II.A. Conventional techniques to examine immune cells in allograft tissue

Prior to the introduction of single-cell techniques, the only options for tissue characterization included immunohistochemistry, immunofluorescence, and confocal microscopy. When using these approaches, it can be very challenging to optimize the staining protocol, minimize background, and detect more than 3–4 markers simultaneously. As mentioned previously, most biopsies performed in SOT are needle cores, which usually only produce 5–8 discrete tissue sections for both clinical diagnosis and research use. Thus, detailed analysis of tissue architecture and single-cell phenotypes, especially in the research setting, has been very limited and a deep characterization of the single-cell immune landscape of rejection in SOT remains a largely unstudied research domain.

II.B. Imaging mass cytometry to examine immune cells in allograft tissue

Prior studies have adopted mass cytometry to examine individual cells obtained from allograft tissue. These first attempts involved tissue dissociation to obtain single-cell suspensions, red blood cell removal, and in some cases cell stimulation. This approach enables deep cellular phenotyping and extended characterization of functional state, without preserving tissue architecture nor the mutual cellular interactions [61,62,63,64]. More recently, the development of imaging mass cytometry (IMC) has offered a powerful tool that allows for detailed single-cell analysis within a tissue section (such as a biopsy section) while preserving spatial relationships. Formalin-fixed paraffin-embedded (FFPE) or frozen tissue sections are stained with a panel of up to 50 antibodies that have been conjugated to metal ions from the lanthanide series to reduce signal background. Tissue is then ablated with a UV laser, vaporized, and analyzed by time-of-flight mass spectrometer that quantifies each metal ion present in as little as 1 μm2 of tissue at 1000-nm resolution, which is fivefold higher than standard immunohistochemistry techniques. The isotope abundance is then used for image reconstruction and downstream analysis, including at the single-cell level (Fig. 2) [65]. Most IMC data has been reported using the Fluidigm hyperion system; however, another metal-based multiplex immunohistochemistry/immunofluorescence platform has been also developed. This is represented by multiplexed ion beam imaging by time-of-flight (MIBI-TOF), which uses oxygen-based primary ion beam for tissue ablation and metal isotopes are liberated from antibodies as secondary ions which are then delivered to a time-of-flight mass spectrometer for quantification of ion abundance [65]. An alternative to IMC involves DNA barcoding-based multiplexed tissue imaging technology called Co-detection by indexing (CODEX) which can detect > 50 antigens simultaneously. CODEX uses primary antibodies conjugated with oligonucleotides that are incubated to either fresh-frozen or FFPE tissue. Fluorophore-labeled oligonucleotides that are complementary to the oligonucleotide-conjugated primary antibodies are serially added and removed for image acquisition and reconstruction. When compared to MIBI and IMC, CODEX does not degrade or destroy the tissue specimen [67, 68]. Cyclic immunofluorescence (CycIF) is based on cyclic staining and imaging, with bleaching for signal removal and re-labeling for multiplexed imaging detection, enabling examination of up to 60 antigens [69, 70]. CycIF uses commercially available antibodies conjugated with fluorophores (e.g., Alexa Fluor Dyes) and image acquisition via conventional microscopy. CycIF has several variants; however, three-channel immunofluorescence combined with a fourth channel for DNA visualization is most commonly used. This multiplex technology provides information on cell morphology and protein translocation essential in studying the cytoskeleton, membrane receptor, and nuclear foci [70].

Thus far, most studies using IMC have focused on cancer immunobiology, inflammation, and autoimmune disease. Our group has recently published the first application of IMC in SOT, focusing on chronic rejection in liver transplantation [71]. Given the paucity of IMC data in SOT, we will review studies using IMC in SOT and in tissue samples obtained from organs that are used in SOT (Tables 2 and 3). The most frequent markers used in IMC studies is shown in Supplemental Table 1. The subcellular resolution of IMC allows localization of antigens within the cell (nucleus vs cytoplasm), and the large number of antibodies available that can be used simultaneously on a single section offers the ability to define cell type and phenotype, activation state, signaling pathway activation, cell-to-cell interaction, as well as proliferation state, features essential for understanding disease pathophysiology, and/or identification of novel biomarkers. For these reasons, IMC (and other multiplexed tissue analysis techniques) is ideally suited for the study of transplant immunology.

Table 2 Summary of IMC studies on SOT allograftTable 3 Summary of IMC studies on organs used for SOTII.C Review of studies using IMC in SOT allografts

The first IMC application in the kidney transplantation was conducted by Avigan et al. to examine the molecular mechanism underlying delayed graft function (DGF) [72]. Preimplantation biopsy of 11 deceased donor kidney transplants (DDKT) at high risk for DGF were compared with 10 biopsies from living donor kidney transplants (LDKT). DDKT showed a significant reduction in tubular cells, mainly proximal tubule cells, and higher proportion of macrophage infiltration compared to LDKT. A subgroup analysis of the DDKT group showed that patients who ultimately developed DGF exhibited a reduction in overall tubular cell number, mostly in the connecting tubules/collecting ducts, with a compensatory increase of stromal cells when compared to high-risk patients with immediate graft function. This analysis using IMC also revealed the presence of a small cell population in the proximal tubule that was vimentin + , megalinlow, and co-expressing Ki67 and KIM-1, both typical markers of injury, in close association with macrophage-enriched infiltrates. These data suggested that preimplantation tubular cell dropout can play an important role in the development of DGF (Table 2) [72].

To our knowledge, our group has been the first to apply IMC to characterize rejection in SOT by investigating the alloimmunity landscape in patients with chronic rejection (CR) post-liver transplantation [71]. A workflow of the entire study is illustrated in Fig. 3. Using a 10-marker pilot IMC panel, a total of 92,791 cell from 18 CR (14 adult and 4 children) and 16,454 cells from 5 normal liver tissues without rejection (no rejection, NR) resulted in 29 meta-clusters, including 11 subpopulations with immune markers. More than 90% of the immune subpopulations identified were present in CR, which demonstrated a greater proportion of macrophages, cytotoxic T cells, and two other CD3 + T cell subpopulations when compared to NR. Interesting, a distinct population of CD68 + macrophages was completely absent, and CD66 + neutrophils were more prominent in NR. Spatial relationships examined using neighborhood analysis demonstrated only rare interactions among immune subpopulations in NR tissue, while strong interactions were observed in CR, particularly within the two CD68 + macrophage subpopulations and the CD3 + CD8 + cytotoxic T cell populations (Fig. 3). Strong interactions were also observed between macrophages and cytotoxic T cells and macrophages and other T and B cells, strongly correlating with the upregulation of the alloimmune response observed in the CR (Table 2). Principal component analysis (PCA) showed that CD20, CD3, CD45, CD66, CD8, and HLA-DR contributed similarly to principal component 1 (PC1), and explained almost 52% of the difference in cell distribution between NR and CR. Additionally, logistic regression model demonstrated that PC1 could predict CR with a probability above 75%(Fig. 3) [71].

Fig. 3

Schematic representation of IMC workflow for investigation of chronic rejection in liver transplantation recipients. Liver tissue sections were obtained from patients who underwent re-transplantation for chronic rejection (CR) of the primary graft. Pre-implantation liver biopsies from donors were used as control for liver with no rejection (NR). Staining was performed using a cocktail of 11 antibodies coupled with metal tags targeting immune cells. Tissue ablation and measurement of the metal ion abundance by time-of-flight mass spectrometry was performed using Hyperion Imaging System. Multidimensional images were segmented using Ilastik and Cell Profiler. t-SNE plots were used for dimensionality reduction to visualize level of expression of individual markers for each cell. PhenoGraph was used to establish immune meta-cluster identification. Cell subpopulation proportions were compared between chronic CR and NR and difference in macrophage and neutrophil proportions were observed between the two cohorts. Principal component and regression analyses were performed and revealed that PC1 had a high accuracy in rejection prediction. (Created with Biorender.com)

II.D. Review of studies using IMC in organs used for SOTII.D.1 Kidney

The complex histopathologic organization of the human kidney makes IMC a well-suited technique to study cellular arrangement and interaction between parenchymal and immune cells with high resolution and essential spatial relationships. Using a 23-marker IMC and kidney-MAPPS (multiplexed antibody-based profiling with preservation of spatial context) pipeline on 16 histologically “normal” kidney samples, it was possible to recapitulate the cellular architecture of tubule, interstitium, and glomeruli of both renal cortex and medulla and identify 22 distinct cell populations, including a rare population of megalin + , aquaporin-1 + , and vimentin + cells that could represent an injured, fibrotic, or regenerative cell type, respectively [41]. Three tumor-remote specimens with immune infiltrate or interstitial nephritis visible on H&E were compared with healthy tissues, demonstrating fewer tubular, stromal, and endothelial cells as well as increase in immune cells mostly represented by CD4+ and CD8+ T cells and CD68+ macrophages [41]. Abundance of CD11b+ macrophages, CD11c+ dendritic cells, CD19+ B cells, and overproduction of TNFα were observed in single-cell analysis using IMC on kidney tissue from patients who died from SARS-CoV2 infection, suggesting a possible role of those cells in mediating multiorgan injuries, while the unequal B cell infiltration among various organs could be responsible for a different susceptibility and tissue-specific immune response to COVID-19 [73].

II.D.2 Liver

The liver is considered an immunologically privileged site, thus an attentive study of its sophisticated immune microenvironment remains essential to understand its response to chronic infection, tumor promoting/suppressing function, and tolerogenic state in transplantation. A 30-marker antibody panel was used to study patients with chronic HBV, showing greater immune cell enrichment, particularly CD4+ and CD8+ T cells, CD20+ B cells, and CD68+ Kupffer cells in the portal tracts of subjects with immune active disease compared to immunotolerant subjects [74]. Investigation of the functional state showed a greater activation (increased expression of HLA-DR, CD45RO, CD38) of immune cells in portal tracts of patients with immune active HBV infection. As well, both cell density and phenotype correlated with serum ALT level, inflammation, and fibrosis scores [74]. In a separate study examining the TME in hepatocellular carcinoma, spatial information gathered with IMC allowed identification of 22 meta-clusters and three distinct regions, with different distribution of stromal and immune cells [42]. Based on neighborhood analysis and identification of different interaction partners, Kupffer cells were hypothesized to be immunosuppressive and induce T cell exhaustion via PD-1-PD1L interaction, while infiltrating macrophages had stronger antigen presentation function, suggesting a tumor suppression role. Interestingly, the IMC data on cellular neighborhood correlated with patient prognosis, specifically that Kupffer cell enriched cellular neighborhoods were associated with worse patient and disease-free survival, while infiltrating macrophages were associated with prolonged survival. Thus, IMC analysis suggested that Kupffer cells may represent a potential target for hepatocellular carcinoma treatment [42].

II.D.3 Lung

The recent COVID-19 pandemic represented a further clinical setting where IMC has been adopted for a comprehensive examination of immune cells and cytokines involved in the infection response within the human lung. Using an IMC panel with 36 markers, Rendeiro et al. demonstrated that lungs from COVID-19 patients had significant macrophage infiltration, composed of predominantly interstitial macrophages, and a higher number of fibroblasts and mesenchymal cells were strongly correlated with increased lung fibrosis scores reported by the clinical pathologist. The observation of an augmented interaction between macrophages and fibroblasts or dendritic cells in the alveolar walls might represent an attempt to repair the tissue damage that results in fibrosis and thickening of the alveolar walls. The hyperinflammatory state as well as apoptosis initiation induced by SARS-CoV2 within alveolar epithelial cells was demonstrated by higher level of IL-6, CASP3 and C5b-C9 in infected cells compared to not infected cells [75]. In a multiorgan study by Wang et al. that included tissues from the lung, intestine, spleen, kidney, and liver obtained from patients with COVID-19 disease, the pulmonary immune infiltrates were constituted by CD11b+ macrophages producing IL-10 and CD11c+ dendritic cells, both characterized by low expression of HLA-DR. Thus, use of IMC highlights the pathophysiology and the dysregulated immune response observed in SARS-CoV2 infection, which may be the result of the activation of immunosuppressive pathway mediated by IL-10 and inhibition of HLA-DR activation on these two antigens presenting cell types, ultimately preventing the adaptive immune response [73].

IMC has also been used to investigate the heterogeneity of the tumor microenvironment (TME) in the study of both lung adenocarcinoma and squamous cell carcinoma, showing a strong interplay between cancer-associated fibroblasts and monocytic myeloid cells which were polarized to adopt a suppressor phenotype [76,77,78]. IMC also revealed recruitment and interaction of effector CD8+ and CD4+ T cells in the TME and their transition to a memory T cell phenotype, as well as the presence of CD33+ immunosuppressive cells. As well, a novel population of CD3−CD4+Foxp3+ cells negative for CD25 and CD127 with an unclear function was identified using IMC, which was hypothesized to have a proinflammatory role due to the high level of TNFα expression [78].

II.D.4. Pancreas

IMC has been used in two studies using human pancreata, aiming to better understand the pathophysiology of type 1 diabetes [79, 80]. Pseudotime analysis, an algorithm that can measure the progression of individuals along a certain biological process of interest based on a collection of high-dimensional molecular data, of 1,581 pancreatic islets was used by Damond et al., showing that patients with recent onset of diabetes had a near-normal fraction of β cells, although their phenotype was altered in the period preceding their autoimmune destruction [79]. More importantly, IMC analysis of spatial interactions between immune cells and islets showed that T-helper and cytotoxic T cells were more abundant at the onset stage, likely driving the immune-mediated destruction of islet cells. Conversely, these cells were less abundant in long duration diabetes, suggesting that T cell inflammation resolves after islet destruction [79]. Wang et al. reported progressive changes in the islet architecture, including reduction in vascular area and modification of the extracellular matrix, associated with ongoing reduction in the number of β cells until their complete disappearance. Analysis of 2,191 islets with a panel of 33 markers showed molecular and phenotype alterations in α cells, suggesting a possible role for transdifferentiation of α cells to β cells as a compensatory response to hyperglycemia. Echoing the previous study, enrichment in CD8+ T cells was found in those islets that still contained β cells, where upregulation of HLA-ABC on both endocrine and ductal cell types was associated with CD8+ T cell recruitment [80]. Analysis of more than 2 million cells from 13 nondiabetic and 16 type II diabetic donors using an IMC panel composed of 33 markers demonstrated a remodeling of the endocrine pancreas, with loss of β cells and simultaneous gain in α cells and accumulation of type I collagen [81]. Moreover, the intra-islet immune infiltration of patients with diabetes showed a twofold increase in HLA-DRhigh macrophages and HLA-DRhigh CD8 T cells when compared to healthy individuals, providing important insights in the phenotype of immune cells involved in type II diabetes [81].