Simone Punt was supported by grant UL2010-4801 from the Dutch Cancer Society. We would like to thank all the co-authors of the original paper that this JoVE protocol is based on: Emilie A. Dronkers, Marij J. P. Welters, Renske Goedemans, Senada Koljenovi&#263;, Elisabeth Bloemena, Peter J. F. Snijders, Arko Gorter, and Sjoerd van der Burg.

Patient samples were handled according to the medical ethical guidelines described in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies (www.federa.org).
1. Prepare Slides
<ol>
	<li>Obtain resected tissue material (any kind of tissue) from a pathology department after obtaining medical ethical committee permission to use resected material. 
	NOTE: For the current experiment, pretreatment tumor samples were obtained from primary oropharyngeal tumors diagnosed in the Leiden University Medical Center, Leiden, the Netherlands between 1970 and 2011, selected as described before (n = 162)13. The size of the tissue was only limited by the requirement for a sufficient amount of tumor tissue to reliably take 4 microscopic images inside the tumor.</li>
	<li>Fix the tissue in 4% buffered formalin for a minimum of 12 h. Dehydrate the tissue in a graded series of ethanol. Wash it in xylene and embed it in paraffin wax using an automated tissue processor.</li>
	<li>Cut 4 &#181;m-thick formalin-fixed, paraffin-embedded (FFPE) tissue sections on glass slides using a microtome. Place the tissue block in the microtone tissue holder using standard procedures.
	<ol>
		<li>Cut ribbons of tissue and lay them on the surface of a water bath containing deionized water at 45 &#186;C. Use a slide suitable for immunohistochemical staining to fish out a section by placing the slide in the water directly underneath the section. Carefully move the slide up at an angle, taking the section out of the water and sticking it onto the slide.</li>
	</ol>
	</li>
	<li>Let the slides dry overnight at 37 &#176;C.</li>
	<li>Deparaffinize the FFPE slides by immersing them completely in fresh 100% xylene, three times for 5 min each. Rehydrate the slides by submerging them twice in fresh 100% ethanol, 70% ethanol, and 50% ethanol for 5 min each.</li>
</ol>
2. Perform Antigen Retrieval
<ol>
	<li>Wash the slides in deionized water for 5 min.</li>
	<li>Preheat Tris-ethylenediaminetetraacetic acid (EDTA) buffer (10 mM Tris plus 1 mM EDTA, pH 9.0) to boiling temperature using a microwave. Perform antigen retrieval by submerging the slides in the preheated EDTA buffer and keeping the buffer at this temperature for 10 min in the microwave. 
	NOTE: Any microwave with a power of 900 W can be used.</li>
	<li>Let the slides cool down in the buffer for 2 h.</li>
</ol>
3. Stain Tissue Slides
<ol>
	<li>Wash the slides twice with phosphate-buffered saline (PBS) for 5 min each.</li>
	<li>Draw a circle around the tissue with a hydrophobic pen to prevent the diluted antibodies from spilling off the slide. Wash once more with PBS; this is optional.</li>
	<li>Incubate the tissue with primary antibodies (anti-CD3 1:50, anti-FoxP3 1:200, and anti-IL-17 1:50) diluted in 1% w/v bovine serum albumin (BSA) in PBS at room temperature overnight. 
	NOTE: The volume per slide depends on the size of the tissue, but it is typically 50 - 150 &#181;L. Substitute the primary antibodies with antibodies of the same isotype class with an unknown specificity for the negative control slides at the same dilution as the CD3, CD8, and FoxP3 antibodies (i.e., rabbit Ig isotype control antibody, mouse IgG1 isotype control antibody, and goat IgG isotype control antibody).</li>
	<li>Wash the slides three times with PBS for 5 min each.</li>
	<li>Incubate the tissue with a combination of fluorescently labeled secondary antibodies targeting the primary antibody species and/or isotypes (i.e., 1:200 donkey anti-goat IgG Alexa 488, donkey anti-rabbit IgG A546, and donkey anti-mouse A647) diluted in 1% BSA in PBS at room temperature for 1 h. 
	NOTE: The volume per slide depends upon the size of the tissue but is typically 50 - 150 &#181;L.
	<ol>
		<li>After adding the secondary antibody, keep the slides protected from light as much as possible by storing them in a dark box or by wrapping the box in aluminum foil.</li>
	</ol>
	</li>
</ol>
4. Mount and Counterstain Tissue Slides
<ol>
	<li>Wash the slides three times in PBS for 5 min each.</li>
	<li>Mount the slides using an aqueous anti-fade mounting medium containing a nuclear counterstain (e.g., DAPI). Analyze the slides using a fluorescent microscope as soon as possible (within two weeks). Store the slides in the dark at 4 &#176;C until analysis.</li>
</ol>
5. Analyze Stained Tissue Slides
<ol>
	<li>Obtain four images of each slide using a fluorescence microscope equipped with a 20 - 25X objective. Take images at random locations throughout the total tumor area included in the slide to capture a representative fraction of the tumor. 
	NOTE: A standard magnification of 250X should be used. Any fluorescent or laser scanning microscope can be used, provided it has the filters and lasers needed to visualize the fluorochromes used.
	<ol>
		<li>For visualization of Alexa 488, use an excitation maximum of 490 and an emission maximum of 525; for visualization of Alexa 546, use an excitation maximum of 556 and an emission maximum of 573; for visualization of Alexa 647, use an excitation maximum of 650 and an emission maximum of 665; and for visualization of DAPI, use an excitation maximum of 358 and an emission maximum of 461.</li>
		<li>Save the images as image files (i.e., jpeg and tiff) in the software available to the user.</li>
	</ol>
	</li>
	<li>Discriminate between tumor epithelium and tumor stroma areas based on the nuclear and cellular shapes of tumor epithelial versus stromal cells after consulting a pathologist.
	<ol>
		<li>To determine the total stromal surface area, draw a line around all area(s) occupied by stromal cells (rather than tumor cells) and record the surface area using the image analysis software provided by the microscope manufacturer.
		<ol>
			<li>Click on the &#34;Overlay&#34; tab under the image; choose the &#34;Closed Poly-line&#34; shape and click on it. Demarcate the boundary between tumor epithelial and stromal fields by clicking around the area until reaching the first point again.; this provides a measure for that area. 
			NOTE: Once the shape is closed, a number will appear next to the shape encircling the surface area of the selected image (A = x &#181;m2).</li>
		</ol>
		</li>
		<li>Subtract this surface area from the total image surface area (provided in image properties) to calculate the epithelial surface area. Exclude vascular, necrotic, and autofluorescent areas by drawing a line around them, recording the size of the provided area and subtracting that from the epithelial surface area.</li>
		<li>Save all surface area numbers in a spreadsheet file to calculate the average surface areas and cell numbers per slide.</li>
		<li>Using the image analysis software, determine if the cells are single-, double-, or triple-positive by checking the fluorescence of all four channels.
		<ol>
			<li>Count the single-, double-, and triple-positive cells in each image using ImageJ.
			<ol>
				<li>Download ImageJ. Open an image by clicking on &#34;File&#34; and &#34;Open&#34; and selecting the image to be analyzed. Right-click on the &#34;Point Tool&#34; (a red square in the middle of four lines) and select the &#34;Multi-Point Tool.&#34; Double-click on the &#34;Multi-Point Tool&#34; and count the number of different cell types in the image by selecting a different counter number for each cell type. 
				NOTE: Count all the cells of each different cell type, as identified by the presence of one, two, or all three fluorescent colors. Exclude DAPI, as this nuclear counterstain is present in all cells and is used to discriminate tumor cells from immune cells. Each cell type is counted using a different counter number. Count the cell numbers of each cell type separately in the tumor epithelial and stromal areas by choosing a different counter number each time. Do not count cells within blood vessels and largely autofluorescent areas.</li>
				<li>Record the number of cells analyzed in each counter bin for each image in a spreadsheet file.</li>
				<li>Divide the total number of cells for each cell type over the total surface area of tumor epithelium and tumor stroma analyzed.</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
6. Statistical Analysis
NOTE: All statistical analyses should be discussed with a statistician to assure quality of data. For general statistics, use any medical statistics guide14.
<ol>
	<li>Test the correlations between cell frequencies using a Spearman&#39;s rank correlation rho test.</li>
	<li>Test the statistical differences in the numbers of positive cells between patient groups using the Wilcoxon Mann-Whitney test.</li>
	<li>Test the correlations between cell numbers and disease-free survival (i.e., time from diagnosis until local or distant recurrence of death or disease) by dividing the patients in groups based on a cut-off number of cells using Kaplan-Meier curve generation and log rank analysis15.</li>
	<li>Perform multivariate analyses using Cox proportional hazard regression analysis.</li>
</ol>

<ol><li>Westra, W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+changing+face+of+head+and+neck+cancer+in+the+21st+century%3A+the+impact+of+HPV+on+the+epidemiology+and+pathology+of+oral+cancer%5BTitle%5D)+AND+%22Head+Neck+Pathol%22%5BJournal%5D)">The changing face of head and neck cancer in the 21st century: the impact of HPV on the epidemiology and pathology of oral cancer.</a> Head Neck Pathol. 3 (1), 78-81 (2009).</li>
<li>Rietbergen, M. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Human+papillomavirus+detection+and+comorbidity%3A+critical+issues+in+selection+of+patients+with+oropharyngeal+cancer+for+treatment+De-escalation+trials%5BTitle%5D)+AND+%22Ann+Oncol%22%5BJournal%5D)">Human papillomavirus detection and comorbidity: critical issues in selection of patients with oropharyngeal cancer for treatment De-escalation trials.</a> Ann Oncol. 24 (11), 2740-2745 (2013).</li>
<li>Wallis, S. P., Stafford, N. D., Greenman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Clinical+relevance+of+immune+parameters+in+the+tumor+microenvironment+of+head+and+neck+cancers%5BTitle%5D)+AND+%22Head+Neck%22%5BJournal%5D)">Clinical relevance of immune parameters in the tumor microenvironment of head and neck cancers.</a> Head Neck. 37 (3), 449-459 (2015).</li>
<li>Ye, J., Livergood, R. S., Peng, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+role+and+regulation+of+human+Th17+cells+in+tumor+immunity%5BTitle%5D)+AND+%22Am+J+Pathol%22%5BJournal%5D)">The role and regulation of human Th17 cells in tumor immunity.</a> Am J Pathol. 182 (1), 10-20 (2013).</li>
<li>Amedei, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ex+vivo+analysis+of+pancreatic+cancer-infiltrating+T+lymphocytes+reveals+that+ENO-specific+Tregs+accumulate+in+tumor+tissue+and+inhibit+Th1%2FTh17+effector+cell+functions%5BTitle%5D)+AND+%22Cancer+Immunol+Immunother%22%5BJournal%5D)">Ex vivo analysis of pancreatic cancer-infiltrating T lymphocytes reveals that ENO-specific Tregs accumulate in tumor tissue and inhibit Th1/Th17 effector cell functions.</a> Cancer Immunol Immunother. 62 (7), 1249-1260 (2013).</li>
<li>Whiteside, T. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((What+are+regulatory+T+cells+%28Treg%29+regulating+in+cancer+and+why%3F%5BTitle%5D)+AND+%22Semin+Cancer+Biol%22%5BJournal%5D)">What are regulatory T cells (Treg) regulating in cancer and why?</a> Semin Cancer Biol. 22 (4), 327-334 (2012).</li>
<li>Punt, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Angels+and+demons%3A+Th17+cells+represent+a+beneficial+response%2C+while+neutrophil+IL-17+is+associated+with+poor+prognosis+in+squamous+cervical+cancer%5BTitle%5D)+AND+%22Oncoimmunology%22%5BJournal%5D)">Angels and demons: Th17 cells represent a beneficial response, while neutrophil IL-17 is associated with poor prognosis in squamous cervical cancer.</a> Oncoimmunology. 4 (1), e984539(2015).</li>
<li>Bamias, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Significant+differences+of+lymphocytes+isolated+from+ascites+of+patients+with+ovarian+cancer+compared+to+blood+and+tumor+lymphocytes.+Association+of+CD3%2BCD56%2B+cells+with+platinum+resistance%5BTitle%5D)+AND+%22Gynecol+Oncol%22%5BJournal%5D)">Significant differences of lymphocytes isolated from ascites of patients with ovarian cancer compared to blood and tumor lymphocytes. Association of CD3+CD56+ cells with platinum resistance.</a> Gynecol Oncol. 106 (1), 75-81 (2007).</li>
<li>Gasparoto, T. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Patients+with+oral+squamous+cell+carcinoma+are+characterized+by+increased+frequency+of+suppressive+regulatory+T+cells+in+the+blood+and+tumor+microenvironment%5BTitle%5D)+AND+%22Cancer+Immunol+Immunother%22%5BJournal%5D)">Patients with oral squamous cell carcinoma are characterized by increased frequency of suppressive regulatory T cells in the blood and tumor microenvironment.</a> Cancer Immunol Immunother. 59 (6), 819-828 (2010).</li>
<li>Jordanova, E. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Human+leukocyte+antigen+class+I%2C+MHC+class+I+chain-related+molecule+A%2C+and+CD8%2B%2Fregulatory+T-cell+ratio%3A+which+variable+determines+survival+of+cervical+cancer+patients%3F%5BTitle%5D)+AND+%22Clin+Cancer+Res%22%5BJournal%5D)">Human leukocyte antigen class I, MHC class I chain-related molecule A, and CD8+/regulatory T-cell ratio: which variable determines survival of cervical cancer patients?</a> Clin Cancer Res. 14 (7), 2028-2035 (2008).</li>
<li>van Esch, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Alterations+in+classical+and+nonclassical+HLA+expression+in+recurrent+and+progressive+HPV-induced+usual+vulvar+intraepithelial+neoplasia+and+implications+for+immunotherapy%5BTitle%5D)+AND+%22Int+J+Cancer%22%5BJournal%5D)">Alterations in classical and nonclassical HLA expression in recurrent and progressive HPV-induced usual vulvar intraepithelial neoplasia and implications for immunotherapy.</a> Int J Cancer. 135 (4), 830-842 (2014).</li>
<li>Heeren, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Prognostic+effect+of+different+PD-L1+expression+patterns+in+squamous+cell+carcinoma+and+adenocarcinoma+of+the+cervix%5BTitle%5D)+AND+%22Mod+Pathol%22%5BJournal%5D)">Prognostic effect of different PD-L1 expression patterns in squamous cell carcinoma and adenocarcinoma of the cervix.</a> Mod Pathol. 29 (7), 753-763 (2016).</li>
<li>Punt, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+beneficial+tumor+microenvironment+in+oropharyngeal+squamous+cell+carcinoma+is+characterized+by+a+high+T+cell+and+low+IL-17%28%2B%29+cell+frequency%5BTitle%5D)+AND+%22Cancer+Immunol+Immunother%22%5BJournal%5D)">A beneficial tumor microenvironment in oropharyngeal squamous cell carcinoma is characterized by a high T cell and low IL-17(+) cell frequency.</a> Cancer Immunol Immunother. 65 (4), 393-403 (2016).</li>
<li>Kirkwood, B. R., Sterne, J. A. C. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aKirkwood%2C+BR+%22Essential+Medical+Statistics%22">Essential Medical Statistics</a>. , 2nd ed, Wiley-Blackwell. (2003).</li>
<li>Kleinbaum, D. G., Klein, M. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aKleinbaum%2C+DG+%22Survival+Analysis%3A+A+Self-Learning+Text%22">Survival Analysis: A Self-Learning Text</a>. , 2nd ed, Springer. (2005).</li>
<li>Fabre, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Targeting+the+Tumor+Microenvironment%3A+The+Protumor+Effects+of+IL-17+Related+to+Cancer+Type%5BTitle%5D)+AND+%22Int+J+Mol+Sci%22%5BJournal%5D)">Targeting the Tumor Microenvironment: The Protumor Effects of IL-17 Related to Cancer Type.</a> Int J Mol Sci. 17 (9), (2016).</li>
<li>Feng, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multispectral+imaging+of+formalin-fixed+tissue+predicts+ability+to+generate+tumor-infiltrating+lymphocytes+from+melanoma%5BTitle%5D)+AND+%22J+Immunother+Cancer%22%5BJournal%5D)">Multispectral imaging of formalin-fixed tissue predicts ability to generate tumor-infiltrating lymphocytes from melanoma.</a> J Immunother Cancer. 3 (47), (2015).</li>
</ol>

The authors declare no commercial or financial conflict of interest.

For the protocol described, one of the most critical steps is to determine the correct dilution of the primary antibodies used. The dilution of the labeled secondary antibodies was 1:200, as recommended by the manufacturer of these specific Alexa-labeled antibodies. The dilution of the primary antibodies should then be determined by a serial dilution, preferably using two different samples of the intended tissue type (in this case, OPSCC). The optimal working dilution is the dilution at which a clear signal is obtained, without background noise and in the absence of a signal for the negative control at the same concentration. Modifications can be made with regard to the type of secondary antibodies and mounting medium used, depending on the type of microscope available and the preference of the researcher. If the intended results are not achieved, we recommend looking into the type of glass slides used, as some are known to cause problems with background signals for particular kinds of staining solutions (e.g., Perma Blue). Second, some antigens may be disrupted by the use of heat-induced epitope retrieval. In that case, the researcher can replace the heating step of the buffer with other techniques, such as enzyme-induced epitope retrieval. Third, if using the hydrophobic pen, the marking should not be made too close to the tissue, as this will prevent the staining solution from working properly. Regarding the number of sections per sample and the required number of images per section, it is up to the researcher and the specific research question to determine the number required to answer the research question with sufficient statistical power. For our analysis, we used one section per sample and four images per section. Finally, when using immunofluorescent staining, care should be taken when using nail polish to seal the cover slips, as alcohol present in the nail polish solution can affect the fluorescent signal.
The protocol described here does not involve high-throughput analysis. We have tried to automate this step, but the subjective interpretation of cellular size and morphology complicates the automation of the analysis with the software packages available at the time. Although tissue preparation and staining can be automated to a great extent, the counting of the cells was performed manually.
We were able to study the correlations between the infiltrating T-cell subsets studied and clinical outcome using the described protocol. A high number of T cells was found to be correlated with improved disease-free survival in patients with a low number of intratumoral IL-17+ non-T cells. This suggests that IL-17+ non-T cells may be related to a poor immune response in OPSCC, which is in agreement with the correlation described between IL-17 and poor survival in cancer patients16.
Improved software programs have now become commercially available to automate this step and are currently replacing the manual cell observation and counting, which will lead to more reliable, objective, reproducible, and fast results.
In addition, the availability of commercial kits allowing for the multiplexing of fluorescent immunohistochemical markers is currently on the rise17. This will allow for the multiplexing of up to 7 different immune markers/biomarkers in combination with a nuclear counterstain. However, we believe that the protocol reported here will still be more efficiently and easily applied in laboratories lacking complex and expensive infrastructure, microscopes, and software packages for multispectral staining analysis.

Oropharyngeal squamous cell carcinomas (OPSCCs) are a heterogeneous group of squamous cell cancers originating in the oropharynx. Risk factors for OPSCC include human papillomavirus (HPV) infection and alcohol and tobacco use1,2. The role of the immune response and how to use this in a clinical setting is just starting to be explored. The tumor microenvironment is infiltrated by immune cells that are attracted to the cancer site. Although a high CD8+ cytotoxic T-cell frequency has been correlated with improved survival in OPSCC patients3, the role of other T-cell subsets, including Tregs and Th17 cells, is still unclear4. Whereas Th1 and Th17 cells are supposed to aid in the immune response targeting tumor cells, Tregs are well known for their abilities to suppress the activity of other T cells5. However, the presence of Tregs has been found to correlate with both favorable and unfavorable responses in different tumor types6. Since not all immune cells present in the blood infiltrate the tumor to the same extent, studying the local tumor microenvironment provides the most reliable measure of the immune response directed against the tumor. The aim of this study is to determine the correlation between the numbers and types of immune cells and the clinical outcome. We used four-color fluorescence IHC imaging to analyze the number and localization of various T-cell subpopulations in human OPSCC.
We focused on total T lymphocytes (CD3+), Th17 cells, and immunosuppressive FoxP3+ Tregs, whose differentiation pathway is closely related to Th17 cells. Th17 cells are characterized by the combination of CD3 and IL-17. The cytokine IL-17 can also be produced by non-T cells7. We determined the distribution of intra-epithelial and stromal T cells, Tregs, Th17, and IL-17+ non-T cells in a large series of OPSCC cases and analyzed the correlations with patient survival. Multicolor fluorescence IHC was used to identify the expression of CD3, Foxp3, and IL-17, in combination with a DAPI counterstain. This assay allowed for the easy and clear identification of both tumor cells (using DAPI nuclear staining) and the infiltrating T-cell populations (using a combination of different markers). Following sample preparation and staining, a fluorescent microscope and imaging software were used to separate the different fluorescent colors used and to determine the number and type of cells present in both the tumor epithelium and the tumor-associated stroma.
An alternative assay to quantify and phenotype immune cell populations is flow cytometry analysis, or cytometry by time of flight (CyTOF) analysis, of tumor or peripheral samples (i.e., blood or ascites). Using this technique, all information about localization and relative distribution of the different cell types is lost. The use and analysis of peripheral samples also does not provide information about which cells are able to infiltrate the tumor microenvironment. Blood and ascite immune-cell analyses have been shown not to reflect the phenotype and frequency of immune cell infiltration of the tumor tissue8,9.
Another alternative is the use of bright-field microscopy. An advantage of this technique over fluorescence imaging is the absence of tissue autofluorescence. Although some samples contain more autofluorescence&#8212;particularly erythrocytes, but also other cell types, including neutrophilic granulocytes&#8212;these areas can easily be removed in the analysis of almost all samples. Immunofluorescence offers the advantage of analyzing multiple markers in one sample by using a panel of targeted fluorescent wavelengths. This is currently impossible to the same extent for bright-field microscopy due to the lack of a sufficient number of labels and commercially available antibody isotypes for a particular antigen.
The multicolor fluorescence IHC technique described here has been used in many different cancer types and antibody combinations to study different immune cell populations, as well as tumor cell-expressed molecules, such as human leukocyte antigens (HLA) and PD-L110,11,12. The protocol has been established and validated using many different types of samples and antibodies.

<table><tbody><tr><td>Pathos Delta Ultra Rapid Tissue Processor</td><td>Milestone and Histostar</td><td></td><td>Automated tissue processor</td></tr><tr><td>Histostar</td><td>Thermo Scientific</td><td></td><td>Tissue block embedding machine</td></tr><tr><td>Formaldehyde</td><td>Baker</td><td></td><td></td></tr><tr><td>Xylol</td><td>Merck</td><td></td><td></td></tr><tr><td>Ethanol</td><td>Merck</td><td></td><td></td></tr><tr><td>milliQ water</td><td>Elaga Purelab Chorus</td><td></td><td></td></tr><tr><td>Paraffin wax/Paraclean</td><td>Klinipath</td><td>5079A</td><td></td></tr><tr><td>Microtome tissue holder</td><td>Leica</td><td>RM225</td><td></td></tr><tr><td>Flex IHC side</td><td>Dako</td><td></td><td>Tissue slide</td></tr><tr><td>Tris</td><td>Merk-Milipore</td><td>1,083,821,000</td><td></td></tr><tr><td>EDTA</td><td>Baker</td><td>1073</td><td></td></tr><tr><td>PBS</td><td>Bio-Rad</td><td>BUF036A</td><td></td></tr><tr><td>BSA</td><td>Sigma</td><td>A9647</td><td></td></tr><tr><td>Rabbit anti-CD3</td><td>Abcam</td><td>ab828</td><td>Titrate required antibody dilution</td></tr><tr><td>Mouse IgG1 anti-FoxP3</td><td>Abcam</td><td>ab20034</td><td>Titrate required antibody dilution</td></tr><tr><td>Goat IgG anti-IL-17</td><td>R&amp;amp;D Systems</td><td>AF-317-NA</td><td>Titrate required antibody dilution</td></tr><tr><td>Rabbit Ig isotype control antibody</td><td>Abcam</td><td>ab27472</td><td>Use at same final concentration as anti-CD3</td></tr><tr><td>Mouse IgG1 isotype control antibody</td><td>Abcam</td><td>ab91353</td><td>Use at same final concentration as anti-FoxP3</td></tr><tr><td>Goat IgG isotype control antibody</td><td>ThermoFisher Scientific</td><td>02-6202</td><td>Use at same final concentration as anti-IL-17</td></tr><tr><td>Donkey anti-rabbit IgG A546</td><td>ThermoFisher Scientific</td><td>A10040</td><td>Dilute 1:200 in 1% BSA/PBS</td></tr><tr><td>Donkey anti-mouse-A647</td><td>ThermoFisher Scientific</td><td>A31571</td><td>Dilute 1:200 in 1% BSA/PBS</td></tr><tr><td>Donkey anti-goat IgG A488</td><td>ThermoFisher Scientific</td><td>A11055</td><td>Dilute 1:200 in 1% BSA/PBS</td></tr><tr><td>VectaShield containing DAPI</td><td>Vector Laboratories</td><td>H-1200</td><td></td></tr><tr><td>LSM700 confocal laser scanning microscope&amp;nbsp;</td><td>Zeiss</td><td></td><td></td></tr><tr><td>LCI Plan-Neofluar 25x/0.8 Imm Korr DIC M27 objective</td><td>Zeiss</td><td>420852-9972-720</td><td></td></tr><tr><td>LSM Zen Software</td><td>Zeiss</td><td>version 2009</td><td></td></tr><tr><td>LSM Image Browser</td><td>Zeiss</td><td>version 4.2.0.121</td><td>Available to download at www.zeiss.com/microscopy/int/website/downloads/lsm-image-browser.html.</td></tr><tr><td>SPSS</td><td>IBM Corp.</td><td>version 20.0</td><td></td></tr><tr><td>ImageJ</td><td></td><td>version 1.50i</td><td>Available to download at http://rsb.info.nih.gov/ij.</td></tr></tbody></table>

four-color fluorescence immunohistochemistry of t-cell subpopulations in archival formalin-fixed, paraffin-embedded human oropharyngeal squamous cell carcinoma samples

The four-color fluorescence immunohistochemistry (IHC) technique is a method to quantify cell populations of interest while taking into account their relative distribution and their localization in the tissue. This technique has been extensively applied to study the immune infiltrate in various tumor types. The tumor microenvironment is infiltrated by immune cells that are attracted to the tumor site. Different immune cell populations have been found to play different roles in the tumor microenvironment and to have a different impact on the outcome of disease. This manuscript describes the use of multiparameter fluorescence IHC on oropharyngeal squamous cell carcinoma (OPSCC) as an example. This technique can be extended to other tissue samples and cell types of interest. In the presented study, we analyzed the intraepithelial and stromal compartment of a large OPSCC cohort (n = 162). We focused on total T lymphocytes (CD3+), immunosuppressive regulatory T cells (Tregs; i.e., FoxP3+), and T helper 17 (Th17) cells (i.e., IL-17+CD3+) using a nuclear counterstain to distinguish tumor epithelium from stroma. A high number of T cells was found to be correlated with improved disease-free survival in patients with a low number of intratumoral IL-17+ non-T cells. This suggests that IL-17+ non-T cells may be correlated with a poor immune response in OPSCC, which is in agreement with the correlation described between IL-17 and poor survival in cancer patients. Currently, novel multiparameter fluorescence IHC techniques are being developed using up to 7 different fluorochromes and will enable the more precise characterization and localization of immune cells in the tumor microenvironment.

A series of FFPE pretreatment tumor samples obtained from primary oropharyngeal tumors diagnosed in the Leiden University Medical Center, Leiden, the Netherlands between 1970 and 2011, selected as described before (n = 162), was stained using the protocol described13. One to four random images of each slide were analyzed (Figure 1). Some autofluorescent cells are indicated, which can clearly be distinguished by their complete yellow appearance. Cells truly double- or triple-positive only stain positive for a particular antibody at the expected localization, which is at the cell membrane or the nucleus, in this case. Negative control slides did not show any specific staining above background tissue autofluorescence (Figure 2 and Figure 4), confirming that all signal is specific to the targets recognized by the primary antibodies. All tumor samples were found to be infiltrated by CD3+ T cells to varying extents. FoxP3+ Tregs always expressed CD3 and were one of the major infiltrating T-cell populations. CD3 cells expressing IL-17 (Th17 cells) were a minor population of the infiltrating T cells. IL-17 expressed by CD3- cells was another abundant infiltrating cell population. IL-17+ FoxP3+ cells comprised no more than 0.01% of all FoxP3+ cells.
All statistical tests were two-sided, and p-values below 0.05 were considered significant14. The correlations between intra-epithelial or total cell numbers and survival are presented, since the correlations between stromal or total cell numbers and patient survival were similar. A high number of infiltrating total CD3+ T cells showed a trend toward a correlation with improved disease-free survival (0.086, Figure 5A) as compared to a low number of T cells (i.e., lowest quartile). When specifically studying patients with a low number of IL-17+ cells, a high number of total infiltrating T cells was correlated with improved disease-free survival (p = 0.012, Figure 5B). The prognostic effect of tumor-infiltrating T cells was lost in the group of patients with a high number of tumor-infiltrating IL-17+ cells (data not shown). Thus, the effect of tumor-infiltrating T cells in OPSCC may be related to the low number of IL-17+ cells present.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55589/55589fig1.jpg" /> 
Figure 1: FFPE Oropharyngeal Cancer Tissue Stained by Four-color Fluorescence IHC. Representative image of an immunofluorescent stain for CD3 (A, red), IL-17 (B, green), and FoxP3 (C, blue), as well as the merged image combined with DAPI (gray) (D). Two autofluorescent cells are indicated by the arrows. <a href="http://cloudflare.jove.com/files/ftp_upload/55589/55589fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55589/55589fig2.jpg" /> 
Figure 2: Negative Control for CD3. Representative image of FFPE oropharyngeal cancer tissue, stained as described in the protocol, substituting the anti-CD3 antibody with a rabbit Ig isotype control antibody with unknown specificity. No staining for rabbit Ig (A, red) combined with staining for IL-17 (B, green), FoxP3 (C, blue), and DAPI (D, gray) is shown. <a href="http://cloudflare.jove.com/files/ftp_upload/55589/55589fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55589/55589fig3.jpg" /> 
Figure 3: Negative Control for IL-17. Representative image of FFPE oropharyngeal cancer tissue, stained as described in the protocol, substituting the anti-IL-17 antibody with a goat Ig isotype control antibody with unknown specificity. No staining for goat Ig (B, green) combined with staining for CD3 (A, red), FoxP3 (C, blue), and DAPI (D, gray) is shown. <a href="http://cloudflare.jove.com/files/ftp_upload/55589/55589fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55589/55589fig4.jpg" /> 
Figure 4: Negative Control for FoxP3. Representative image of FFPE oropharyngeal cancer tissue, stained as described in the protocol, substituting the anti-FoxP3 antibody with a mouse IgG1 isotype control antibody with unknown specificity. No staining for mouse IgG1 (C, blue) combined with staining for CD3 (A, red), IL-17 (B, green), and DAPI (D, gray) is shown. <a href="http://cloudflare.jove.com/files/ftp_upload/55589/55589fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/55589/55589fig5.jpg" /> 
Figure 5: Kaplan-Meier Survival Curves. For patients with a below-median number of IL-17+ cells/mm2, disease-free survival curves are shown for a very low (i.e., lowest quartile) versus high number of total T cells (A) and a low (i.e., below median) versus high number of total T cells (B) in the total tumor area. Reproduced with permission from the Cancer Immunology Immunotherapy journal13. <a href="http://cloudflare.jove.com/files/ftp_upload/55589/55589fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Four-color Fluorescence Immunohistochemistry of T-cell Subpopulations in Archival Formalin-fixed, Paraffin-embedded Human Oropharyngeal Squamous Cell Carcinom

Four-color Fluorescence Immunohistochemistry of T-cell Subpopulations in Archival Formalin-fixed, Paraffin-embedded Human Oropharyngeal Squamous Cell Carcinoma Samples

Multiparameter fluorescence immunohistochemistry can be used to assess the number, relative distribution, and localization of immune cell populations in the tumor microenvironment. This manuscript describes the use of this technique to analyze T-cell subpopulations in oropharyngeal cancer.

The four-color fluorescence immunohistochemistry (IHC) technique is a method to quantify cell populations of interest while taking into account their ...

four-color-fluorescence-immunohistochemistry-t-cell-subpopulations

Nanyang Technological University

Research

JoVE Journal

Cancer Research

9.6K Views.  Leiden University Medical Center. Multiparameter fluorescence immunohistochemistry can be used to assess the number, relative distribution, and localization of immune cell populations in the tumor microenvironment. This manuscript describes the use of this technique to analyze T-cell subpopulations in oropharyngeal cancer.

Video: Four-color Fluorescence Immunohistochemistry of T-cell Subpopulations in Archival Formalin-fixed, Paraffin-embedded Human Oropharyngeal Squamous Cell Carcinoma Samples

Automated Multiplex Immunofluorescence Panel for Immuno-oncology Studies on Formalin-fixed Carcinoma Tissue Specimens

Continued developments in immuno-oncology require an increased understanding of the mechanisms of cancer immunology. The immunoprofiling analysis of tissue samples from formalin-fixed, paraffin-embedded (FFPE) biopsies has become a key tool for understanding the complexity of tumor immunology and discovering novel predictive biomarkers for cancer immunotherapy. Immunoprofiling analysis of tissues requires the evaluation of combined markers, including inflammatory cell subpopulations and immune checkpoints, in the tumor microenvironment. The advent of novel multiplex immunohistochemical methods allows for a more efficient multiparametric analysis of single tissue sections than does standard monoplex immunohistochemistry (IHC). One commercially available multiplex immunofluorescence (IF) method is based on tyramide-signal amplification and, combined with multispectral microscopic analysis, allows for a better signal separation of diverse markers in tissue. This methodology is compatible with the use of unconjugated primary antibodies that have been optimized for standard IHC on FFPE tissue samples. Herein we describe in detail an automated protocol that allows multiplex IF labeling of carcinoma tissue samples with a six-marker multiplex antibody panel comprising PD-L1, PD-1, CD68, CD8, Ki-67, and AE1/AE3 cytokeratins with 4&#8242;,6-diamidino-2-phenylindole as a nuclear cell counterstain. The multiplex panel protocol is optimized in an automated IHC stainer for a staining time that is shorter than that of the manual protocol and can be directly applied and adapted by any laboratory investigator for immuno-oncology studies on human FFPE tissue samples. Also described are several controls and tools, including a drop-control method for fine quality control of a new multiplex IF panel, that are useful for the optimization and validation of the technique.

A detailed protocol for a six-marker multiplex immunofluorescence panel is optimized and performed, using an automated stainer for more consistent results and a shorter procedure time. This approach can be directly adapted by any laboratory for immuno-oncology studies.

Continued developments in immuno-oncology require an increased understanding of the mechanisms of cancer immunology. The immunoprofiling analysis of ...

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is an effective methodology for tumor evaluation that improves the understanding of the tumor microenvironment. The visualization of protein expression in formalin-fixed, paraffin-embedded&#160;tissues is achieved when a specific fluorophore is annealed to an antibody-bound barcode via complementary oligonucleotides and then sample imaging is performed; indeed, this method allows for the use of customizable panels of more than 40 antibodies in a single tissue staining reaction. This method is compatible with fresh frozen tissue, formalin-fixed, paraffin-embedded tissue, cultured cells, and peripheral blood mononuclear cells, meaning that researchers can use this technology to view a variety of sample types at single-cell resolution. This method starts with a manual staining and fixing protocol, and all the antibody barcodes are applied using an antibody cocktail. The staining fluidics instrument is fully automated and performs iterative cycles of labeling, imaging, and removing spectrally distinct fluorophores until all the biomarkers have been imaged using a standard fluorescence microscope. The images are then collected and compiled across all the imaging cycles to achieve single-cell resolution for all the markers. The single-step staining and gentle fluorophore removal not only allow for highly multiplexed biomarker analysis but also preserve the sample for additional downstream analysis if desired (e.g., hematoxylin and eosin staining). Furthermore, the image analysis software enables image processing-drift compensation, background subtraction, cell segmentation, and clustering-as well as the visualization and analysis of the images and cell phenotypes for the generation of spatial network maps. In summary, this technology employs a computerized microfluidics system and fluorescence microscope to iteratively hybridize, image, and strip fluorescently labeled DNA probes that are complementary to tissue-bound, oligonucleotide-conjugated antibodies.

Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image&#160;analysis technique.

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is ...

Multiplex Immunofluorescence and Spatial Image Analysis of the Tumor Microenvironment

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.
We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.
This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment  

In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending ...

Mapping the Tumor Immune Landscape: An In-Depth Multiplex IHC Analysis Protocol

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

This protocol describes in detail how immune cell characterization of the tumor microenvironment using multiplex immunohistochemistry is carried out.

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. ...

Deciphering Tumor Microenvironment Using mIHC in Lung Squamous Carcinoma

Multiplex Immunohistochemistry Staining for Paraffin-embedded Lung Cancer Tissue

Lung cancer is the leading cause of malignant tumor-related morbidity and mortality all over the world, and the complex tumor microenvironment has been considered the leading cause of death in lung cancer patients. The complexity of the tumor microenvironment requires effective methods to understand cell-to-cell relationships in tumor tissues. The multiplex immunohistochemistry (mIHC) technique has become a key tool for inferring the relationship between the expression of proteins upstream and downstream of signaling pathways in tumor tissues and developing clinical diagnoses and treatment plans. mIHC is a multi-label immunofluorescence staining method based on Tyramine Signal Amplification (TSA) technology, which can simultaneously detect multiple target molecules on the same tissue section sample to achieve different protein co-expression and co-localization analysis. In this experimental protocol, paraffin-embedded tissue sections of lung squamous carcinoma of clinical origin were subjected to multiplex immunohistochemical staining. By optimizing the experimental protocol, multiplex immunohistochemical staining of labeled target cells and proteins was achieved, solving the problem of autofluorescence and channel crosstalk in lung tissues. In addition, multiplex immunohistochemical staining is widely used in the experimental validation of tumor-related, high-throughput sequencing, including single-cell sequencing, proteomics, and tissue space sequencing, providing intuitive and visual pathology validation results.

Author Spotlight: Enhancing Multicolor Fluorescence Localization in Lung Carcinoma Sample

This experimental protocol describes and optimizes a multiplex immunohistochemistry (IHC) staining method, mainly by optimizing single-channel antibody incubation conditions and adjusting the settings of antibodies and channels to solve the problems of autofluorescence and channel crosstalk in lung cancer tissues of clinical origin.

Lung cancer is the leading cause of malignant tumor-related morbidity and mortality all over the world, and the complex tumor microenvironment has been ...

In Situ Immunohistochemical Detection of Immune Cell Markers in Cancer Tissues

Multiplex Cyclic Fluorescent Immunohistochemistry

The tumor microenvironment involves interactions between host cells, tumor cells, immune cells, stromal cells, and vasculature. Characterizing and spatially organizing immune cell subsets and target proteins are crucial for prognostic and therapeutic purposes. This has led to the development of multiplexed immunohistochemistry staining methods. Multiplex fluorescence immunohistochemistry allows the simultaneous detection of multiple markers, facilitating a comprehensive understanding of cell function and intercellular interactions. In this paper, we describe a workflow for the multiplex cyclic fluorescent immunohistochemistry assay and its application in the quantification analysis of lymphocyte subsets. The multiplex cyclic fluorescent immunohistochemistry staining follows similar steps and reagents as standard immunohistochemistry, involving antigen retrieval, cyclic antibody incubation, and staining on a formalin-fixed paraffin-embedded (FFPE) tissue slide. During the antigen-antibody reaction, a mixture of antibodies from different species is prepared. Conditions, such as antigen retrieval time and antibody concentration, are optimized and validated to increase the signal-to-noise ratio. This technique is reproducible and serves as a valuable tool for immunotherapy research and clinical applications.

Author Spotlight: Efficient Detection of Immune Cell-Infiltration in Cancer Tissues Using Fluorescent Immunohistochemistry

Multiplex cyclic immunohistochemistry allows in situ detection of multiple markers simultaneously using repeated antigen-antibody incubation, image scanning, and image alignment and integration. Here, we present the operating protocol for identifying immune cell substrates with this technology in lung cancer and paired brain metastasis samples.

The tumor microenvironment involves interactions between host cells, tumor cells, immune cells, stromal cells, and vasculature. Characterizing and ...

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells

Cytotoxic T cells play a key role in the elimination of tumor cells and are, therefore, intensively studied in cancer immunology. The frequency and activity of cytotoxic T cells within tumors and their tumor microenvironment (TME) are now well-established prognostic and predictive biomarkers for numerous tumor types. However, it is well-known that various tumor treatment modalities, including radiotherapy, chemotherapy, immunotherapy, and targeted therapy, modulate not only the immunogenicity of the tumor but also the immune system itself. Consequently, the interaction between tumor cells and T cells requires more intensive study in different therapeutic contexts to fully understand the complex role of T cells during tumor therapy. To address this need, a protocol was developed to analyze the activity and proliferative capacity of human cytotoxic (CD8+) T cells in co-culture with pre-treated tumor cells. Specifically, CD8+ T cells from healthy donors are stained with the non-toxic proliferation marker carboxyfluorescein diacetate succinimidyl ester (CFSE) and stimulated using CD3/CD28-coated plates. Subsequently, T cells are co-cultured with pre-treated tumor cells. As a readout, T cell proliferation is quantified by measuring CFSE signal distribution and assessing the expression of surface activation markers via flow cytometry. This can be further complemented by quantifying cytokine release using enzyme-linked immunosorbent assay (ELISA). This method facilitates the evaluation of treatment-induced changes in the interaction between tumor cells and T cells, providing a foundation for more detailed analyses of tumor treatment modalities and their immunogenicity in a human ex vivo setting. Additionally, it contributes to the reduction of pre-clinical in vivo analyses.

The present protocol describes an experimental workflow that allows for the ex vivo analysis of human T cell stimulation in an allogenic co-culture system with pre-treated tumor cells.

Cytotoxic T cells play a key role in the elimination of tumor cells and are, therefore, intensively studied in cancer immunology. The frequency and ...

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma

Immunohistochemical (IHC) methods for the in-situ analysis of protein expression by light microscopy are a powerful tool for both research and diagnostic purposes. However, the visualization and quantification of multiple antigens in a single tissue section using conventional chromogenic IHC is challenging. Multiplexed imaging is especially relevant in lymphoma research and diagnostics, where markers have to be interpreted in the context of a complex tumor microenvironment. Here we describe a protocol for multiplexed fluorescent IHC staining to enable the quantitative assessment of multiple targets in specific cell types of interest in lymphoma.The method covers aspects of antibody validation, antibody optimization, the multiplex optimization with markers of lymphoma subtypes, the staining of tissue microarray (TMA) slides, and the scanning of the slides, followed by data analysis, with specific reference to lymphoma. Using this method, scores for both the mean intensity of a marker of interest and the percentage positivity are generated to facilitate further quantitative analysis. Multiplexing minimizes sample utilization and provides spatial information for each marker of interest.

Here we describe a protocol for multiplex fluorescent immunohistochemical staining and imaging for the simultaneous localization of multiple cancer-associated antigens in lymphoma. This protocol can be extended to the colocalization analysis of biomarkers within all tissue sections.

Immunohistochemical (IHC) methods for the in-situ analysis of protein expression by light microscopy are a powerful tool for both research and diagnostic ...

Immunology and Infection

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

The immune landscape of the tumor microenvironment (TME) is a determining factor in cancer progression and response to therapy. Specifically, the density and the location of immune cells in the TME have important diagnostic and prognostic values. Multiomic profiling of the TME has exponentially increased our understanding of the numerous cellular and molecular networks regulating tumor initiation and progression. However, these techniques do not provide information about the spatial organization of cells or cell-cell interactions. Affordable, accessible, and easy to execute multiplexing techniques that allow spatial resolution of immune cells in tissue sections are needed to complement single cell-based high-throughput technologies. Here, we describe a strategy that integrates serial imaging, sequential labeling, and image alignment to generate virtual multiparameter slides of whole tissue sections. Virtual slides are subsequently analyzed in an automated fashion using user-defined protocols that enable identification, quantification, and mapping of cell populations of interest. The image analysis is done, in this case using the analysis modules Tissuealign, Author, and HISTOmap. We present an example where we applied this strategy successfully to one clinical specimen, maximizing the information that can be obtained from limited tissue samples and providing an unbiased view of the TME in the entire tissue section.

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.

The immune landscape of the tumor microenvironment (TME) is a determining factor in cancer progression and response to therapy. Specifically, the density ...

A Rapid Method for Multispectral Fluorescence Imaging of Frozen Tissue Sections

Multispectral fluorescence imaging on formalin-fixed paraffin-embedded (FFPE) tissues enables the detection of multiple markers in a single tissue sample that can provide information about antigen coexpression and spatial distribution of the markers. However, a lack of suitable antibodies for formalin-fixed tissues may restrict the nature of markers that can be detected. In addition, the staining method is time-consuming. Here we describe a rapid method to perform multispectral fluorescence imaging on frozen tissues. The method includes the fluorophore combinations used, detailed steps for the staining of mouse and human frozen tissues, and the scanning, acquisition, and analysis procedures. For staining analysis, a commercially available semiautomated multispectral fluorescence imaging system is used. Through this method, up to six different markers were stained and detected in a single frozen tissue section. The machine learning analysis software can phenotype cells that can be used for quantitative analysis. The method described here for frozen tissues is useful for the detection of markers that cannot be detected in FFPE tissues or for which antibodies are not available for FFPE tissues.

We describe a rapid staining method to perform multispectral imaging on frozen tissues.

Multispectral fluorescence imaging on formalin-fixed paraffin-embedded (FFPE) tissues enables the detection of multiple markers in a single tissue sample ...