The Clinical Relevance of the Infiltrating Immune Cell Composition in Kidney Transplant Rejection

BACKGROUND

The link between the histology of kidney transplant rejection, especially Antibody-mediated rejection, T cell-mediated rejection and Mixed rejection, and the types of infiltrating immune cells is currently not well charted. Cost and technical complexity of single cell analysis hinder large scale studies of the relationship between cell infiltrate profiles and histological heterogeneity.

METHODS

In this cross-sectional study, we assessed the composition of nine intragraft immune cell types by using a validated kidney transplant-specific signature matrix for deconvolution of bulk transcriptomics in three different kidney transplant biopsy datasets (N=403, N=224, N=282). The association and the discrimination of the immune cell types with the Banff histology and the association with graft failure were assessed individually and with multivariable models. Unsupervised clustering algorithms were applied on the overall immune cells composition and compared to the Banff phenotypes.

RESULTS

Banff-defined rejection was related to high presence of CD8+ effector T cells, Natural Killer cells, monocytes/macrophages and to a lesser extent B cells, whereas CD4+ memory T cells were lower in rejection compared to no rejection. Estimated intragraft effector memory-expressing CD45RA (TEMRA) CD8+ T cells were strongly and consistently associated with graft failure. The large heterogeneity in immune cell composition across rejection types prevented supervised and unsupervised methods to accurately recover the Banff phenotypes based solely on immune cell estimates. The lack of correlation between immune cell composition and Banff-defined rejection types was validated using multiplex immunohistochemistry.

CONCLUSIONS

Although some specific cell types (FCGR3A+ myeloid cells, CD14+ monocytes/macrophages and NK cells), partly discriminate between rejection phenotypes, the overall estimated immune cell composition of kidney transplants is ill related to main Banff-defined rejection categories and adds to the Banff lesion scoring and evaluation of rejection severity. The estimated intragraft CD8temra cells bear strong and consistent association with graft failure and independent of Banff-grade rejection.

A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma

To better understand intrinsic resistance to immune checkpoint blockade (ICB), we established a comprehensive view of the cellular architecture of the treatment-naive melanoma ecosystem and studied its evolution under ICB. Using single-cell, spatial multi-omics, we showed that the tumor microenvironment promotes the emergence of a complex melanoma transcriptomic landscape. Melanoma cells harboring a mesenchymal-like (MES) state, a population known to confer resistance to targeted therapy, were significantly enriched in early on-treatment biopsies from non-responders to ICB. TCF4 serves as the hub of this landscape by being a master regulator of the MES signature and a suppressor of the melanocytic and antigen presentation transcriptional programs. Targeting TCF4 genetically or pharmacologically, using a bromodomain inhibitor, increased immunogenicity and sensitivity of MES cells to ICB and targeted therapy. We thereby uncovered a TCF4-dependent regulatory network that orchestrates multiple transcriptional programs and contributes to resistance to both targeted therapy and ICB in melanoma.

Transcriptional and spatial profiling of the kidney allograft unravels a central role for FcyRIII+ innate immune cells in rejection

Rejection remains the main cause of premature graft loss after kidney transplantation, despite the use of potent immunosuppression. This highlights the need to better understand the composition and the cell-to-cell interactions of the alloreactive inflammatory infiltrate. Here, we performed droplet-based single-cell RNA sequencing of 35,152 transcriptomes from 16 kidney transplant biopsies with varying phenotypes and severities of rejection and without rejection, and identified cell-type specific gene expression signatures for deconvolution of bulk tissue. A specific association was identified between recipient-derived FCGR3A+ monocytes, FCGR3A+ NK cells and the severity of intragraft inflammation. Activated FCGR3A+ monocytes overexpressed CD47 and LILR genes and increased paracrine signaling pathways promoting T cell infiltration. FCGR3A+ NK cells overexpressed FCRL3, suggesting that antibody-dependent cytotoxicity is a central mechanism of NK-cell mediated graft injury. Multiplexed immunofluorescence using 38 markers on 18 independent biopsy slides confirmed this role of FcγRIII+ NK and FcγRIII+ nonclassical monocytes in antibody-mediated rejection, with specificity to the glomerular area. These results highlight the central involvement of innate immune cells in the pathogenesis of allograft rejection and identify several potential therapeutic targets that might improve allograft longevity.

CD4+ T cell-induced inflammatory cell death controls immune-evasive tumours

Most clinically applied cancer immunotherapies rely on the ability of CD8⁺ cytolytic T cells to directly recognize and kill tumour cells^1-3. These strategies are limited by the emergence of major histocompatibility complex (MHC)-deficient tumour cells and the formation of an immunosuppressive tumour microenvironment^4-6. The ability of CD4⁺ effector cells to contribute to antitumour immunity independently of CD8⁺ T cells is increasingly recognized, but strategies to unleash their full potential remain to be identified^7-10. Here, we describe a mechanism whereby a small number of CD4⁺ T cells is sufficient to eradicate MHC-deficient tumours that escape direct CD8⁺ T cell targeting. The CD4⁺ effector T cells preferentially cluster at tumour invasive margins where they interact with MHC-II⁺CD11c⁺ antigen-presenting cells. We show that T helper type 1 cell-directed CD4⁺ T cells and innate immune stimulation reprogramme the tumour-associated myeloid cell network towards interferon-activated antigen-presenting and iNOS-expressing tumouricidal effector phenotypes. Together, CD4⁺ T cells and tumouricidal myeloid cells orchestrate the induction of remote inflammatory cell death that indirectly eradicates interferon-unresponsive and MHC-deficient tumours. These results warrant the clinical exploitation of this ability of CD4⁺ T cells and innate immune stimulators in a strategy to complement the direct cytolytic activity of CD8⁺ T cells and natural killer cells and advance cancer immunotherapies.

Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis

Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma

BACKGROUND

Functional profiling of freshly isolated glioblastoma (GBM) cells is being evaluated as a next-generation method for precision oncology. While promising, its success largely depends on the method to evaluate treatment activity which requires sufficient resolution and specificity.

METHODS

Here, we describe the 'precision oncology by single-cell profiling using ex vivo readouts of functionality' (PROSPERO) assay to evaluate the intrinsic susceptibility of high-grade brain tumor cells to respond to therapy. Different from other assays, PROSPERO extends beyond life/death screening by rapidly evaluating acute molecular drug responses at single-cell resolution.

RESULTS

The PROSPERO assay was developed by correlating short-term single-cell molecular signatures using mass cytometry by time-of-flight (CyTOF) to long-term cytotoxicity readouts in representative patient-derived glioblastoma cell cultures (n = 14) that were exposed to radiotherapy and the small-molecule p53/MDM2 inhibitor AMG232. The predictive model was subsequently projected to evaluate drug activity in freshly resected GBM samples from patients (n = 34). Here, PROSPERO revealed an overall limited capacity of tumor cells to respond to therapy, as reflected by the inability to induce key molecular markers upon ex vivo treatment exposure, while retaining proliferative capacity, insights that were validated in patient-derived xenograft (PDX) models. This approach also allowed the investigation of cellular plasticity, which in PDCLs highlighted therapy-induced proneural-to-mesenchymal (PMT) transitions, while in patients' samples this was more heterogeneous.

CONCLUSION

PROSPERO provides a precise way to evaluate therapy efficacy by measuring molecular drug responses using specific biomarker changes in freshly resected brain tumor samples, in addition to providing key functional insights in cellular behavior, which may ultimately complement standard, clinical biomarker evaluations.

Abstract 6773: Spatial dynamics of cytotoxic T lymphocyte exhaustion in reactive and tumoral tissue

Background The study of cytotoxic T-lymphocytes (Tcy) has shown increased attention from the scientific community in the last years because of their predictive role in anti-cancer therapy with specific interest in immune check point blocking therapy. However, most of these studies have used bulk or dissociation-based single-cell technologies to draw their biological insights. Lately, new spatial -omics technologies are increasing our knowledge on this population by adding the spatial location of these cells in-situ in the native structure of the tissue. In this study, we have compared the activation of Tcy in reactive and cancerous conditions at single cell level and in the micro-anatomical context of the tissue.

Experimental procedures One tissue micro array slide containing: reactive tonsil, inflammatory liver disease, breast cancer, glioblastoma and melanoma was stained using the COMET™ instrument (Lunaphore Technologies SA) for a multiplex panel of 20 markers. The derived multiplexed images were analyzed using the DISSCOVERY software platform developed by the MILAN Unit at KU Leuven (Belgium). 12/20 markers were specifically aimed at identifying the main cell populations in the tissue (CD11b, CD163, CD20, CD3, CD31, CD4, CD56, CD68, CD8, CK, FOXP3, S100) while the remaining 8 markers were aimed at adding functional information on immune cell types of interest (CD69, HLA-DR, Ki67, LAG3, OX40, PD-1, PD-L1, TIM3).

Results The general activation levels of the Tcy in the reactive conditions were higher than in the three cancer subtypes. When looking at Tcy activation as a function of the distance from the vascular structures (identified via CD31+ endothelial cells), we observed an orderly distribution of activated Tcy around CD31+ endothelial cells with a gradient of increasing exhaustion levels with increasing distance from the vessel in the reactive conditions. In the cancer samples, on the contrary, a patchy disorderly organized pattern of exhausted and activated Tcy was observed around the vessels.

Conclusion The spatial location of inflammatory cells plays a critical role to understand their functional behavior and thanks to technological progress it is now possible to start doing this at scale. The study of the dynamics of exhaustion of Tcy in the tissue will help clarify the interplay between cancer cells and immune environment. These results will be crucial to better select patients who may benefit the most of immune check point blockade.

Citation Format: Maxim De Schepper, Asier Antoranz, Nikolina Dubroja, Giuseppe Floris, Frederik De Smet, Francesca Bosisio. Spatial dynamics of cytotoxic T lymphocyte exhaustion in reactive and tumoral tissue. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6773.

Ambra1 modulates the tumor immune microenvironment and response to PD-1 blockade in melanoma

BACKGROUND

Loss of Ambra1 (autophagy and beclin 1 regulator 1), a multifunctional scaffold protein, promotes the formation of nevi and contributes to several phases of melanoma development. The suppressive functions of Ambra1 in melanoma are mediated by negative regulation of cell proliferation and invasion; however, evidence suggests that loss of Ambra1 may also affect the melanoma microenvironment. Here, we investigate the possible impact of Ambra1 on antitumor immunity and response to immunotherapy.

METHODS

This study was performed using an Ambra1-depleted Braf^V600E /Pten^{-/ -} genetically engineered mouse (GEM) model of melanoma, as well as GEM-derived allografts of Braf^V600E /Pten^{-/ -} and Braf^V600E /Pten^{-/ -}/Cdkn2a^{-/ -} tumors with Ambra1 knockdown. The effects of Ambra1 loss on the tumor immune microenvironment (TIME) were analyzed using NanoString technology, multiplex immunohistochemistry, and flow cytometry. Transcriptome and CIBERSORT digital cytometry analyses of murine melanoma samples and human melanoma patients (The Cancer Genome Atlas) were applied to determine the immune cell populations in null or low-expressing AMBRA1 melanoma. The contribution of Ambra1 on T-cell migration was evaluated using a cytokine array and flow cytometry. Tumor growth kinetics and overall survival analysis in Braf^V600E /Pten^{-/ -}/Cdkn2a^{-/ -} mice with Ambra1 knockdown were evaluated prior to and after administration of a programmed cell death protein-1 (PD-1) inhibitor.

RESULTS

Loss of Ambra1 was associated with altered expression of a wide range of cytokines and chemokines as well as decreased infiltration of tumors by regulatory T cells, a subpopulation of T cells with potent immune-suppressive properties. These changes in TIME composition were associated with the autophagic function of Ambra1. In the Braf^V600E /Pten^{-/ -}/Cdkn2a^{-/ -} model inherently resistant to immune checkpoint blockade, knockdown of Ambra1 led to accelerated tumor growth and reduced overall survival, but at the same time conferred sensitivity to anti-PD-1 treatment.

CONCLUSIONS

This study shows that loss of Ambra1 affects the TIME and the antitumor immune response in melanoma, highlighting new functions of Ambra1 in the regulation of melanoma biology.

TMIC-37. SINGLE-CELL CHARACTERIZATION OF THE IMMUNE LANDSCAPE OF EXTREME LONG-TERM SURVIVORS WITH MALIGNANT GLIOMA

Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond two years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contribute significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and despite its dismal prognosis, small fractions of GBM patients seem to display extreme extended survival compared to the large majority of patients. The underlying mechanisms for this peculiarity remain largely unknown however, even though emerging data suggest that both cancer cell-autonomous and microenvironmental factors and their interplay probably play an important role. We used high-dimensional, multiplexed immunohistochemistry to spatially, and cytometry by time-of-flight to quantitively, characterize the cell constitution and interactions within the tumor microenvironment (TME) in 21 extreme long-term survivors (living over 10 year) and 42 deeply matched controls and therefore short-term survivors (living under 1.5 year) on a single cell level. For all tumors (epi)genetic data was also collected. We identified a high level of both inter-and intrapatient heterogeneity defined by several distinct tumoral niches, as well as described interactions within these niches and with the surrounding infiltrating immune cells of the TME in GBM. Finally, by linking patient characteristics with the heterogeneous immune composition we are able to create an immune stratification that can be linked to patient survival in GBM. Therefore, this study is an essential initial step towards strategies to alter the TME in a favorable way with a personalized modulation strategy.

Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response

While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI.

SIGNIFICANCE

This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.

KS05.7.A Characterization of the immune composition of extreme long-term survivors with malignant glioma at single-cell level

Background

Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond two years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contribute significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and in spite of its dismal prognosis, small fractions of GBM patients seem to display extended survival compared to the large majority of patients. The underlying mechanisms for this peculiarity remain largely unknown however, even though emerging data suggest that both cancer cell-autonomous and microenvironmental factors and their interplay probably play an important role.

Material and Methods

We used high-dimensional, multiplexed immunohistochemistry to spatially, and cytometry by time-of-flight to quantitively characterize the cell constitution and interactions within the tumor microenvironment (TME) in 21 extreme long-term survivors (living over ten years since primary diagnosis or five years after recurrence) and 42 deeply matched short-term controls (living under 1.5 year) on a single cell level. For all tumors (epi-)genetic data was also collected.

Results

We identified a high level of both inter-and intrapatient heterogeneity defined by several distinct tumor niches, as well as described interactions within these niches and with the surrounding infiltrating immune cells of the TME. By linking patient characteristics with the heterogeneous immune composition we are building an immune stratification that can be linked to patient survival in GBM.

Conclusion

Generating an immune stratification for GBM will allow us to identify immune characteristics responsible for longer or even exceptional survival, as well as thoroughly identify tumor components that may serve as a potential target for personalized treatment strategies. Therefore, this study is also an essential initial step towards such clinical trials which alter the TME in a favorable way with a personalized modulation strategy.

Next-Generation Pathology Using Multiplexed Immunohistochemistry: Mapping Tissue Architecture at Single-Cell Level

Single-cell omics aim at charting the different types and properties of all cells in the human body in health and disease. Over the past years, myriads of cellular phenotypes have been defined by methods that mostly required cells to be dissociated and removed from their original microenvironment, thus destroying valuable information about their location and interactions. Growing insights, however, are showing that such information is crucial to understand complex disease states. For decades, pathologists have interpreted cells in the context of their tissue using low-plex antibody- and morphology-based methods. Novel technologies for multiplexed immunohistochemistry are now rendering it possible to perform extended single-cell expression profiling using dozens of protein markers in the spatial context of a single tissue section. The combination of these novel technologies with extended data analysis tools allows us now to study cell-cell interactions, define cellular sociology, and describe detailed aberrations in tissue architecture, as such gaining much deeper insights in disease states. In this review, we provide a comprehensive overview of the available technologies for multiplexed immunohistochemistry, their advantages and challenges. We also provide the principles on how to interpret high-dimensional data in a spatial context. Similar to the fact that no one can just “read” a genome, pathological assessments are in dire need of extended digital data repositories to bring diagnostics and tissue interpretation to the next level.

HGG-56. Spatial mapping of the tumor micro-environment in pediatric glioma

High-grade glioma are the main cause of cancer-related death in children. The highly heterogeneous composition of the tumor cells and their interactions with the tumor micro-environment (TME), contribute substantially to the poor response to treatment and the high levels of morbidity and mortality. Here, we used high-dimensional, multiplexed immunohistochemistry to map the single-cell tissue architecture of 26 pediatric glioma samples covering 8 histologic diagnoses, allowing us to determine the spatial distribution of the various tumoral subtypes and how these interact with their local immune-microenvironment. Overall, this analysis showed that tumor grade anti-correlated with the amount of infiltrating cytotoxic T-lymphocytes (CTLs), which were typically more exhausted in the higher grade tumors. In addition, tumor associated macrophages were primarily infiltrating from the blood and presented an M2-like anti-inflammatory phenotype which became more extended with tumor grade. Using the spatial information, possible cell-cell interactions could be determined. In lower grade glioma, we observed an increased activation level of CTLs that were closely located to neighboring T-helper cells. In pediatric glioblastoma, on the other hand, CTLs, even though they were located close to a T-helper cell, could only minimally be activated, and showed more extended exhaustion when residing further away. Additionally, the activation of the CTLs was associated to the distance to the closest PD-L1 positive macrophage in pilocytic astrocytoma and desmoplastic infantile ganglioglioma. In conclusion, with the use of multiplex immunohistochemistry, we are able to study the tumor and TME of pediatric glioma in depth on a single-cell and spatial level, which allows us to further study the heterogeneous landscape of these tumors.

TMOD-22. DIFFERENTIAL DRUG SENSITIVITY ANALYSIS IN PAIRED PATIENT-DERIVED CELL LINES OF GLIOBLASTOMA

Glioblastoma (GBM) remains the most aggressive adult brain tumour with dismal prognosis. Even when treated by the most optimal standard-of-care modalities, disease progression remains consistently inevitable. Understanding how tumours evolve from a newly diagnosed to a recurrent setting is therefore critical, but research models to functionally test how therapeutic interventions evolve accordingly remain scarce. Here, we describe our efforts to develop paired models including newly diagnosed and recurrent GBM cell lines derived from the same patients. Overall, we collected 50 tumour samples originating from 24 patients at different time points in their treatment scheme. This resulted in the generation of 27 models overall, from which 18 originated from 9 patients at different timepoints. The latter were subsequently investigated extensively. First, using genomic profiling, we consistently observed an increase in mutational burden and chromosomal aberrations in the recurrent samples, while transcriptomic profiling showed that tumour subtypes evolved in a very patient-specific way. A large fraction of the recurrent models showed resistance to temozolomide (TMZ), which coincided with a downregulation of DNA repair (MMR) pathways or mutations. Half of the tested models also acquired resistance to radiation therapy. Next to standard-of-care therapy, we investigated several small molecule inhibitors that are currently in clinical evaluation, which also showed differential sensitivity. Overall, the developed paired cell lines recapitulate the most important features related to tumour recurrence, and offer the opportunity for more elaborate dependency screening efforts.

EXTH-20. SINGLE-CELL DRUG ACTIVITY MAPPING IN GLIOBLASTOMA IDENTIFIES EXTENDED DRUG RESPONSE HETEROGENEITY AND THERAPY-INDUCED CELLULAR PLASTICITY

Glioblastoma (GBM) remains a highly malignant and incurable brain tumour. The inability to achieve clinical improvements in GBM treatment can be attributed to the excessive heterogeneity and plasticity of GBM cells, which is reflected by the presence of various cellular states within each tumour. How each of these tumour cell subtypes respond to therapy remains largely unknown. In this work, we developed a functional diagnostic analysis pipeline to measure therapeutic activity in GBM tumour cells at single-cell resolution using mass cytometry by time-of-flight (CyTOF). By applying an optimised GBM-specific and therapy-tailored antibody panel, we measured therapeutic activity upon exposure to ionising radiation (RT) or a small molecule MDM2 inhibitor (AMG232) in a cohort of patient-derived GBM cell lines (n=14). As such, extended heterogeneity in drug responsiveness was reflected by diverse degrees of alterations in cell cycle progression and apoptotic signalling, in addition to shifts in tumoral phenotypic states implying therapy-induced plasticity. A similar approach was used to measure drug activity in freshly resected tumour samples (n=18) harvested from different tumour regions (core or invasive front) within hours following surgery. Accordingly, we identified highly variable fractions of responsive tumour and microenvironmental cell populations in a patient-specific way. The ability to measure drug activity at single-cell resolution in a patient-tailored manner by applying a genotype-agnostic method, paves the way for advanced precision cancer medicine in GBM by offering a novel approach to more precisely select eligible patients for prospective clinical trials.

PATH-21. THE SINGLE-CELL PATHOLOGY LANDSCAPE OF PEDIATRIC GLIOMA

High-grade glioma are the main cause of cancer-related death in children. Despite extensive research, their prognosis remains poor with very few treatment options. This can be attributed to the highly heterogeneous and plastic nature of glioma tumor cells and their interactions with the microenvironment, although quantitative data are still largely missing. Here, we used high-dimensional, multiplexed immunohistochemistry to map the spatial, single-cell tissue architecture of 31 pediatric glioma samples covering 9 histologic diagnoses. This novel approach allowed us to map the spatial distribution of the various tumoral subtypes, which typically occur in specific tumoral niches, and how these interact with their local immune-microenvironment. Finally, by aligning these findings to the clinical data of the patients and comparing these to adult glioblastoma, we are now able to more precisely describe the heterogeneous landscape of pediatric glioma at single-cell resolution.

PATH-20. SPATIAL MAPPING OF THERAPY-INDUCED, PATHOLOGICAL CHANGES IN GLIOBLASTOMA AT SINGLE-CELL RESOLUTION

Glioblastoma (GBM) remains a highly malignant, intrinsically resistant and inevitably recurring brain tumor with dismal prognosis. The aggressiveness and lack of effective GBM treatments can be attributed to the highly heterogeneous and plastic nature of GBM tumor cells, which easily confer resistance to standard-of-care (SOC) therapy. While tumor progression has also been attributed to interactions with the tumor microenvironment, quantitative data describing these interactions are still largely missing. Here, we used high-dimensional, multiplexed immunohistochemistry to map evolutions in the spatial, single-cell tissue architecture of 120 paired adult GBM tumor samples derived from 60 patients at diagnosis (ND) and upon recurrence (REC) following SOC treatment. We mapped the spatial distribution of a multitude of GBM tumoral subtypes across this multicentric cohort, through which we identified a high level of heterogeneity defined by specific tumoral niches within and across patients and which evolved when subjected to SOC therapy. In addition, we describe the relationship of the various tumoral niches with their local immune-infiltrates, highlighting an even more immunosuppressive environment following SOC resistance. Finally, by aligning these findings to the observed genomic aberrations and the clinical data of the patients, we are now able to more precisely describe the heterogeneous landscape of glioblastoma and how it evolves under SOC treatment at spatial, single-cell resolution.

A fully defined matrix to support a pluripotent stem cell derived multi-cell-liver steatohepatitis and fibrosis model

Chronic liver injury, as observed in non-alcoholic steatohepatitis (NASH), progressive fibrosis, and cirrhosis, remains poorly treatable. Steatohepatitis causes hepatocyte loss in part by a direct lipotoxic insult, which is amplified by derangements in the non-parenchymal cellular (NPC) interactive network wherein hepatocytes reside, including, hepatic stellate cells, liver sinusoidal endothelial cells and liver macrophages. To create an in vitro culture model encompassing all these cells, that allows studying liver steatosis, inflammation and fibrosis caused by NASH, we here developed a fully defined hydrogel microenvironment, termed hepatocyte maturation (HepMat) gel, that supports maturation and maintenance of pluripotent stem cell (PSC) derived hepatocyte- and NPC-like cells for at least one month. The HepMat-based co-culture system modeled key molecular and functional features of TGFβ-induced liver fibrosis and fatty-acid induced inflammation and fibrosis better than monocultures of its constituent cell populations. The novel co-culture system should open new avenues for studying mechanisms underlying liver steatosis, inflammation and fibrosis as well as for assessing drugs counteracting these effects.

Monocyte-driven atypical cytokine storm and aberrant neutrophil activation as key mediators of COVID-19 disease severity

Epidemiological and clinical reports indicate that SARS-CoV-2 virulence hinges upon the triggering of an aberrant host immune response, more so than on direct virus-induced cellular damage. To elucidate the immunopathology underlying COVID-19 severity, we perform cytokine and multiplex immune profiling in COVID-19 patients. We show that hypercytokinemia in COVID-19 differs from the interferon-gamma-driven cytokine storm in macrophage activation syndrome, and is more pronounced in critical versus mild-moderate COVID-19. Systems modelling of cytokine levels paired with deep-immune profiling shows that classical monocytes drive this hyper-inflammatory phenotype and that a reduction in T-lymphocytes correlates with disease severity, with CD8+ cells being disproportionately affected. Antigen presenting machinery expression is also reduced in critical disease. Furthermore, we report that neutrophils contribute to disease severity and local tissue damage by amplification of hypercytokinemia and the formation of neutrophil extracellular traps. Together our findings suggest a myeloid-driven immunopathology, in which hyperactivated neutrophils and an ineffective adaptive immune system act as mediators of COVID-19 disease severity.

Multiplexed Immunohistochemistry and Digital Pathology as the Foundation for Next-Generation Pathology in Melanoma: Methodological Comparison and Future Clinical Applications

The state-of-the-art for melanoma treatment has recently witnessed an enormous revolution, evolving from a chemotherapeutic, "one-drug-for-all" approach, to a tailored molecular- and immunological-based approach with the potential to make personalized therapy a reality. Nevertheless, methods still have to improve a lot before these can reliably characterize all the tumoral features that make each patient unique. While the clinical introduction of next-generation sequencing has made it possible to match mutational profiles to specific targeted therapies, improving response rates to immunotherapy will similarly require a deep understanding of the immune microenvironment and the specific contribution of each component in a patient-specific way. Recent advancements in artificial intelligence and single-cell profiling of resected tumor samples are paving the way for this challenging task. In this review, we provide an overview of the state-of-the-art in artificial intelligence and multiplexed immunohistochemistry in pathology, and how these bear the potential to improve diagnostics and therapy matching in melanoma. A major asset of in-situ single-cell profiling methods is that these preserve the spatial distribution of the cells in the tissue, allowing researchers to not only determine the cellular composition of the tumoral microenvironment, but also study tissue sociology, making inferences about specific cell-cell interactions and visualizing distinctive cellular architectures - all features that have an impact on anti-tumoral response rates. Despite the many advantages, the introduction of these approaches requires the digitization of tissue slides and the development of standardized analysis pipelines which pose substantial challenges that need to be addressed before these can enter clinical routine.

Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization

Glioblastomas are aggressive primary brain cancers that recur as therapy-resistant tumors. Myeloid cells control glioblastoma malignancy, but their dynamics during disease progression remain poorly understood. Here, we employed single-cell RNA sequencing and CITE-seq to map the glioblastoma immune landscape in mouse tumors and in patients with newly diagnosed disease or recurrence. This revealed a large and diverse myeloid compartment, with dendritic cell and macrophage populations that were conserved across species and dynamic across disease stages. Tumor-associated macrophages (TAMs) consisted of microglia- or monocyte-derived populations, with both exhibiting additional heterogeneity, including subsets with conserved lipid and hypoxic signatures. Microglia- and monocyte-derived TAMs were self-renewing populations that competed for space and could be depleted via CSF1R blockade. Microglia-derived TAMs were predominant in newly diagnosed tumors, but were outnumbered by monocyte-derived TAMs following recurrence, especially in hypoxic tumor environments. Our results unravel the glioblastoma myeloid landscape and provide a framework for future therapeutic interventions.

A Multi-Omics Analysis of Metastatic Melanoma Identifies a Germinal Center-Like Tumor Microenvironment in HLA-DR-Positive Tumor Areas

The emergence of immune checkpoint inhibitors has dramatically changed the therapeutic landscape for patients with advanced melanoma. However, relatively low response rates and a high incidence of severe immune-related adverse events have prompted the search for predictive biomarkers. A positive predictive value has been attributed to the aberrant expression of Human Leukocyte Antigen-DR (HLA-DR) by melanoma cells, but it remains unknown why this is the case. In this study, we have examined the microenvironment of HLA-DR positive metastatic melanoma samples using a multi-omics approach. First, using spatial, single-cell mapping by multiplexed immunohistochemistry, we found that the microenvironment of HLA-DR positive melanoma regions was enriched by professional antigen presenting cells, including classical dendritic cells and macrophages, while a more general cytotoxic T cell exhaustion phenotype was present in these regions. In parallel, transcriptomic analysis on micro dissected tissue from HLA-DR positive and HLA-DR negative areas showed increased IFNγ signaling, enhanced leukocyte adhesion and mononuclear cell proliferation in HLA-DR positive areas. Finally, multiplexed cytokine profiling identified an increased expression of germinal center cytokines CXCL12, CXCL13 and CCL19 in HLA-DR positive metastatic lesions, which, together with IFNγ and IL4 could serve as biomarkers to discriminate tumor samples containing HLA-DR overexpressing tumor cells from HLA-DR negative samples. Overall, this suggests that HLA-DR positive areas in melanoma attract the anti-tumor immune cell infiltration by creating a dystrophic germinal center-like microenvironment where an enhanced antigen presentation leads to an exhausted microenvironment, nevertheless representing a fertile ground for a better efficacy of anti-PD-1 inhibitors due to simultaneous higher levels of PD-1 in the immune cells and PD-L1 in the HLA-DR positive melanoma cells.

High dimensional profiling identifies specific immune types along the recovery trajectories of critically ill COVID19 patients

The COVID-19 pandemic poses a major burden on healthcare and economic systems across the globe. Even though a majority of the population develops only minor symptoms upon SARS-CoV-2 infection, a significant number are hospitalized at intensive care units (ICU) requiring critical care. While insights into the early stages of the disease are rapidly expanding, the dynamic immunological processes occurring in critically ill patients throughout their recovery at ICU are far less understood. Here, we have analysed whole blood samples serially collected from 40 surviving COVID-19 patients throughout their recovery in ICU using high-dimensional cytometry by time-of-flight (CyTOF) and cytokine multiplexing. Based on the neutrophil-to-lymphocyte ratio (NLR), we defined four sequential immunotypes during recovery that correlated to various clinical parameters, including the level of respiratory support at concomitant sampling times. We identified classical monocytes as the first immune cell type to recover by restoration of HLA-DR-positivity and the reduction of immunosuppressive CD163 + monocytes, followed by the recovery of CD8 + and CD4 + T cell and non-classical monocyte populations. The identified immunotypes also correlated to aberrant cytokine and acute-phase reactant levels. Finally, integrative analysis of cytokines and immune cell profiles showed a shift from an initially dysregulated immune response to a more coordinated immunogenic interplay, highlighting the importance of longitudinal sampling to understand the pathophysiology underlying recovery from severe COVID-19.

SOX10 is as specific as S100 protein in detecting metastases of melanoma in lymph nodes and is recommended for sentinel lymph node assessment

BACKGROUND

Sentinel lymph node (SLN) biopsy remains crucial for melanoma staging. The European Organisation for Research and Treatment of Cancer Melanoma Group recommends performing immunohistochemical stainings for reproducible identification of melanoma metastases. S100 protein (pS100) is a commonly used melanocytic antigen because of its high sensitivity in spite of relatively low specificity. SRY-related HMG-box 10 protein (SOX10) is a transcription factor characterising neural crest-derived cells. It is uniformly expressed mostly in the nuclei of melanocytes, neural, and myoepithelial cells. Pathologists sometimes prefer SOX10 as a melanoma marker, but it has not yet been investigated on a large-scale to confirm that it is reliable and recommendable for routine SLN evaluation.

METHODS

Four hundred one treatment-naïve lymph node (LN) metastatic melanomas were included in high-density tissue microarrays and were assessed for the presence of SOX10 and pS100 by immunohistochemistry. The slides were digitalised, shared and evaluated by a panel of experienced melanoma pathologists.

RESULTS

The vast majority of melanomas were double-positive for pS100 and SOX10 (93.2%); a small percentage of the cases (3.9%) were double-negative melanomas. Discordance between the two markers was observed: 1.9% pS100(-)/SOX10(+) and 0.75% pS100(+)/SOX10(-). SOX10 was not expressed by immune cell types in the LN, resulting in a less controversial interpretation of the staining.

CONCLUSIONS

SOX10 is as equally specific as pS100 for the detection of melanoma metastases in LNs. The interpretation of SOX10 staining is highly reproducible among different centres and different pathologists because of the absence of staining of immune cells.

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4⁺ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Computerised scoring protocol for identification and quantification of different immune cell populations in breast tumour regions by the use of QuPath software

AIMS

As important prognostic and predictive information can be obtained from the composition, functionality and spatial arrangement of different immune cell subtypes, this study aims at characterizing the immune infiltrate in breast tumours.

METHODS AND RESULTS

Tumour-infiltrating lymphocytes (TILs) in 62 patients with luminal B-like breast cancer were characterised by immunohistochemical staining with standard markers, and were subsequently classified and quantified by the use of QuPath software. In different delineated tumour regions, the proportion and density of CD3⁺ , CD4⁺ , CD5⁺ , CD8⁺ , CD20⁺ and FOXP3⁺ cells were assessed. The results of the software analysis were compared with those of manual counting for CD8 and CD20 staining. The QuPath scoring protocol slightly overestimated positive, negative and total lymphocyte counts and density, while minimally underestimating the proportion of positively stained lymphocytes. However, for density and proportion, no real differences from manual counting were observed. For all markers, the density of positively stained immune cells was higher in the invasive front than in the tumour centre, pointing to an accumulation of immune cells near the tumour boundaries. When we looked at the proportion of immunohistochemically positive immune cells, we observed enrichment of CD5 (P = 0.025) and CD20 (P < 0.001) at the periphery, and FOXP3 enrichment in the centre (P < 0.001).

CONCLUSION

The QuPath scoring protocol can adequately identify positively stained immune cells in breast tumours, and allows the evaluation of differences in immune cell proportion and density within different tumour regions. The entire tumour section can be quantitatively assessed quite rapidly, which is a major advantage over manual counting.

Functional heterogeneity of lymphocytic patterns in primary melanoma dissected through single-cell multiplexing

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into 'brisk', 'non-brisk' and 'absent' entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single-cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns are heterogeneous functional categories that can be further sub-classified into active, transitional or exhausted. The classification of primary melanomas based on the functional paradigm also shows correlation with spontaneous regression, and an improved prognostic value when compared to that of the brisk classification. Finally, the main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis.

A Functional Landscape of CKD Entities From Public Transcriptomic Data

Introduction

To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.

Methods

We integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure.

Results

We performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib.

Conclusion

These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sensitisation strategies in melanoma

Malignant melanoma is a highly aggressive form of skin cancer responsible for the majority of skin cancer-related deaths. Recent insight into the heterogeneous nature of melanoma suggests more personalised treatments may be necessary to overcome drug resistance and improve patient care. To this end, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified. In this study, we applied multiplex phosphoproteomic profiling across a panel of 24 melanoma cell lines with different disease-relevant mutations, to predict responsiveness to MEK inhibitor trametinib. Supported by multivariate statistical analysis and multidimensional pattern recognition algorithms, the responsiveness of individual cell lines to trametinib could be predicted with high accuracy (83% correct predictions), independent of mutation status. We also successfully employed this approach to case specifically predict whether individual melanoma cell lines could be sensitised to trametinib. Our predictions identified that combining MEK inhibition with selective targeting of c-JUN and/or FAK, using siRNA-based depletion or pharmacological inhibitors, sensitised resistant cell lines and significantly enhanced treatment efficacy. Our study indicates that multiplex proteomic analyses coupled with pattern recognition approaches could assist in personalising trametinib-based treatment decisions in the future.

Network-based technologies for early drug discovery

Although the traditional drug discovery approach has led to the development of many successful drugs, the attrition rates remain high. Recent advances in systems-oriented approaches (systems-biology and/or pharmacology) and 'omics technologies has led to a plethora of new computational tools that promise to enable a more-informed and successful implementation of the reductionist, one drug for one target for one disease, approach. These tools, based on biomolecular pathways and interaction networks, offer a systematic approach to unravel the mechanism(s) of a disease and link them to the chemical space and network footprint of a drug. Drug discovery can draw upon this holistic approach to identify the most-promising targets and compounds during the early phases of development.