Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment

This article is featured in In This Issue, p.1

The success of mAb therapies directed toward molecules modulating antitumor responses has spurred many developments in the field of cancer immunotherapy. So far, mAbs against immune checkpoints CTLA-4, PD-1, and PD-L1 have been approved for the treatment of melanoma (1–3), lung (4, 5), head and neck (6), and bladder cancer (7, 8), and their use is rapidly expanding toward treatment of other cancer types (9–11). However, long-lasting (>2 y) responses are still limited to ∼20–40% of patients (12). This has led to the development of many new mAbs targeting other immune checkpoint molecules, which are currently being tested in clinical trials (13). These include targets such as TIM3 (14–16), CD27 (17–19), and OX40 (20–22), sometimes combined with already approved mAbs, such as ipilimumab, pembrolizumab, and nivolumab (23–26). To make educated decisions with the expanding choice of mAbs targeting different immune checkpoints, it is of great importance to investigate the expression profiles of these immune checkpoint molecules on both immune cells and tumor cells within the tumor microenvironment (TME).

The goal of this research is therefore to study the expression of multiple immune checkpoints simultaneously by means of immunohistochemistry (IHC). This technique offers detailed information regarding the distribution of different phenotypes within one sample, while also maintaining the morphological context of the tissue, which is lost with other techniques like gene expression profiling or flow cytometry. In clinical practice, tissue is often available only in formalin-fixed paraffin-embedded (FFPE) form, which hampers extensive expression analysis because of epitope destruction or limited applicability of Abs (27, 28). Also, the accuracy of the detection by Abs targeting novel immune checkpoint molecules can be questioned. Furthermore, performing IHC with more than one target requires the use of primary Abs raised in different species to prevent cross-reactivity of the secondary Abs that are used, which limits the choice of primary Abs. To circumvent all these limitations, we have made use of multiplex IHC with tyramide signal amplification (TSA), a powerful tool to study the expression of multiple markers at once in a single tissue section (29–33). This was carried out with Abs validated to target specific immune checkpoint molecules. Still, we observed that multiplex IHC using TSA with a maximized number of markers presents a high level of complexity and requires careful optimization to limit epitope damage and signal loss during the sequential staining protocol.

In this article, we report on the development, optimization, and application of an eight-color multiplex IHC panel, consisting of PD-1, PD-L1, OX40, CD27, TIM3, CD3, a tumor marker, and DAPI. This optimized panel allows for the simultaneous quantification of five different immune checkpoint molecules on individual cells within different tumor types.

Sections of 4-μm thickness were cut from FFPE tissue microarrays (TMAs) or control tonsil tissue. The slides were deparaffinized in xylene, rehydrated, and washed in tap water before boiling in Tris-EDTA buffer (pH 9; 643901; Klinipath) for epitope retrieval/microwave treatment (MWT). In chromogenic IHC experiments, endogenous peroxidase was blocked using 3% hydrogen peroxidase in methanol (76051800.1000 and 1.06009.1000, respectively; EMD Millipore). In TSA IHC experiments, protein blocking was performed using TBS-Tween 1% BSA (10735108001; Roche). Primary Abs CD3 (RM-9107, clone RM-9107; Thermo Fisher), PD-1 (315M-94, clone NAT105; Sanbio), PD-L1 (13684, clone E1L3N; Cell Signaling), OX40 (555863, clone ACT35; BD Biosciences), TIM3 (45208, clone D5D5R; Cell Signaling), CD27 (ab131254, clone EPR8569; Abcam), a melanoma mix consisting of HMB-45 (M063401, clone HMB45; Dako), Mart-1 (MS-799, clone A103; Thermo Immunologic), Tyrosinase (MONX10591, clone T311; Monosan), and SOX-10 (383R, clone EP268; Cell Marque), used for the tumor tissue within melanoma samples, and pan cytokeratin (ab86734, clone AE1/AE3 + 5D3; Abcam), to visualize tumor tissue within all other tumor samples, were incubated for 1 h at room temperature. Next, incubation with BrightVision poly-HRP-anti-Ms/Rb/Rt IgG (DPVO999HRP; ImmunoLogic) was performed at room temperature for 30 min.

Chromogenic visualization was performed with Bright-DAB (VWRKBS04-999; ImmunoLogic) for 7 min at room temperature. After dehydration, slides were counterstained with hematoxylin and were enclosed with Quick-D mounting medium (7281; Klinipath).

TSA visualization was performed with the Opal seven-color IHC Kit (NEL797B001KT; PerkinElmer) containing fluorophores DAPI, Opal 520, Opal 540, Opal 570, Opal 620, Opal 650, Opal 690, and TSA Coumarin system (NEL703001KT; PerkinElmer). MWT was performed to remove the Ab TSA complex with Tris-EDTA buffer (pH 9). TSA single stain slides were finished with MWT and counterstained with DAPI for 5 min and were enclosed in Fluoromount-G (0100-01; SouthernBiotech).

Multiplex TSA was optimized by performing a duplex (PD-L1, Opal 570 and PD-1, Opal 650), followed by a triplex (addition of OX40, Opal 690), 4plex (addition of CD27, Opal 540), 5plex (addition of TIM3, Opal 620), and 6plex (addition of CD3, Opal 520). All multiplex TSA experiments were performed by repeating staining cycles in series, with MWTs in between each cycle and at the end of the multiplex TSA. Finally, 7plex was performed with the addition of a “tumor marker” (pan cytokeratin or melanoma mix, both coumarin) and omission of the MWT at the end to prevent epitope damage or signal loss. All multiplex TSA stainings were finished with a DAPI counterstain and were enclosed in Fluoromount-G.

Slides were scanned using the PerkinElmer Vectra (Vectra 2.0.7 and 3.0.3; PerkinElmer). Multispectral images were unmixed using spectral libraries built from images of single stained tissues for each reagent using the inForm Advanced Image Analysis software (inForm 2.1.1 and 2.2.1; PerkinElmer). A selection of 15–25 representative original multispectral images was used to train the inForm software (tissue segmentation, cell segmentation, phenotyping tool, and positivity score). All the settings applied to the training images were saved within an algorithm to allow batch analysis of multiple original multispectral images of the same tumor.

Chinese hamster ovary (CHO) cells were cultured in Ham’s F-12 medium (21765-029; Invitrogen) supplemented with 10% FCS (758093; Greiner Bio-One) and antibiotic antimycotic (15240; Life Technologies). Cells were maintained at 37°C in a humidified atmosphere of 5% carbon dioxide. One day prior to transfection, CHO cells were seeded into T75 flasks at a confluency of ∼70%. Cells were transfected with the cDNA constructs cloned into the mammalian expression vector pcDNA3.1+/C-(K)-DYK encoding for PD-1, PD-L1, OX40, CD27, and TIM3 (OHu26320D, OHu22144D, OHu20164D, OHu19616D, and OHu20832D, respectively; all from Genscript) using Lipofectamine 2000 (11668-019; Invitrogen) according to manufacturers’ guidelines. Expression of the recombinant proteins was maintained for 48 h before measurement. Flow cytometry was performed on cells to check transfection efficiency. The remainder of cells was embedded in paraffin with the AgarCyto cell block preparation (34), and sections of 4-μm thickness were cut.

Flow cytometry was performed on (transfected) CHO cells with conjugated Abs suitable for flow cytometric assays. The following primary mAbs were used: anti–PD-1-PerCp-Cy5.5, anti–OX40-FITC, and anti–CD27-PE-Cy7 (561273, 555837, and 560609, respectively; all BD Biosciences), anti–PD-L1-allophycocyanin and anti-TIM3-PE (329708 and 345006, respectively; both from BioLegend). Flow cytometry was conducted with the FACS Verse (BD Biosciences). Flow cytometry data were analyzed using FlowJo software (v10; Tree Star).

From the Radboud university medical center, a total of 33 tumor specimens was selected for this study, including melanoma, squamous cell carcinoma of the lung, adenocarcinoma of the lung, urothelial cell carcinoma of the bladder, colorectal adenocarcinoma, head and neck squamous cell carcinoma, diffuse large B cell lymphoma (DLBCL), ovarian serous adenocarcinoma, clear cell carcinoma of the kidney, invasive ductal breast carcinoma, and adenocarcinoma of the prostate. Three samples were included of each tumor type. Specimens were randomly included based on the availability of a resection specimen, with enough material to create a TMA of 2 mm. TMA cores were acquired at the tumor–stroma border, where immune infiltrates were detected. No ethical approval was required according to current Dutch legislation because we used leftover coded material (35) and patients were given the opportunity to object to their leftover material being used in (clinical) research.

The knowledge on expression of immune checkpoint molecules within the TME remains incomplete. We set out to study immune checkpoint molecules for which mAb therapies have been approved or are currently being explored in clinical trials for the treatment of cancer. Of these, a wide variety of immune checkpoint Abs is commercially available claiming to work for IHC on FFPE tissue. However, most checkpoint targets are relatively new, and IHC staining Abs have not been validated for in vitro diagnostics. We screened Abs targeting a wide variety of immune checkpoint molecules for specific IHC staining signal. We continued with those Abs that showed specific IHC staining signals (Fig. 1A), after confirming the specificity of these Abs on CHO cells that expressed the targeted immune checkpoint molecule of interest (Fig. 1B, 1C). The most promising targets were scored for cell positivity from 3,3′-diaminobenzidine (DAB) chromogenic IHC on control tonsil tissue (Fig. 2A), which is considered to be the golden standard in pathology (36). To use these Abs within a multiplex panel, we applied a TSA staining technique, which is more sensitive than conventional fluorescence or DAB IHC (30). Equal concentrations of Ab yielded higher numbers of positive cells in the TSA application compared with DAB (Fig. 2B). It is therefore important to balance the signals through titration (Fig. 2C). Primary Ab dilutions were chosen for the TSA staining that correlated to the number of positive cells in the DAB IHC (Fig. 2D).

A multiplex TSA can be established by performing sequential cycles of primary Ab, secondary Ab, and TSA application separated by MWT (used for epitope retrieval and removing the primary/secondary Ab complexes while leaving covalently bound TSA fluorophores in place) (30). However, caution should be taken in determining the order of Abs when optimizing a multiplex panel. Random integration of sequential Abs within a multiplex panel may lead to imbalanced signals, incomplete staining through interference with previously applied TSA, disruption of epitopes, and removal of TSA fluorophores because of repetitive MWTs (30, 33). Therefore, the sequence of Abs used in the panel was developed sequentially, starting with a duplex staining with two Abs and determining the optimal Ab order before continuing with the next step. Results of TSA single stains (Fig. 3A) were used as a reference to determine the optimal Ab order for the multiplex stains (Fig. 3B, 3C, Supplemental Fig. 1). This process was repeated until six different markers were combined in a 6plex. The duplex with PD-L1 first, followed by PD-1, most resembled the TSA single staining. Vice versa, starting with PD-1, followed by PD-L1, resulted in reduced PD-L1 staining and an overestimation of the PD-1 signal. Next, OX40 was implemented in the first, middle, or last position, within the predetermined order of PD-L1 and PD-1. OX40 at the second position yielded results most comparable with the single TSA staining. Other primary Ab orders resulted in an underestimation of OX40 or an overestimation of not only OX40 signal, but also PD-L1 and PD-1 signals (Supplemental Fig. 1). From this, we concluded that the optimal order for the triplex is PD-L1, OX40, and PD-1. We continued optimizing a 4plex, resulting in CD27 at the second position, followed by a 5plex, where TIM3 was optimal at the third position, and lastly a 6plex, where CD3 was best at the second position. We observed that the implementation of additional Abs within the panel affected not only the signal intensity of the new target, but also all other targets. Thus, reliable multiplex TSA staining requires a careful fine-tuning of the order in which primary Abs are used.

As a proof of principle, the developed TSA multiplex panel was used to detect differences in the expression of immune checkpoint molecules on immune cells and tumor cells within different tumor tissues. TMAs consisting of invasive margin cores of different tumor types, which are known for their different levels of immunogenicity, were compared (37). Slides were stained with the developed immune checkpoint panel with the addition of a “tumor marker” (a mixture of melanoma-associated Abs for melanoma or pan cytokeratin for the other cancer types) at the last position (Fig. 4). Analysis was performed using inForm Cell Analysis, by segmenting the tumor from stroma (based on the tumor marker) and dividing the cells into immune cells (based on positivity of PD-1, PD-L1, OX40, CD27, TIM3, and/or CD3), tumor cells (tumor marker positive), and other cells (all markers negative) (Fig. 5A). Expression of immune checkpoint markers was determined on both tumor and immune cells, which were further separated into CD3⁺ and CD3⁻ immune cells. As expected, DLBCL was tumor marker/cytokeratin negative, and therefore checkpoint expression could not be determined on tumor cells specifically. We observed that immune checkpoint molecule expression is heterogeneous on immune cells and tumor cells. Nonetheless, differential expression patterns were observed within and among tumor types (Fig. 5B). In melanoma and lung squamous cell carcinoma, for instance, a high percentage of CD3⁺ immune cells expressed CD27. OX40 was expressed by CD3⁺ immune cells in some cases in melanoma, lung, bladder, colorectal, head and neck, ovarian, and breast carcinoma. PD-1 expression was detected only on immune cells in melanoma and DLBCL. PD-L1 expression was found on CD3⁺ and CD3⁻ immune cells in almost all cancers, whereas PD-L1 expression on tumor cells was visible in only a minority of cancers. PD-L1 on tumor cells was strongest in bladder cancer, followed by head and neck carcinoma, and partial on melanoma, lung, and breast carcinoma. TIM3 was mostly detected in head and neck, ovarian, kidney clear cell, and prostate carcinoma on both CD3⁺ and CD3⁻ immune cells. These results demonstrate that the immune checkpoint landscape is highly diverse.

The success or failure of immunotherapy might depend on the expression of immune-stimulating and -inhibiting checkpoint molecules. Understanding the balance between these molecules on (immune) cells and their location within the TME is therefore critical (38–40). Recent advances in multiple immunolabeling and multispectral imaging enable simultaneous analysis of more than three markers within a single FFPE tissue section, with accurate cell discrimination and spatial information (30–33). For this reason, multiplex IHC is one of the most sought-after techniques that might allow for the identification of new prognostic and predictive biomarkers in cancer immunotherapy. However, we and others have experienced that multiplex IHC using TSA is not straightforward, and caution should be taken in the choice of the primary Ab concentration and the order of Abs within a multiplex panel. TSA is a more sensitive technique compared with regular chromogenic IHC and can potentially detect lower levels of expressed proteins (30), but this can also lead to more unspecific background staining. In this study, a TSA IHC was developed that showed comparable staining results as obtained with chromogenic IHC. Furthermore, we discovered that the position of the Abs within the multiplex staining panel is an important factor that affects the signal levels of not only the newly added Ab, but of all Abs within a panel. A reason for this could be that a random order of Abs within a multiplex panel can lead to imbalanced signals, incomplete staining through interference of previous TSA applications, disruption of epitopes, and removal of TSA fluorophores because of repetitive MWTs (30, 33). Therefore, we compared our multiplex staining results throughout the whole optimization process with the TSA singles, starting from optimized singles to duplex staining and so on until eventually a 6plex panel was developed. Eight-color multiplex IHC was completed with the addition of a tumor marker for tumor cell/region discrimination and DAPI staining for cell nucleus identification.

Immune checkpoint molecules were studied for which mAb therapies have been approved or are being explored in clinical trials for the treatment of several types of cancers (12). Not all commercially available Abs that claim to work in FFPE tissue showed a strong and/or a specific staining in our hands (results not shown). A wide variety of primary Abs targeting immune checkpoint molecules were tested for FFPE tissue IHC, of which the ones targeting PD-1, PD-L1, OX40, CD27, and TIM3 worked well. Besides the Abs described in this manuscript, we also obtained specific immune checkpoint Abs for CTLA-4, LAG3, and ICOS, which worked well on FFPE tissue (M.A.J. Gorris, A. Halilovic, C. Wefers, M. Tazzari, I.M.N. Wortel, L.L. van der Woude, A. van Duffelen, D. Verweij, I.J.M. de Vries, C.G. Figdor, and J. Textor, manuscript in preparation). These targets can be implemented in additional multiplex panels because they are of major clinical interest and may result in novel (therapeutical) insights. Abs targeting PD-L2, 4-1BB, BTLA, and HVEM have thus far been tested by us without success.

Staining multiple TMA cores of various tumor types with this multiplex panel identified major differences in immune checkpoint expression, both within the same tumor type and among different tumor types. This was already apparent using the limited number of samples in this study. This demonstrates the necessity for analysis of immune checkpoint multiplex IHC in individual patients. For instance, PD-L1 expression was found on a fraction of both CD3⁺ and CD3⁻ cells in almost all cancers. In contrast, PD-L1 expression on tumor cells was visible in only a minority of tumor types, with the strongest expression in carcinoma of the bladder, followed by head and neck carcinoma, and partly in melanoma and lung carcinoma. However, it is worth noting that because the TMA cores were selected at the invasive margin of the tumor where immune cell infiltrates were present, heterogeneity within a whole tumor section cannot be excluded (41–43). Therefore, these findings need to be further explored by performing analyses on whole tumor sections and larger cohorts.

To the best of our knowledge, this study is the first report on multiple immune checkpoint analyses simultaneously within FFPE sections of the TME. Importantly, this panel allows the simultaneous analysis of multiple immune checkpoint molecules on individual immune cells and tumor cells. This method could ultimately, by characterizing the TME of patients who have been treated with different immune checkpoint modulators, form the rationale for the design of individualized immune checkpoint-based immunotherapy for (treatment-naive) patients in the future.

We thank the technicians of the Immunodiagnostic Laboratory of the Department of Pathology at the Radboud university medical center, under the supervision of Monique Link. We thank Dr. Willeke Blokx for advice in selecting tumor tissue samples for this study. Irene Otte-Holler is acknowledged for efforts in the initial phase of this research.

The authors have no financial conflicts of interest.