The PhenoImager HT was purchased through funding provided by the Radboud University Medical Center and Radboud Technology Center for Microscopy. CF is financially supported by a Dutch Cancer Society grant (10673) and ERC Adv grant ARTimmune (834618). JT is financially supported by an NWO Vidi grant (VI.Vidi.192.084). The authors would like to thank Eric van Dinther and Ankur Ankan for their assistance in creating workflows to store multiplex IHC data and Bengt Phung is thanked for instructions on how to implement multiplex IHC data in QuPath for ROI drawing.

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

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<li>van den Brand, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Peptide-mediated+delivery+of+therapeutic+mRNA+in+ovarian+cancer%5BTitle%5D)+AND+%22European+Journal+of+Pharmaceutics+and+Biopharmaceutics%22%5BJournal%5D)">Peptide-mediated delivery of therapeutic mRNA in ovarian cancer.</a> European Journal of Pharmaceutics and Biopharmaceutics. 141, 180-190 (2019).</li>
<li>van den Brand, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((EpCAM-binding+DARPins+for+targeted+photodynamic+therapy+of+ovarian+cancer%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">EpCAM-binding DARPins for targeted photodynamic therapy of ovarian cancer.</a> Cancers. 12 (7), 1762(2020).</li>
<li>Di Blasio, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+tumour+microenvironment+shapes+dendritic+cell+plasticity+in+a+human+organotypic+melanoma+culture%5BTitle%5D)+AND+%22Nature+Communications%22%5BJournal%5D)">The tumour microenvironment shapes dendritic cell plasticity in a human organotypic melanoma culture.</a> Nature Communications. 11 (1), 2749(2020).</li>
<li>van Beek, J. J. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Human+pDCs+are+superior+to+cDC2s+in+attracting+cytolytic+lymphocytes+in+melanoma+patients+receiving+DC+vaccination%5BTitle%5D)+AND+%22Cell+Reports%22%5BJournal%5D)">Human pDCs are superior to cDC2s in attracting cytolytic lymphocytes in melanoma patients receiving DC vaccination.</a> Cell Reports. 30 (4), 1027-1038 (2020).</li>
<li>Rodriguez-Rosales, Y. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immunomodulatory+aged+neutrophils+are+augmented+in+blood+and+skin+of+psoriasis+patients%5BTitle%5D)+AND+%22Journal+of+Allergy+and+Clinical+Immunology%22%5BJournal%5D)">Immunomodulatory aged neutrophils are augmented in blood and skin of psoriasis patients.</a> Journal of Allergy and Clinical Immunology. 148 (4), 1030-1040 (2021).</li>
<li>Hoeijmakers, Y. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immune+cell+composition+in+the+endometrium+of+patients+with+a+complete+molar+pregnancy%3A+Effects+on+outcome%5BTitle%5D)+AND+%22Gynecologic+Oncology%22%5BJournal%5D)">Immune cell composition in the endometrium of patients with a complete molar pregnancy: Effects on outcome.</a> Gynecologic Oncology. 160 (2), 450-456 (2021).</li>
<li>van Ravensteijn, S. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immunological+and+genomic+analysis+reveals+clinically+relevant+distinctions+between+angiosarcoma+subgroups%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Immunological and genomic analysis reveals clinically relevant distinctions between angiosarcoma subgroups.</a> Cancers. 14 (23), 5938(2022).</li>
<li>van der Woude, L. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tumor+microenvironment+shows+an+immunological+abscopal+effect+in+patients+with+NSCLC+treated+with+pembrolizumab-radiotherapy+combination%5BTitle%5D)+AND+%22Journal+for+Immunotherapy+of+Cancer%22%5BJournal%5D)">Tumor microenvironment shows an immunological abscopal effect in patients with NSCLC treated with pembrolizumab-radiotherapy combination.</a> Journal for Immunotherapy of Cancer. 10 (10), e005248(2022).</li>
<li>Graham Martinez, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+immune+microenvironment+landscape+shows+treatment-specific+differences+in+rectal+cancer+patients%5BTitle%5D)+AND+%22Frontiers+in+Immunology%22%5BJournal%5D)">The immune microenvironment landscape shows treatment-specific differences in rectal cancer patients.</a> Frontiers in Immunology. 13, 1011498(2022).</li>
<li>Cortenbach, K. R. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Topography+of+immune+cell+infiltration+in+different+stages+of+coronary+atherosclerosis+revealed+by+multiplex+immunohistochemistry%5BTitle%5D)+AND+%22International+Journal+of+Cardiology.+Heart+%26+Vasculature%22%5BJournal%5D)">Topography of immune cell infiltration in different stages of coronary atherosclerosis revealed by multiplex immunohistochemistry.</a> International Journal of Cardiology. Heart & Vasculature. 44, 101111(2023).</li>
<li>van Wilpe, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Homologous+recombination+repair+deficient+prostate+cancer+represents+an+immunologically+distinct+subtype%5BTitle%5D)+AND+%22Oncoimmunology%22%5BJournal%5D)">Homologous recombination repair deficient prostate cancer represents an immunologically distinct subtype.</a> Oncoimmunology. 11 (1), 2094133(2022).</li>
<li>Gorris, M. A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Paired+primary+and+metastatic+lesions+of+patients+with+ipilimumab-treated+melanoma%3A+high+variation+in+lymphocyte+infiltration+and+HLA-ABC+expression+whereas+tumor+mutational+load+is+similar+and+correlates+with+clinical+outcome%5BTitle%5D)+AND+%22Journal+for+Immunotherapy+of+Cancer%22%5BJournal%5D)">Paired primary and metastatic lesions of patients with ipilimumab-treated melanoma: high variation in lymphocyte infiltration and HLA-ABC expression whereas tumor mutational load is similar and correlates with clinical outcome.</a> Journal for Immunotherapy of Cancer. 10 (5), e004329(2022).</li>
<li>van Wilpe, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Intratumoral+T+cell+depletion+following+neoadjuvant+chemotherapy+in+patients+with+muscle-invasive+bladder+cancer+is+associated+with+poor+clinical+outcome%5BTitle%5D)+AND+%22Cancer+Immunology%2C+Immunotherapy%22%5BJournal%5D)">Intratumoral T cell depletion following neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer is associated with poor clinical outcome.</a> Cancer Immunology, Immunotherapy. 72 (1), 137-149 (2023).</li>
<li>Sultan, S., Gorris, M. A. J., Buytenhuijs, F., Lvan de Woude, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+Segmentation-free+machine+learning+architecture+for+immune+land-scape+phenotyping+in+solid+tumors+by+multichannel+imaging%5BTitle%5D)+AND+%22bioRxiv%22%5BJournal%5D)">A Segmentation-free machine learning architecture for immune land-scape phenotyping in solid tumors by multichannel imaging.</a> bioRxiv. , (2021).</li>
<li>Parra, E. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immuno-profiling+and+cellular+spatial+analysis+using+five+immune+oncology+multiplex+immunofluorescence+panels+for+paraffin+tumor+tissue%5BTitle%5D)+AND+%22Scientific+Reports%22%5BJournal%5D)">Immuno-profiling and cellular spatial analysis using five immune oncology multiplex immunofluorescence panels for paraffin tumor tissue.</a> Scientific Reports. 11 (1), 8511(2021).</li>
<li>Parra, E. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Validation+of+multiplex+immunofluorescence+panels+using+multispectral+microscopy+for+immune-profiling+of+formalin-fixed+and+paraffin-embedded+human+tumor+tissues%5BTitle%5D)+AND+%22Scientific+Reports%22%5BJournal%5D)">Validation of multiplex immunofluorescence panels using multispectral microscopy for immune-profiling of formalin-fixed and paraffin-embedded human tumor tissues.</a> Scientific Reports. 7 (1), 13380(2017).</li>
<li>Sun, Z., Nyberg, R., Wu, Y., Bernard, B., Redmond, W. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Developing+an+enhanced+7-color+multiplex+IHC+protocol+to+dissect+immune+infiltration+in+human+cancers%5BTitle%5D)+AND+%22PLoS+One%22%5BJournal%5D)">Developing an enhanced 7-color multiplex IHC protocol to dissect immune infiltration in human cancers.</a> PLoS One. 16 (2), e0247238(2021).</li>
<li>LeicaBiosystems. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((BOND+RX+Fully+Automated+Research+Stainer+Protocols%5BTitle%5D)+AND+%22%22%5BJournal%5D)">BOND RX Fully Automated Research Stainer Protocols.</a> , https://www.leicabiosystems.com/en-nl/ihc-ish/ihc-ish-instruments/bond-rx/ (2022).</li>
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The authors have no conflicts of interest to disclose.

Spatial analysis of the TME is a sought-after technique to learn more about the immune cell compartment and discover new prognostic and predictive biomarkers, particularly in the field of immuno-oncology16. Many different techniques are being developed for this purpose, involving the detection of proteins, mRNA transcripts, or a combination of the two, with estimations up to 100-1,000 targets. However, higher multiplexing comes at the cost of less high-throughput experiments, higher experimental costs, and technical challenges, and often, only a small part of the TME can be analyzed. Multiplex IHC using the TSA-based method that we describe here, detects six different markers + DAPI simultaneously, is relatively less expensive to perform, and whole tissue sections are imaged in under 20 min, ready to be analyzed fully. This technique has become less complex with the automation of the staining procedure. Improvements in the multispectral microscope, which include the addition of two extra filters, have improved spectral unmixing and scanning times tremendously. It is possible to detect up to eight different markers + DAPI simultaneously. However, by expanding the multiplexing with more markers, the aforementioned benefits disappear as spectral unmixing becomes more challenging and scanning times for whole slides increase substantially. Efforts are being undertaken to standardize multiplex IHC between different institutions to facilitate implementation in the diagnostic setting more easily. For this standardization of multiplex IHC, we advise users to adhere to the more accessible protocol with six different markers + DAPI. Nevertheless, still quite some technical know-how is necessary and downstream analysis can be challenging, for which we have developed methodologies that are described in this protocol.
Standardization begins with multiplex IHC panel development. The importance of the choice of primary antibodies detecting particular protein targets has been emphasized before17. Our multiplex IHC panels are mostly developed with primary antibody clones that are also used and validated for IHC at our diagnostics department. However, in the case of the dendritic cell multiplex IHC panel, most antibodies were not used in the diagnostic setting (van der Hoorn et al., manuscript in submission). To ensure specificity and minimize batch differences, we chose to use monoclonal antibodies over polyclonal antibodies and have also validated most antibodies using transfected cell lines and primary cells. Over the years, different versions of multiplex IHC panels have been used in numerous studies using the Vectra 3 system18,21,23,24,25,26,27,28,29,30,31,32. To implement these multiplex IHC panels optimally on the PhenoImager HT system, some adjustments had to be made in primary antibody and fluorophore combinations. To benefit from better spectral unmixing and faster scanning times of whole tissue sections, implementation of the latest Opal480 and Opal780 fluorophores and avoiding the use of Opal540 and Opal650 fluorophores in seven-color multiplex IHC panels is necessary. Scanning times are ~3-10 times faster depending on the size of the tissue section. Multiplex IHC panel adjustments were quite easy to achieve, but some considerations need to be kept in mind. The fluorescent spectrum of Opal480 overlaps a lot with the autofluorescence spectrum and therefore, interferes with the spectral unmixing of erythrocytes and other autofluorescent structures. Using an increased concentration of the primary antibody paired with Opal480 solved this issue in most cases. The implementation of the proprietary Sample AF filter on the PhenoImager HT facilitates the unmixing of Opal480 and autofluorescence. However, it is best to use a primary antibody that yields a clear signal when used with Opal480 so that its signal is higher than the autofluorescence.
Even though these multiplex IHC panels are established, batch-to-batch variation is something that needs to be considered. By performing monoplex IHC controls before starting the full multiplex IHC experiment, we sometimes observed that primary antibodies perform either stronger or weaker from experiment to experiment. The reasons for this could be pipetting errors, suboptimal reagent storage conditions, and shelf life. We solved this by adjusting the primary antibody solution based on our experience. Even when none of the aforementioned adjustments had to be made, with every multiplex IHC batch experiment, it is important to set exposure times based on monoplex IHC-stained control slides.
Because our research was initially focused on different types of carcinomas and melanoma, multiplex IHC panels were required to be interchangeable between tumor types with minimal adjustments. Therefore, we always included multiple (tumor) tissue types in the optimization process and observed that dilutions for primary antibodies for immune cell markers can be kept similar between different tumor types. However, tumor tissue detection between carcinomas and melanoma needs different tumor markers. Accordingly, the tumor marker was always optimized to work at the end of each multiplex IHC panel and is currently always used in conjunction with Opal780, which coincidentally also has to be at the last fluorophore in a multiplex IHC staining procedure. By using the tumor marker consequently at the end of the multiplex IHC, these multiplex IHC panels can be easily exchanged for other tumor types, such as glioblastoma (i.e., GFAP) and Hodgkin lymphoma (i.e., CD30). For angiosarcoma, we used this lymphocyte multiplex IHC panel with erythroblast transformation-specific-related gene (ERG) as the tumor marker with only two optimization experiments25. The optimization included titration of the ERG primary antibody and testing the multiplex IHC panel with ERG at the end.
Other adjustments to these multiplex IHC panels can also be made by exchanging a certain immune cell marker for another immune or functional marker. Every change requires optimization. The protocol for optimization could be followed as described previously17. Certain changes to the proposed multiplex IHC panels will interfere with the ImmuNet algorithms that we have created. Sufficient data must be generated and time has to be spent to implement these changes into the algorithm (at least 750 annotations for every new marker and/or cell phenotypes, and 150 annotations for validation of previously trained markers). The panels presented here do not contain functional markers, although the implementation of immune checkpoint markers such as PD-1 and PD-L1 into multiplex IHC panels is performed in our laboratory. However, the analysis of markers that are less binary in negative and positive signals has proven to be more difficult and is an area of active research in our group.
The number of markers that can be simultaneously assessed with multiplex IHC is limited compared to other novel techniques. While this can be circumvented by analyzing different panels on consecutive slices of an FFPE block, it will be hard to compare these slices spatially. Orientation and folded artifacts are likely not the same after slide preparation. Nevertheless, multiplex IHC is quite accessible, which makes it an attractive tool for more institutions and researchers and therefore, more suitable for future implementation in a diagnostic setting. With the standardization of multiplex IHC immune cell panels for multiple tumor types and downstream analysis pipelines, more knowledge could be gained about differences in TME between patients and tumor types. This can, for instance, lead to more insights into the role of the TME in antitumor response to specific treatments. This may even give rise to new biomarkers to predict factors such as response to treatment and expected survival. Overall, this can enable multiplex IHC to become a clinical tool to aid with clinical decision-making, in a personalized medicine approach. Admittedly, more steps of the analysis procedure should probably be automated and standardized for it to be feasible for use in a daily diagnostic setting, so as of yet, it is mostly a futuristic perspective.
Analysis of multiple markers on a single sample slide can be a very powerful tool in spite of its technical challenges. With standardized experimental protocols and a robust analysis method, as we described here using ImmuNet, the quantification of multiple markers makes it more informative than classical IHC, while multiplex IHC remains relatively high-throughput compared to novel higher plex experimental methods.

Immune cells play a crucial role in the protection against pathogens such as viruses and bacteria, but also against cancerous cells1. Therefore, the immune system within the tumor microenvironment (TME) holds a lot of promise for discovering prognostic and predictive biomarkers2. Immune cell infiltrates have been correlated to prognosis in various types of cancer, although this has not been implemented in clinical care yet3,4. In most tumor types, high numbers of cytotoxic T cells and T helper 1 cells and/or low numbers of regulatory T cells are linked to good prognoses. Efforts are ongoing to incorporate a so-called &#34;Immunoscore&#34; into the TNM staging of colorectal cancer, turning it into TNM-I staging5,6. The Immunoscore is derived from the total number of T cells (detected with CD3) and cytotoxic T cells (detected with CD8) in two different tumor regions: the tumor core versus the invasive margin (IM) of tumors. The Immunoscore has also been proposed to be of prognostic value in other cancer types, such as melanoma, lung cancer, and breast cancer6,7,8,9. Furthermore, immune cell infiltrates may also correlate to response to checkpoint blockade immunotherapy10. However, these predictive biomarkers must be validated in prospective studies before they can be routinely implemented in clinical practice. Moreover, it has also been proposed that a single biomarker will be insufficient for meaningful prediction11. Therefore, creating a complete map of a patient sample by combining different biomarkers has been proposed as a more comprehensive predictive biomarker in a so-called &#34;cancer immunogram&#34;12.
Among the methods for studying immune cells within the TME, the oldest and most well-known technique is immunohistochemistry (IHC), routinely used for diagnostic testing in several diseases, especially cancer13. This technique was limited to the use of one or only a few markers14 for a long time and therefore, was outcompeted in research settings by other techniques such as flow cytometry and gene expression profiling (GEP). However, the formalin-fixed and paraffin-embedded (FFPE) tumor tissues typically used in routine diagnostics and research are not (optimally) suitable for flow cytometry and GEP. Furthermore, although GEP and flow cytometry provide a lot of insight into cell phenotype and function, the lack of spatial information is a major disadvantage. Therefore, heterogeneity within a sample, such as differences in immune cell-infiltrated versus immune cell-excluded areas of a tumor, could go undetected15. Novel platforms have been developed for multiplex analysis of FFPE tissues, such as multiplex IHC, imaging mass cytometry, and CO-Detection by indEXing (CODEX) that can be used to detect multiple markers simultaneously within a tissue section16. Immune cells in the TME are being widely studied to find the best biomarkers for immunotherapy. However, multiplex techniques and automated image analysis pose hurdles of their own.
Our laboratory has extensive experience in multiplex IHC staining using the Opal/Tyramide signal amplification (TSA) method and has automated this on a&#160;IHC platform (see the Table of Materials)17,18,19,20,21,22,23,24,25,26,27,28,29,30,31. We have optimized immune cell panels for the detection of different subsets of lymphocytes, myeloid cells, and dendritic cells (DCs). Tissues that contain dense immune cell areas - for lymphocytes or complex cell morphologies (i.e., myeloid cells and DCs) - are particularly challenging to analyze, with a risk of over- or underestimating the number of immune cells present. To overcome this problem, ImmuNet analysis software was developed by our group32, and this machine-learning pipeline improved the quality of the detection of these different types of immune cells immensely. A detailed protocol from obtaining the FFPE material to the analysis of immune cell densities in different tissue compartments and distances between immune cell types is described here.
This protocol outlines how the multiplex IHC panels are performed at the Radboud University Medical Center since the implementation of the digital pathology imager in 2022. The described multiplex IHC panels can be used for different carcinomas (e.g., lung, prostate, colorectal, bladder, breast) with the use of a pan-cytokeratin antibody as a tumor marker or for melanoma with the use of melanocyte-associated antibodies as tumor markers. These multiplex IHC protocols have been carefully optimized in terms of primary antibody concentration, fluorophore combinations, and the sequence of the staining procedure. We and others have described multiplex IHC panel optimization earlier17,33,34,35. Multiplex IHC panels can be adapted, but the described analysis pipelines need to be evaluated and potentially adjusted or retrained accordingly. The described seven-color multiplex IHC protocols make use of the Opal fluorophores Opal480, Opal520, Opal570, Opal620, Opal690, Opal780, and 4&#39;,6-diamidino-2-phenylindole (DAPI), so that easy unmixing and fast scanning on the imager is enabled with &#34;Multispectral One Touch ImmunoFluorescence&#34; (MOTiF). Nine-color staining and scanning is not described in this protocol as this requires even more finetuning of the experimental setup and another mode of scanning on the imager that uses the liquid crystal tunable filter.

<table><tbody><tr><td>anti-CD14</td><td>Cell Marque&amp;nbsp;</td><td>114R-16</td><td>section 3, clone EPR3653</td></tr><tr><td>anti-CD163</td><td>Cell Marque&amp;nbsp;</td><td>163M-15</td><td>section 3, clone MRQ-26</td></tr><tr><td>anti-CD19</td><td>Abcam</td><td>ab134114</td><td>section 3, clone EPR5906</td></tr><tr><td>anti-CD1c (BDCA1)</td><td>Thermo Scientific</td><td>TA505411</td><td>section 3, clone OTI2F4</td></tr><tr><td>anti-CD20</td><td>Thermo Scientific</td><td>MS-340-S</td><td>section 3, clone L26</td></tr><tr><td>anti-CD3</td><td>Thermo Scientific</td><td>RM-9107</td><td>section 3, clone sp7</td></tr><tr><td>anti-CD303/BDCA2</td><td>Dendritics via Enzo Lifesciences/Axxora</td><td>DDX0043</td><td>section 3, clone 124B3.13</td></tr><tr><td>anti-CD56</td><td>Cell Marque&amp;nbsp;</td><td>156R-94</td><td>section 3, clone MRQ-42</td></tr><tr><td>anti-CD66b</td><td>BD Biosciences</td><td>555723</td><td>section 3, clone G10F5</td></tr><tr><td>anti-CD68</td><td>Dako Agilent</td><td>M087601</td><td>section 3, clone PG-M1</td></tr><tr><td>anti-CD8</td><td>Dako Agilent</td><td>M7103</td><td>section 3, clone C8/144B</td></tr><tr><td>anti-Foxp3</td><td>Thermo Scientific</td><td>14-4777</td><td>section 3, clone 236A/E7</td></tr><tr><td>anti-Gp100</td><td>Dako Agilent</td><td>M063401</td><td>section 3, clone HMB45</td></tr><tr><td>anti-HLA-DR, DP, DQ</td><td>Santa Cruz</td><td>sc-53302</td><td>section 3, clone CR3/43</td></tr><tr><td>anti-MART-1</td><td>Thermo Scientific</td><td>MS-799</td><td>section 3, clone A103</td></tr><tr><td>anti-pan cytokeratin</td><td>Abcam</td><td>ab86734</td><td>section 3, clone AE1/AE3 + 5D3</td></tr><tr><td>anti-SOX10</td><td>Sigma Aldrich</td><td>383R</td><td>section 3, clone EP268</td></tr><tr><td>anti-Tyrosinase</td><td>Sanbio</td><td>MONX10591</td><td>section 3, clone T311</td></tr><tr><td>anti-XCR1</td><td>Cell Signaling Technologies via Biok&amp;eacute;</td><td>44665S</td><td>section 3, clone D2F8T</td></tr><tr><td>antibody diluent</td><td>Akoya BioSciences</td><td>SKU&amp;nbsp;ARD1001EA</td><td>section 3, from Opal 7-Color Automation IHC Kit 50 slide (can optionally also be replaced by TBST with 10% BSA)</td></tr><tr><td>Bond Aspirating Probe</td><td>Leica Biosciences</td><td>S21.0605</td><td>section 3</td></tr><tr><td>Bond Aspirating Probe Cleaning</td><td>Leica Biosciences</td><td>CS9100</td><td>section 3</td></tr><tr><td>Bond Dewax Solution</td><td>Leica Biosciences</td><td>AR9222</td><td>section 3</td></tr><tr><td>Bond Objectglas label + print lint</td><td>Leica Biosciences</td><td>S21.4564.A</td><td>section 3</td></tr><tr><td>Bond Research Detection System 2</td><td>Leica Biosciences</td><td>DS9777</td><td>section 3</td></tr><tr><td>Bond RX autostainer&amp;nbsp;</td><td>Leica Biosciences</td><td>-</td><td>section 3, automated platform</td></tr><tr><td>Bond TM Epitope Retrieval 1 - 1 L</td><td>Leica Biosciences</td><td>AR9961</td><td>section 3</td></tr><tr><td>Bond TM Epitope Retrieval 2 - 1 L</td><td>Leica Biosciences</td><td>AR9640</td><td>section 3</td></tr><tr><td>Bond TM Wash Solution 10x - 1 L</td><td>Leica Biosciences</td><td>AR9590</td><td>section 3</td></tr><tr><td>BOND Universal Covertile</td><td>Leica Biosciences</td><td>S21.4611</td><td>section 3</td></tr><tr><td>Bond(TM) Titration Kit</td><td>Leica Biosciences</td><td>OPT9049</td><td>section 3</td></tr><tr><td>Coverslip 24 x 32 mm #1 (0.13-0.16 mm)</td><td>Fisher Scientific</td><td>15717592</td><td>section 2</td></tr><tr><td>coverslip 24 x 50 mm</td><td>VWR</td><td>631-0146</td><td>section 2</td></tr><tr><td>DAPI Fluoromount-G</td><td>VWR</td><td>0100-20</td><td>section 3, whenever monoplex slides need to be quickly checked, not for official analysis, then DAPI is stained seperately for better results</td></tr><tr><td>Eosine</td><td></td><td></td><td>section 2, home made</td></tr><tr><td>Ethanol 99.5%</td><td>VWR</td><td>4099.9005</td><td>section 2</td></tr><tr><td>Fluoromount-G</td><td>VWR</td><td>0100-01</td><td>section 3&amp;nbsp;</td></tr><tr><td>haematoxyline</td><td></td><td>-</td><td>section 2, home made</td></tr><tr><td>ImmuNet</td><td></td><td>-</td><td>immune cell detection and phenotyping pipeline</td></tr><tr><td>inForm software 2.4.10</td><td>Akoya BioSciences</td><td>-</td><td>section 4 &amp;amp; 6</td></tr><tr><td>OPAL 480 reagent pack</td><td>Akoya BioSciences</td><td>FP1500001KT</td><td>section 3</td></tr><tr><td>OPAL 520 reagent pack</td><td>Akoya BioSciences</td><td>FP1487001KT</td><td>section 3</td></tr><tr><td>OPAL 570 reagent pack</td><td>Akoya BioSciences</td><td>FP1488001KT</td><td>section 3</td></tr><tr><td>OPAL 620 reagent pack</td><td>Akoya BioSciences</td><td>FP1495001KT</td><td>section 3</td></tr><tr><td>OPAL 690 reagent pack</td><td>Akoya BioSciences</td><td>FP1497001KT</td><td>section 3</td></tr><tr><td>OPAL 780 reagent pack</td><td>Akoya BioSciences</td><td>FP1501001KT</td><td>section 3</td></tr><tr><td>Opal 7-Color Automation IHC Kit 50 slide</td><td>Akoya BioSciences</td><td>NEL821001KT</td><td>section 3</td></tr><tr><td>PhenoChart 1.1.0</td><td>Akoya BioSciences</td><td>-</td><td>section 5</td></tr><tr><td>PhenoImagerHT</td><td>Akoya BioSciences</td><td>CLS143455</td><td>section 4, digital pathology imager with slide viewer and imaging software (formerly known as Vectra Polaris)</td></tr><tr><td>Quick-D mounting medium</td><td>Klinipath</td><td>7280</td><td>section 2</td></tr><tr><td>QuPath 0.3.2</td><td></td><td></td><td>whole slide image analysis software platform</td></tr><tr><td>R 4.1.1</td><td></td><td></td><td></td></tr><tr><td>Slide boxes</td><td>VWR</td><td>631-0737</td><td>section 1</td></tr><tr><td>SuperFrost Plus</td><td>Thermo Scientific through VWR</td><td>631-9483</td><td>section 1</td></tr><tr><td>Vectra Polaris software 1.0.13</td><td>Akoya BioSciences</td><td>-</td><td>section 4</td></tr><tr><td>Xylene</td><td>VWR</td><td>4055-9005</td><td>section 2</td></tr></tbody></table>

multiplex immunohistochemical analysis of the spatial immune cell landscape of the tumor microenvironment

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

Read this Scientific Article Protocol about Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment at JoVE.com

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

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

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

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

multiplex-immunohistochemical-analysis-spatial-immune-cell-landscape

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JoVE Journal

Cancer Research

1.9K Views.  Radboudumc. Ons doel is om de hoeveelheid, het type en de locatie van immuuncellen in de micro-omgevingen van de tumor te identificeren. Op het gebied van immunochemie is er de afgelopen jaren een grote technologische vooruitgang geboekt. Vooruitgang in multiplex immunochemietechnologie maakt het mogelijk om meer markers betrouwbaar te bestuderen.De huidige experimentele uitdagingen zijn het visualiseren van specifieke soorten immuuncellen in tumormonsters, die zijn overwonnen met behulp van de mu...

Video: Auteur in de schijnwerpers: inzichten ontsluiten in het immuuncellandschap van tumoren

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Understanding the early heterotypic interactions between cancer cells and the surrounding non-cancerous stroma is important in elucidating the events leading to stromal activation and establishment of the tumor microenvironment (TME). Several in vitro and in vivo models of the TME have been developed; however, in general these models do not readily permit isolation of individual cell populations, under non-perturbing conditions, for further study. To circumvent this difficulty, we have employed an in vitro TME model using a cell growth substrate consisting of a permeable microporous membrane insert that permits simple generation of highly enriched cell populations grown intimately, yet separately, on either side of the insert&#39;s membrane for extended co-culture times. Through use of this model, we are capable of generating greatly enriched cancer-associated fibroblast (CAF) populations from normal diploid human fibroblasts following co-culture (120 hr) with highly metastatic human breast carcinoma cells, without the use of fluorescent tagging and/or cell sorting. Additionally, by modulating the pore-size of the insert, we can control for the mode of intercellular communication (e.g., gap-junction communication, secreted factors) between the two heterotypic cell populations, which permits investigation of the mechanisms underlying the development of the TME, including the role of gap-junction permeability. This model serves as a valuable tool in enhancing our understanding of the initial events leading to cancer-stroma initiation, the early evolution of the TME, and the modulating effect of the stroma on the responses of cancer cells to therapeutic agents.

We adapted a permeable microporous membrane insert to mimic the tumor microenvironment (TME). The model consists of a mixed cell culture, allows simplified generation of highly enriched individual cell populations without using fluorescent tagging or cell sorting, and permits studying intercellular communication within the TME under normal or stress conditions.

Understanding the early heterotypic interactions between cancer cells and the surrounding non-cancerous stroma is important in elucidating the events ...

Conditional Knockdown of Gene Expression in Cancer Cell Lines to Study the Recruitment of Monocytes/Macrophages to the Tumor Microenvironment

siRNA and shRNA-mediated knock down (KD) methods of regulating gene expression are invaluable tools for understanding gene and protein function. However, in the case that the KD of the protein of interest has a lethal effect on cells or the anticipated effect of the KD is time-dependent, unconditional KD methods are not appropriate. Conditional systems are more suitable in these cases and have been the subject of much interest. These include Ecdysone-inducible overexpression systems, Cytochrome P-450 induction system1, and the tetracycline regulated gene expression systems. 
The tetracycline regulated gene expression system enables reversible control over protein expression by induction of shRNA expression in the presence of tetracycline. In this protocol, we present an experimental design using functional Tet-ON system in human cancer cell lines for conditional regulation of gene expression. We then demonstrate the use of this system in the study of tumor cell-monocyte interaction.

This protocol serves as a scheme for setting up a functional Tet-ON system in cancer cell lines and its subsequent use, in particular for studying the role of tumor cell-derived proteins in recruitment of monocytes/macrophages to the tumor microenvironment.

siRNA and shRNA-mediated knock down (KD) methods of regulating gene expression are invaluable tools for understanding gene and protein function. However, ...

Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells

Immune cells are important components of the tumor microenvironment and influence tumor growth and evolution at all stages of carcinogenesis. Notably, it is now well established that the immune infiltrate in human tumors can correlate with prognosis and response to therapy. The analysis of the immune infiltrate in the tumor microenvironment has become a major challenge for the classification of patients and the response to treatment.
The co-expression of inhibitory receptors such as Program Cell Death Protein 1 (PD1; also known as CD279), Cytotoxic T Lymphocyte Associated Protein 4 (CTLA-4), T-Cell Immunoglobulin and Mucin Containing Protein-3 (Tim-3; also known as CD366), and Lymphocyte Activation Gene 3 (Lag-3; also known as CD223), is a hallmark of T cell exhaustion. We developed a multiparametric in situ immunofluorescence staining to identify and quantify at the cellular level the co-expression of these inhibitory receptors. On a retrospective series of frozen tissue of renal cell carcinomas (RCC), using a fluorescence multispectral imaging technology coupled with an image analysis software, it was found that co-expression of PD-1 and Tim-3 on tumor infiltrating CD8+ T cells is correlated with a poor prognosis in RCC. To our knowledge, this represents the first study demonstrating that this automated multiplex in situ technology may have some clinical relevance.

Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells

Studying tumor microenvironment may identify prognostic or predictive biomarkers of clinical response to immunotherapy. Presented here, is an innovative method based on in situ fluorescence multispectral imaging to analyze and count automatically various subpopulations of CD8+ T cells. This reproducible and reliable technique is suitable for large cohort analyses.

Immune cells are important components of the tumor microenvironment and influence tumor growth and evolution at all stages of carcinogenesis. Notably, it ...

In Vivo EPR Assessment of pH, pO2, Redox Status, and Concentrations of Phosphate and Glutathione in the Tumor Microenvironment

This protocol demonstrates the capability of low-field electron paramagnetic resonance (EPR)-based techniques in combination with functional paramagnetic probes to provide quantitative information on the chemical tumor microenvironment (TME), including pO2, pH, redox status, concentrations of interstitial inorganic phosphate (Pi), and intracellular glutathione (GSH). In particular, an application of a recently developed soluble multifunctional trityl probe provides unsurpassed opportunity for in vivo concurrent measurements of pH, pO2 and Pi in Extracellular space (HOPE probe). The measurements of three parameters using a single probe allow for their correlation analyses independent of probe distribution and time of the measurements.

In Vivo EPR Assessment of pH, pO2, Redox Status, and Concentrations of Phosphate and Glutathione in the Tumor Microenvironment

Low-field (L-band, 1.2 GHz) electron paramagnetic resonance using soluble nitroxyl and trityl probes is demonstrated for assessment of physiologically important parameters in the tumor microenvironment in mouse models of breast cancer.

This protocol demonstrates the capability of low-field electron paramagnetic resonance (EPR)-based techniques in combination with functional paramagnetic ...

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for immunotherapies. Recent clinical advances in immunotherapy highlight the need for reproducible methods to accurately and thoroughly characterize the tumor and its associated immune infiltrate. Tumor enzymatic digestion and flow cytometric analysis allow broad characterization of numerous immune cell subsets and phenotypes; however, depth of analysis is often limited by fluorophore restrictions on panel design and the need to acquire large tumor samples to observe rare immune populations of interest. Thus, we have developed an effective and high throughput method for separating and enriching the tumor immune infiltrate from the non-immune tumor components. The described tumor digestion and centrifugal density-based separation technique allows separate characterization of tumor and tumor immune infiltrate fractions and preserves cellular viability, and thus, provides a broad characterization of the tumor immunologic state. This method was used to characterize the extensive spatial immune heterogeneity in solid tumors, which further demonstrates the need for consistent whole tumor immunologic profiling techniques. Overall, this method provides an effective and adaptable technique for the immunologic characterization of subcutaneous solid murine tumors; as such, this tool can be used to better characterize the tumoral immunologic features and in the preclinical evaluation of novel immunotherapeutic strategies.

Here we describe a method to separate and enrich components of the tumor immune and non-immune microenvironment in established subcutaneous tumors. This technique allows for the separate analysis of tumor immune infiltrate and non-immune tumor fractions which can permit comprehensive characterization of the tumor immune microenvironment.

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for ...

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

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

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

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

Multiplex Immunofluorescence and Spatial Image Analysis of the Tumor Microenvironment

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

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

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

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

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

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 ...

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 ...

Immunology and Infection

Multiplexed Immunofluorescence Imaging to Analyze Immunotherapy-Resistant T Cell Subpopulations

Source: Granier, C., et al. <a href="https://app.jove.com/v/56606">Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells.</a> J. Vis. Exp. (2018).
This video demonstrates an in-situ fluorescence multispectral imaging technique to analyze different subpopulations of infiltrating T cells in tumor tissue. A renal cell carcinoma tissue cryosection is treated with antibodies to label CD8+ T cells that express specific inhibitory receptors and exhibit an immunotherapy-resistant phenotype. The labeled section is visualized using a multispectral microscope to identify the distinct CD8+ T cell subpopulations.

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

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