The authors acknowledge Don Norwood from Editing Services, Research Medical Library at MD Anderson for editing this article and the Multiplex Immunofluorescence and Image Analysis Laboratory at the Department of Translational Molecular Pathology at MD Anderson. This publication resulted in part from research facilitated by the scientific and financial support for the Cancer Immune Monitoring and Analysis Centers-Cancer Immunologic Data Commons Network (CIMAC-CIDC) provided through the National Cancer Institute (NCI) Cooperative Agreement (U24CA224285) to The University of Texas MD Anderson Cancer Center Cancer Immune Monitoring and Analysis Center (CIMAC).

Tissue samples were obtained for research purposes in accordance with the Institutional Review Board of The University of Texas MD Anderson Cancer Center, and samples were further de-identified.
1. Antibody selection
<ol>
	<li>Define the research questions to choose the best available antibody clones. Use the Human Protein Atlas, published research, and antibody manufacturer websites as research resources. 
	NOTE: The selection of adequate human tissue controls and the same human tissue controls to be stained in the different steps is critical to make sure that the markers are stained correctly, in the right place, and in the correct cellular compartment. A small tissue microarray (TMA) including normal tissue and neoplastic tissues is always recommended for staining validation.</li>
	<li>Use only carrier-free antibodies to design the panel. 
	NOTE: The use of carrier-free antibody formulations is required if a commercial carrier-free antibody is not available; purification kits can be used to adjust the antibody to the correct formulation. Protein additives such as bovine serum albumin are known to diminish conjugation capacity.</li>
	<li>Test and titrate each antibody using standard chromogenic immunohistochemistry to determine the subcellular pattern of a marker&#39;s expression; membrane, cytoplasmic, or nuclear staining; and expression in specific cells in control tissues. 
	NOTE: However, each antibody must be tested in pH 6 citrate and pH 9 ethylenediaminetetraacetic acid (EDTA), and whether the panel will be stained with pH 6 citrate or pH 9 EDTA must be determined. The use of pH 9 EDTA is recommended to obtain good signals, especially when working with this methodology.</li>
	<li>Choose the optimal staining concentration according to the pattern of expression in positive controls.</li>
	<li>Assign each antibody to one of the available metal isotopes according to the immunohistochemical marker abundance, subcellular localization, and cellular co-expression with the other targets.</li>
	<li>Stain the antibody with the corresponding assigned metal and compare with the expression in the same control tissue used previously. 
	NOTE: Antibody metal conjugation starts with antibody preparation, reduction, and subsequent conjugation (Supplementary File 1). Each metal-loaded polymer tube is sufficient for labeling 100 &#181;g of an antibody.</li>
</ol>
2. Antibody panel design
<ol>
	<li>Create small batches of antibody staining. Test up to five markers in a cocktail. 
	NOTE: Testing antibodies already conjugated and analyzed using immunohistochemistry in batches facilitates the early identification of channel interferences and provides the opportunity to reconjugate the antibodies with another metal. It also provides an opportunity to evaluate adequate marker co-expression.</li>
	<li>Stain each small batch with four different antibody concentrations (0.05 &#181;g/mL, 0.2 &#181;g/mL, 1 &#181;g/mL, and 4.0 &#181;g/mL). 
	NOTE: Comparing different titers, identify the antibody concentration that results in the correct location and highest expression with minimum background staining (best signal-to-noise ratio).</li>
</ol>
3. FFPE tissue sectioning
<ol>
	<li>Select gold-coated slides (specific for this purpose) and keep them close to the microtome. Prepare the microtome by inserting a new blade into the holder. Set the section thickness to 4-5 &#956;m.</li>
	<li>Put FFPE blocks on ice before sectioning. Prepare a tissue floatation bath by heating distilled water or deionized water (diH2O) to 40-45 &#176;C. 
	NOTE: Using diH2O or distilled water reduces the possibility of contamination.</li>
	<li>Start sectioning. Place the tissue section in the water using tweezers and let it flatten. Use the slides to remove tissue sections from the water.</li>
	<li>Place the slides in a slide rack and let them dry at room temperature overnight.</li>
</ol>
4. FFPE antibody staining
NOTE: The staining process takes place on two separate days.
CAUTION: The solutions employed in this protocol are potentially corrosive and represent hazards to the skin and eyes. Wearing gloves, a lab coat, and protective eye and face equipment is advised and part of our institution&#39;s biosafety policy.
<ol>
	<li>Reagent preparation (day 1)
	<ol>
		<li>Dilute 50 mL of 20x Tris-buffered saline with Tween (TBS-T) into 950 mL of diH2O to make 1 L of TBS-T.</li>
		<li>Dilute 8 mL of 10x Tris-ethylenediaminetetraacetic acid (EDTA) into 72 mL of diH2O to make a 1x heat-induced epitope retrieval (HIER) solution.</li>
		<li>Dilute donkey serum in 1x TBS-T to a final concentration of 5% to make blocking buffer. Store the solution at 4 &#176;C until ready to use.</li>
	</ol>
	</li>
	<li>HIER preparation: Pretreatment (PT) module 
	CAUTION: Wear chemical protective gloves when handling any reagents or parts immersed in any reagents used in the PT module.
	<ol>
		<li>Dilute 140 mL of 10x phosphate-buffered saline (PBS) into 1,260 mL of diH2O to make 1.4 L of 1x PBS. Alternatively, dilute seven PBS tablets into 1.4 L of diH2O.</li>
		<li>Fill a tank with 1.4 L of PBS and place the prepared slide chamber container with 100 mL of 1x HIER solution into the tank.</li>
		<li>Preheat the tank in a PT module to 75 &#176;C.</li>
	</ol>
	</li>
	<li>Excess paraffin removal
	<ol>
		<li>Bake slides at 70 &#176;C in an oven for at least 20 min. 
		NOTE: Some tissues or sections may need longer baking times. The recommended baking time for brain tissue or a TMA is 1 h. This can be extended to 16 h (overnight) or according to lab experience.</li>
		<li>Place baked slides in a slide holder and perform the following washing steps on a shaker under a fume hood. Wash the slides in the following solution: Xylene 2x for 30 s (metal-free), 100% alcohol 2x for 30 s (metal-free), 95% alcohol 2x for 30 s (metal-free), 80% alcohol for 30 s (metal-free), 70% alcohol for 30 s (metal-free), and diH2O 2x for 30 s (metal-free).</li>
		<li>Keep the slides in a fresh diH2O container until ready for antigen retrieval. 
		NOTE: The slides should not be dried until the end of the procedure.</li>
	</ol>
	</li>
	<li>Antigen retrieval
	<ol>
		<li>Place the slides in a preheated slide chamber containing 1x HIER buffer inside the PT module. Place the cover on the tank. Close and latch the lid.</li>
		<li>Press the Menu button on the PT module to open the main menu and press the Setup cycle (time and temperature) button to create a custom program.</li>
		<li>Run the PT module at 97 &#176;C for 40 min. Afterward, the PT module will automatically cool to 65 &#176;C.</li>
		<li>Remove the slides from the PT module once the 65 &#176;C temperature is reached. Keep the slides at room temperature for 30 min. 
		NOTE: The PT module will not open until the temperature cools to 65 &#176;C. Do not touch the golden surface of the slides during this process, and always use gloves.</li>
	</ol>
	</li>
	<li>Antibody blocking
	<ol>
		<li>Set a shaker to 70 rpm.</li>
		<li>Wash the slides by dipping them in 1x TBS-T for 5 min 2x.</li>
		<li>Using a hydrophobic barrier pen, draw a border around the tissue section at least 1 mm away from the slide edges and let it dry for 15-30 s. 
		NOTE: Take care to prevent the pen fluid from touching the tissue section to avoid any tissue interference with the staining. Do not press the pen down too hard while drawing the barrier to avoid potential leaks. For optimal staining and image acquisition results, the tissue sections are placed in the middle of the gold-coated slides in a frame no larger than 15 mm x 30 mm to allow enough space to draw the barrier without touching the tissue or the guide dots placed on the outer edge of the slide.</li>
		<li>To remove any pen residue, dip the slides in TBS-T.</li>
		<li>In a moisture chamber at room temperature, incubate the tissue section with 100-200 &#956;L of blocking buffer for 20 min. Leave the tissue incubating in the blocking buffer until an antibody master mix is ready.</li>
	</ol>
	</li>
	<li>Antibody panel preparation 
	NOTE: The final volume of the antibody panel cocktail varies according to the estimated tissue section surface area. To cover an area of 20 mm x 20 mm, prepare 100-200 &#956;L of the cocktail. 
	Do the following to prepare an antibody panel cocktail of metal isotope-conjugated antibodies:
	<ol>
		<li>Confirm the final volume of the cocktail that equals the antibody cocktail volume added to the blocking buffer volume.</li>
		<li>Confirm the specifications for all antibodies, dilutions, and/or antibody concentrations in a panel spreadsheet for the project.</li>
		<li>Spin down all the antibody-containing tubes at 10,000 x g for 5 min. Add individual antibodies to the blocking buffer and mix very well. Do not disturb the bottom of the antibody tube when pipetting it.</li>
		<li>Filter the antibody panel by prewetting a 0.1 &#956;m centrifugal filter device with 100 &#956;L of blocking buffer. Spin the filter at 10,000 x g for 2 min and remove the blocking buffer flow-through with a pipette.</li>
		<li>Transfer the antibody panel into a spin column and spin the filter at 10,000 x g for 2 min. Discard the spin column and use the flow-through as the filtered antibody panel. 
		NOTE: Perform the staining immediately after making the cocktail to prevent metal exchange. If storage of the antibody cocktail for an extended time is needed, it can be subjected to lyophilization.</li>
	</ol>
	</li>
	<li>Antibody staining
	<ol>
		<li>Carefully remove the blocking buffer from the slides by tipping each slide on its side and gently tapping the edges against a task wiper.</li>
		<li>Place the slides in a moisture chamber and add 100-200 &#956;L of antibody master mix to the tissue (avoid contact with tissue and the creation of air bubbles).</li>
		<li>Add positive and negative control slides to the staining batch.</li>
		<li>Incubate the slides at 4 &#176;C overnight (14-16 h).</li>
	</ol>
	</li>
	<li>Reagent preparation (day 2)
	<ol>
		<li>Dilute 100 mL of 10x low-barium PBS, pH 7.4, in 900 mL of diH2O to make 1x PBS.</li>
		<li>Prepare 350 mL of a working stock solution of 2% glutaraldehyde in low-barium PBS (340 mL of low-barium PBS + 10 mL of 70% glutaraldehyde). 
		NOTE: Perform the dilution under a hood. Glutaraldehyde is a very viscous liquid. Use a 1 mL pipette and add 1 mL of low-barium PBS to the glutaraldehyde tube every time until it becomes liquid enough to pour out of the tube.</li>
		<li>Dilute 10x Tris, pH 8.5, in 900 mL of diH20 to make 1x Tris.</li>
	</ol>
	</li>
	<li>Fixation and dehydration
	<ol>
		<li>Remove the antibody master mix from each slide by tipping the slide on its side and gently tapping the edge against a task wiper.</li>
		<li>Wash the slides with light to moderate agitation in the following buffers: 1x TBS-T, 3x times for 5 min each (metal-free); filtered 2% glutaraldehyde for 5 min; filtered 1x tris, pH 8.5, 3x for 30 s; filtered diH2O 2x for 30 s; 70% alcohol for 30 s (metal-free); 80% alcohol for 30 s (metal-free); 95% alcohol for 30 s (metal-free); and 100% alcohol for 30 s (metal-free).</li>
		<li>Gently tap the edge of each slide against a task wiper to remove excess alcohol and allow residual alcohol to evaporate at room temperature (~5-10 min).</li>
		<li>Dry slides in a desiccator for at least 1 h prior to image acquisition or keep the slides in a vacuum chamber for long-term storage.</li>
	</ol>
	</li>
</ol>
5. Image acquisition
<ol>
	<li>Slide setup 
	NOTE: Before scanning using the instrument, the slides must be defined and set up using the web-based image management application following the steps described below.
	<ol>
		<li>On the slide page in the web-based image management application, click Accession New Slide and enter the desired details (name, slide identification, location, and description).</li>
		<li>Create scanning sections by clicking Add Section. Fill in the information for each section (name of the project, slide name, block, and position). To save the new slides/sections created, click Submit.</li>
		<li>Under the resources tab, open the panels page and select the panel to be used. For new panels, click Create New Panel.</li>
		<li>After selecting the panel, click on Sections. Add the sections created in step 2. by clicking Edit Section Assignment. Save by clicking Submit.</li>
	</ol>
	</li>
	<li>Instrument setup 
	NOTE: This instrument (see Table of Materials) is operated using a specific control software program (see Table of Materials).
	<ol>
		<li>Log in to the control software. Click Wake Up if the instrument is in sleep mode. 
		NOTE: At least 1 h before the operation, warming up the instrument is recommended, which helps with beam focus stabilization.</li>
		<li>To load a slide, click on Exchange Sample and then click Continue to open the door. Put the slide in the loading slot with the sample facing up and the label on the right. Click Continue to close the door. 
		NOTE: If the slide is not loaded correctly, a warning sound and notification to adjust the slide will appear.</li>
		<li>Select the project and then select the slide name for the loaded sample.</li>
		<li>Visualize the panoramic image on the slide optical image pane.</li>
	</ol>
	</li>
	<li>Field of view (FOV) selection and acquisition
	<ol>
		<li>Click on the Mode&#160;menu and select SED (Secondary Electron Detector). Click on the imaging mode menu and pick QC &#8722;300 &#956;m.</li>
		<li>Click on Jog Stage to control the FOV location and then click on the arrows to navigate and select the position of the FOV.</li>
		<li>Click Add FOV, set 400 &#956;m x 400 &#956;m as the field size, and select fine as the imaging mode and 1 ms of dwell time. Click Confirm. 
		NOTE: The set dwell time will depend on the desired resolution. The dwell time increases as the resolution increases. The acquisition time may vary depending on multiple factors, including detector break-in period and length of operation. Our mean acquisition time for one FOV is about 17 min. Use the instrument nonstop for up to 8 h, which allows for scanning of about 28 FOVs. The quality of the acquired images decreases after many consecutive hours of use.</li>
		<li>After creating an FOV list, proceed to image focus and adjust the stigmation by moving the beam to a tissue region that will not be imaged. Adjust the parameters until a clear central image is obtained. 
		NOTE: To optimize image acquisition, keeping the tissue section centralized on the slide is ideal. While focusing, a clear image of only the central area can be obtained. If the tissue section is too large, the edges will be out of focus, and the image will be blurred.</li>
		<li>Click on Start Run. Acquired images will be automatically uploaded and stored in the web-based image management application.</li>
	</ol>
	</li>
</ol>
6. Image preparation
<ol>
	<li>Image isobaric correction 
	NOTE: The purpose of isobaric correction is to remove spillover signal between channels resulting from the presence of isotopes of equal or very similar mass whose differences in mass cannot be detected using the mass analyzer.
	<ol>
		<li>In the web-based image management application, click on the green Download icon to save the FOVs (TIFF images).</li>
		<li>Download the most updated version of the image processing software (see Table of Materials) available on the about tab in the web-based image management application and save it in a file. Open the .zip archive file and follow the installation steps. Open the software once the installation is complete.</li>
		<li>Select the folder containing the images to be corrected by clicking on the File icon on the input pane of the image processing software. An FOV list will be loaded.</li>
		<li>Click on the Filter icon on the input pane to apply default corrections. For each channel, visualize images obtained before and after correction on the right side of the screen.</li>
		<li>Click on the Floppy disk icon on the output pane to save the corrected image.</li>
	</ol>
	</li>
	<li>Image filtering: Voronoi tessellation 
	NOTE: Voronoi tessellation diagrams illustrate a partition of space containing seed points into Voronoi cells. The aim is to estimate the cell density and define cell boundaries. Using the Voronoi tessellation calculation, a mask is generated and applied to the original image for filtering.
	<ol>
		<li>Click on the Filtering tab and select Voronoi Tesselation on the filtering parameters menu.</li>
		<li>On the input pane, select the MassCorrected.tiff image. Click on the Filter icon on the input pane.</li>
		<li>Click on the Floppy disk icon on the output pane to save the filtered image. The two resulting files will have the suffixes -Filtered.tiff and -Filtered.json. 
		NOTE: The image named MassCorrected-Filtered.tiff then can be uploaded to a third-party digital analysis software program or open-source software program.</li>
	</ol>
	</li>
</ol>

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The authors have no conflicts to disclose.

The comprehensive elucidation of the complex, intricate interactions among the multiple components of a TME remains a pivotal objective of cancer research. Manufacturers have introduced numerous multiplexed assays as part of this effort, especially over the past 5 years. Multiplexed spatial analysis is a versatile and powerful tool that facilitates the simultaneous categorization of several targets while preserving structural morphology in tumor samples. Spatial analysis techniques can be performed using fluorescence ima...

The importance of the numerous cell types surrounding clonal tumor populations is a crucial element in the categorization of carcinogenesis. Interest in elucidating this tumor microenvironment (TME) composition and interactions has risen continuously following the establishment of immune-based therapy as part of the cancer treatment arsenal. Therefore, treatment strategies have shifted from a tumor-centric approach to a TME-centric one1.
Efforts to elucidate the roles of immune cells in tumor surveillance and cancer development have increased strikingly in recent years2,3. In medical research, a plethora of methods, including cytometry-based methods and singleplex and multiplex imaging technologies, arose as part of this attempt to decipher the unique interactions of multiple elements of TMEs.
Pioneering methods such as flow cytometry (invented in the 1960s), fluorescence-activated cell sorting, and mass cytometry are focused mainly on identifying and quantifying TME components4. Even though cytometry-based quantitative techniques allow for immune landscape phenotyping, determining the cellular spatial distribution is impossible. Conversely, methods such as standard singleplex immunohistochemistry preserve the tissue architecture and enable researchers to analyze cellular distribution, though a reduced number of targets in a single tissue section is a limitation of these methods5,6. Over the past several years, multiplexed imaging technologies for single-cell resolution such as multiplex immunofluorescence, barcoding fluorescence imaging, and imaging mass spectrometry have emerged as comprehensive strategies for acquiring information on simultaneous marker staining using the same tissue section7.
Here we present a technology that couples metal tagged antibodies and secondary ion mass spectrometry and enables single-cell resolution quantification, marker co-expression (phenotyping), and spatial analysis using formalin-fixed, paraffin-embedded (FFPE), and fresh frozen (FF) tissue samples8,9. FFPE samples are the most widely used materials for tissue archiving samples and represent a more readily available resource for multiplexed imaging technologies than fresh frozen samples10. Additionally, this technology offers the possibility of reacquiring images months after. Herein, we discuss our staining and image processing protocols using FFPE tissue samples.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>100% Reagent Alcohol</td>
			<td>Sigma-Aldrich</td>
			<td>R8382</td>
			<td></td>
		</tr>
		<tr>
			<td>95% Reagent Alcohol</td>
			<td>Sigma-Aldrich</td>
			<td>R3404</td>
			<td></td>
		</tr>
		<tr>
			<td>80% Reagent Alcohol</td>
			<td>Sigma-Aldrich</td>
			<td>R3279</td>
			<td></td>
		</tr>
		<tr>
			<td>70% Reagent Alcohol</td>
			<td>Sigma-Aldrich</td>
			<td>R315</td>
			<td></td>
		</tr>
		<tr>
			<td>20X TBS-T</td>
			<td>Ionpath</td>
			<td>567005</td>
			<td></td>
		</tr>
		<tr>
			<td>10X Low-Barium PBS pH 7.4</td>
			<td>Ionpath</td>
			<td>567004</td>
			<td></td>
		</tr>
		<tr>
			<td>10X Tris pH 8.5&#160;</td>
			<td>Ionpath</td>
			<td>567003</td>
			<td></td>
		</tr>
		<tr>
			<td>4&#176;C Refrigerator</td>
			<td>ThermoScientific</td>
			<td>REVCO</td>
			<td></td>
		</tr>
		<tr>
			<td>Aerosol Barrier Pipette Tips P10</td>
			<td>Olympus</td>
			<td>24-401</td>
			<td></td>
		</tr>
		<tr>
			<td>Aerosol Barrier Pipette Tips P20</td>
			<td>Olympus</td>
			<td>24-404</td>
			<td></td>
		</tr>
		<tr>
			<td>Aerosol Barrier Pipette Tips P200</td>
			<td>Olympus</td>
			<td>24-412</td>
			<td></td>
		</tr>
		<tr>
			<td>Aerosol Barrier Pipette Tips P1000</td>
			<td>Olympus</td>
			<td>24-430</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifugal Filter Ultrafree-MC</td>
			<td>Fisher Scientific</td>
			<td>UFC30VV00</td>
			<td></td>
		</tr>
		<tr>
			<td>Deionized H2O</td>
			<td>Ionpath</td>
			<td>567002</td>
			<td></td>
		</tr>
		<tr>
			<td>Donkey serum</td>
			<td>Sigma-Aldrich</td>
			<td>D9663</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyDip Slide Staining Jar, Green</td>
			<td>Electron Microscopy Sciences</td>
			<td>71385-G</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyDip Slide Staining Jar, Yellow</td>
			<td>Electron Microscopy Sciences</td>
			<td>71385-Y</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyDip Slide Staining Kit (Jar+Rack), White</td>
			<td>Electron Microscopy Sciences</td>
			<td>71388-01</td>
			<td></td>
		</tr>
		<tr>
			<td>EasyDip Stainless Steel Holder</td>
			<td>Electron Microscopy Sciences</td>
			<td>71388-50</td>
			<td></td>
		</tr>
		<tr>
			<td>Glutaraldehyde 70% EM Grade</td>
			<td>Electron Microscopy Sciences</td>
			<td>16360</td>
			<td></td>
		</tr>
		<tr>
			<td>Heat Induced Epitope Retrieval (HIER) buffer: 10X Tris with EDTA, pH 9</td>
			<td>Dako</td>
			<td>S2367</td>
			<td></td>
		</tr>
		<tr>
			<td>Heat resistant slide chamber</td>
			<td>Electron Microscopy Sciences</td>
			<td>62705-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Hydrophobic barrier pen</td>
			<td>Fisher</td>
			<td>50-550-221</td>
			<td></td>
		</tr>
		<tr>
			<td>MIBI/O software</td>
			<td>Ionpath</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIcontrol software</td>
			<td>Ionpath</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIslide</td>
			<td>Ionpath</td>
			<td>567001</td>
			<td></td>
		</tr>
		<tr>
			<td>MIBIscope</td>
			<td>Ionpath</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge</td>
			<td>Eppendorf</td>
			<td>5415D</td>
			<td></td>
		</tr>
		<tr>
			<td>Microtome</td>
			<td>Leica</td>
			<td>RM2135</td>
			<td></td>
		</tr>
		<tr>
			<td>Moisture Chamber (Humid Chamber)</td>
			<td>Simport</td>
			<td>M922-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS) Tablets</td>
			<td>Fisher Scientific</td>
			<td>BP2944100</td>
			<td></td>
		</tr>
		<tr>
			<td>PT Module</td>
			<td>Thermo Scientific</td>
			<td>A80400012</td>
			<td></td>
		</tr>
		<tr>
			<td>Rapid-Flow Sterile Disposable Filter Units</td>
			<td>Fisher Scientific</td>
			<td>097403A</td>
			<td></td>
		</tr>
		<tr>
			<td>Shaker</td>
			<td>BioRocker</td>
			<td>S2025</td>
			<td></td>
		</tr>
		<tr>
			<td>Spin column (Ultrafree-MC Spin Filter, 0.5mL 0.1&#956;m )</td>
			<td>MillQ</td>
			<td>UFC30VV00</td>
			<td></td>
		</tr>
		<tr>
			<td>Slide oven</td>
			<td>Fisher Scientific</td>
			<td>6901</td>
			<td></td>
		</tr>
		<tr>
			<td>Vaccum Cabinet Desiccator</td>
			<td>VWR</td>
			<td>30621-076</td>
			<td></td>
		</tr>
		<tr>
			<td>Task-whipe</td>
			<td>Kimberly Clark</td>
			<td>34155</td>
			<td></td>
		</tr>
		<tr>
			<td>Xylene</td>
			<td>Sigma-Aldrich</td>
			<td>534056-4L</td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

Tonsil and lung adenocarcinoma TMA tissue sections (5 mm thick) were obtained and placed on the middle of gold-coated slides following the specifications regarding tissue size and secure margins of the slides. Free glass margins of 5 mm and 10 mm between the edge of the tissue and the lateral and inferior borders of the glass slides, respectively, are necessary for optimal staining. The tissue sections were baked overnight in an oven prior to staining to assure proper adherence of the section to the slide. The antibody p...

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

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 ...

expanding-comprehension-tumor-microenvironment-using-mass

Research

JoVE Journal

Cancer Research

2.1K Views.  The University of Texas MD Anderson Cancer Center. 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.

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

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.

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 ...

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome

Human pituitary adenoma (PA) is a common tumor that occurs in the human pituitary gland in the hypothalamus-pituitary-targeted organ axis systems, and may be classified as either clinically functional or nonfunctional PA (FPA and NFPA). NFPA is difficult for early stage diagnosis and therapy due to barely elevating hormones in the blood compared to FPA. Our long-term goal is to use proteomics methods to discover reliable biomarkers for clarification of PA molecular mechanisms and recognition of effective diagnostic, prognostic markers and therapeutic targets. Effective two-dimensional gel electrophoresis (2DE) coupled with mass spectrometry (MS) methods were presented here to analyze human PA proteomes, including preparation of samples, 2D gel electrophoresis, protein visualization, image analysis, in-gel trypsin digestion, peptide mass fingerprint (PMF), and tandem mass spectrometry (MS/MS). 2-Dimensional gel electrophoresis matrix-assisted laser desorption/ionization mass spectrometry PMF (2DE-MALDI MS PMF), 2DE-MALDI MS/MS, and 2DE-liquid chromatography (LC) MS/MS procedures have been successfully applied in an analysis of NFPA proteome. With the use of a high-sensitivity mass spectrometer, many proteins were identified with the 2DE-LC-MS/MS method in each 2D gel spot in an analysis of complex PA tissue to maximize the coverage of human PA proteome.

Here, we present a two-dimensional gel electrophoresis (2DE) coupled with mass spectrometry (MS) to separate and identify human pituitary adenoma tissue proteome, which presents a good and reproducible 2DE pattern. Many proteins are observed in each 2DE spot when analyzing complex cancer proteome with the use of high-sensitivity MS.

Human pituitary adenoma (PA) is a common tumor that occurs in the human pituitary gland in the hypothalamus-pituitary-targeted organ axis systems, and may ...

Elastic Staining on Paraffin-embedded Slides of pT3N0M0 Gastric Cancer Tissue

The elastic lamina, which is usually located in the sub-mesothelial layer, adjacent to the peritoneum mesothelial cells, is amphiphilic on hematoxylin and eosin (H&amp;E) staining but can be visualized through elastic staining. One of the important benefits of elastic staining is that it makes it easy to determine whether tumor cells have invaded beyond the elastic lamina. This helps in examining the extent of peritoneal surface invasion, thereby distinguishing the pT3 and pT4 stages in gastrointestinal cancer. In this study, we present a protocol to identify elastic fibers in the formalin-fixed, paraffin-embedded pT3N0M0 gastric cancer tissue sections. We prepare 5-&#181;m paraffin sections fixed on slides, and then all the slides are deparaffinated and rehydrated during the staining procedure. Subsequently, all the sections are oxidized by potassium permanganate, bleached by oxalic acid, stained by elastic staining, and counterstained by Van Gieson's. Finally, we examine the effect of staining; elastic lamina is stained blue-black and collagen fibers are stained red, while the cancer cells are stained in varying shades of yellow. We also describe in detail the methods used for determining the positional relationship between cancer cells and elastic lamina. This method is simple, low-cost, and widely applicable in the identification of peritoneal surface invasion in gastrointestinal cancer because of its outstanding selectivity for elastic fibers and authentic results.

Here, we present a protocol of elastic staining to identify elastic fibers in pT3N0M0 gastric cancer tissues on formalin-fixed, paraffin-embedded sections. Subsequently, we describe a method to determine whether tumor cells invade beyond the elastic lamina.

The elastic lamina, which is usually located in the sub-mesothelial layer, adjacent to the peritoneum mesothelial cells, is amphiphilic on hematoxylin and ...

Measuring Bone Remodeling and Recreating the Tumor-Bone Microenvironment Using Calvaria Co-culture and Histomorphometry

Bone is a connective tissue constituted of osteoblasts, osteocytes, and osteoclasts and a mineralized extracellular matrix, which gives it its strength and flexibility and allows it to fulfill its functions. Bone is continuously exposed to a variety of stimuli, which in pathological conditions can deregulate bone remodeling. To study bone biology and diseases and evaluate potential therapeutic agents, it has been necessary to develop in vitro and in vivo models.
This manuscript describes the dissection process and culture conditions of calvarias isolated from neonatal mice to study bone formation and the bone tumor microenvironment. In contrast to in vitro and in vivo models, this ex vivo model allows preservation of the three-dimensional environment of the tissue as well as the cellular diversity of the bone while culturing under defined conditions to simulate the desired microenvironment. Therefore, it is possible to investigate bone remodeling and its mechanisms, as well as the interactions with other cell types, such as the interactions between cancer cells and bone.
The assays reported here use calvarias from 5-7 day old BALB/C mice. The hemi-calvarias obtained are cultured in the presence of insulin, breast cancer cells (MDA-MB-231), or conditioned medium from breast cancer cell cultures. After analysis, it was established that insulin induced new bone formation, while cancer cells and their conditioned medium induced bone resorption. The calvarial model has been successfully used in basic and applied research to study bone development and cancer-induced bone diseases. Overall, it is an excellent option for an easy, informative, and low-cost assay.

The ex vivo culture of bone explants can be a valuable tool for the study of bone physiology and the potential evaluation of drugs in bone remodeling and bone diseases. The presented protocol describes the preparation and culture of calvarias isolated from newborn mice skulls, as well as its applications.

Bone is a connective tissue constituted of osteoblasts, osteocytes, and osteoclasts and a mineralized extracellular matrix, which gives it its strength ...

Capturing Small Molecule Communication Between Tissues and Cells Using Imaging Mass Spectrometry

Imaging mass spectrometry (IMS) has routinely been applied to three types of samples: tissue sections, spheroids, and microbial colonies. These sample types have been analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to visualize the distribution of proteins, lipids, and metabolites across the biological sample of interest. We have developed a novel sample preparation method that combines the strengths of the three previous applications to address an underexplored approach for identifying chemical communication in cancer, by seeding mammalian cell cultures into agarose in coculture with healthy tissues followed by desiccation of the sample. Mammalian tissue and cells are cocultured in close proximity allowing chemical communication via diffusion between the tissue and cells. At specific time points, the agarose-based sample is dried in the same manner as microbial colonies prepared for IMS analysis. Our method was developed to model the communication between high grade serous ovarian cancer derived from the fallopian tube as it interacts with the ovary during metastasis. Optimization of the sample preparation resulted in the identification of norepinephrine as a key chemical component in the ovarian microenvironment. This newly developed method can be applied to other biological systems that require an understanding of chemical communication between adjacent cells or tissues.

A novel method of sample preparation was developed to accommodate cell and tissue coculture to detect small molecule exchange using imaging mass spectrometry.

Imaging mass spectrometry (IMS) has routinely been applied to three types of samples: tissue sections, spheroids, and microbial colonies. These sample ...

Assessing Tumor Microenvironment of Metastasis Doorway-Mediated Vascular Permeability Associated with Cancer Cell Dissemination using Intravital Imaging and Fixed Tissue Analysis

The most common cause of cancer related mortality is metastasis, a process that requires dissemination of cancer cells from the primary tumor to secondary sites. Recently, we established that cancer cell dissemination in primary breast cancer and at metastatic sites in the lung occurs only at doorways called Tumor MicroEnvironment of Metastasis (TMEM). TMEM doorway number is prognostic for distant recurrence of metastatic disease in breast cancer patients. TMEM doorways are composed of a cancer cell which over-expresses the actin regulatory protein Mena in direct contact with a perivascular, proangiogenic macrophage which expresses high levels of TIE2 and VEGF, where both of these cells are tightly bound to a blood vessel endothelial cell. Cancer cells can intravasate through TMEM doorways due to transient vascular permeability orchestrated by the joint activity of the TMEM-associated macrophage and the TMEM-associated Mena-expressing cancer cell. In this manuscript, we describe two methods for assessment of TMEM-mediated transient vascular permeability: intravital imaging and fixed tissue immunofluorescence. Although both methods have their advantages and disadvantages, combining the two may provide the most complete analyses of TMEM-mediated vascular permeability as well as microenvironmental prerequisites for TMEM function. Since the metastatic process in breast cancer, and possibly other types of cancer, involves cancer cell dissemination via TMEM doorways, it is essential to employ well established methods for the analysis of the TMEM doorway activity. The two methods described here provide a comprehensive approach to the analysis of TMEM doorway activity, either in na&#239;ve or pharmacologically treated animals, which is of paramount importance for pre-clinical trials of agents that prevent cancer cell dissemination via TMEM.

We describe two methods for assessing transient vascular permeability associated with tumor microenvironment of metastasis (TMEM) doorway function and cancer cell intravasation using intravenous injection of high-molecular weight (155 kDa) dextran in mice. The methods include intravital imaging in live animals and fixed tissue analysis using immunofluorescence.

The most common cause of cancer related mortality is metastasis, a process that requires dissemination of cancer cells from the primary tumor to secondary ...

Isolation of Proximal Fluids to Investigate the Tumor Microenvironment of Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death, and soon to become the second. There is an urgent need of variables associated to specific pancreatic pathologies to help preoperative differential diagnosis and patient profiling. Pancreatic juice is a relatively unexplored body fluid, which, due to its close proximity to the tumor site, reflects changes in the surrounding tissue. Here we describe in detail the intraoperative collection procedure. Unfortunately, translating pancreatic juice collection to murine models of PDAC, to perform mechanistic studies, is technically very challenging. Tumor interstitial fluid (TIF) is the extracellular fluid, outside blood and plasma, which bathes tumor and stromal cells. Similarly to pancreatic juice, for its property to collect and concentrate molecules that are found diluted in plasma, TIF can be exploited as an indicator of microenvironmental alterations and as a valuable source of disease-associated biomarkers. Since TIF is not readily accessible, various techniques have been proposed for its isolation. We describe here two simple and technically undemanding methods for its isolation: tissue centrifugation and tissue elution.

Pancreatic juice is a precious source of biomarkers for human pancreatic cancer. We describe here a method for intraoperative collection procedure. To overcome the challenge of adopting this procedure in murine models, we suggest an alternative sample, tumor interstitial fluid, and describe here two protocols for its isolation.

Pancreatic adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death, and soon to become the second. There is an urgent need of variables ...

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

The ability to visualize complex and dynamic physiological interactions between numerous cell types and the extracellular matrix (ECM) within a live tumor microenvironment is an important step toward understanding mechanisms that regulate tumor progression. While this can be accomplished through current intravital imaging techniques, it remains challenging due to the heterogeneous nature of tissues and the need for spatial context within the experimental observation. To this end, we have developed an intravital imaging workflow that pairs collagen second harmonic generation imaging, endogenous fluorescence from the metabolic co-factor NAD(P)H, and fluorescence lifetime imaging microscopy (FLIM) as a means to non-invasively compartmentalize the tumor microenvironment into basic domains of the tumor nest, the surrounding stroma or ECM, and the vasculature. This non-invasive protocol details the step-by-step process ranging from the acquisition of time-lapse images of mammary tumor models to post-processing analysis and image segmentation. The primary advantage of this workflow is that it exploits metabolic signatures to contextualize the dynamically changing live tumor microenvironment without the use of exogenous fluorescent labels, making it advantageous for human patient-derived xenograft (PDX) models and future clinical use where extrinsic fluorophores are not readily applicable.

The intravital imaging method described here utilizes collagen second harmonic generation and endogenous fluorescence from the metabolic co-factor NAD(P)H to non-invasively segment an unlabeled tumor microenvironment into tumor, stromal, and vascular compartments for in-depth analysis of 4D intravital images.

The ability to visualize complex and dynamic physiological interactions between numerous cell types and the extracellular matrix (ECM) within a live tumor ...

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&#38;E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.

This protocol describes a high-throughput workflow for artificial intelligence-driven segmentation of pathology-confirmed regions of interest from stained, thin tissue section images for enrichment of histology-resolved cell populations using laser microdissection. This strategy includes a novel algorithm enabling the transfer of demarcations denoting cell populations of interest directly to laser microscopes.

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell ...

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 ...