IHC Immune Status in situ APP: CD3⁺ cells in epithelial and interstitial tissues

The aim of the project was to quantify the distribution of CD3⁺ cells in and around the epithelial areas of prostate biopsies from a clinical study. The biopsies were provided by the Medical University of Vienna. The following images show some of the analysis steps.

The first step in the APP is Tissue Detection.

In a second step a composite image of both brown and blue channels is created.

Then, a density map of the nuclei is built to determine areas with denser and larger nuclei (epithelial area candidates). 

Based on the density map the epithelial areas are detected and cleaned.

Finally, distance ranges are projected from the perimeters of the epithelial areas to provide distance measurements for CD3⁺ cells.

Detailed View

The three detailed view images below show the detection of nuclei and CD3⁺ staining.

IHC 2 APP: Ki-67 nuclear staining analysis

Ki-67 staining and evaluation is an integral part of cancer diagnosis. Despite it being routinely used in pathology there still are issues to its correct use. Automated tissue analysis can provide a valuable supplement to visual evaluation. The IHC2 APP is among the StrataQuest easiest to use APPs and requires very little preparation time.

The first step of brightfield analysis is a color separation. Hematoxylin (blue) and Ki-67 (brown) stain are shown in separated grayscale images.

The nuclear segmentation algorithm is used on the nuclei, stained in hematoxylin and Ki-67. A virtual channel can be used for data from both stains.

Backward gating provides visual control of the correctness of the nuclear segmentation. This can be visualized both on the orginal and grayscale images.

IF Dots APP: FISH

This example shows how the IF Dots APP can be applied to FISH evaluations. The APP can also be applied to any analysis of dot sized objects, in conjunction with all other StrataQuest features. For FISH evaluation the recommended workflow is to run the dot algorithm on all dot stainings and the to select suitable nuclei by their large size and high compactness.

Overview of triple staining showing the nucleus in DAPI (blue), the housekeeping gene (green) and HER2/neu (red).

Selection of suitable nuclei by size and compactness.

Detection of green housekeeping gene signal is shown in yellow in the right image and the detection of red HER2/neu signal in yellow in the left image.

Cells with a 3 to 2 dots ratio (only one in this image) are shown by backward gating from the "3 x 2" gate.

FISH dot can be displayed and exported in two ways, as shown below. Scattergrams showing the number of cells with each dot number combination is useful, especially with the Heat Map function enabled which shows those groups with more cells. For the immediate export of data for pathology applications a special table view showing 16 parameters is provided (shown partially on the right side) which offers export to Excel, CSV and PDF formats.

IHC Immune Status in situ APP: Tumor immunology

The IHC Immune Status in situ APP is ideally suited for immunological investigations due to its capability to measure the distance of single cells from tissue metastructures. In this example this is applied to bladder cancer  Tissue Microarrays (TMA). In this TMA core DAB stained CD3⁺ lymphocytes (brown) are evaluted in the context of their distance from automatically detected tumor regions as well as from large and small lymphocyte clusters.

TMA core with tumor detection and tumor proximity ranges

TMA core with lymphocyte cluster detection and lymphocyte cluster proximity ranges

Lymphocytes (CD3⁺, purple contour) within tumor proximity

Lymphocytes (CD3⁺, purple contour) within lymphocyte cluster proximity

Sample courtesy of Dr. Kathleen Williamson, Centre for Cancer Research and Cell Biology, Queen’s University, Belfast

Distance of tumor cells from blood vessels

The following example was analysed using the IF Tumor Foci Angio App. It was done for the Johns Hopkins Hospital in New York. The aim was to evaluate the distance of tumor cells from blood vessels within the tumor cell clusters.

Tumor areas are detected using cytokeratin⁺ cells (green) and cell density. Blood vessels are detected using CD31⁺ cells (red). The distance of tumor cells from blood vessels within the tumor areas can then be measured. Some basic steps of the analysis are shown below. Final result: Number of tumor cells within each distance range of a blood vessel: 0-50 μm: 6.988/52%; 50-100 μm: 3.483/26%; 100-150 μm: 1.845/14%

Brain tumor whole digital slide

IHC Membrane APP: HER2/neu in Breast Cancer

Within this project the aim was to measure the prominent diagnostic parameter for breast cancer, the intensity of the HER2/neu membrane staining and the completeness of the closure of the respective membrane rings. The biopsies were provided by the Medical University of Vienna.

The following images show some results of steps in the automated analysis process.

Result of automated color separation for HER2/neu staining

HER2/neu membrane detection algorithm results

 

Tumor nuclei selected (red contour vs. green) in strong HER2/neu areas

Low angle of HER2/neu staining, low intensity

High angle of HER2/neu staining, high intensity

Analysis of cyclic stain and bleach samples

Multi-epitope ligand cartography (MELC) is a technology using samples subjected to cycles of fluorescent staining, imaging and photobleaching. Each cycle can use an antibody for a different protein. The result is a set of images of the distributions of many proteins for the same samples.

Tumor areas are detected using cytokeratin⁺ cells and their density. Blood vessels are detected using CD31⁺ cells. The distance of tumor cells from blood vessels within the tumor areas can then be measured. A specialized APP was established to analyse a MELC sample of skin from a melanoma patient. The aim was to quantify the expression of 90 proteins in close proximity to Melan-A positive areas. Some of the resulting images are shown below. StrataQuest is ideal to fully address the immense potential of such samples with automated context analysis. 

The possibilities of the combination of cyclic stain-bleach methods and StrataQuest context-based analysis are almost endless. Which protein increases in its expression density and which one decreases in relation to its distance to:

• Normal melanocytes,
• Melanoma cells,
• Blood vessels,
• Inflammation sites,
• Sweat glands,
• Hair follicles,
• Basal membrane,
• Langerhans cells,
• Intraepithelial T-cells,
• Regulatory T-cells
• ...

Leishmaniasis APP: Leishmaniasis parasite detection & analysis in cell culture and tissue

The APP was designed to assist in immunology research into Leishmaniasis and can be adapted for research on other intracellular parasites. It can be used both on cell cultures and tissue sections. Its main function is to automatically detect parasite stages in cell compartments and quantify them in context with specific immune markers. The parasite load and the status of parasite stages, e.g. “live/dead” can also be evaluated and all results can be output.

Cell detection with specific live/dead parasite stage combinations

Mouse skin-draining lymph node stained with DAPI (nucelus, blue) and resulting epithelial area detection