Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis

Intratumoral Cell Neighborhoods Coordinate Outcomes in Pancreatic Ductal Adenocarcinoma

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDA) is a highly lethal disease characterized by a spatially heterogeneous tumor microenvironment. Within the PDA microenvironment, cells organize into communities where cell fate is influenced by neighboring cells of diverse ontogeny and function. However, it remains unclear how cell neighborhoods in the tumor microenvironment evolve with treatment and impact clinical outcomes.

METHODS

Here, using automated chromogenic multiplex immunohistochemistry and unsupervised computational image analysis of human PDA tumors, we investigated cell neighborhoods in surgically resected tumors from patients with chemotherapy-naïve PDA (n = 59) and neoadjuvant chemotherapy-treated PDA (n = 57). Single cells were defined by lineage markers (CD3, CD8, Foxp3, CD68, CK19), proliferation (Ki67), and neighboring cells.

RESULTS

Distinct intratumoral immune and tumor cell subsets were defined by neighboring cells. Higher content of stromal-associated macrophages was seen in chemotherapy-naïve tumors from long-term survivors (overall survival >3 years) compared with short-term survivors (overall survival <1 year), whereas immune-excluded tumor cells were higher in short-term survivors. Chemotherapy-treated vs -naïve tumors showed lower content of tumor-associated T cells and macrophages but similar densities of stromal-associated immune cells. However, proliferating tumor cell subsets with immune-rich neighborhoods were higher in chemotherapy-treated tumors. In a blinded analysis of tumors from patients treated with neoadjuvant chemotherapy, a composite index comprising lower quantities of immune-excluded tumor cells and higher spatially distinct immune cell subsets was associated with prolonged survival.

CONCLUSIONS

Together, these data provide new insights into discrete cell communities in PDA and show their clinical relevance.

Ultrasensitive and Multiplexed Protein Imaging with Clickable and Cleavable Fluorophores

Single-cell spatial proteomic analysis holds great promise to advance our understanding of the composition, organization, interaction, and function of the various cell types in complex biological systems. However, the current multiplexed protein imaging technologies suffer from low detection sensitivity, limited multiplexing capacity, or are technically demanding. To tackle these issues, here, we report the development of a highly sensitive and multiplexed in situ protein profiling method using off-the-shelf antibodies. In this approach, the protein targets are stained with horseradish peroxidase (HRP) conjugated antibodies and cleavable fluorophores via click chemistry. Through repeated cycles of target staining, fluorescence imaging, and fluorophore cleavage, many proteins can be profiled in single cells in situ. Applying this approach, we successfully quantified 28 different proteins in human formalin-fixed paraffin-embedded (FFPE) tonsil tissue, which represents the highest multiplexing capacity among the tyramide signal amplification (TSA) methods. Based on their unique protein expression patterns and their microenvironment, ∼820,000 cells in the tissue are classified into distinct cell clusters. We also explored the cell-cell interactions between these varied cell clusters and observed that different subregions of the tissue are composed of cells from specific clusters.

Clonal hematopoiesis and its impact on the aging osteo-hematopoietic niche

Clonal hematopoiesis (CH) defines a premalignant state predominantly found in older persons that increases the risk of developing hematologic malignancies and age-related inflammatory diseases. However, the risk for malignant transformation or non-malignant disorders is variable and difficult to predict, and defining the clinical relevance of specific candidate driver mutations in individual carriers has proved to be challenging. In addition to the cell-intrinsic mechanisms, mutant cells rely on and alter cell-extrinsic factors from the bone marrow (BM) niche, which complicates the prediction of a mutant cell's fate in a shifting pre-malignant microenvironment. Therefore, identifying the insidious and potentially broad impact of driver mutations on supportive niches and immune function in CH aims to understand the subtle differences that enable driver mutations to yield different clinical outcomes. Here, we review the changes in the aging BM niche and the emerging evidence supporting the concept that CH can progressively alter components of the local BM microenvironment. These alterations may have profound implications for the functionality of the osteo-hematopoietic niche and overall bone health, consequently fostering a conducive environment for the continued development and progression of CH. We also provide an overview of the latest technology developments to study the spatiotemporal dependencies in the CH BM niche, ideally in the context of longitudinal studies following CH over time. Finally, we discuss aspects of CH carrier management in clinical practice, based on work from our group and others.

Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies

The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

Increased Multiplexity in Optical Tissue Clearing-Based Three-Dimensional Immunofluorescence Microscopy of the Tumor Microenvironment by Light-Emitting Diode Photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy is transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only 3 or 4 cellular and noncellular TME components can be localized in cleared tumor tissue. Here we report a light-emitting diode (LED) photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through 3 work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Digital Pathology for Better Clinical Practice

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Integrating multiplexed imaging and multiscale modeling identifies tumor phenotype conversion as a critical component of therapeutic T cell efficacy

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here, we integrated CODEX multiplexed tissue imaging with multiscale modeling software to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface. A record of this paper's transparent peer review process is included in the supplemental information.

Applicability of Spatial Technology in Cancer Research

This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a significant impact on tumor dynamics and treatment outcomes. This review closely examines cutting-edge spatial mapping technologies, categorizing them into capture-, imaging-, and antibody-based approaches. Each technology was scrutinized for its advantages and disadvantages, factoring in aspects such as spatial profiling area, multiplexing capabilities, and resolution. Additionally, we draw attention to the nuanced choices researchers face, with capture-based methods lending themselves to hypothesis generation, and imaging/antibody-based methods that fit neatly into hypothesis testing. Looking ahead, we anticipate a scenario in which multi-omics data are seamlessly integrated, artificial intelligence enhances data analysis, and spatiotemporal profiling opens up new dimensions.

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

A Comparison of Spatial and Phenotypic Immune Profiles of Pancreatic Ductal Adenocarcinoma and Its Precursor Lesions

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a 5-year survival rate of 12.5%. PDAC predominantly arises from non-cystic pancreatic intraepithelial neoplasia (PanIN) and cystic intraductal papillary mucinous neoplasm (IPMN). We used multiplex immunofluorescence and computational imaging technology to characterize, map, and compare the immune microenvironments (IMEs) of PDAC and its precursor lesions. We demonstrate that the IME of IPMN was abundantly infiltrated with CD8+ T cells and PD-L1-positive antigen-presenting cells (APCs), whereas the IME of PanIN contained fewer CD8+ T cells and fewer PD-L1-positive APCs but elevated numbers of immunosuppressive regulatory T cells (Tregs). Thus, immunosuppression in IPMN and PanIN seems to be mediated by different mechanisms. While immunosuppression in IPMN is facilitated by PD-L1 expression on APCs, Tregs seem to play a key role in PanIN. Our findings suggest potential immunotherapeutic interventions for high-risk precursor lesions, namely, targeting PD-1/PD-L1 in IPMN and CTLA-4-positive Tregs in PanIN to restore immunosurveillance and prevent progression to cancer. Tregs accumulate with malignant transformation, as observed in PDAC, and to a lesser extent in IPMN-associated PDAC (IAPA). High numbers of Tregs in the microenvironment of PDAC went along with a markedly decreased interaction between CD8+ T cells and cancerous epithelial cells (ECs), highlighting the importance of Tregs as key players in immunosuppression in PDAC. We found evidence that a defect in antigen presentation, further aggravated by PD-L1 expression on APC, may contribute to immunosuppression in IAPA, suggesting a role for PD-L1/PD-1 immune checkpoint inhibitors in the treatment of IAPA.

Landscape of infiltrating immune cells and related genes in diabetic kidney disease

INTRODUCTION

Diabetic kidney disease (DKD) is one of the prominent microvascular complications of diabetes and the leading cause of end-stage renal disease. Inflammation plays a crucial role in the development and progression of DKD. Currently, only a few studies depict the landscape of infiltrating immune cells and their potential regulatory network in DKD. To gain a better understanding of the role of immune cells in the renal microenvironment, we sought to reveal the profile of infiltrating immune cells and their potential regulatory network in DKD.

METHODS

We obtained the transcriptomes and the corresponding clinical data of 19 DKD and 25 control samples from the Gene Expression Omnibus and Nephroseq databases, respectively. Thereafter, we conducted an analysis on the infiltrating immune cells and identified immune-related differentially expressed genes through bioinformatics. Finally, correlation analyses among immune cells, immune genes, and clinical manifestations were performed, and differentially infiltrating immune cell subsets were verified through multiplex immunofluorescence staining.

RESULTS

We demonstrated the landscape of infiltrating immune cells in patients with DKD and identified the top five hub immune regulatory genes (C3, IL7R, TYROBP, BMP2, and CXCL6). Three of the core genes (C3, BMP2, and CXCL6) were significantly correlated with the estimated glomerular filtration rate. Through multiplex immunofluorescence staining, we verified that macrophage numbers were remarkably elevated, whereas Treg cells were remarkably reduced in diabetic kidney tissues. Th2 cells were scarce in the kidney tissue.

CONCLUSION

Collectively, our findings shed light on new, possible therapeutic strategies for DKD, from an immune microenvironment perspective.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

Phenotypic characterization of liver tissue heterogeneity through a next-generation 3D single-cell atlas

Three-dimensional (3D) geometrical models are potent tools for quantifying complex tissue features and exploring structure-function relationships. However, these models are generally incomplete due to experimental limitations in acquiring multiple (> 4) fluorescent channels in thick tissue sections simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we combined deep-tissue immunostaining, multiphoton microscopy, deep-learning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatial single-cell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the effect on the liver's overall structure when changing the hepatic environment after removing KCs. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs results in morphological changes in hepatocytes and HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, opening up avenues for in-depth investigations into tissue structure across both normal and pathological conditions.

Single-Cell Atlas of Atherosclerosis Patients by Cytof: Circulatory and Local Immune Disorders

Atherosclerosis (AS) is a common underlying pathology of coronary artery disease, peripheral artery disease, and stroke. The characteristics of immune cells within plaques and their functional relationships with blood are crucial in AS. In this study, Mass cytometry (CyTOF), RNA-sequencing and immunofluorescence were combined to comprehensively analyze plaque tissues and peripheral blood from 25 AS patients (22 for Mass cytometry and 3 for RNA-sequencing), as well as blood from 20 healthy individuals. The study identified a complexity of leukocytes in the plaque, including both defined anti-inflammatory and pro-inflammatory subsets such as M2-like CD163+ macrophages, Natural killer T cells (NKT), CD11b+ CD4+ T effector memory cells (Tem), and CD8+ terminally differentiated effector memory cells (TEMRA). Functionally activated cell subsets were also found in peripheral blood in AS patients, highlighting the vivid interactions between leukocytes in plaque and blood. The study provides an atlas of the immune landscape in atherosclerotic patients, where pro-inflammatory activation was found to be a major feature of peripheral blood. The study identified NKT, CD11b+ CD4+ Tem, CD8+ TEMRA and CD163+ macrophages as key players in the local immune environment.

Expression Analysis of Retinal G Protein-coupled Receptor and its Correlation with Regulation of the Balance between Proliferation and Aberrant Differentiation in Cutaneous Squamous Cell Carcinoma

Retinal G protein-coupled receptor (RGR), a photosensitive protein, functions as a retinal photoisomerase under light conditions in humans. Cutaneous squamous cell carcinoma (cSCC) is linked to chronic ultraviolet exposure, which suggests that the photoreceptor RGR may be associated with tumorigenesis and progression of squamous cell carcinoma (SCC). However, the expression and function of RGR remain uncharacterized in SCC. This study analysed RGR expression in normal skin and in lesions of actinic keratosis, Bowen's disease and invasive SCC of the skin with respect to SCC initiation and development. A total of 237 samples (normal skin (n = 28), actinic keratosis (n = 42), Bowen's (n = 35) and invasive SCC (n = 132) lesions) were examined using immunohistochemistry. Invasive SCC samples had higher expression of RGR protein than the other samples. A high immunohistochemical score for RGR was associated with increased tumour size, tumour depth, Clark level, factor classification, and degree of differentiation and a more aggressive histological subtype. In addition, RGR expression was inversely correlated with involucrin expression and positively correlated with proliferating cell nuclear antigen (PCNA) and Ki67 expression. Furthermore, RGR regulates SCC cell differentiation through the PI3K-Akt signalling pathway, as determined using molecular biology approaches in vitro, suggesting that high expression of RGR is associated with aberrant proliferation and differentiation in SCC.

Task design for crowdsourced glioma cell annotation in microscopy images

Crowdsourcing has been used in computational pathology to generate cell and cell nuclei annotations for machine learning. Herein, we broaden its scope to the previously unsolved challenging task of glioma cell detection. This requires multiplexed immunofluorescence microscopy due to diffuse invasiveness and exceptional similarity between glioma cells and reactive astrocytes. In four pilot experiments, we iteratively developed a task design enabling high-quality annotations by crowdworkers on Amazon Mechanical Turk. We applied majority or weighted vote and validated them against ground truth in the final setting. On the base of a YOLO convolutional neural network architecture, we used these consensus labels for training with different image representations regarding colors, intensities, and immmunohistochemical marker combinations. A crowd of 712 workers defined aggregated point annotations in 235 images with an average [Formula: see text] score of 0.627 for majority vote. The networks resulted in acceptable [Formula: see text] scores up to 0.69 for YOLOv8 on average and indicated first evidence for transferability to images lacking tumor markers, especially in IDH-wildtype glioblastoma. Our work confirms feasibility of crowdsourcing to generate labels suitable for training of machine learning tools in the challenging and clinically relevant use case of glioma microenvironment.

Association between spatial distribution of leukocyte subsets and clinical presentation of head and neck squamous cell carcinoma

Background

Interactions between tumor cells and cells in the microenvironment contribute to tumor development and metastasis. The spatial arrangement of individual cells in relation to each other influences the likelihood of whether and how these cells interact with each other.

Methods

This study investigated the effect of spatial distribution on the function of leukocyte subsets in the microenvironment of human head and neck squamous cell carcinoma (HNSCC) using multiplex immunohistochemistry (IHC). Leukocyte subsets were further classified based on analysis of two previously published HNSCC single-cell RNA datasets and flow cytometry (FC).

Results

IHC revealed distinct distribution patterns of leukocytes differentiated by CD68 and CD163. While CD68hiCD163lo and CD68hiCD163hi cells accumulated near tumor sites, CD68loCD163hi cells were more evenly distributed in the tumor stroma. PD-L1hi and PD-1hi cells accumulated predominantly around tumor sites. High cell density of PD-L1hi CD68hiCD163hi cells or PD-1hi T cells near the tumor site correlated with improved survival. FC and single cell RNA revealed high variability within the CD68/CD163 subsets. CD68hiCD163lo and CD68hiCD163hi cells were predominantly macrophages (MΦ), whereas CD68loCD163hi cells appeared to be predominantly dendritic cells (DCs). Differentiation based on CD64, CD80, CD163, and CD206 revealed that TAM in HNSCC occupy a broad spectrum within the classical M1/M2 polarization. Notably, the MΦ subsets expressed predominantly CD206 and little CD80. The opposite was observed in the DC subsets.

Conclusion

The distribution patterns and their distinct interactions via the PD-L1/PD-1 pathway suggest divergent roles of CD68/CD163 subsets in the HNSCC microenvironment. PD-L1/PD-1 interactions appear to occur primarily between specific cell types close to the tumor site. Whether PD-L1/PD-1 interactions have a positive or negative impact on patient survival appears to depend on both the spatial localization and the entity of the interacting cells. Co-expression of other markers, particularly CD80 and CD206, supports the hypothesis that CD68/CD163 IHC subsets have distinct functions. These results highlight the association between spatial leukocyte distribution patterns and the clinical presentation of HNSCC.

Pathological complete response to neoadjuvant chemotherapy may improve antitumor immune response via reduction of regulatory T cells in muscle-invasive bladder cancer

The prognosis for patients who achieve a pathologic complete response in bladder cancer is excellent, but the association between their prognosis and the tumor microenvironment is unclear. We investigated the tumor immune microenvironment of those with pathological complete response after platinum-based neoadjuvant chemotherapy for cT2-4aN0M0 bladder cancer using multiplex fluorescence immunohistochemistry. Our retrospective study included 12 patients with pathological complete response who underwent radical cystectomy following neoadjuvant chemotherapy for cT2-4aN0M0 muscle-invasive bladder cancer. We assessed the density of several immune cell types in pretreatment and posttreatment tissues via multiplex fluorescence immunohistochemical analysis. The median age was 67 years; 10 patients were male. Nine (75%) and 3 (25%) patients were cT2 and cT3, respectively. The 5-year progression-free and overall survivals were 90% and 100%, respectively. The densities of regulatory T cells (Treg; CD3+CD4+FoxP3+ cell) were significantly decreased and almost disappeared in the tumor microenvironment of posttreatment tissue compared with pretreatment tissue. Other immune cells, such as effector T cells or M2 macrophages, were not significantly changed between posttreatment and pretreatment tissues. In pathological complete response, Tregs in the tumor immune microenvironment were significantly decreased after platinum-based chemotherapy for muscle-invasive bladder cancer. The temporary arresting of immune response in the tumor microenvironment may reflect a favorable prognosis due to the decrease of Tregs with tumor shrinkage and improve the host tumor immune response.

An overview of the detection of bovine respiratory disease complex pathogens using immunohistochemistry: emerging trends and opportunities

The bovine respiratory disease complex (BRDC) is caused by a variety of pathogens, as well as contributing environmental and host-related risk factors. BRDC is the costliest disease for feedlot cattle globally. Immunohistochemistry (IHC) is a valuable tool for enhancing our understanding of BRDC given its specificity, sensitivity, cost-effectiveness, and capacity to provide information on antigen localization and immune response. Emerging trends in IHC include the use of multiplex IHC for the detection of coinfections, the use of digital imaging and automation, improved detection systems using enhanced fluorescent dyes, and the integration of IHC with spatial transcriptomics. Overall, identifying biomarkers for early detection, utilizing high-throughput IHC for large-scale studies, developing standardized protocols and reagents, and integrating IHC with other technologies are some of the opportunities to enhance the accuracy and applicability of IHC. We summarize here the various techniques and protocols used in IHC and highlight their current and potential role in BRDC research.

Cytotoxic chemotherapy potentiates the immune response and efficacy of combination CXCR4/PD-1 inhibition in models of pancreatic ductal adenocarcinoma

Purpose

The CXCL12-CXCR4 chemokine axis plays a significant role in modulating T-cell infiltration into the pancreatic tumor microenvironment. Despite promising preclinical findings, clinical trials combining inhibitors of CXCR4 (AMD3100/BL-8040) and anti-programmed death 1/ligand1 (anti-PD1/PD-L1) have failed to improve outcomes.

Experimental Design

We utilized a novel ex vivo autologous patient-derived immune/organoid (PDIO) co-culture system using human peripheral blood mononuclear cells and patient derived tumor organoids, and in vivo the autochthonous LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre (KPC) pancreatic cancer mouse model to interrogate the effects of either monotherapy or all combinations of gemcitabine, AMD3100, and anit-PD1 on CD8+ T cell activation and survival.

Results

We demonstrate that disruption of the CXCL12-CXCR4 axis using AMD3100 leads to increased migration and activation of CD8+ T-cells. In addition, when combined with the cytotoxic chemotherapy gemcitabine, CXCR4 inhibition further potentiated CD8+ T-cell activation. We next tested the combination of gemcitabine, CXCR4 inhibition, and anti-PD1 in the KPC pancreatic cancer mouse model and demonstrate that this combination markedly impacted the tumor immune microenvironment by increasing infiltration of natural killer cells, the ratio of CD8+ to regulatory T-cells, and tumor cell death while decreasing tumor cell proliferation. Moreover, this combination extended survival in KPC mice.

Conclusions

These findings suggest that combining gemcitabine with CXCR4 inhibiting agents and anti-PD1 therapy controls tumor growth by reducing immunosuppression and potentiating immune cell activation and therefore may represent a novel approach to treating pancreatic cancer.

Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient's TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.

Tumor-immune microenvironment and NRF2 associate with clinical efficacy of PD-1 blockade combined with chemotherapy in lung squamous cell carcinoma

The RATIONALE-307 study (ClinicalTrials.gov: NCT03594747) demonstrates prolonged progression-free survival (PFS) with first-line tislelizumab plus chemotherapy versus chemotherapy in advanced lung squamous cell carcinoma (LUSC; N = 360). Here we describe an immune-related gene expression signature (GES), composed of genes involved in both innate and adaptive immunity, that appears to differentiate tislelizumab plus chemotherapy PFS benefit versus chemotherapy. In contrast, a tislelizumab plus chemotherapy PFS benefit is observed regardless of programmed death ligand 1 (PD-L1) expression or tumor mutational burden (TMB). Genetic analysis reveals that NRF2 pathway activation is enriched in PD-L1positive and TMBhigh patients. NRF2 pathway activation is negatively associated with PFS, which affects efficacy outcomes associated with PD-L1 and TMB status, impairing their predictive potential. Mechanistic studies demonstrate that NRF2 directly mediates PD-L1 constitutive expression independent of adaptive PD-L1 regulation in LUSC. In summary, the GES is an immune signature that might identify LUSC patients likely to benefit from first-line tislelizumab plus chemotherapy.

Lipidomic Phenotyping Of Human Small Intestinal Organoids Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging

In the past decade, interest in organoids for biomedical research has surged, resulting in a higher demand for advanced imaging techniques. Traditional specimen embedding methods pose challenges, such as analyte delocalization and histological assessment. Here, we present an optimized sample preparation approach utilizing an Epredia M-1 cellulose-based embedding matrix, which preserves the structural integrity of fragile small intestinal organoids (SIOs). Additionally, background interference (delocalization of analytes, nonspecific (histological) staining, matrix ion clusters) was minimized, and we demonstrate the compatibility with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). With our approach, we can conduct label-free lipid imaging at the single-cell level, thereby yielding insights into the spatial distribution of lipids in both positive and negative ion modes. Moreover, M-1 embedding allows for an improved coregistration with histological and immunohistochemical (IHC) stainings, including MALDI-IHC, facilitating combined untargeted and targeted spatial information. Applying this approach, we successfully phenotyped crypt-like (CL) and villus-like (VL) SIOs, revealing that PE 36:2 [M - H]- (m/z 742.5) and PI 38:4 [M - H]- (m/z 885.5) display higher abundance in CL organoids, whereas PI 36:1 [M - H]- (m/z 863.6) was more prevalent in VL organoids. Our findings demonstrate the utility of M-1 embedding for advancing organoid research and unraveling intricate biological processes within these in vitro models.

Integrating Multiplexed Imaging and Multiscale Modeling Identifies Tumor Phenotype Transformation as a Critical Component of Therapeutic T Cell Efficacy

Cancer progression is a complex process involving interactions that unfold across molecular, cellular, and tissue scales. These multiscale interactions have been difficult to measure and to simulate. Here we integrated CODEX multiplexed tissue imaging with multiscale modeling software, to model key action points that influence the outcome of T cell therapies with cancer. The initial phenotype of therapeutic T cells influences the ability of T cells to convert tumor cells to an inflammatory, anti-proliferative phenotype. This T cell phenotype could be preserved by structural reprogramming to facilitate continual tumor phenotype conversion and killing. One takeaway is that controlling the rate of cancer phenotype conversion is critical for control of tumor growth. The results suggest new design criteria and patient selection metrics for T cell therapies, call for a rethinking of T cell therapeutic implementation, and provide a foundation for synergistically integrating multiplexed imaging data with multiscale modeling of the cancer-immune interface.

Increased multiplexity in optical tissue clearing-based 3D immunofluorescence microscopy of the tumor microenvironment by LED photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy have been transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only three or four cellular and non-cellular TME components can be localized in a cleared tumor tissue. Here we report a LED photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through three work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Spatial Proximity and Relative Distribution of Tumor-Infiltrating Lymphocytes and Macrophages Predict Survival in Melanoma

Tumor microenvironment plays a crucial role in primary cutaneous melanoma (CM) progression. Although the role of tumor-infiltrating lymphocyte (TIL) density has been known for a long time, its spatial distribution and impact with or without tumor-associated macrophages (TAMs) remain controversial. Herein, we investigated spatial proximity between tumor cells and immune cells in 113 primary CM and its correlation with disease-free (DFS) and overall survival (OS). The study cohort included clinical stage II (n = 79) and stage III (n = 34) primary CM with a Breslow thickness of >2 mm (with a median age of 64 years, including 72 men and 41 women). In univariate models, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs in a 20 μm radius showed longer DFS (hazard ratio [HR], 0.58; 95% CI, 0.36-0.93; P = .025) and OS (HR, 0.55; 95% CI, 0.32-0.92; P = .023). Furthermore, at multivariate combined analysis, patients with SOX10+ melanoma cells with high proximity to CD8+ TILs or low proximity to CD163+ TAMs in a 20 μm radius showed an increased OS (aHR, 0.37; 95% CI, 0.14-0.96; P = .04) compared with melanoma patients with low proximity to CD8+ TILs or high proximity to CD163+ TAMs. In a subgroup analysis including 92 patients, a significant negative impact on DFS (aHR, 4.49; 95% CI, 1.73-11.64; P = .002) and OS (aHR, 3.97; 95% CI, 1.37-11.49; P = .01) was observed in sentinel lymph node (SLN)-negative patients with a high proximity of CD163+ TAMs to CD8+ TILs. These findings could help identify high-risk patients in the context of thick melanoma and a negative SLN. Our study suggests the importance of quantifying not only the density of immune cells but also the individual and combined relative spatial distributions of tumor cells and immune cells for clinical outcomes in SLN-negative primary CM patients.

Optimising multiplex immunofluorescence staining for characterising the tumour immune micro-environment

Exploring the tumour microenvironment provides insight into the unique interaction between the host and tumour. Ultimately, its study improves understanding of how an individual mounts and achieves an anti-tumour immune response. In the context of colorectal cancer, immune biomarkers within the tumour microenvironment outperform traditional histopathological staging in predicting disease recurrence. Multiplex immunofluorescence enables simultaneous assessment of multiple markers to provide a highly accurate classification of immune cells and their spatial characterisation relative to tumour tissue. Further, automated slide staining provides staining consistency and reduces labour costs. Image acquisition using a non-spectral scanner allows more researchers to utilise multiplexed immunofluorescence for translational research. Herein we describe the optimisation process of conducting automated staining using a five-colour, tyramide signal amplification-based multiplex immunofluorescence panel. Using antibodies against CD3, CD8, CD103 and cytokeratin, the panel characterises T cell populations within human colorectal adenocarcinoma tissue. We provide an overview of primary antibody titration and the development of tyramide signal amplification immunofluorescence monoplex assays. We detail the processes of antibody stripping and the role of exogenous horseradish peroxidase inhibition to facilitate multiplexing. An account of determining the staining sequence and fluorophore assignment is provided. We describe image acquisition using a standard fluorescence microscope slide scanner and the management of spectral crosstalk using this system. Finally, we briefly document the digital image analysis required to characterise cells and determine their spatial distribution within the colorectal tumour microenvironment.

Prognostic Markers within the Tumour Microenvironment in Classical Hodgkin Lymphoma

Classical Hodgkin lymphoma (cHL) accounts for 0.4% of all new cancer cases globally. Despite high cure rates with standard treatment, approximately 15% of patients still experience relapsed or refractory (RR) disease, and many of these eventually die from lymphoma-related causes. Exciting new targeted agents such as anti-PD-1 agents and brentuximab vedotin have changed the therapeutic paradigm beyond chemotherapy and radiotherapy alone. Advances in understanding of the molecular biology are providing insights in the context of novel therapies. The signature histology of cHL requires the presence of scant malignant Hodgkin Reed-Sternberg cells (HRSCs) surrounded by a complex immune-rich tumour microenvironment (TME). The TME cellular composition strongly influences outcomes, yet knowledge of the precise characteristics of TME cells and their interactions with HRSCs is evolving. Novel high-throughput technologies and single-cell sequencing allow deeper analyses of the TME and mechanisms elicited by HRSCs to propagate growth and avoid immune response. In this review, we explore the evolution of knowledge on the prognostic role of immune cells within the TME and provide an up-to-date overview of emerging prognostic data on cHL from new technologies that are starting to unwind the complexity of the cHL TME and provide translational insights into how to improve therapy in the clinic.

Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level

In this perspective we discuss how tumor heterogeneity and therapy resistance necessitate a focus on more personalized approaches, prompting a shift toward precision medicine. At the heart of the shift towards personalized medicine, omics-driven systems biology becomes a driving force as it leverages high-throughput technologies and novel bioinformatics tools. These enable the creation of systems-based maps, providing a comprehensive view of individual tumor's functional plasticity. We highlight the innovative PHENOSTAMP program, which leverages high-dimensional data to construct a visually intuitive and user-friendly map. This map was created to encapsulate complex transitional states in cancer cells, such as Epithelial-Mesenchymal Transition (EMT) and Mesenchymal-Epithelial Transition (MET), offering a visually intuitive way to understand disease progression and therapeutic responses at single-cell resolution in relation to EMT-related single-cell phenotypes. Most importantly, PHENOSTAMP functions as a reference map, which allows researchers and clinicians to assess one clinical specimen at a time in relation to their phenotypic heterogeneity, setting the foundation on constructing phenotypic maps for personalized medicine. This perspective argues that such dynamic predictive maps could also catalyze the development of personalized cancer treatment. They hold the potential to transform our understanding of cancer biology, providing a foundation for a future where therapy is tailored to each patient's unique molecular and cellular tumor profile. As our knowledge of cancer expands, these maps can be continually refined, ensuring they remain a valuable tool in precision oncology.

Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study

The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.

Donor-derived regulatory dendritic cell infusion modulates effector CD8+ T cell and NK cell responses after liver transplantation

Immune cell-based therapies are promising strategies to facilitate immunosuppression withdrawal after organ transplantation. Regulatory dendritic cells (DCreg) are innate immune cells that down-regulate alloimmune responses in preclinical models. Here, we performed clinical monitoring and comprehensive assessment of peripheral and allograft tissue immune cell populations in DCreg-infused live-donor liver transplant (LDLT) recipients up to 12 months (M) after transplant. Thirteen patients were given a single infusion of donor-derived DCreg 1 week before transplant (STUDY) and were compared with 40 propensity-matched standard-of-care (SOC) patients. Donor-derived DCreg infusion was well tolerated in all STUDY patients. There were no differences in postoperative complications or biopsy-confirmed acute rejection compared with SOC patients up to 12M. DCreg administration was associated with lower frequencies of effector T-bet+Eomes+CD8+ T cells and CD16bright natural killer (NK) cells and an increase in putative tolerogenic CD141+CD163+ DCs compared with SOC at 12M. Antidonor proliferative capacity of interferon-γ+ (IFN-γ+) CD4+ and CD8+ T cells was lower compared with antithird party responses in STUDY participants, but not in SOC patients, at 12M. In addition, lower circulating concentrations of interleukin-12p40 (IL-12p40), IFN-γ, and CXCL10 were detected in STUDY participants compared with SOC patients at 12M. Analysis of 12M allograft biopsies revealed lower frequencies of graft-infiltrating CD8+ T cells, as well as attenuation of cytolytic TH1 effector genes and pathways among intragraft CD8+ T cells and NK cells, in DCreg-infused patients. These reductions may be conducive to reduced dependence on immunosuppressive drug therapy or immunosuppression withdrawal.

Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics

Tissues are complex environments where different cell types are in constant interaction with each other and with non-cellular components. Preserving the spatial context during proteomics analyses of tissue samples has become an important objective for different applications, one of the most important being the investigation of the tumor microenvironment. Here, we describe a multiplexed protein biomarker detection method on the COMET instrument, coined sequential ImmunoFluorescence (seqIF). The fully automated method uses successive applications of antibody incubation and elution, and in-situ imaging enabled by an integrated microscope and a microfluidic chip that provides optimized optical access to the sample. We show seqIF data on different sample types such as tumor and healthy tissue, including 40-plex on a single tissue section that is obtained in less than 24 h, using off-the-shelf antibodies. We also present extensive characterization of the developed method, including elution efficiency, epitope stability, repeatability and reproducibility, signal uniformity, and dynamic range, in addition to marker and panel optimization strategies. The streamlined workflow using off-the-shelf antibodies, data quality enabling downstream analysis, and ease of reaching hyperplex levels make seqIF suitable for immune-oncology research and other disciplines requiring spatial analysis, paving the way for its adoption in clinical settings.

Spatial Single Cell Analysis of Proteins in 2D Human Gastruloids Using Iterative Immunofluorescence

During development, cell signaling instructs tissue patterning, the process by which initially identical cells give rise to spatially organized structures consisting of different cell types. How multiple signals combinatorially instruct fate in space and time remains poorly understood. Simultaneous measurement of signaling activity through multiple signaling pathways and of the cell fates they control is critical to addressing this problem. Here we describe an iterative immunofluorescence protocol and computational pipeline to interrogate pattern formation in a 2D model of human gastrulation with far greater multiplexing than is possible with standard immunofluorescence techniques. This protocol and computational pipeline together enable imaging followed by spatial and co-localization analysis of over 27 proteins in the same gastruloids. We demonstrate this by clustering single cell protein expression, using techniques familiar from scRNA-seq, and linking this to spatial position to calculate spatial distributions and cell signaling activity of different cell types. These methods are not limited to patterning in 2D gastruloids and can be easily extended to other contexts. In addition to the iterative immunofluorescence protocol and analysis pipeline, Support Protocols for 2D gastruloid differentiation and producing micropatterned multi-well slides are included. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Iterative immunofluorescence Basic Protocol 2: Computational analysis pipeline Support Protocol 1: Generating micropatterned multi-well slides Support Protocol 2: Differentiation of 2D gastruloids.

Quantitative multiplexed imaging technologies for single-cell analysis to assess predictive markers for immunotherapy in thoracic immuno-oncology: promises and challenges

The past decade has witnessed a revolution in cancer treatment by the shift from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular the immune-checkpoint inhibitors (ICIs). These immunotherapies selectively release the host immune system against the tumour and have shown unprecedented durable remission for patients with cancers that were thought incurable such as advanced non-small cell lung cancer (aNSCLC). The prediction of therapy response is based since the first anti-PD-1/PD-L1 molecules FDA and EMA approvals on the level of PD-L1 tumour cells expression evaluated by immunohistochemistry, and recently more or less on tumour mutation burden in the USA. However, not all aNSCLC patients benefit from immunotherapy equally, since only around 30% of them received ICIs and among them 30% have an initial response to these treatments. Conversely, a few aNSCLC patients could have an efficacy ICIs response despite low PD-L1 tumour cells expression. In this context, there is an urgent need to look for additional robust predictive markers for ICIs efficacy in thoracic oncology. Understanding of the mechanisms that enable cancer cells to adapt to and eventually overcome therapy and identifying such mechanisms can help circumvent resistance and improve treatment. However, more than a unique universal marker, the evaluation of several molecules in the tumour at the same time, particularly by using multiplex immunostaining is a promising open room to optimise the selection of patients who benefit from ICIs. Therefore, urgent further efforts are needed to optimise to individualise immunotherapy based on both patient-specific and tumour-specific characteristics. This review aims to rethink the role of multiplex immunostaining in immuno-thoracic oncology, with the current advantages and limitations in the near-daily practice use.

Multiplex imaging in immuno-oncology

Multiplex imaging has emerged as an invaluable tool for immune-oncologists and translational researchers, enabling them to examine intricate interactions among immune cells, stroma, matrix, and malignant cells within the tumor microenvironment (TME). It holds significant promise in the quest to discover improved biomarkers for treatment stratification and identify novel therapeutic targets. Nonetheless, several challenges exist in the realms of study design, experiment optimization, and data analysis. In this review, our aim is to present an overview of the utilization of multiplex imaging in immuno-oncology studies and inform novice researchers about the fundamental principles at each stage of the imaging and analysis process.

Advancing Understanding of Non-Small Cell Lung Cancer with Multiplexed Antibody-Based Spatial Imaging Technologies

Non-small cell lung cancer (NSCLC) remains a cause of significant morbidity and mortality, despite significant advances made in its treatment using immune checkpoint inhibitors (ICIs) over the last decade; while a minority experience prolonged responses with ICIs, benefit is limited for most patients. The development of multiplexed antibody-based (MAB) spatial tissue imaging technologies has revolutionised analysis of the tumour microenvironment (TME), enabling identification of a wide range of cell types and subtypes, and analysis of the spatial relationships and interactions between them. Such study has the potential to translate into a greater understanding of treatment susceptibility and resistance, factors influencing prognosis and recurrence risk, and identification of novel therapeutic approaches and rational treatment combinations to improve patient outcomes in the clinic. Herein we review studies that have leveraged MAB technologies to deliver novel insights into the TME of NSCLC.

Novel quantitative immunohistochemical analysis for evaluating PD-L1 expression with phosphor-integrated dots for predicting the efficacy of patients with cancer treated with immune checkpoint inhibitors

Introduction

Programmed cell death ligand 1 (PD-L1) expression in tumor tissues is measured as a predictor of the therapeutic efficacy of immune checkpoint inhibitors (ICIs) in many cancer types. PD-L1 expression is evaluated by immunohistochemical staining using 3,3´-diaminobenzidine (DAB) chronogenesis (IHC-DAB); however, quantitative and reproducibility issues remain. We focused on a highly sensitive quantitative immunohistochemical method using phosphor-integrated dots (PIDs), which are fluorescent nanoparticles, and evaluated PD-L1 expression between the PID method and conventional DAB method.

Methods

In total, 155 patients with metastatic or recurrent cancer treated with ICIs were enrolled from four university hospitals. Tumor tissue specimens collected before treatment were subjected to immunohistochemical staining with both the PID and conventional DAB methods to evaluate PD-L1 protein expression.

Results

PD-L1 expression assessed using the PID and DAB methods was positively correlated. We quantified PD-L1 expression using the PID method and calculated PD-L1 PID scores. The PID score was significantly higher in the responder group than in the non-responder group. Survival analysis demonstrated that PD-L1 expression evaluated using the IHC-DAB method was not associated with progression-free survival (PFS) or overall survival (OS). Yet, PFS and OS were strikingly prolonged in the high PD-L1 PID score group.

Conclusion

Quantification of PD-L1 expression as a PID score was more effective in predicting the treatment efficacy and prognosis of patients with cancer treated with ICIs. The quantitative evaluation of PD-L1 expression using the PID method is a novel strategy for protein detection. It is highly significant that the PID method was able to identify a group of patients with a favorable prognosis who could not be identified by the conventional DAB method.

H3K18 lactylation of senescent microglia potentiates brain aging and Alzheimer's disease through the NFκB signaling pathway

Cellular senescence serves as a fundamental and underlying activity that drives the aging process, and it is intricately associated with numerous age-related diseases, including Alzheimer's disease (AD), a neurodegenerative aging-related disorder characterized by progressive cognitive impairment. Although increasing evidence suggests that senescent microglia play a role in the pathogenesis of AD, their exact role remains unclear. In this study, we quantified the levels of lactic acid in senescent microglia, and hippocampus tissues of naturally aged mice and AD mice models (FAD4T and APP/PS1). We found lactic acid levels were significantly elevated in these cells and tissues compared to their corresponding counterparts, which increased the level of pan histone lysine lactylation (Kla). We aslo identified all histone Kla sites in senescent microglia, and found that both the H3K18 lactylation (H3K18la) and Pan-Kla were significantly up-regulated in senescent microglia and hippocampus tissues of naturally aged mice and AD modeling mice. We demonstrated that enhanced H3K18la directly stimulates the NFκB signaling pathway by increasing binding to the promoter of Rela (p65) and NFκB1(p50), thereby upregulating senescence-associated secretory phenotype (SASP) components IL-6 and IL-8. Our study provides novel insights into the physiological function of Kla and the epigenetic regulatory mechanism that regulates brain aging and AD. Specifically, we have identified the H3K18la/NFκB axis as a critical player in this process by modulating IL-6 and IL-8. Targeting this axis may be a potential therapeutic strategy for delaying aging and AD by blunting SASP.

A platform-independent framework for phenotyping of multiplex tissue imaging data

Multiplex imaging is a powerful tool to analyze the structural and functional states of cells in their morphological and pathological contexts. However, hypothesis testing with multiplex imaging data is a challenging task due to the extent and complexity of the information obtained. Various computational pipelines have been developed and validated to extract knowledge from specific imaging platforms. A common problem with customized pipelines is their reduced applicability across different imaging platforms: Every multiplex imaging technique exhibits platform-specific characteristics in terms of signal-to-noise ratio and acquisition artifacts that need to be accounted for to yield reliable and reproducible results. We propose a pixel classifier-based image preprocessing step that aims to minimize platform-dependency for all multiplex image analysis pipelines. Signal detection and noise reduction as well as artifact removal can be posed as a pixel classification problem in which all pixels in multiplex images can be assigned to two general classes of either I) signal of interest or II) artifacts and noise. The resulting feature representation maps contain pixel-scale representations of the input data, but exhibit significantly increased signal-to-noise ratios with normalized pixel values as output data. We demonstrate the validity of our proposed image preprocessing approach by comparing the results of two well-accepted and widely-used image analysis pipelines.

AHR, a novel inhibitory immune checkpoint receptor, is a potential therapeutic target for chemoresistant glioblastoma

PURPOSE

This study aims to elucidate the mechanism underlying temozolomide resistance in patients with MGMT promoter hypomethylated glioblastoma, which is correlated with poor prognosis. The objective is to identify therapeutic targets and drugs suitable for temozolomide-resistant glioblastoma patients using big data analysis.

METHODS

In this retrospective study, transcriptome sequencing data from 457 glioblastoma patients, multi-omics data, and single-cell sequencing data were employed to assess the expression pattern, prognostic value, and biological functions of AHR in glioblastoma. The HERB database was utilized to screen for AHR-targeted drugs for glioblastoma treatment. Validation of our findings was conducted using multiplex immunofluorescence staining of clinical samples and T cells and tumor cells co-culture models.

RESULTS

Our findings demonstrated that patients with MGMT promoter unmethylation did not benefit from postoperative temozolomide chemotherapy due to resistance arising from DNA repair function and tumor immune response. AHR was found to be expressed in immune cells and exhibited an immunomodulatory role in glioblastoma with MGMT promoter unmethylation. AHR was identified as a potential novel inhibitory immune checkpoint receptor, serving as a therapeutic target for temozolomide-resistant glioblastoma. Furthermore, targeting AHR with Semen aesculi markedly enhanced the cytotoxic effect of T cells on glioma cells.

CONCLUSIONS

In addition to DNA repair function, the tumor immune response plays a pivotal role in temozolomide resistance of glioblastoma. Herbal compounds targeting AHR may offer an effective treatment for temozolomide-resistant glioblastoma.

Skin Infiltrate Composition as a Telling Measure of Responses to Checkpoint Inhibitors

Checkpoint inhibitors treat a variety of tumor types with significant benefits. Unfortunately, these therapies come with diverse adverse events. Skin rash is observed early into treatment and might serve as an indicator of downstream responses to therapy. We studied the cellular composition of cutaneous eruptions and whether their contribution varies with the treatment applied. Skin samples from 18 patients with cancer and 11 controls were evaluated by mono- and multiplex imaging, quantification, and statistical analysis. T cells were the prime contributors to skin rash, with T cells and macrophages interacting and proliferating on site. Among T cell subsets examined, type 1 and 17 T cells were relatively increased among inflammatory skin infiltrates. A combination of increased cytotoxic T cell content and decreased macrophage abundance was associated with dual checkpoint inhibition over PD1 inhibition alone. Importantly, responders significantly separated from nonresponders by greater CD68+ macrophage and either CD11c+ antigen-presenting cell or CD4+ T cell abundance in skin rash. The microenvironment promoted epidermal proliferation and thickening as well. The combination of checkpoint inhibitors used affects the development and composition of skin infiltrates, whereas the combined abundance of two cell types in cutaneous eruptions aligns with responses to checkpoint inhibitor therapy.

Postoperative adjuvant aspirin for patients with hepatitis B virus-related hepatocellular carcinoma and portal vein tumor thrombus: An open-label, randomized controlled trial

Purpose

To compare the survival outcomes of postoperative adjuvant aspirin with surgery alone in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT).

Methods

From June 2013 to July 2015, an open-label, randomized controlled study was conducted in patients with resectable HBV-related HCC and PVTT. Patients were randomly assigned to undergo surgical resection and postoperative adjuvant aspirin (n = 40) or hepatectomy alone (n = 40). The primary end point was overall survival (OS). The secondary end points were time to recurrence of primary tumor (t-TTR) and time to recurrence of PVTT (p-TTR). The expression levels of COX1 and COX2 in surgical specimens of the aspirin group were correlated with patients' survival.

Results

The median OS were 16.2 and 13.4 months for the adjuvant aspirin and surgery alone groups, respectively. The median t-TTR were 5.3 and 3.2 months for the adjuvant aspirin and surgery alone groups, respectively. There was no significant difference in the OS and t-TTR between the two groups of patients (P = 0.078 and 0.336, respectively). The median p-TTR were 12.0 months and 5.4 months for the adjuvant aspirin group and the surgery alone group, respectively. Patients in the adjuvant aspirin group had markedly longer p-TTR (P = 0.001). Increased expressions of COX1 or COX2 in tumor tissues denoted better prognosis for patients receiving adjuvant aspirin.

Conclusion

For patients with resectable HBV-related HCC and PVTT, postoperative adjuvant aspirin significantly prolonged time to recurrence of PVTT than surgery alone. Expression of COX1 or COX2 may predict survival in these patients.

Heterogeneity of the Tumor Microenvironment Across Molecular Subtypes of Breast Cancer

Breast cancer is a heterogenous disease at the molecular level thus, it can be hypothesized that different molecular subtypes differ in their tumor microenvironment (TME) also. Understanding the TME heterogeneity may provide new prognostic biomarkers and new targets for cancer therapy. For deciphering heterogeneity in the TME, immunohistochemistry for immune markers (CD3, CD4, CD8, CD68, CD163, and programmed death-ligand 1), Cancer-associated fibroblast markers [anti-fibroblast activating protein α (FAP-α), platelet-derived growth factor receptor α (PDGFR-α), S100A4, Neuron-glial antigen 2, and Caveolin-1], and angiogenesis (CD31) was performed on tissue microarrays of different molecular subtypes of breast cancer. High CD3 + T cells were noted in the Luminal B subtype ( P =0.002) of which the majority were CD8 + cytotoxic T cells. Programmed death-ligand 1 expression in immune cells was highest in the human epidermal growth factor receptor 2 (Her-2)-positive and Luminal B subtypes compared with the triple-negative breast cancer (TNBC) subtype ( P =0.003). Her-2 subtype is rich in M2 tumor-associated macrophages ( P =0.000) compared with TNBC and Luminal B subtypes. M2 immune microenvironment correlated with high tumor grade and high Ki-67. Her-2 and TNBC subtypes are rich in extracellular matrix remodeling (FAP-α, P =0.003), angiogenesis-promoting (PDGFR-α; P =0.000) and invasion markers (Neuron-glial antigen 2, P =0.000; S100A4, P =0.07) compared with Luminal subtypes. Mean Microvessel density showed an increasing trend: Luminal A>Luminal B>Her-2 positive>TNBC; however, this difference was not statistically significant. The cancer-associated fibroblasts (FAP-α, PDGFR-α, and Neuron-glial antigen 2) showed a positive correlation with lymph node metastasis in specific subtypes. Immune cells, tumor-associated macrophage, and cancer-associated fibroblast-related s tromal markers showed higher expression in Luminal B, Her-2 positive, and TNBC respectively. This differential expression of different components of TME indicates heterogeneity of the TME across molecular subtypes of breast cancer.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets due to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of 10 RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of 10 channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

SUMMARY

Spectral imaging with signal amplification based on the mechanism of hybridization chain reaction enables robust 10-plex, quantitative, high-resolution imaging of RNA and protein targets in whole-mount vertebrate embryos and brain sections.

IL-25 induces airway remodeling in asthma by orchestrating the phenotypic changes of epithelial cell and fibrocyte

BACKGROUND

Previous studies have shown that IL-25 levels are increased in patients with asthma with fixed airflow limitation (FAL). However, the mechanism by which IL-25 contributes to airway remodeling and FAL remains unclear. Here, we hypothesized that IL-25 facilitates pro-fibrotic phenotypic changes in bronchial epithelial cells (BECs) and circulating fibrocytes (CFs), orchestrates pathological crosstalk from BECs to CFs, and thereby contributes to airway remodeling and FAL.

METHODS

Fibrocytes from asthmatic patients with FAL and chronic asthma murine models were detected using flow cytometry, multiplex staining and multispectral imaging analysis. The effect of IL-25 on BECs and CFs and on the crosstalk between BECs and CFs was determined using cell culture and co-culture systems.

RESULTS

We found that asthmatic patients with FAL had higher numbers of IL-25 receptor (i.e., IL-17RB)+-CFs, which were negatively correlated with forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC). The number of airway IL-17RB+-fibrocytes was significantly increased in ovalbumin (OVA)- and IL-25-induced asthmatic mice versus the control subjects. BECs stimulated with IL-25 exhibited an epithelial-mesenchymal transition (EMT)-like phenotypic changes. CFs stimulated with IL-25 produced high levels of extracellular matrix (ECM) proteins and connective tissue growth factors (CTGF). These profibrotic effects of IL-25 were partially blocked by the PI3K-AKT inhibitor LY294002. In the cell co-culture system, OVA-challenged BECs facilitated the migration and expression of ECM proteins and CTGF in CFs, which were markedly blocked using an anti-IL-17RB antibody.

CONCLUSION

These results suggest that IL-25 may serve as a potential therapeutic target for asthmatic patients with FAL.

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures important tissue heterogeneity, which make it impossible for proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single tissue voxel and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single tissue voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ∼900 and ∼4,600 proteins for single voxel from fresh frozen human spleen tissue at 20 μm × 20 μm × 10 μm (close to single cells) and 200 μm × 200 μm × 10 μm (∼100 cells), respectively. 100s-1000s of protein signatures with differential expression levels were identified to be spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. Antibody-based CODEX imaging was used to validate label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

Exploratory study of macrophage polarization and spatial distribution in colorectal cancer liver metastasis: a pilot study

Background

The liver is the most typical site of metastatic disease for patients with colorectal cancer (CRC), and up to half the patients with CRC will develop colorectal liver metastasis (CLM). Studying the tumor microenvironment, particularly macrophages and their spatial distribution, can give us critical insight into treatment.

Methods

Ten CLMs (five treatment-naïve and five post-neoadjuvant chemotherapy) were stained with multiplex immunofluorescence panels against cytokeratins, CD68, Arg1, CD206, CD86, CD163, PD-L1, and MRP8-14. Densities of cell phenotypes and their spatial distribution in the tumor center and the normal liver-tumor interface were correlated with clinicopathological variables.

Results

M2 macrophages were the predominant subtype in both the tumor center and the periphery, with a relatively higher density at the periphery. The larger tumors, more than 3.9 cm, were associated with higher densities of total CD68+ macrophages and CD68+CD163+ CD206neg and CD68+CD206+ CD163neg M2 macrophage subtypes. Total macrophages in the tumor periphery demonstrated significantly greater proximity to malignant cells than did those in the tumor center (p=0.0371). The presence of higher than median CD68+MRP8-14+CD86neg M1 macrophages in the tumor center was associated with poor overall survival (median 2.34 years) compared to cases with lower than median M1 macrophages at the tumor center (median 6.41 years) in univariate analysis.

Conclusion

The dominant polarization of the M2 macrophage subtype could drive new therapeutic approaches in CLM patients.

Quantile Index Biomarkers Based on Single-Cell Expression Data

Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.

Spatial immunophenotypes predict clinical outcome in intrahepatic cholangiocarcinoma

Background & Aims

Intrahepatic cholangiocarcinoma (iCCA) is a severe malignant tumour that shows only modest responses to immunotherapy. We aimed to identify the spatial immunophenotypes of iCCA and delineate potential immune escape mechanisms.

Method

Multiplex immunohistochemistry (mIHC) was performed to quantitatively evaluate the distribution of 16 immune cell subsets in intratumour, invasive margin and peritumour areas in a cohort of 192 treatment-naïve patients with iCCA. Multiregion unsupervised clustering was used to determine three spatial immunophenotypes, and multiomics analyses were carried out to explore functional differences.Results: iCCA displayed a region-specific distribution of immune cell subsets with abundant CD15⁺ neutrophil infiltration in intratumour areas. Three spatial immunophenotypes encompassing inflamed (35%), excluded (35%) and ignored (30%) phenotypes were identified. The inflamed phenotype showed characteristics of abundant immune cell infiltration in intratumour areas, increased PD-L1 expression and relatively favourable overall survival. The excluded phenotype with a moderate prognosis was characterized by immune cell infiltration restricted to the invasive margin or peritumour areas and upregulation of activated hepatic stellate cells, extracellular matrix and Notch signalling pathways. The ignored phenotype, with scarce immune cell infiltration across all subregions, was associated with MAPK signalling pathway elevation and a poor prognosis. The excluded and ignored phenotypes, constituting non-inflamed phenotypes, shared features of an increased angiogenesis score, TGF-β and Wnt-β catenin pathway upregulation and were enriched for BAP1 mutations and FGFR2 fusions.

Conclusion

We identified three spatial immunophenotypes with different overall prognoses in iCCA. Tailored therapies based on the distinct immune evasion mechanisms of the spatial immunophenotypes are needed.

Impact and implications

The contribution of immune cell infiltration in the invasive margin and peritumour areas has been proved. We explored the multiregional immune contexture of 192 patients to identify three spatial immunophenotypes in intrahepatic cholangiocarcinoma (iCCA). By integrating genomic and transcriptomic data, phenotype-specific biological behaviours and potential immune escape mechanisms were analysed. Our findings provide a rationale to develop personalized therapies for iCCA.

Understanding virus-host interactions in tissues

Although virus-host interactions are usually studied in a single cell type using in vitro assays in immortalized cell lines or isolated cell populations, it is important to remember that what is happening inside one infected cell does not translate to understanding how an infected cell behaves in a tissue, organ or whole organism. Infections occur in complex tissue environments, which contain a host of factors that can alter the course of the infection, including immune cells, non-immune cells and extracellular-matrix components. These factors affect how the host responds to the virus and form the basis of the protective response. To understand virus infection, tools are needed that can profile the tissue environment. This Review highlights methods to study virus-host interactions in the infection microenvironment.