 0.021, Cohen’s d = 0.28) between Grade 2 ( n = 141) and Grade 3 ( n = 211) patients. For CD68+ macrophages, a two-sided Welch’s t -test was applied due to unequal variances ( t (279.74) = −3.472, p = 6×10 -4 , Glass’s Δ = −0.345).

Article Snippet: CD3 (Atlas Antibodies, HPA043955) was used at a 1:500 dilution, CD68 (Cell Signaling Technologies, 76437) at 1:200 dilution, each followed by HRP-conjugated donkey anti-rabbit secondary (Jackson ImmunoResearch, 711-035-152) and OPAL 650 (Akoya, FP1496001KT) or OPAL 570 (Akoya, FP1488001KT), respectively.

Techniques: Imaging, Staining, Mass Cytometry

Journal: Nature Communications

Article Title: Integrated spatial proteomic analysis of breast cancer heterogeneity unravels cancer cell phenotypic plasticity

doi: 10.1038/s41467-025-65477-6

Figure Lengend Snippet: A Scatter plots show Pearson’s correlation between log 2 protein expression values and blood vessel percentages in the P-ROI and the surrounding ring area. Each dot represents a valid data point. The solid line represents the linear regression fit, with the grey shaded area representing the 95% confidence interval. Pearson’s r , two-sided p -value from a t -test on the correlation coefficient, and FDR-adjusted p -values are shown. B Representative immunofluorescent images after cell segmentation and cell type classification show the spatial distribution of CD3+ T cells (cyan), CD68+ macrophages (magenta), panCK+ cancer cells (green), and other cell populations (red). Among 47 tumor slides from 11 patients, patient BC1 is shown as an example. The immune phenotype classification of each region is indicated. Scale = 200 µm. C Dot plot example of immune phenotypes of BC1 based on percentages of CD3+ T cells and CD68+ macrophages within the P-ROIs and surrounding rings. D Heatmap of 414 significantly changing proteins associated with immune phenotypes, as determined by a three-way ANOVA, not confounded by Grade and molecular subtype. Color scale denotes Tukey’s HSD post-hoc score values Colors represent Tukey’s HSD post-hoc scores. Visualization was generated using the “ComplexHeatmap” (v2.22.0) R package. E Heatmap of 658 significantly changing proteins between immune phenotypes in TNBC P-ROIs. Color scale denotes Tukey’s HSD post-hoc score. F Heatmap of 2822 significantly changing proteins between immune phenotypes in HR+ P-ROIs. Color scale denotes Tukey’s HSD post-hoc score values. Protein network representation of the Kynurenine pathway, Aryl Hydrocarbon Receptor (AHR), and Prostaglandins in TNBC ( G ) and HR+ ( H ) subtypes. Each node is divided into four immune-phenotype quadrants, color-coded by Tukey’s HSD post-hoc scores. Protein-protein interactions were obtained from the STRING database, and visualized in Cytoscape (v3.10.0) using the Omics Visualizer app 63 .

Article Snippet: CD3 (Atlas Antibodies, HPA043955) was used at a 1:500 dilution, CD68 (Cell Signaling Technologies, 76437) at 1:200 dilution, each followed by HRP-conjugated donkey anti-rabbit secondary (Jackson ImmunoResearch, 711-035-152) and OPAL 650 (Akoya, FP1496001KT) or OPAL 570 (Akoya, FP1488001KT), respectively.

Techniques: Expressing, Generated, Protein-Protein interactions