Whole slide images (WSI) were captured on the Zeiss Axio. Scan Z1 tissue slide scanner using a 20× objective. Dedicated algorithmic solutions were developed using the Definiens Tissue Studio and Developer XD software platform for co-registration and for image analysis. The images analysis results were correlated to the patient clinical outcome data for the identification of potential image-based prognostic biomarkers. Co-registration of patient related WSIs was done by using Definiens Tissue Studio and enables quantification of co-expression for all applied immunohistochemical biomarkers in the same tumor microenvironment. In a next step, immunohistochemically positive single cells were detected, segmented and classified in T-cells (CD3 and CD8), B-cells (CD20), and macrophages (CD68) as well as blood (CD34) and lymphatic vessels (D2-40 and LYVE1). After object detection, segmentation, and classification multiparametric data extraction was achieved using algorithms quantifying absolute, relative, neighborhood's and spatial relationships properties for total numbers, color, and morphological properties of single objects like shape, object groups cell groups and spatial relations between such properties.
Tissue studio
Manufactured by Definiens
Sourced in Germany, United States
Tissue Studio is a digital pathology solution that enables advanced analysis of tissue samples. It provides automated segmentation and quantification of cells, structures, and biomarkers within histological images.
Automatically generated - may contain errors
Lab products found in correlation
Nanozoomer digital pathology system, by Hamamatsu Photonics (4 mentions)
Nanozoomer 2.0 ht, by Hamamatsu Photonics (3 mentions)
Developer xd, by Definiens (3 mentions)
Aperio scanscope xt, by Leica Biosystems (3 mentions)
Nanozoomer digital pathology c9600, by Hamamatsu Photonics (3 mentions)
Tissue studio library, by Definiens (2 mentions)
Sox10, by Cell Signaling Technology (2 mentions)
Scanscope at, by Leica Biosystems (2 mentions)
Permafluor, by Thermo Fisher Scientific (2 mentions)
Fv1000, by Olympus (2 mentions)
Metamorph imaging software, by Molecular Devices (2 mentions)
Hoechst 33342, by Thermo Fisher Scientific (2 mentions)
Anti c met, by Cell Signaling Technology (1 mentions)
3 3 diaminobenzidine dab substrate, by Agilent Technologies (1 mentions)
Anti phospho c met, by Cell Signaling Technology (1 mentions)
Anti ki67, by Abcam (1 mentions)
Anti cleaved caspase 3, by Abcam (1 mentions)
Anti mmp9, by Cell Signaling Technology (1 mentions)
Anti cd31, by Abcam (1 mentions)
Anti e cadherin, by BD (1 mentions)
86 protocols using tissue studio
1
Whole Slide Image Analysis Pipeline
2
Automated Quantification of Protein Expression
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Using a Ventana iScan HT scanner (Ventana, Tucson, AZ, USA) the slides were digitalized, and “.bif” files were generated. For evaluation of the scanned slides, the semi-automatic commercially available image analysis software Definiens Tissue Studio® (Definiens Developer XD 2.0, Definiens AG, Munich, Germany) was employed. This software allows objective assessment of the staining intensity in different cellular compartments within specified regions of interest (ROI). ROIs were defined as tumor cell areas that were manually annotated in each TMA core to exclude stromal cells and benign areas from evaluation. In addition, cores that comprised staining artifacts or tissue folds were excluded from later analysis. Staining intensity was measured on a continuous arbitrary scale to reflect protein expression of the cells. Data acquisition was performed on a Windows-7-based computer with a 24″ monitor and resolution 1920 × 1080 px for Definiens Tissue Studio®.
3
Immunohistochemical Analysis of Mouse Tumor Tissues
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Immunohistochemistry on paraformaldehyde fixed, paraffin embedded, 3 μm thick sections of mouse tumor tissues was performed manually using anti-Ki67 (1:2000), anti-CD31 (1:200) (abcam), anti-cleaved Caspase3 (1:1000), anti-phospho cMET (1:1000), anti-cMET (1:1000), anti-MMP9 (1:1000) (Cell Signaling Technologies), anti-E-cadherin (1:1000) (BD Biosciences) and anti-ILEI (1:1000) [6 (link)] primary antibodies and Lab Vision™ UltraVision™ LP Detection System (Thermo Scientific) with 3,3′-diaminobenzidine (DAB) substrate (Dako) for detection according to the manufacturer’s instruction. Cell nuclei were visualized by hematoxylin staining. Histological samples were scanned using a Pannoramic MIDI slide scanner (3D Histech) with a 40X objective. Subsequently, quantification of immunomhistochemistry was performed by the histomorphometric software package Tissue Studio® (Definiens AG). The E-cadherin membrane score was obtained by the formula: 3 x ratio of high membrane staining intensity + 2 x ratio of medium membrane staining intensity +1x ratio of low membrane staining intensity, giving a range of 1 to 3.
4
Immunohistochemical Analysis of Mouse Brains
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Mouse brains were processed and immunostained as previously described [9 (link)–12 (link)]. In brief, mice were decapitated under isoflurane anesthesia and brains were harvested and drop fixed in 4% formaldehyde for 24 h, then transferred to graded ethanol series, embedded in paraffin, and sectioned. Eyes were processed and fixed as previously described [13 (link)]. In brief, eyes were harvested after decapitation, injected with 4% formaldehyde, and then drop fixed, embedded in paraffin, and sectioned.
Primary antibodies used were: BAK diluted 1:200 (Cell Signaling, #12105), Myelin Basic Protein (MBP) diluted 1:1000 (Abcam, #ab7349), SOX10 diluted 1:100 (Santa Cruz, #sc-17342), cleaved-Caspase 3 (cC3) diluted 1:400 (Biocare Medical, #CP229C), glial fibrillary acidic protein (GFAP) diluted 1:2000 (Dako, Z0334), PDGFRA diluted 1:200 (Cell Signaling, #3174), SOX2 diluted 1:200 (Cell Signaling, #4900S), SOX9 diluted 1:200 (R&D Systems, #AF3075), NESTIN diluted 1:500 (Cell Signaling, #4760), and IBA1 diluted 1:2000 (Wako Chemicals, #019-19741). Stained images were counterstained with DAPI, digitally imaged using an Aperio Scan Scope XT (Aperio), and subjected to automated cell counting using Tissue Studio (Definiens).
Primary antibodies used were: BAK diluted 1:200 (Cell Signaling, #12105), Myelin Basic Protein (MBP) diluted 1:1000 (Abcam, #ab7349), SOX10 diluted 1:100 (Santa Cruz, #sc-17342), cleaved-Caspase 3 (cC3) diluted 1:400 (Biocare Medical, #CP229C), glial fibrillary acidic protein (GFAP) diluted 1:2000 (Dako, Z0334), PDGFRA diluted 1:200 (Cell Signaling, #3174), SOX2 diluted 1:200 (Cell Signaling, #4900S), SOX9 diluted 1:200 (R&D Systems, #AF3075), NESTIN diluted 1:500 (Cell Signaling, #4760), and IBA1 diluted 1:2000 (Wako Chemicals, #019-19741). Stained images were counterstained with DAPI, digitally imaged using an Aperio Scan Scope XT (Aperio), and subjected to automated cell counting using Tissue Studio (Definiens).
5
Quantitative Analysis of Tumor Microenvironment
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All serial sections (50 µm separation between sections) were cut from frozen block tumor tissue. Sections were stained for CA9 (Rabbit Monoclonal, Thermo Scientific, Burlington, ON, Canada) and CD31 (provided by Dr. Cameron Koch, University of Pennsylvania). Secondary antibodies were used alone to control for nonspecific background. Sections were counterstained with 1 µg/mL DAPI (4′,6-Diamidino-2-phenylindole dihycrochloride) to outline the nuclear area. Images were scanned on the TS4000 (Huron Technologies, Waterloo, ON, Canada) at 0.5 µm/pixel. Regions of tumor, necrosis, stroma, and folds were specified, creating a training rule-set for tissue recognition using Tissue Studio (Definiens, Munich, Germany). Cellular analyses included nucleus identification and separation, objects <10 µm2 being excluded.
6
Automated Immunostaining and Quantification of COX-2 in Tumors
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Immunostainings were performed with the automated immunostaining machine Ventana Discovery XT (Roche Diagnostics/Ventana Medical Systems), as per the manufacturer's instructions and using the ultraView Universal DAB Detection Kit (Roche/Ventana). The COX-2 primary antibody (catalog number 760–4254, product code 518101862) was purchased from Roche Diagnostics K.K. The ratio of COX-2 positive tumor cells was calculated by using the computational software Tissue Studio® (Definiens, Inc.). For each slide, the region of interest (ROI) was set for the whole tumor or for biopsy specimens for the tumorous area. A hematoxylin threshold of 0.1, typical nucleus size of 60 µm2, maximum cell growth of 10, and classification of 0.1 were set, and the expression of COX-2 was automatically calculated by the number of COX-2-positive tumor cells divided by the number of total tumor cells.
7
Quantifying Cell Phenotypes in TMA
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TMA images were digitally segmented into individual cores using Tissue Studio in IF TMA mode (Tissue Studio version 2.7 with Tissue Studio Library version 4.4.2; Definiens Inc.). Cellular Coexpression analysis algorithms were used to quantify the number of cells expressing individual markers, two of three markers, and all three markers, and cells that were negative for all markers. Tumor microenvironment analysis algorithm was used to segment cores into regions of interest (ROI) based on designated epithelial marker (pan-CK or p16, respectively) and quantify cell number expressing/coexpressing each marker. The average cytoplasmic intensity was also determined for all ROIs. Tumor stroma was defined as 25 μm on either side of the border of the tumor core.
8
Automated Quantitative Image Analysis
9
Immunohistochemical Analysis of Explant Cells
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Formalin-fixed and paraffin embedded sections of explants were stained on a Leica BOND-III immunohistochemistry instrument according to the manufacturer’s suggestions, using the following antibodies to detect alpha smooth muscle actin (ACTA2, Abcam ab125044); CD22 (Leica PA0249); CD3 (Leica PA0553); CD34 (Leica PA0212); CDX2 (Abcam ab76541); chromogranin A (Abcam ab68271); FOXA2 (Abcam ab108422); glucagon (Sigma G2654); insulin (Cell Signaling Technology 3014S); NKX6-1 (LSBio LS-C124275). Quantitation of insulin-staining cells and CD34-staining density determinations were made with Tissue Studio image analysis software from Definiens.
10
Quantifying Immune Cell Infiltration in Tumors
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After immunohistochemistry, the microscopic images were imported as digital photo files using a NanoZoomer Digital Pathology system (Hamamatsu Photonics, Hamamatsu, Japan), and the density of the immunolabeled cells was analyzed using the image analysis software, Tissue Studio (Definiens, Munich, Germany). We manually selected one area as region of interest (ROI), in which the CD3‐labeled T cells had infiltrated into the tumor most densely in the specimen, when we checked it in low‐power view. In each individual case, the same ROI was applied to all the other immunostained images. The immunolabeled cells inside the ROI were automatically counted on the basis of staining intensity. In each analysis we confirmed that the immunohistochemically positive lymphocytes were appropriately detected. The density of positive cells was calculated by dividing their number by the ROI area (cells/μm2). Also, we calculated the density ratio of FOXP3 to CD4 (FOXP3/CD4), that of BTLA to CD3 or CD8 (BTLA/CD3, BTLA/CD8), and that of Cbl‐b to CD3 or CD8 (Cbl‐b/CD3, Cbl‐b/CD8). For survival and correlation analyses, patients were divided into two groups showing high and low cell infiltration, using the median value as a cut‐off.
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