Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Here, we describe a simple and accessible strategy for visualizing, quantifying, and mapping immune cells in formalin-fixed paraffin-embedded tumor tissue sections. This methodology combines existing imaging and digital analysis techniques with the purpose of expanding the multiplexing capability and multiparameter analysis of imaging assays.

Transcript

The spatial organization of the immune cells in the tumor microenvironment has clinical value. This strategy can be easily used for visualizing, quantifying, and mapping immune cells within tumor tissue. Immunotherapy has revolutionized cancer treatment.

However, not all patients respond well. This strategy may serve to define the tissue-immune signatures that can predict a good anti-tumor response. Before conducting an experiment, test the antibody combinations and stripping techniques on control tissues and verify that the APPs are accurate in their detection of markers of interest.

As written descriptions of image analysis methods use sophisticated technical language, combining text with video facilitates a better understanding and replication of the methodology. For antigen retrieval of formalin-fixed, paraffin-embedded tumor tissue sections, immerse the dewaxed tissue sample in a Coplin jar of antigen retrieval solution and place the jar into an electric pressure cooker containing tap water. The water level should not exceed half of the height of the jar so that the water does not mix with the antigen retrieval solution.

Close the lid and the pressure valve on the cooker and treat the slides with high pressure for 10 minutes. At the end of the treatment, unplug the cooker, release the pressure, and open the lid. After the slides have cooled in the cooker for 30 minutes, wash the samples two times for five minutes in fresh PBS per wash in a new Coplin jar, then use a hydrophobic pen to draw a barrier around each tissue section.

Next, immerse the slides in 0.1-molar glycine in PBS for 15 minutes at room temperature before rinsing the slides two times in PBS as demonstrated. After the second wash, transfer the slides into a humidity chamber and cover each tissue section with blocking solution. After 30 minutes at room temperature, rinse the sections two times for five minutes in fresh PBS-Tween per wash then add the primary antibodies of interest, diluted in blocking solution, to each slide, protected from light.

At the end of the incubation, rinse the slides three times in fresh PBS-Tween for five minutes per wash, then label the sections with the appropriate secondary antibodies for one hour at room temperature. At the end of the incubation, rinse the slides three times in fresh PBS-Tween for five minutes per wash. Follow with a single rinse in double-distilled water.

Remove the excess water from each slide and mount the tissues with mounting medium supplemented with DAPI and a cover slide. After squeezing out the excess mounting medium, let the slides dry for 20 minutes at room temperature, protected from light, before acquiring images for all of the channels using a whole-slide scanner. After scanning, open the images in the image analysis software and click the Tissuealign tab.

To import the images to be aligned into the slide tray, select the first image to be aligned from the database. When all of the images have been loaded, click Next in the Workflow steps to link the images and drag and drop all of the images to be aligned onto the first image. When all of the images have been linked as appropriate, use a minimum of three pins per image indicating homologous tissue features in the linked images.

Use a pin to trace the first image to check the quality of the resulting alignment. If a satisfactory alignment has been obtained, click Next to view the image layers and save the composite image in the database. To perform a tissue detection using the user-defined protocol APP 1, open the Image Analysis tab and open the composite image in the image analysis module.

Click the Open APP icon and selection the appropriate APP. To confirm that the APP is working, navigate to a selected tissue location and click Preview. If the results are satisfactory, click to process the image using the selected APP.

During the processing the APP will determine whether or not the pixel is associated with the tissue to allow conversion of all of the tissue-associated pixels into a region of interest. The newly created region of interest can then be transferred to any of the aligned images. At the end of the analysis, click File and Save to save the modified image with the newly created region of interest.

For segmentation of the tissue into stroma and parenchyma, open the Image Analysis tab and select the files of interest from the database. Open APP 2, APP 2 uses the PSR-stained image for tissue segmentation. Preview APP 2 by processing the image in a selected field of view.

If the results are satisfactory, click Run to process APP 2 on the full image. The region of interest of the tissue will be segmented into stroma and parenchyma and their respective areas determined. The newly created regions of interest for the stroma and parenchyma can be transferred to the aligned images, then export and save the modified image as demonstrated.

To identify and quantify cell populations of interest, import the segmented image of interest into the image analysis module. After adjusting the color, open APP 3. APP 3 will detect the cell populations of interest and quantify them within the parenchyma and the stroma.

If the results are satisfactory, run APP 3 on the full image. All of the individual cells of interest will be labeled, their tissue coordinates stored, and the densities of the cells of interest in the stroma and parenchymal regions determined. The modified image can then be saved as demonstrated.

To perform tissue heatmapping of the cell-of-interest labeled objects, open the appropriate user-defined protocol in the APP selection window and click Run to prompt the APP to use the coordinates of the antibody-labeled objects to generate the heat map. Hot spot areas, highlighted in red, contain the highest density of the cell population of interest while the dark blue areas have the lowest. The heat map of a specific cell population can be superimposed onto the aligned images to provide additional information about how these cells are organized within the tumor microenvironment.

Then export and save the tissue heat map. It is critical to verify the specificity of the labeling, the accuracy of the designed APPs, and the stripping and reprobing efficiency of the different stains on the same section. By integrating serial imaging, sequential labeling, and tissue alignment, more markers can be visualized simultaneously and more information can be extracted from limited clinical specimens.

H&E staining of resected tumor tissue sections allows evaluation of the tissue architecture, cell morphology, and clinically relevant parameters such as the type of malignancy, tumor grade, and overall immune infiltration. CD34 staining allows the detection of endothelial cells. Cytokeratin 8/18 staining reveals the presence of epithelial cells, and anti-alpha smooth muscle actin staining allows the identification of fibrogenic, activated, hepatic stellate cells.

Reprobing with antibodies against CD68 and Desmin allow the detection of macrophages and myofibroblasts respectively. To better characterize the tumor-immune infiltrate, staining for T-cell markers and myeloperoxidase can be performed. Picro Sirius Red staining can also be performed to visualize fibrillar collagen and to facilitate stroma and parenchyma segmentation.

Tissue-associated pixels within the stained sections can be identified to allow the segmentation of different compartments within a specific region of interest. The cell populations of interest can then be identified within each region, allowing the generation of tissue maps for which regions of high density for a given cell population are displayed as hot spots and regions with a relatively low density appear as cold spots. This methodology for identifying, quantifying, and mapping immune cells in tissue samples can be adapted to and validated for a specific research questions and marker of interest.

This strategy can be applied to tissue micro arrays for high throughput analysis. It can also be combined with in situ hybridization to simultaneously examine in situ protein and gene expression. We have used this strategy to identify and map IL-17A-producing cells in situ in fibrotic liver tissue from patients.

As indicated in the protocol, several reagents are chemically hazardous and the relevant procedures should be performed in a chemical hood using the appropriate personal protective gear and precautions.

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Journal (Immunology and Infection)

Journal (Immunology and Infection)

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

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