Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy

Interleukin 17 signaling supports clinical benefit of dual CTLA-4 and PD-1 checkpoint inhibition in melanoma

Recent studies suggest that BRAFV600-mutated melanomas in particular respond to dual anti-programmed cell death protein 1 (PD-1) and anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) immune checkpoint inhibition (ICI). Here we identified an over-representation of interleukin (IL)-17-type 17 helper T (TH17) gene expression signatures (GES) in BRAFV600-mutated tumors. Moreover, high baseline IL-17 GES consistently predicted clinical responses in dual-ICI-treated patient cohorts but not in mono anti-CTLA-4 or anti-PD-1 ICI cohorts. High IL-17 GES corresponded to tumor infiltration with T cells and neutrophils. Accordingly, high neutrophil infiltration correlated with clinical response specifically to dual ICI, and tumor-associated neutrophils also showed strong IL-17-TH17 pathway activity and T cell activation capacity. Both the blockade of IL-17A and the depletion of neutrophils impaired dual-ICI response and decreased T cell activation. Finally, high IL-17A levels in the blood of patients with melanoma indicated a higher global TH17 cytokine profile preceding clinical response to dual ICI but not to anti-PD-1 monotherapy, suggesting a future role as a biomarker for patient stratification.

A distinct stimulatory cDC1 subpopulation amplifies CD8+ T cell responses in tumors for protective anti-cancer immunity

Type 1 conventional dendritic cells (cDC1) can support T cell responses within tumors but whether this determines protective versus ineffective anti-cancer immunity is poorly understood. Here, we use imaging-based deep learning to identify intratumoral cDC1-CD8+ T cell clustering as a unique feature of protective anti-cancer immunity. These clusters form selectively in stromal tumor regions and constitute niches in which cDC1 activate TCF1+ stem-like CD8+ T cells. We identify a distinct population of immunostimulatory CCR7neg cDC1 that produce CXCL9 to promote cluster formation and cross-present tumor antigens within these niches, which is required for intratumoral CD8+ T cell differentiation and expansion and promotes cancer immune control. Similarly, in human cancers, CCR7neg cDC1 interact with CD8+ T cells in clusters and are associated with patient survival. Our findings reveal an intratumoral phase of the anti-cancer T cell response orchestrated by tumor-residing cDC1 that determines protective versus ineffective immunity and could be exploited for cancer therapy.

Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response

In recent years, the application of advanced analytics, especially artificial intelligence (AI), to digital H&E images, and other histological image types, has begun to radically change how histological images are used in the clinic. Alongside the recognition that the tumour microenvironment (TME) has a profound impact on tumour phenotype, the technical development of highly multiplexed immunofluorescence platforms has enhanced the biological complexity that can be captured in the TME with high precision. AI has an increasingly powerful role in the recognition and quantitation of image features and the association of such features with clinically important outcomes, as occurs in distinct stages in conventional machine learning. Deep-learning algorithms are able to elucidate TME patterns inherent in the input data with minimum levels of human intelligence and, hence, have the potential to achieve clinically relevant predictions and discovery of important TME features. Furthermore, the diverse repertoire of deep-learning algorithms able to interrogate TME patterns extends beyond convolutional neural networks to include attention-based models, graph neural networks, and multimodal models. To date, AI models have largely been evaluated retrospectively, outside the well-established rigour of prospective clinical trials, in part because traditional clinical trial methodology may not always be suitable for the assessment of AI technology. However, to enable digital pathology-based advanced analytics to meaningfully impact clinical care, specific measures of 'added benefit' to the current standard of care and validation in a prospective setting are important. This will need to be accompanied by adequate measures of explainability and interpretability. Despite such challenges, the combination of expanding datasets, increased computational power, and the possibility of integration of pre-clinical experimental insights into model development means there is exciting potential for the future progress of these AI applications. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumor-derived GDF-15 blocks LFA-1 dependent T cell recruitment and suppresses responses to anti-PD-1 treatment

Immune checkpoint blockade therapy is beneficial and even curative for some cancer patients. However, the majority don't respond to immune therapy. Across different tumor types, pre-existing T cell infiltrates predict response to checkpoint-based immunotherapy. Based on in vitro pharmacological studies, mouse models and analyses of human melanoma patients, we show that the cytokine GDF-15 impairs LFA-1/β2-integrin-mediated adhesion of T cells to activated endothelial cells, which is a pre-requisite of T cell extravasation. In melanoma patients, GDF-15 serum levels strongly correlate with failure of PD-1-based immune checkpoint blockade therapy. Neutralization of GDF-15 improves both T cell trafficking and therapy efficiency in murine tumor models. Thus GDF-15, beside its known role in cancer-related anorexia and cachexia, emerges as a regulator of T cell extravasation into the tumor microenvironment, which provides an even stronger rationale for therapeutic anti-GDF-15 antibody development.

CellSighter: a neural network to classify cells in highly multiplexed images

Multiplexed imaging enables measurement of multiple proteins in situ, offering an unprecedented opportunity to chart various cell types and states in tissues. However, cell classification, the task of identifying the type of individual cells, remains challenging, labor-intensive, and limiting to throughput. Here, we present CellSighter, a deep-learning based pipeline to accelerate cell classification in multiplexed images. Given a small training set of expert-labeled images, CellSighter outputs the label probabilities for all cells in new images. CellSighter achieves over 80% accuracy for major cell types across imaging platforms, which approaches inter-observer concordance. Ablation studies and simulations show that CellSighter is able to generalize its training data and learn features of protein expression levels, as well as spatial features such as subcellular expression patterns. CellSighter's design reduces overfitting, and it can be trained with only thousands or even hundreds of labeled examples. CellSighter also outputs a prediction confidence, allowing downstream experts control over the results. Altogether, CellSighter drastically reduces hands-on time for cell classification in multiplexed images, while improving accuracy and consistency across datasets.

Expanded vacuum-stable gels for multiplexed high-resolution spatial histopathology

Cellular organization and functions encompass multiple scales in vivo. Emerging high-plex imaging technologies are limited in resolving subcellular biomolecular features. Expansion Microscopy (ExM) and related techniques physically expand samples for enhanced spatial resolution, but are challenging to be combined with high-plex imaging technologies to enable integrative multiscaled tissue biology insights. Here, we introduce Expand and comPRESS hydrOgels (ExPRESSO), an ExM framework that allows high-plex protein staining, physical expansion, and removal of water, while retaining the lateral tissue expansion. We demonstrate ExPRESSO imaging of archival clinical tissue samples on Multiplexed Ion Beam Imaging and Imaging Mass Cytometry platforms, with detection capabilities of > 40 markers. Application of ExPRESSO on archival human lymphoid and brain tissues resolved tissue architecture at the subcellular level, particularly that of the blood-brain barrier. ExPRESSO hence provides a platform for extending the analysis compatibility of hydrogel-expanded biospecimens to mass spectrometry, with minimal modifications to protocols and instrumentation.

Predictive value of CXCL10 for the occurrence of immune-related adverse events in patient with renal cell carcinoma

Immune checkpoint inhibitors (ICIs) have recently improved the prognosis of various cancers. By contrast, some immune-related adverse events (irAEs) caused by ICIs are fatal and have become problematic. The pathogenesis of irAEs remains unknown and must be elucidated to establish biomarkers. This study investigated plasma cytokine, chemokine, and anti-CD74 autoantibody levels in patients with renal cell carcinoma (RCC) and analyzed their association with irAEs. In a discovery cohort of 13 patients, plasma levels of chemokine (C-X-C motif) ligand (CXCL) 1, IL-17A, IL-1β, IL-6, IL-8, CXCL10, MCP-1, and TNFα were measured at baseline and post-dose 1. Only CXCL10, at post-dose 1 but not at baseline, was significantly associated with grade 2 or higher irAEs (P = 0.0413). Plasma CXCL10 levels were then measured at baseline and post-dose 1 in an extended cohort of 43 patients with RCC who received ICI-based treatment. Higher plasma CXCL10 levels both at baseline and post-dose1 were significantly associated with the occurrence of grade 2 or higher irAEs (P = 0.0246 and 0.0137, respectively). Plasma CXCL13 levels, which we measured in a previous study, were significantly higher in patients with grade 2 or higher irAEs at baseline but not at post-dose 1 (P = 0.0037 and 0.052, respectively). No significant association between plasma anti-CD74 autoantibody level and both irAE pneumonitis and any grade 2 or higher irAE was observed. In conclusion, plasma CXCL10 is significantly associated with the occurrence of irAEs in patients with RCC treated with ICIs. CXCL10 is a potential predictive and on-treatment biomarker for irAEs.

Tertiary lymphoid structures and cytokines interconnections: The implication in cancer immunotherapy

Tertiary lymphoid structures (TLSs) are organized aggregates of lymphocytes and antigen-presenting cells that develop in non-lymphoid tissues during chronic inflammation, resembling the structure and features of secondary lymphoid organs. Numerous studies have shown that TLSs may be an important source of antitumor immunity within solid tumors, facilitating T cell and B cell differentiation and the subsequent production of antitumor antibodies, which are beneficial for cancer prognosis and responses to immunotherapy. The formation of TLS relies on the cytokine signaling network between heterogeneous cell populations, such as stromal cells, lymphocytes and cancer cells. The coordinated action of various cytokines drives the complex process of TLS development. In this review, we will comprehensively describe the mechanisms by which various cytokines regulate TLS formation and function, and the recent advancements and therapeutic potential of exploiting these mechanisms to induce TLS as an emerging immunotherapeutic approach or to enhance existing immunotherapy.

Mechanistic rationales for combining immunotherapy with radiotherapy

Immunotherapy consisted mainly of immune checkpoint inhibitors (ICIs) has led to significantly improved antitumor response. However, such response has been observed only in tumors possessing an overall responsive tumor immune micro-environment (TIME), in which the presence of functional tumor-infiltrating lymphocytes (TILs) is critical. Various mechanisms of immune escape from immunosurveillance exist, leading to different TIME phenotypes in correlation with primary or acquired resistance to ICIs. Radiotherapy has been shown to induce antitumor immunity not only in the irradiated primary tumor, but also at unirradiated distant sites of metastases. Such antitumor immunity is mainly elicited by radiation's stimulatory effects on antigenicity and adjuvanticity. Furthermore, it may be significantly augmented when irradiation is combined with immunotherapy, such as ICIs. Therefore, radiotherapy represents one potential therapeutic strategy to restore anti-tumor immunity in tumors presenting with an unresponsive TIME. In this review, the generation of anti-tumor immunity, its impairment, radiation's immunogenic properties, and the antitumor effects of combining radiation with immunotherapy will be comprehensively discussed.

Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments

The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then generate melanoma histocytometry whole slide images and verify that CISA can detect similar interactions across data modalities. Interestingly, CISA histoctyometry analysis also reveals that T-cell:macrophage synapse formation is associated with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.

cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data

Highly multiplexed imaging enables single-cell-resolved detection of numerous biological molecules in their spatial tissue context. Interactive data visualization of multiplexed imaging data is necessary for quality control and hypothesis examination. Here, we describe cytoviewer, an R/Bioconductor package for interactive visualization and exploration of multi-channel images and segmentation masks. The cytoviewer package supports flexible generation of image composites, allows side-by-side visualization of single channels, and facilitates the spatial visualization of single-cell data in the form of segmentation masks. The package operates on SingleCellExperiment, SpatialExperiment and CytoImageList objects and therefore integrates with the Bioconductor framework for single-cell and image analysis. Users of cytoviewer need little coding expertise, and the graphical user interface allows user-friendly navigation. We showcase the functionality of cytoviewer by analysis of an imaging mass cytometry dataset of cancer patients.

B cell-rich niches support stem-like CD8+ T cells in cancer microenvironment

Cytotoxic T cells are indispensable for the body's fight against most cancers. In the current issue of Cancer Cell, Gaglia et al. reveal how changes in the tumor tissue architecture creating niches of T cell-B cell interactions may support anti-tumor T cell responses.

Dissecting metastasis using preclinical models and methods

Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.

Identification of Hub Genes and Biological Mechanisms Associated with Non-Alcoholic Fatty Liver Disease and Triple-Negative Breast Cancer

The relationship between non-alcoholic fatty liver disease (NAFLD) and triple-negative breast cancer (TNBC) has been widely recognized, but the underlying mechanisms are still unknown. The objective of this study was to identify the hub genes associated with NAFLD and TNBC, and to explore the potential co-pathogenesis and prognostic linkage of these two diseases. We used GEO, TCGA, STRING, ssGSEA, and Rstudio to investigate the common differentially expressed genes (DEGs), conduct functional and signaling pathway enrichment analyses, and determine prognostic value between TNBC and NAFLD. GO and KEGG enrichment analyses of the common DEGs showed that they were enriched in leukocyte aggregation, migration and adhesion, apoptosis regulation, and the PPAR signaling pathway. Fourteen candidate hub genes most likely to mediate NAFLD and TNBC occurrence were identified and validation results in a new cohort showed that ITGB2, RAC2, ITGAM, and CYBA were upregulated in both diseases. A univariate Cox analysis suggested that high expression levels of ITGB2, RAC2, ITGAM, and CXCL10 were associated with a good prognosis in TNBC. Immune infiltration analysis of TNBC samples showed that NCF2, ICAM1, and CXCL10 were significantly associated with activated CD8 T cells and activated CD4 T cells. NCF2, CXCL10, and CYBB were correlated with regulatory T cells and myeloid-derived suppressor cells. This study demonstrated that the redox reactions regulated by the NADPH oxidase (NOX) subunit genes and the transport and activation of immune cells regulated by integrins may play a central role in the co-occurrence trend of NAFLD and TNBC. Additionally, ITGB2, RAC2, and ITGAM were upregulated in both diseases and were prognostic protective factors of TNBC; they may be potential therapeutic targets for treatment of TNBC patients with NAFLD, but further experimental studies are still needed.

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Different approaches to Imaging Mass Cytometry data analysis

Imaging Mass Cytometry (IMC) is a novel, high multiplexing imaging platform capable of simultaneously detecting and visualizing up to 40 different protein targets. It is a strong asset available for in-depth study of histology and pathophysiology of the tissues. Bearing in mind the robustness of this technique and the high spatial context of the data it gives, it is especially valuable in studying the biology of cancer and tumor microenvironment. IMC-derived data are not classical micrographic images, and due to the characteristics of the data obtained using IMC, the image analysis approach, in this case, can diverge to a certain degree from the classical image analysis pipelines. As the number of publications based on the IMC is on the rise, this trend is also followed by an increase in the number of available methodologies designated solely to IMC-derived data analysis. This review has for an aim to give a systematic synopsis of all the available classical image analysis tools and pipelines useful to be employed for IMC data analysis and give an overview of tools intentionally developed solely for this purpose, easing the choice to researchers of selecting the most suitable methodologies for a specific type of analysis desired.

Advancing CAR T cell therapy through the use of multidimensional omics data

Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the treatment of certain haematological malignancies, challenges remain in optimizing CAR designs and cell products, improving response rates, extending the durability of remissions, reducing toxicity and broadening the utility of this therapeutic modality to other cancer types. Data from multidimensional omics analyses, including genomics, epigenomics, transcriptomics, T cell receptor-repertoire profiling, proteomics, metabolomics and/or microbiomics, provide unique opportunities to dissect the complex and dynamic multifactorial phenotypes, processes and responses of CAR T cells as well as to discover novel tumour targets and pathways of resistance. In this Review, we summarize the multidimensional cellular and molecular profiling technologies that have been used to advance our mechanistic understanding of CAR T cell therapies. In addition, we discuss current applications and potential strategies leveraging multi-omics data to identify optimal target antigens and other molecular features that could be exploited to enhance the antitumour activity and minimize the toxicity of CAR T cell therapy. Indeed, fully utilizing multi-omics data will provide new insights into the biology of CAR T cell therapy, further accelerate the development of products with improved efficacy and safety profiles, and enable clinicians to better predict and monitor patient responses.

Spatial profiling technologies illuminate the tumor microenvironment

The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.

Human intestinal B cells in inflammatory diseases

The intestinal lumen contains an abundance of bacteria, viruses and fungi alongside ingested material that shape the chronically active intestinal immune system from early life to maintain the integrity of the gut epithelial barrier. In health, the response is intricately balanced to provide active protection against pathogen invasion whilst tolerating food and avoiding inflammation. B cells are central to achieving this protection. Their activation and maturation generates the body's largest plasma cell population that secretes IgA, and the niches they provide support systemic immune cell specialization. For example, the gut supports the development and maturation of a splenic B cell subset - the marginal zone B cells. In addition, cells such as the T follicular helper cells, which are enriched in many autoinflammatory diseases, are intrinsically associated with the germinal centre microenvironment that is more abundant in the gut than in any other tissue in health. In this Review, we discuss intestinal B cells and their role when a loss of homeostasis results in intestinal and systemic inflammatory diseases.

Revisiting the Role of the CXCL13/CXCR5-Associated Immune Axis in Melanoma: Potential Implications for Anti-PD-1-Related Biomarker Research

CXCL13 is a potent chemoattractant cytokine that promotes the migration of cells expressing its cognate receptor, CXCR5. Accordingly, T follicular helper cells and B cells migrate towards B cell follicles in lymph nodes, where the resulting spatial proximity promotes B cell/T cell interaction and antibody formation. Moreover, effector cells of the CXCL13/CXCR5-associated immune axis express PD-1, with corresponding circulating cells occurring in the blood. The formation of so-called ectopic or tertiary lymphoid structures, recently detected in different cancer types, represents an integral part of this axis, particularly in the context of its emerging role in anti-tumor defense. These aspects of the CXCL13/CXCR5-associated immune axis are highlighted in this review, which focuses on cutaneous malignant melanoma. Specifically, we elaborate on the role of this important immune axis as a possible ancillary target of immune checkpoint inhibition with anti-PD-1 antibodies in different therapeutic settings and as a potential source of predictive biomarkers regarding treatment efficacy.

Targeting tumor-associated macrophages in hepatocellular carcinoma: biology, strategy, and immunotherapy

Hepatocellular carcinoma (HCC), one of the most malignant tumors, is characterized by its stubborn immunosuppressive microenvironment. As one of the main members of the tumor microenvironment (TME) of HCC, tumor-associated macrophages (TAMs) play a critical role in its occurrence and development, including stimulating angiogenesis, enhancing immunosuppression, and promoting the drug resistance and cancer metastasis. This review describes the origin as well as phenotypic heterogeneity of TAMs and their potential effects on the occurrence and development of HCC and also discusses about various adjuvant therapy based strategies that can be used for targeting TAMs. In addition, we have highlighted different treatment modalities for TAMs based on immunotherapy, including small molecular inhibitors, immune checkpoint inhibitors, antibodies, tumor vaccines, adoptive cellular immunotherapy, and nanocarriers for drug delivery, to explore novel combination therapies and provide feasible therapeutic options for clinically improving the prognosis and quality of life of HCC patients.

The contradictory roles of macrophages in non-alcoholic fatty liver disease and primary liver cancer-Challenges and opportunities

Chronic liver diseases from varying etiologies generally lead to liver fibrosis and cirrhosis. Among them, non-alcoholic fatty liver disease (NAFLD) affects roughly one-quarter of the world population, thus representing a major and increasing public health burden. Chronic hepatocyte injury, inflammation (non-alcoholic steatohepatitis, NASH) and liver fibrosis are recognized soils for primary liver cancer, particularly hepatocellular carcinoma (HCC), being the third most common cause for cancer-related deaths worldwide. Despite recent advances in liver disease understanding, therapeutic options on pre-malignant and malignant stages remain limited. Thus, there is an urgent need to identify targetable liver disease-driving mechanisms for the development of novel therapeutics. Monocytes and macrophages comprise a central, yet versatile component of the inflammatory response, fueling chronic liver disease initiation and progression. Recent proteomic and transcriptomic studies performed at singular cell levels revealed a previously overlooked diversity of macrophage subpopulations and functions. Indeed, liver macrophages that encompass liver resident macrophages (also named Kupffer cells) and monocyte-derived macrophages, can acquire a variety of phenotypes depending on microenvironmental cues, and thus exert manifold and sometimes contradictory functions. Those functions range from modulating and exacerbating tissue inflammation to promoting and exaggerating tissue repair mechanisms (i.e., parenchymal regeneration, cancer cell proliferation, angiogenesis, fibrosis). Due to these central functions, liver macrophages represent an attractive target for the treatment of liver diseases. In this review, we discuss the multifaceted and contrary roles of macrophages in chronic liver diseases, with a particular focus on NAFLD/NASH and HCC. Moreover, we discuss potential therapeutic approaches targeting liver macrophages.

High-multiplex tissue imaging in routine pathology-are we there yet?

High-multiplex tissue imaging (HMTI) approaches comprise several novel immunohistological methods that enable in-depth, spatial single-cell analysis. Over recent years, studies in tumor biology, infectious diseases, and autoimmune conditions have demonstrated the information gain accessible when mapping complex tissues with HMTI. Tumor biology has been a focus of innovative multiparametric approaches, as the tumor microenvironment (TME) contains great informative value for accurate diagnosis and targeted therapeutic approaches: unraveling the cellular composition and structural organization of the TME using sophisticated computational tools for spatial analysis has produced histopathologic biomarkers for outcomes in breast cancer, predictors of positive immunotherapy response in melanoma, and histological subgroups of colorectal carcinoma. Integration of HMTI technologies into existing clinical workflows such as molecular tumor boards will contribute to improve patient outcomes through personalized treatments tailored to the specific heterogeneous pathological fingerprint of cancer, autoimmunity, or infection. Here, we review the advantages and limitations of existing HMTI technologies and outline how spatial single-cell data can improve our understanding of pathological disease mechanisms and determinants of treatment success. We provide an overview of the analytic processing and interpretation and discuss how HMTI can improve future routine clinical diagnostic and therapeutic processes.

Eosinophil-derived IL-4 is necessary to establish the inflammatory structure in innate inflammation

Pathogen-induced inflammation comprises pro- and anti-inflammatory processes, which ensure pathogen removal and containment of the proinflammatory activities. Here, we aimed to identify the development of inflammatory microenvironments and their maintenance throughout the course of a toll-like receptor 2-mediated paw inflammation. Within 24 h after pathogen-injection, the immune cells were organized in three zones, which comprised a pathogen-containing "core-region", a bordering proinflammatory (PI)-region and an outer anti-inflammatory (AI)-region. Eosinophils were present in all three inflammatory regions and adapted their cytokine profile according to their localization. Eosinophil depletion reduced IL-4 levels and increased edema formation as well as mechanical and thermal hypersensitivities during resolution of inflammation. Also, in the absence of eosinophils PI- and AI-regions could not be determined anymore, neutrophil numbers increased, and efferocytosis as well as M2-macrophage polarization were reduced. IL-4 administration restored in eosinophil-depleted mice PI- and AI-regions, normalized neutrophil numbers, efferocytosis, M2-macrophage polarization as well as resolution of zymosan-induced hypersensitivity. In conclusion, IL-4-expressing eosinophils support the resolution of inflammation by enabling the development of an anti-inflammatory framework, which encloses proinflammatory regions.

CXCL9 correlates with antitumor immunity and is predictive of a favorable prognosis in uterine corpus endometrial carcinoma

Background

The C-X-C motif chemokine ligand-9 (CXCL9) is related to the progression of multiple neoplasms. Yet, its biological functions in uterine corpus endometrioid carcinoma (UCEC) remain shrouded in confusion. Here, we assessed the prognostic significance and potential mechanism of CXCL9 in UCEC.

Methods

Firstly, bioinformatics analysis of the public cancer database, including the Cancer Genome Atlas / the Genotype-Tissue Expression project (TCGA+ GTEx, n=552) and Gene Expression Omnibus (GEO): GSE63678 (n=7), were utilized for the CXCL9 expression-related analysis in UCEC. Then, the survival analysis of TCGA-UCEC was performed. Futher, the gene set enrichment analysis (GSEA) was carried out to reveal the potential molecular signaling pathway in UCEC associated with CXCL9 expression. Moreover, the immunohistochemistry (IHC) assay of our validation cohort (n=124) from human specimens were used to demonstrate the latent significance of CXCL9 in UCEC.

Results

The bioinformatics analysis suggested that CXCL9 expression was significantly upregulated in UCEC patients; and hyper-expression of CXCL9 was related to prolonged survival. the GSEA enrichment analysis showed various immune response-related pathways, including T/NK cell, lymphocyte activation, cytokine-cytokine receptor interaction network, and chemokine signaling pathway, mediated by CXCL9. In addition, the cytotoxic molecules (IFNG, SLAMF7, JCHAIN, NKG7, GBP5, LYZ, GZMA, GZMB, and TNF3F9) and the immunosuppressive genes (including PD-L1) were positively related to the expression of CXCL9. Further, the IHC assay indicated that the CXCL9 protein expression was mainly located in intertumoral and significantly upregulated in the UCEC patients; UCEC with high intertumoral CXCL9 cell abundance harbored an improved prognosis; a higher ratio of anti-tumor immune cells (CD4⁺, CD8⁺, and CD56⁺ cell) and PD-L1 was found in UCEC with CXCL9 high expression.

Conclusion

Overexpressed CXCL9 correlates with antitumor immunity and is predictive of a favorable prognosis in UCEC. It hinted that CXCL9 may serve as an independent prognostic biomarker or therapeutic target in UCEC patients, which augmented anti-tumor immune effects to furnish survival benefits.

Multiplex Immunofluorescence: A Powerful Tool in Cancer Immunotherapy

Traditional immunohistochemistry (IHC) has already become an essential method of diagnosis and therapy in cancer management. However, this antibody-based technique is limited to detecting a single marker per tissue section. Since immunotherapy has revolutionized the antineoplastic therapy, developing new immunohistochemistry strategies to detect multiple markers simultaneously to better understand tumor environment and predict or assess response to immunotherapy is necessary and urgent. Multiplex immunohistochemistry (mIHC)/multiplex immunofluorescence (mIF), such as multiplex chromogenic IHC and multiplex fluorescent immunohistochemistry (mfIHC), is a new and emerging technology to label multiple biomarkers in a single pathological section. The mfIHC shows a higher performance in cancer immunotherapy. This review summarizes the technologies, which are applied for mfIHC, and discusses how they are employed for immunotherapy research.

A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer

Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1^high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I - but not PD-L1 - on tumor cells are strong distinguishing features between these environments.

Proteomics to study cancer immunity and improve treatment

Cancer survival and progression depend on the ability of tumor cells to avoid immune recognition. Advances in the understanding of cancer immunity and tumor immune escape mechanisms enabled the development of immunotherapeutic approaches. In patients with otherwise incurable metastatic cancers, immunotherapy resulted in unprecedented response rates with the potential for durable complete responses. However, primary and acquired resistance mechanisms limit the efficacy of immunotherapy. Further therapeutic advances require a deeper understanding of the interplay between immune cells and tumors. Most high-throughput studies within the past decade focused on an omics characterization at DNA and RNA level. However, proteins are the molecular effectors of genomic information; therefore, the study of proteins provides deeper understanding of cellular functions. Recent advances in mass spectrometry (MS)-based proteomics at a system-wide scale may allow translational and clinical discoveries by enabling the analysis of understudied post-translational modifications, subcellular protein localization, cell signaling, and protein-protein interactions. In this review, we discuss the potential contribution of MS-based proteomics to preclinical and clinical research findings in the context of tumor immunity and cancer immunotherapies.

Single-cell high-dimensional imaging mass cytometry: one step beyond in oncology

Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).

Towards multiomic analysis of oral mucosal pathologies

Oral mucosal pathologies comprise an array of diseases with worldwide prevalence and medical relevance. Affecting a confined space with crucial physiological and social functions, oral pathologies can be mutilating and drastically reduce quality of life. Despite their relevance, treatment for these diseases is often far from curative and remains vastly understudied. While multiple factors are involved in the pathogenesis of oral mucosal pathologies, the host's immune system plays a major role in the development, maintenance, and resolution of these diseases. Consequently, a precise understanding of immunological mechanisms implicated in oral mucosal pathologies is critical (1) to identify accurate, mechanistic biomarkers of clinical outcomes; (2) to develop targeted immunotherapeutic strategies; and (3) to individualize prevention and treatment approaches. Here, we review key elements of the immune system's role in oral mucosal pathologies that hold promise to overcome limitations in current diagnostic and therapeutic approaches. We emphasize recent and ongoing multiomic and single-cell approaches that enable an integrative view of these pathophysiological processes and thereby provide unifying and clinically relevant biological signatures.

Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment

Background

Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown.

Method

Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs).

Results

Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group.

Conclusion

Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.

From thymus to tissues and tumors: A review of T-cell biology

T cells are critical orchestrators of the adaptive immune response that optimally eliminate a specific pathogen. Aberrant T-cell development and function are implicated in a broad range of human disease including immunodeficiencies, autoimmune diseases, and allergic diseases. Accordingly, therapies targeting T cells and their effector cytokines have markedly improved the care of patients with immune dysregulatory diseases. Newer discoveries concerning T-cell-mediated antitumor immunity and T-cell exhaustion have further prompted development of highly effective and novel treatment modalities for malignancies, including checkpoint inhibitors and antigen-reactive T cells. Recent discoveries are also uncovering the depth and variability of T-cell phenotypes: while T cells have long been described using a subset-based classification system, next-generation sequencing technologies suggest an astounding degree of complexity and heterogeneity at the single-cell level.

Identification of hub genes correlated with tumor-associated M1-like macrophage infiltration in soft tissue sarcomas

Soft tissue sarcomas (STS) are a heterogeneous series of tumors that might result in severe disability and death. Tumor-associated M1-like macrophage infiltration plays a critical role in tumor development and progression. This study aimed at identifying the hub genes associated with M1-like macrophage infiltration in STS cells. First, the expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were imported to calculate the level of M1-like macrophage infiltration by CIBERSORTx. Afterward, the Kaplan-Meier survival analysis was performed to evaluate the correlation between macrophage infiltration and prognosis. Then, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction analysis of GEO data were applied to identify the key gene related to M1-like macrophage infiltration, followed by the functional analysis using TCGA cohort to validate downstream signaling associated with the gene. Finally, pan-cancer analysis was conducted to investigate the gene function in other types of tumors. We found LCK expression positively related to the M1-like macrophage infiltration level, and it positively regulated the expression level of genes regulated to macrophage polarization, and chemotaxis, including interferon-γ (INF-γ), interleukin-12 (IL12), tumor necrosis factor (TNF), PI3K, NF-κB, and CXCL9, 10, and 11. In summary, an 'LCK-INF-γ/IL-12-TNF/PI3K-NF-κB' axis might exist in STS cells that regulate M1-like macrophage infiltration.

Spatial multi-omics analyses of the tumor immune microenvironment

In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell-cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial 'omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

Multiplexed In Situ Spatial Protein Profiling in the Pursuit of Precision Immuno-Oncology for Patients with Breast Cancer

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many solid tumors. In breast cancer (BC), immunotherapy is currently approved in combination with chemotherapy, albeit only in triple-negative breast cancer. Unfortunately, most patients only derive limited benefit from ICIs, progressing either upfront or after an initial response. Therapeutics must engage with a heterogeneous network of complex stromal-cancer interactions that can fail at imposing cancer immune control in multiple domains, such as in the genomic, epigenomic, transcriptomic, proteomic, and metabolomic domains. To overcome these types of heterogeneous resistance phenotypes, several combinatorial strategies are underway. Still, they can be predicted to be effective only in the subgroups of patients in which those specific resistance mechanisms are effectively in place. As single biomarker predictive performances are necessarily suboptimal at capturing the complexity of this articulate network, precision immune-oncology calls for multi-omics tumor microenvironment profiling in order to identify unique predictive patterns and to proactively tailor combinatorial treatments. Multiplexed single-cell spatially resolved tissue analysis, through precise epitope colocalization, allows one to infer cellular functional states in view of their spatial organization. In this review, we discuss-through the lens of the cancer-immunity cycle-selected, established, and emerging markers that may be evaluated in multiplexed spatial protein panels to help identify prognostic and predictive patterns in BC.

Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis

The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in ~30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients.

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.

CXCL9 and CXCL10 bring the heat to tumors

CXCL9 and CXCL10 can be produced by antigen-presenting cells (dendritic cells or macrophages) and by tumor cells. Hoch et al. demonstrated that CXCL9 and CXCL10 co-localize with LAG3+ T cells expressing CCL4 or CXCL13 and contribute to the generation of a "hot" tumor microenvironment.

CCL5-Secreting Virtual Memory CD8+ T Cells Inversely Associate With Viral Reservoir Size in HIV-1-Infected Individuals on Antiretroviral Therapy

Recent studies highlighted that CD8+ T cells are necessary for restraining reservoir in HIV-1-infected individuals who undergo antiretroviral therapy (ART), whereas the underlying cellular and molecular mechanisms remain largely unknown. Here, we enrolled 60 virologically suppressed HIV-1-infected individuals, to assess the correlations of the effector molecules and phenotypic subsets of CD8+ T cells with HIV-1 DNA and cell-associated unspliced RNA (CA usRNA). We found that the levels of HIV-1 DNA and usRNA correlated positively with the percentage of CCL4+CCL5- CD8+ central memory cells (T_CM) while negatively with CCL4-CCL5+ CD8+ terminally differentiated effector memory cells (T_EMRA). Moreover, a virtual memory CD8+ T cell (T_VM) subset was enriched in CCL4-CCL5+ T_EMRA cells and phenotypically distinctive from CCL4+ T_CM subset, supported by single-cell RNA-Seq data. Specifically, T_VM cells showed superior cytotoxicity potentially driven by T-bet and RUNX3, while CCL4+ T_CM subset displayed a suppressive phenotype dominated by JUNB and CREM. In viral inhibition assays, T_VM cells inhibited HIV-1 reactivation more effectively than non-T_VM CD8+ T cells, which was dependent on CCL5 secretion. Our study highlights CCL5-secreting T_VM cells subset as a potential determinant of HIV-1 reservoir size. This might be helpful to design CD8+ T cell-based therapeutic strategies for cure of the disease.

Combinations of Toll-like receptor 8 agonist TL8-506 activate human tumor-derived dendritic cells

BACKGROUND

Dendritic cells (DCs) are professional antigen presenting cells that initiate immune defense to pathogens and tumor cells. Human tumors contain only few DCs that mostly display a non-activated phenotype. Hence, activation of tumor-associated DCs may improve efficacy of cancer immunotherapies. Toll-like receptor (TLR) agonists and interferons are known to promote DC maturation. However, it is unclear if DCs in human tumors respond to activation signals and which stimuli induce the optimal activation of human tumor DCs.

METHODS

We first screened combinations of TLR agonists, a STING agonist and interferons (IFNs) for their ability to activate human conventional DCs (cDCs). Two combinations: TL8-506 (a TLR8 agonist)+IFN-γ and TL8-506+Poly(I:C) (a TLR3 agonist) were studied in more detail. cDC1s and cDC2s derived from cord blood stem cells, blood or patient tumor samples were stimulated with either TL8-506+IFN-γ or TL8-506+Poly(I:C). Different activation markers were analyzed by ELISA, flow cytometry, NanoString nCounter Technology or single-cell RNA-sequencing. T cell activation and migration assays were performed to assess functional consequences of cDC activation.

RESULTS

We show that TL8-506 synergized with IFN-γ or Poly(I:C) to induce high expression of different chemokines and cytokines including interleukin (IL)-12p70 in human cord blood and blood cDC subsets in a combination-specific manner. Importantly, both combinations induced the activation of cDC subsets in patient tumor samples ex vivo. The expression of immunostimulatory genes important for anticancer responses including CD40, IFNB1, IFNL1, IL12A and IL12B were upregulated on stimulation. Furthermore, chemokines associated with CD8⁺ T cell recruitment were induced in tumor-derived cDCs in response to TL8-506 combinations. In vitro activation and migration assays confirmed that stimulated cDCs induce T cell activation and migration.

CONCLUSIONS

Our data suggest that cord blood-derived and blood-derived cDCs are a good surrogate to study treatment responses in human tumor cDCs. While most cDCs in human tumors display a non-activated phenotype, TL8-506 combinations drive human tumor cDCs towards an immunostimulatory phenotype associated with Th1 responses on stimulation. Hence, TL8-506-based combinations may be promising candidates to initiate or boost antitumor responses in patients with cancer.

MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives

Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.

Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research

Imaging mass cytometry (IMC) enables the in situ analysis of in-depth-phenotyped cells in their native microenvironment within the preserved architecture of a single tissue section. To date, it permits the simultaneous analysis of up to 50 different protein- markers targeted by metal-conjugated antibodies. The application of IMC in the field of cancer research may notably help 1) to define biomarkers of prognostic and theragnostic significance for current and future treatments against well-established and novel therapeutic targets and 2) to improve our understanding of cancer progression and its resistance mechanisms to immune system and how to overcome them. In the present article, we not only provide a literature review on the use of the IMC in cancer-dedicated studies but we also present the IMC method and discuss its advantages and limitations among methods dedicated to deciphering the complexity of cancer tissue.