Name: four-color fluorescence immunohistochemistry of t-cell subpopulations in archival formalin-fixed, paraffin-embedded human oropharyngeal squamous cell carcinoma samples
Uploaded: 2017-07-29T14:00:00.000+00:00
Duration: 7 min 43 s
Description: 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

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>

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S., Peng, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+and+regulation+of+human+Th17+cells+in+tumor+immunity.">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/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=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.">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. 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S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=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?.">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. 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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, ...

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 ap...

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

Universidad de Cartagena UDEC

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

Multi-photon Imaging of Tumor Cell Invasion in an Orthotopic Mouse Model of Oral Squamous Cell Carcinoma

Loco-regional invasion of head and neck cancer is linked to metastatic risk and presents a difficult challenge in designing and implementing patient management strategies. Orthotopic mouse models of oral cancer have been developed to facilitate the study of factors that impact invasion and serve as model system for evaluating anti-tumor therapeutics. In these systems, visualization of disseminated tumor cells within oral cavity tissues has typically been conducted by either conventional histology or with in vivo bioluminescent methods. A primary drawback of these techniques is the inherent inability to accurately visualize and quantify early tumor cell invasion arising from the primary site in three dimensions. Here we describe a protocol that combines an established model for squamous cell carcinoma of the tongue (SCOT) with two-photon imaging to allow multi-vectorial visualization of lingual tumor spread. The OSC-19 head and neck tumor cell line was stably engineered to express the F-actin binding peptide LifeAct fused to the mCherry fluorescent protein (LifeAct-mCherry). Fox1nu/nu mice injected with these cells reliably form tumors that allow the tongue to be visualized by ex-vivo application of two-photon microscopy. This technique allows for the orthotopic visualization of the tumor mass and locally invading cells in excised tongues without disruption of the regional tumor microenvironment. In addition, this system allows for the quantification of tumor cell invasion by calculating distances that invaded cells move from the primary tumor site. Overall this procedure provides an enhanced model system for analyzing factors that contribute to SCOT invasion and therapeutic treatments tailored to prevent local invasion and distant metastatic spread. This method also has the potential to be ultimately combined with other imaging modalities in an in vivo setting.

A comprehensive overview of the techniques involved in generating a mouse model of oral cancer and quantitative monitoring of tumor invasion within the tongue through multi-photon microscopy of labeled cells is presented. This system can serve as a useful platform for the molecular assessment and drug efficacy of anti-invasive compounds.

Loco-regional invasion of head and neck cancer is linked to metastatic risk and presents a difficult challenge in designing and implementing patient ...

Medicine

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. 
Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.
We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.
To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of ...

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 ...

Chromogenic In Situ Hybridization as a Tool for HPV-Related Head and Neck Cancer Diagnosis

Human papillomavirus (HPV) infection is a major risk factor for a subtype of oropharyngeal squamous cell carcinoma (OPSCC), which tends to be associated with a better outcome than alcohol- and tobacco-related OPSCC. Chromogenic in situ hybridization (CISH) of HPV viral RNA could allow the semiquantitative evaluation of viral transcripts of the oncogenic proteins E6 and E7 and an in situ visualization with a good spatial resolution. This technique allows the diagnosis of an active infection with the visualization of HPV transcription in the tumoral HPV-infected cells. An advantage of this technique is the avoidance of contamination from nonneoplastic HPV-infected cells adjacent to the tumor. Overall, its good diagnosis performances have it considered to be the gold standard for active HPV infection identification. Since E6 and E7 viral protein interaction with cell proteins pRb and p53 is mandatory for cell transformation, HPV RNA CISH is functionally relevant and acutely reflects active oncogenic HPV infection. This technique is clinically relevant as well since &#34;low&#34; or &#34;high&#34; HPV transcription levels helped the identification of two prognosis groups among HPV-related p16-positive head and neck cancer patients. Here we present the protocol for manual HPV RNA CISH performed on formalin-fixed paraffin-embedded (FFPE) slides with a kit obtained from the manufacturer. Instead of chromogenic revelation, RNA in situ hybridization may also be performed with fluorescent revelation (RNA FISH). It may also be combined with conventional immunostaining.

Human papillomavirus (HPV) RNA chromogenic in situ hybridization is considered to be one of the gold standards for active human papillomavirus infection detection within tumors. It allows the visualization of HPV E6-E7 mRNA expression with localization and semiquantitative evaluation of its signal.

Human papillomavirus (HPV) infection is a major risk factor for a subtype of oropharyngeal squamous cell carcinoma (OPSCC), which tends to be associated ...

Genetics

Expanding the Comprehension of the Tumor Microenvironment using Mass Spectrometry Imaging of Formalin-Fixed and Paraffin-Embedded Tissue Samples

Advances in immune-based therapies have revolutionized cancer treatment and research. This has triggered growing demand for the characterization of the tumor immune landscape. Although standard immunohistochemistry is suitable for studying tissue architecture, it is limited to the analysis of a small number of markers. Conversely, techniques such as flow cytometry can evaluate multiple markers simultaneously, although information about tissue morphology is lost. In recent years, multiplexed strategies that integrate phenotypic and spatial analysis have emerged as comprehensive approaches to the characterization of the tumor immune landscape. Herein, we discuss an innovative technology combining metal-labeled antibodies and secondary ion mass spectrometry focusing on the technical steps in assay development and optimization, tissue preparation, and image acquisition and processing. Before staining, a metal-labeled antibody panel must be developed and optimized. This hi-plex image system supports up to 40 metal-tagged antibodies in a single tissue section. Of note, the risk of signal interference increases with the number of markers included in the panel. After panel design, particular attention should be given to the metal isotope assignment to the antibody to minimize this interference. Preliminary panel testing is performed using a small subset of antibodies and subsequent testing of the entire panel in control tissues. Formalin-fixed, paraffin-embedded tissue sections are obtained and mounted on gold-coated slides and further stained. The staining takes 2 days and closely resembles standard immunohistochemical staining. Once samples are stained, they are placed in the image acquisition instrument. Fields of view are selected, and images are acquired, uploaded, and stored. The final stage is image preparation for the filtering and removal of interference using the system&#39;s image processing software. A disadvantage of this platform is the lack of analytical software. However, the images generated are supported by different computational pathology software.

In the era of cancer immunotherapy, interest in elucidating tumor microenvironment dynamics has increased strikingly. This protocol details a mass spectrometry imaging technique with respect to its staining and imaging steps, which allow for highly multiplexed spatial analysis.

Advances in immune-based therapies have revolutionized cancer treatment and research. This has triggered growing demand for the characterization of the ...

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 ...

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 ...