Spatial Mapping of Myeloid Cells and Macrophages by Multiplexed Tissue Staining

Machine Learning Identification and Classification of Mitosis and Migration of Cancer Cells in a Lab-on-CMOS Capacitance Sensing Platform

Cell culture assays play a vital role in various fields of biology. Conventional assay techniques like immunohistochemistry, immunofluorescence, and flow cytometry offer valuable insights into cell phenotype and behavior. However, each of these techniques requires labeling or staining, and this is a major drawback, specifically in applications that require compact and integrated analytical devices. To address this shortcoming, CMOS capacitance sensors capable of conducting label-free cell culture assays have been proposed. In this paper, we present a computational framework for further augmenting the capabilities of these capacitance sensors. In our framework, identification and classification of mitosis and migration are achieved by leveraging observations from measured capacitance time series data. Specifically, we engineered two time series features that enable discriminating cell behaviors at the single-cell level. Our feature representation achieves an area under curve (AUC) of 0.719 in the receiver operating characteristic (ROC) curve. Additionally, we show that our feature representation technique is applicable across arbitrary experiments, as validated by a leave-one-run-out test yielding an F-1 score of 0.803 and a G-Mean of 0.647.

A protocol for immunostaining of macrophages in whole-mount mouse cornea, conjunctiva, and lacrimal gland

The healthy lacrimal functional unit contains a resident macrophage population. Here, we present a protocol for immunofluorescent staining of macrophage markers, CD11b, F4/80, and CD206, in whole-mount mouse cornea, conjunctiva, and 50-μM-thick lacrimal gland section. We describe steps for dissection, fixation, permeabilization, and blocking. We then detail procedures for the detection and spatial localization of macrophages through immunostaining and confocal imaging. This approach circumvents the need to obtain thin tissue sections and acquire macrophage images from each tissue section.

Immunohistochemistry annotations enhance AI identification of lymphocytes and neutrophils in digitized H&E slides from inflammatory bowel disease

BACKGROUND AND OBJECTIVE

Histologic assessment of the immune infiltrate in H&E slides is vital in diagnosing and managing inflammatory bowel diseases, but these assessments are subjective and time-consuming even for those with expertise. The development of deep learning models to aid in these assessments has been limited by the paucity of image data with reliably annotated immune cells available for training.

METHODS

To address these challenges, we developed a pipeline that automates the neutrophil and lymphocyte labeling in ROIs from digital H&E slides. The data included ROIs extracted from 19 digitized H&E slides and the same slides restained with immunohistochemistry. Our pipeline first delineates each nucleus in H&E ROIs. Using the colorimetric features of the immunohistochemical stains (red: neutrophils, green: lymphocytes) in the immunohistochemistry ROIs, each cell was labeled as a neutrophil, a lymphocyte, or another cell. The labels were then transferred to the corresponding H&E ROIs by image registration, and the ROI registration accuracy was assessed by the median target registration error resulting in a labeled dataset. The newly formed dataset (NeuLy-IHC) comprising 519 ROIs with 235,256 labeled cells (74,339 lymphocytes, 16,326 neutrophils and 144,591 other cells) was used to train the HoVer-Net(NeuLy) model. The performance of HoVer-Net(NeuLy) measured by DICE coefficient (segmentation accuracy) and F1-scores (classification accuracy), was compared to those achieved by HoVer-Net(MoNuSAC) and SMILE(MoNuSAC) publicly available models trained on cancer-containing ROIs from the MoNuSAC dataset with manual cell labeling and pathologists' annotations.

RESULTS

The 1.0 μm median target registration error of ROIs observed was low demonstrating robust transferring of cellular labels from immunohistochemistry ROIs to H&E ROIs. In the test set comprising 76 NeuLy-IHC and 78 MoNuSAC ROIs, the HoVer-Net(NeuLy) achieved a DICE coefficient of 0.861 and F1-sores of 0.827, 0.838, and 0.828, for neutrophils, lymphocytes, and other cells, respectively, outperforming the HoVer-Net(MoNuSAC)'s and SMILE(MoNuSAC)'s DICE coefficient and F1 scores for each cell category.

CONCLUSIONS

We attribute the improved performance of HoVer-Net(NeuLy) to the larger number of immune cells in the NeuLy-IHC dataset (in total 5x more, including 21x more neutrophils) than in the MoNuSAC dataset. Despite being trained on data from inflammatory bowel disease specimens, our model maintained robust performance when tested on previously unseen data derived from cancer specimens. The NeuLy-IHC set provides opportunities for training accurate models to quantify the inflammatory infiltrate in digital histologic slides.

Tissue-Resident Macrophages in Cancer: Friend or Foe?

INTRODUCTION

Macrophages are essential in maintaining homeostasis, combating infections, and influencing the process of various diseases, including cancer. Macrophages originate from diverse lineages: Notably, tissue-resident macrophages (TRMs) differ from hematopoietic stem cells and circulating monocyte-derived macrophages based on genetics, development, and function. Therefore, understanding the recruited and TRM populations is crucial for investigating disease processes.

METHODS

By searching literature databses, we summarized recent relevant studies. Research has shown that tumor-associated macrophages (TAMs) of distinct origins accumulate in tumor microenvironment (TME), with TRM-derived TAMs closely resembling gene signatures of normal TRMs.

RESULTS

Recent studies have revealed that TRMs play a crucial role in cancer progression. However, organ-specific effects complicate TRM investigations. Nonetheless, the precise involvement of TRMs in tumors is unclear. This review explores the multifaceted roles of TRMs in cancer, presenting insights into their origins, proliferation, the latest research methodologies, their impact across various tumor sites, their potential and strategies as therapeutic targets, interactions with other cells within the TME, and the internal heterogeneity of TRMs.

CONCLUSIONS

We believe that a comprehensive understanding of the multifaceted roles of TRMs will pave the way for targeted TRM therapies in the treatment of cancer.

Copper Nanoparticle Loaded Electrospun Patches for Infected Wound Treatment: From Development to In-Vivo Application

This study investigates the development and application of electrospun wound dressings based on polylactic acid (PLA) nanofibers, chitosan, and copper nanoparticles (CuNPs) for the treatment of purulent skin wounds. The materials were evaluated for their structural, antibacterial, and wound healing properties using an animal model. PLA/Ch-CuNPs demonstrated the most significant antibacterial activity against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa, surpassing the other tested materials. The integration of CuNPs into the nanofiber matrices not only enhanced the antimicrobial efficacy but also maintained the structural integrity and biocompatibility of the dressings. In vivo experiments using a rat model showed that PLA/Ch-CuNPs facilitated faster wound healing with reduced exudative and inflammatory responses compared to PLA alone or PLA-CuNPs. Histological and immunohistochemical assessments revealed that the combination of PLA, chitosan, and CuNPs mitigated the inflammatory processes and promoted tissue regeneration more effectively. However, this study identified potential toxicity related to copper ions, emphasizing the need for careful optimization of CuNP concentrations. These findings suggest that PLA/Ch-CuNPs could serve as a potent, cost-effective wound dressing with broad-spectrum antibacterial properties, addressing the challenge of antibiotic-resistant infections and enhancing wound healing outcomes.

Microglia at sites of atrophy restrict the progression of retinal degeneration via galectin-3 and Trem2

Outer retinal degenerations, including age-related macular degeneration (AMD), are characterized by photoreceptor and retinal pigment epithelium (RPE) atrophy. In these blinding diseases, macrophages accumulate at atrophic sites, but their ontogeny and niche specialization remain poorly understood, especially in humans. We uncovered a unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and human AMD. In disease models, conditional deletion of galectin-3 in microglia led to phagocytosis defects and consequent augmented photoreceptor death, RPE damage, and vision loss, indicating protective roles. Mechanistically, Trem2 signaling orchestrated microglial migration to atrophic sites and induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection but in a galectin-3-dependent manner. In elderly human subjects, we identified this highly conserved microglial population that expressed galectin-3 and Trem2. This population was significantly enriched in the macular RPE-choroid of AMD subjects. Collectively, our findings reveal a neuroprotective population of microglia and a potential therapeutic target for mitigating retinal degeneration.

INHBA(+) cancer-associated fibroblasts generate an immunosuppressive tumor microenvironment in ovarian cancer

Effective targeting of cancer-associated fibroblasts (CAFs) is hindered by the lack of specific biomarkers and a poor understanding of the mechanisms by which different populations of CAFs contribute to cancer progression. While the role of TGFβ in CAFs is well-studied, less attention has been focused on a structurally and functionally similar protein, Activin A (encoded by INHBA). Here, we identified INHBA(+) CAFs as key players in tumor promotion and immunosuppression. Spatiotemporal analyses of patient-matched primary, metastatic, and recurrent ovarian carcinomas revealed that aggressive metastatic tumors enriched in INHBA(+) CAFs were also enriched in regulatory T cells (Tregs). In ovarian cancer mouse models, intraperitoneal injection of the Activin A neutralizing antibody attenuated tumor progression and infiltration with pro-tumorigenic subsets of myofibroblasts and macrophages. Downregulation of INHBA in human ovarian CAFs inhibited pro-tumorigenic CAF functions. Co-culture of human ovarian CAFs and T cells revealed the dependence of Treg differentiation on direct contact with INHBA(+) CAFs. Mechanistically, INHBA/recombinant Activin A in CAFs induced the autocrine expression of PD-L1 through SMAD2-dependent signaling, which promoted Treg differentiation. Collectively, our study identified an INHBA(+) subset of immunomodulatory pro-tumoral CAFs as a potential therapeutic target in advanced ovarian cancers which typically show a poor response to immunotherapy.

Microglia at Sites of Atrophy Restrict the Progression of Retinal Degeneration via Galectin-3 and Trem2 Interactions

Degenerative diseases of the outer retina, including age-related macular degeneration (AMD), are characterized by atrophy of photoreceptors and retinal pigment epithelium (RPE). In these blinding diseases, macrophages are known to accumulate ectopically at sites of atrophy, but their ontogeny and functional specialization within this atrophic niche remain poorly understood, especially in the human context. Here, we uncovered a transcriptionally unique profile of microglia, marked by galectin-3 upregulation, at atrophic sites in mouse models of retinal degeneration and in human AMD. Using disease models, we found that conditional deletion of galectin-3 in microglia led to defects in phagocytosis and consequent augmented photoreceptor death, RPE damage and vision loss, suggestive of a protective role. Mechanistically, Trem2 signaling orchestrated the migration of microglial cells to sites of atrophy, and there, induced galectin-3 expression. Moreover, pharmacologic Trem2 agonization led to heightened protection, but only in a galectin-3-dependent manner, further signifying the functional interdependence of these two molecules. Likewise in elderly human subjects, we identified a highly conserved population of microglia at the transcriptomic, protein and spatial levels, and this population was enriched in the macular region of postmortem AMD subjects. Collectively, our findings reveal an atrophy-associated specialization of microglia that restricts the progression of retinal degeneration in mice and further suggest that these protective microglia are conserved in AMD.

Geospatial characterization of immune cell distributions and dynamics across the microenvironment in clear cell renal cell carcinoma

INTRODUCTION

In clear cell renal cell carcinoma (ccRCC), tumor-associated macrophage (TAM) induction of CD8+T cells into a terminally exhausted state has been implicated as a major mechanism of immunotherapy resistance, but a deeper biological understanding is necessary.

METHODS

Primary ccRCC tumor samples were obtained from 97 patients between 2004 and 2018. Multiplex immunofluorescence using lymphoid and myeloid markers was performed in seven regions of interest per patient across three predefined zones, and geospatial analysis was performed using Ripley's K analysis, a methodology adapted from ecology.

RESULTS

Clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stroma interface was associated with worse clinical stage (tumor/CD163+nK(75): stage I/II: 4.4 (IQR -0.5 to 5.1); stage III: 1.4 (IQR -0.3 to 3.5); stage IV: 0.6 (IQR -2.1 to 2.1); p=0.04 between stage I/II and stage IV), and worse overall survival (OS) and cancer-specific survival (CSS) (tumor/CD163+nK(75): median OS-hi=149 months, lo=86 months, false-discovery rate (FDR)-adj. Cox p<0.001; median CSS-hi=174 months, lo=85 months; FDR-adj. Cox p<0.001). An RNA-seq differential gene expression score was developed using this geospatial metric, and was externally validated in multiple independent cohorts of patients with ccRCC including: TCGA KIRC, and the IMmotion151, IMmotion150, and JAVELIN Renal 101 clinical trials. In addition, this CD163+ geospatial pattern was found to be associated with a higher TIM-3+ proportion of CD8+T cells, indicative of terminal exhaustion (tumor-core: 0.07 (IQR 0.04-0.14) vs 0.40 (IQR 0.15-0.66), p=0.05).

CONCLUSIONS

Geospatial clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stromal interface was associated with poor clinical outcomes and CD8+T cell terminal exhaustion.

Significant changes in macrophage and CD8 T cell densities in primary prostate tumors 2 weeks after SBRT

BACKGROUND

Radiotherapy impacts the local immune response to cancers. Prostate Stereotactic Body Radiotherapy (SBRT) is a highly focused method to deliver radiotherapy often used to treat prostate cancer. This is the first direct comparison of immune cells within prostate cancers before and after SBRT in patients.

METHODS

Prostate cancers before and 2 weeks after SBRT are interrogated by multiplex immune fluorescence targeting various T cells and macrophages markers and analyzed by cell and pixel density, as part of a clinical trial of SBRT neoadjuvant to radical prostatectomy.

RESULTS

Two weeks after SBRT, CD68, and CD163 macrophages are significantly increased while CD8 T cells are decreased. SBRT markedly alters the immune environment within prostate cancers.

Measuring and Modeling Macrophage Growth using a Lab-on-CMOS Capacitance Sensing Microsystem

We report on the use of a lab-on-CMOS biosensor platform for quantitatively tracking the growth of RAW 264.7 murine Balb/c macrophages. We show that macrophage growth over a wide sensing area correlates linearly with an average capacitance growth factor resulting from capacitance measurements at a plurality of electrodes dispersed in the sensing area. We further show a temporal model that captures the cell evolution in the area of interest over long periods (e.g., 30 hours). The model links the cell numbers and the average capacitance growth factor associated with the sensing area to describe the observed growth kinetics.

MNPmApp: An image analysis tool to quantify mononuclear phagocyte distribution in mucosal tissues

Mononuclear phagocytes (MNPs) such as dendritic cells and macrophages perform key sentinel functions in mucosal tissues and are responsible for inducing and maintaining adaptive immune responses to mucosal pathogens. Positioning of MNPs at the epithelial interface facilitates their access to luminally-derived antigens and regulates MNP function through soluble mediators or surface receptor interactions. Therefore, accurately quantifying the distribution of MNPs within mucosal tissues as well as their spatial relationship with other cells is important to infer functional cellular interactions in health and disease. In this study, we developed and validated a MATLAB-based tissue cytometry platform, termed "MNP mapping application" (MNPmApp), that performs high throughput analyses of MNP density and distribution in the gastrointestinal mucosa based on digital multicolor fluorescence microscopy images and that integrates a Monte Carlo modeling feature to assess randomness of MNP distribution. MNPmApp identified MNPs in tissue sections of the human gastric mucosa with 98 ± 2% specificity and 76 ± 15% sensitivity for HLA-DR+ MNPs and 98 ± 1% specificity and 85 ± 12% sensitivity for CD11c+ MNPs. Monte Carlo modeling revealed that mean MNP-MNP distances for both HLA-DR+ and CD11c+ MNPs were significantly lower than anticipated based on random cell placement, whereas MNP-epithelial distances were similar to randomly placed cells. Surprisingly, H. pylori infection had no significant impact on the number of HLA-DR and CD11c MNPs or their distribution within the gastric lamina propria. However, our study demonstrated that MNPmApp is a reliable and user-friendly tool for unbiased quantitation of MNPs and their distribution at mucosal sites.

Distinct Phenotypes of Inflammation Associated Macrophages and Microglia in the Prefrontal Cortex Schizophrenia Compared to Controls

Approximately 40% of people with schizophrenia are classified as having "high inflammation." This subgroup has worse neuropathology than patients with "low inflammation." Thus, one would expect the resident microglia and possibly monocyte-derived macrophages infiltrating from the periphery to be "activated" in those with schizophrenia with elevated neuroinflammation. To test whether microglia and/or macrophages are associated with increased inflammatory signaling in schizophrenia, we measured microglia- and macrophage-associated transcripts in the postmortem dorsolateral prefrontal cortex of 69 controls and 72 people with schizophrenia. Both groups were stratified by neuroinflammatory status based on cortical mRNA levels of cytokines and SERPINA3. We found microglial mRNAs levels were either unchanged (IBA1 and Hexb, p > 0.20) or decreased (CD11c, <62% p < 0.001) in high inflammation schizophrenia compared to controls. Conversely, macrophage CD163 mRNA levels were increased in patients, substantially so in the high inflammation schizophrenia subgroup compared to low inflammation subgroup (>250%, p < 0.0001). In contrast, high inflammation controls did not have elevated CD163 mRNA compared to low inflammation controls (p > 0.05). The pro-inflammatory macrophage marker (CD64 mRNA) was elevated (>160%, all p < 0.05) and more related to CD163 mRNA in the high inflammation schizophrenia subgroup compared to high inflammation controls, while anti-inflammatory macrophage and cytokine markers (CD206 and IL-10 mRNAs) were either unchanged or decreased in schizophrenia. Finally, macrophage recruitment chemokine CCL2 mRNA was increased in schizophrenia (>200%, p < 0.0001) and CCL2 mRNA levels positively correlated with CD163 mRNA (r = 0.46, p < 0.0001). Collectively, our findings support the co-existence of quiescent microglia and increased pro-inflammatory macrophages in the cortex of people with schizophrenia.

Comparison of manual and automated digital image analysis systems for quantification of cellular protein expression

OBJECTIVE

Quantifying protein expression in immunohistochemically stained histological slides is an important tool for oncologic research. The use of computer-aided evaluation of IHC-stained slides significantly contributes to objectify measurements. Manual digital image analysis (mDIA) requires a user-dependent annotation of the region of interest (ROI). Others have built-in machine learning algorithms with automated digital image analysis (aDIA) and can detect the ROIs automatically. We aimed to investigate the agreement between the results obtained by aDIA and those derived from mDIA systems.

METHODS

We quantified chromogenic intensity (CI) and calculated the positive index (PI) in cohorts of tissue microarrays (TMA) using mDIA and aDIA. To consider the different distributions of staining within cellular sub-compartments and different tumor architecture our study encompassed nuclear and cytoplasmatic stainings in adenocarcinomas and squamous cell carcinomas.

RESULTS

Within all cohorts, we were able to show a high correlation between mDIA and aDIA for the CI (p<0.001) along with high agreement for the PI. Moreover, we were able to show that the cell detections of the programs were comparable as well and both proved to be reliable when compared to manual counting.

CONCLUSION

mDIA and aDIA show a high correlation in acquired IHC data. Both proved to be suitable to stratify patients for evaluation with clinical data. As both produce the same level of information, aDIA might be preferable as it is time-saving, can easily be reproduced, and enables regular and efficient output in large studies in a reasonable time period.

Systemic Inflammation Associates With a Myeloid Inflamed Tumor Microenvironment in Primary Resected Colon Cancer-May Cold Tumors Simply Be Too Hot?

Systemic inflammation measured by the acute-phase protein CRP associates with poor outcome across cancer types. In contrast, local tumor-associated inflammation, primarily evaluated by T-lymphocytes, correlates with favorable prognosis. Yet, little is known whether these two responses are related or opposing processes and why elevated CRP in relation to cancer is detrimental for clinical outcome. As proof of concept, we developed a platform combining multiplexed IHC and digital imaging, enabling a virtual readout of both lymphoid and myeloid immune markers and their spatial patterns in the primary tumors of resected stage II and III colon cancer (CC) patients with and without accompanying systemic inflammation. Twenty-one patients with elevated CRP (>30 mg/l) and 15 patients with low CRP (<10 mg/l) were included in the analyses. Whole slides from the primary tumors were stained for markers of adaptive (CD8+, CD4+, foxp3 regulatory T cells, CD20+ B cells) and innate (CD68+ macrophages, CD66b+ neutrophils) immunity and the immune checkpoint molecule PD-L1. Associations between individual immune markers, preoperative CRP values, mismatch repair status (MMR), and risk of recurrence or death were assessed. Unsupervised hierarchical clustering was used to explore whether distinct immune phenotypes were present. Tumors from systemically inflamed patients (CRP >30 mg/l) displayed significantly more myeloid features in terms of higher densities of CD66b+neutrophils (p = 0.001) and CD68+macrophages (p = 0.04) and less lymphoid features (lower CD8 T cell, p = 0.03, and foxp3 regulatory T cell densities, p = 0.03) regardless of MMR status. Additionally, systemically inflamed patients harbored lower mean distances between neutrophils and tumor cells within the TME. Intriguingly, microsatellite instable (MSI) tumor status correlated with systemic inflammation. However, using a combinatorial approach, we found that regardless of an adaptive composite score (compounded CD4+ and CD8+ T cells), a high innate score (CD66b+ neutrophils and CD68+ macrophages) associated significantly with elevated CRP. In conclusion, tumor-associated systemic inflammation correlated with a myeloid-dominated TME in a small cohort of resectable CC patients. Our data highlight the importance of a comprehensive immune classification of tumors including players of innate immunity and support a role for CRP as an informative biomarker of the immune response taking place at the tumor site.

Macrophage targeting in cancer

Tumorigenesis is not only determined by the intrinsic properties of cancer cells but also by their interactions with components of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are among the most abundant immune cells in the TME. During initial stages of tumor development, macrophages can either directly promote antitumor responses by killing tumor cells or indirectly recruit and activate other immune cells. As genetic changes occur within the tumor or T helper 2 (TH 2) cells begin to dominate the TME, TAMs begin to exhibit an immunosuppressive protumor phenotype that promotes tumor progression, metastasis, and resistance to therapy. Thus, targeting TAMs has emerged as a strategy for cancer therapy. To date, TAM targeting strategies have focused on macrophage depletion and inhibition of their recruitment into the TME. However, these strategies have shown limited therapeutic efficacy, although trials are still underway with combination therapies. The fact that macrophages have the potential for antitumor activity has moved the TAM targeting field toward the development of TAM-reprogramming strategies to support this antitumor immune response. Here, we discuss the various roles of TAMs in cancer therapy and their immunosuppressive properties, as well as implications for emerging checkpoint inhibitor-based immunotherapies. We review state-of-the-art TAM-targeting strategies, focusing on current ones at the preclinical and clinical trial stages that aim to reprogram TAMs as an oncological therapy.

In Situ Characterization of Human Lymphoid Tissue Immune Cells by Multispectral Confocal Imaging and Quantitative Image Analysis; Implications for HIV Reservoir Characterization

CD4 T cells are key mediators of adaptive immune responses during infection and vaccination. Within secondary lymphoid organs, helper CD4 T cells, particularly those residing in germinal centers known as follicular helper T cells (Tfh), provide critical help to B-cells to promote their survival, isotype switching and selection of high affinity memory B-cells. On the other hand, the important role of Tfh cells for the maintenance of HIV reservoir is well documented. Thus, interrogating and better understanding the tissue specific micro-environment and immune subsets that contribute to optimal Tfh cell differentiation and function is important for designing successful prevention and cure strategies. Here, we describe the development and optimization of eight multispectral confocal microscopy immunofluorescence panels designed for in depth characterization and immune-profiling of relevant immune cells in formalin-fixed paraffin-embedded human lymphoid tissue samples. We provide a comprehensive library of antibodies to use for the characterization of CD4+ T-cells -including Tfh and regulatory T-cells- as well as CD8 T-cells, B-cells, macrophages and dendritic cells and discuss how the resulting multispectral confocal datasets can be quantitatively dissected using the HistoCytometry pipeline to collect information about relative frequencies and immune cell spatial distributions. Cells harboring actively transcribed virus are analyzed using an in-situ hybridization assay for the characterization of HIV mRNA positive cells in combination with additional protein markers (multispectral RNAscope). The application of this methodology to lymphoid tissues offers a means to interrogate multiple relevant immune cell targets simultaneously at increased resolution in a reproducible manner to guide CD4 T-cell studies in infection and vaccination.

Mimicking Physiologically Relevant Hepatocyte Zonation Using Immunomodulatory Silk Liver Extracellular Matrix Scaffolds toward a Bioartificial Liver Platform

Mimicking nativelike metabolic zonation is indispensable to develop an efficient bioartificial liver model, as it facilitates physiological cues, hepatocyte polarity, and phenotypic functions. The present study shows the first evidence of hepatocyte metabolic heterogeneity in an in vitro liver model encompassing liver extracellular matrix (ECM)-functionalized silk scaffolds (LECM-SF) by altering ECM proportion. Upon static culture, individual LECM-SF scaffold supports differential synthetic and metabolic functions of cultured primary neonatal rat hepatocytes (PNRHs), owing to discrete biophysical attributes. A single in vitro liver system comprising PNRHs seeded LECM-SF scaffolds assisting periportal to pericentral gradient functions is stacked and matured in a perfusion bioreactor to simulate oxygen gradient. The scaffold with high ECM supports periportal-specific albumin synthesis, urea secretion, and bile duct formation, albeit scaffold with low ECM supports pericentral-specific cytochrome P450 activity. Extensive physicochemical characterizations confirmed the stability and interconnected porous network of scaffolds, signifying cellular infiltration and bidirectional nutrient diffusion. Furthermore, scaffolds demonstrate minimal thrombogenicity, reduced foreign-body response, and enhanced pro-remodeling macrophage activation, supporting constructive tissue remodeling. The developed liver model with zone-specific functions would be a promising avenue in bioartificial liver and drug screening.

Macrophage-Mediated Tissue Vascularization: Similarities and Differences Between Cornea and Skin

Macrophages are critical mediators of tissue vascularization both in health and disease. In multiple tissues, macrophages have been identified as important regulators of both blood and lymphatic vessel growth, specifically following tissue injury and in pathological inflammatory responses. In development, macrophages have also been implicated in limiting vascular growth. Hence, macrophages provide an important therapeutic target to modulate tissue vascularization in the clinic. However, the molecular mechanisms how macrophages mediate tissue vascularization are still not entirely resolved. Furthermore, mechanisms might also vary among different tissues. Here we review the role of macrophages in tissue vascularization with a focus on their role in blood and lymphatic vessel formation in the barrier tissues cornea and skin. Comparing mechanisms of macrophage-mediated hem- and lymphangiogenesis in the angiogenically privileged cornea and the physiologically vascularized skin provides an opportunity to highlight similarities but also tissue-specific differences, and to understand how macrophage-mediated hem- and lymphangiogenesis can be exploited for the treatment of disease, including corneal wound healing after injury, graft rejection after corneal transplantation or pathological vascularization of the skin.

Combined Effects of Myeloid Cells in the Neuroblastoma Tumor Microenvironment

Despite multimodal treatment, survival chances for high-risk neuroblastoma patients remain poor. Immunotherapeutic approaches focusing on the activation and/or modification of host immunity for eliminating tumor cells, such as chimeric antigen receptor (CAR) T cells, are currently in development, however clinical trials have failed to reproduce the preclinical results. The tumor microenvironment is emerging as a major contributor to immune suppression and tumor evasion in solid cancers and thus has to be overcome for therapies relying on a functional immune response. Among the cellular components of the neuroblastoma tumor microenvironment, suppressive myeloid cells have been described as key players in inhibition of antitumor immune responses and have been shown to positively correlate with more aggressive disease, resistance to treatments, and overall poor prognosis. This review article summarizes how neuroblastoma-driven inflammation induces suppressive myeloid cells in the tumor microenvironment and how they in turn sustain the tumor niche through suppressor functions, such as nutrient depletion and generation of oxidative stress. Numerous preclinical studies have suggested a range of drug and cellular therapy approaches to overcome myeloid-derived suppression in neuroblastoma that warrant evaluation in future clinical studies.

HIV-Exposed Seronegative Sex Workers Express Low T-Cell Activation and an Intact Ectocervical Tissue Microenvironment

Immunological correlates of natural resistance to HIV have been identified in HIV-exposed seronegative (HESN) individuals and include a low-inflammatory genital mucosal status. The cervicovaginal epithelium has not been studied for such correlates despite constituting an important barrier against sexual HIV transmission. To fill this gap in knowledge, we collected samples of blood, cervical mononuclear cells, cervicovaginal lavage, and ectocervical tissue from Kenyan HESN sex workers (n = 29) and controls (n = 33). The samples were analyzed by flow cytometry, protein profiling, 16S rRNA gene sequencing, in situ image analysis, and tissue-based RNA sequencing. A significantly higher relative proportion of regulatory T cells in blood (B7⁺CD25^hiFoxP3⁺CD127^loCD4⁺ and B7⁺Helios⁺FoxP3⁺CD4⁺), and a significantly lower proportion of activated cervical T cells (CCR5⁺CD69⁺CD4⁺ and CCR5⁺CD69⁺CD8⁺), were found in the HESN group compared with the controls. In contrast, there were no statistically significant differences between the study groups in cervicovaginal protein and microbiome compositions, ectocervical epithelial thickness, E-cadherin expression, HIV receptor expression, and tissue RNA transcriptional profiles. The identification of an intact ectocervical microenvironment in HESN individuals add new data to current knowledge about natural resistance to sexual transmission of HIV.

The presence of TIM-3 positive cells in WHO grade III and IV astrocytic gliomas correlates with isocitrate dehydrogenase mutation status

Diffuse gliomas are aggressive brain tumors that respond poorly to immunotherapy including immune checkpoint inhibition. This resistance may arise from an immunocompromised microenvironment and deficient immune recognition of tumor cells because of low mutational burden. The most prominent genetic alterations in diffuse glioma are mutations in the isocitrate dehydrogenase (IDH) genes that generate the immunosuppressive oncometabolite d-2-hydroxyglutarate. Our objective was to explore the association between IDH mutation and presence of cells expressing the immune checkpoint proteins galectin-9 and/or T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Astrocytic gliomas of World Health Organization (WHO) grades III or IV (36 IDH-mutant and 36 IDH-wild-type) from 72 patients were included in this study. A novel multiplex chromogenic immunohistochemistry panel was applied using antibodies against galectin-9, TIM-3, and the oligodendrocyte transcription factor 2 (OLIG2). Validation studies were performed using data from The Cancer Genome Atlas (TCGA) project. IDH mutation was associated with decreased levels of TIM-3⁺ cells (p < 0.05). No significant association was found between galectin-9 and IDH status (p = 0.10). Most TIM-3⁺ and galectin-9⁺ cells resembled microglia/macrophages, and very few TIM-3⁺ and/or galectin-9⁺ cells co-expressed OLIG2. The percentage of TIM-3⁺ T cells was generally low, however, IDH-mutant tumors contained significantly fewer TIM-3⁺ T cells (p < 0.01) and had a lower interaction rate between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages (p < 0.05). TCGA data confirmed lower TIM-3 mRNA expression in IDH-mutant compared to IDH-wild-type astrocytic gliomas (p = 0.013). Our results show that IDH mutation is associated with diminished levels of TIM-3⁺ cells and fewer interactions between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages, suggesting reduced activity of the galectin-9/TIM-3 immune checkpoint pathway in IDH-mutant astrocytic gliomas.

Interrogating the microenvironmental landscape of tumors with computational image analysis approaches

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.

Immune contexture analysis in immuno-oncology: applications and challenges of multiplex fluorescent immunohistochemistry

The tumor microenvironment is an integral player in cancer initiation, tumor progression, response and resistance to anti-cancer therapy. Understanding the complex interactions of tumor immune architecture (referred to as 'immune contexture') has therefore become increasingly desirable to guide our approach to patient selection, clinical trial design, combination therapies, and patient management. Quantitative image analysis based on multiplexed fluorescence immunohistochemistry and deep learning technologies are rapidly developing to enable researchers to interrogate complex information from the tumor microenvironment and find predictive insights into treatment response. Herein, we discuss current developments in multiplexed fluorescence immunohistochemistry for immune contexture analysis, and their application in immuno-oncology, and discuss challenges to effectively use this technology in clinical settings. We also present a multiplexed image analysis workflow to analyse fluorescence multiplexed stained tumor sections using the Vectra Automated Digital Pathology System together with FCS express flow cytometry software. The benefit of this strategy is that the spectral unmixing accurately generates and analyses complex arrays of multiple biomarkers, which can be helpful for diagnosis, risk stratification, and guiding clinical management of oncology patients.

Regular use of depot medroxyprogesterone acetate causes thinning of the superficial lining and apical distribution of HIV target cells in the human ectocervix

BACKGROUND

The hormonal contraceptive depot medroxyprogesterone acetate (DMPA) may be associated with an increased risk of acquiring human immunodeficiency virus (HIV). We hypothesize that DMPA use influences the ectocervical tissue architecture and HIV target cell localization.

METHODS

Quantitative image analysis workflows were developed to assess ectocervical tissue samples collected from DMPA users and control subjects not using hormonal contraception.

RESULTS

Compared to controls, the DMPA group exhibited a significantly thinner apical ectocervical epithelial layer and a higher proportion of CD4+CCR5+ cells with a more superficial location. This localization corresponded to an area with a non-intact E-cadherin net structure. CD4+Langerin+ cells were also more superficially located in the DMPA group, while fewer in number compared to the controls. Natural plasma progesterone levels did not correlate with any of these parameters, whereas estradiol levels were positively correlated with E-cadherin expression and a more basal location for HIV target cells of the control group.

CONCLUSIONS

DMPA users have a less robust epithelial layer and a more apical distribution of HIV target cells in the human ectocervix, which could confer a higher risk of HIV infection. Our results highlight the importance of assessing intact genital tissue samples to gain insights into HIV susceptibility factors.

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images

BACKGROUND

Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel.

METHODS

Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and ensemble methods that employ both ColorAE and U-Net, collectively referred to as (3) ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor).

RESULTS

We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect 6 different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net into ensemble methods outperform using either ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also present a use case, wherein we apply the ColorAE:U-Net ensemble method across 3 mIHC WSIs and use the predictions to quantify all stained cell populations and perform nearest neighbor spatial analysis. Thus, we provide proof of concept that these methods can be employed to quantitatively describe the spatial distribution immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.

A manual multiplex immunofluorescence method for investigating neurodegenerative diseases

BACKGROUND

Neurodegenerative diseases feature stereotypical deposits of protein aggregates that selectively accumulate in vulnerable cells. The ability to simultaneously localize multiple targets in situ is critical to facilitate discovery and validation of pathogenic molecular pathways. Immunostaining methods enable in situ detection of specific targets. Effective stripping of antibodies, allowing successive rounds of staining while maintaining tissue adhesion and antigen integrity, is the main roadblock for enabling multiplex immunostaining in standard labs. Furthermore, stripping techniques require antibody-specific optimization, validation, and quality control steps.

NEW METHOD

Aiming to create protocols for multiplex localization of neurodegenerative-related processes, without the need for specialized equipment, we evaluated several antibody stripping techniques. We also recommend quality control steps to validate stripping efficacy and ameliorate concerns of cross-reactivity and false positives based on extensive testing.

RESULTS

A protocol using β-mercaptoethanol and SDS consistently enables reliable antibody stripping across multiple rounds of staining and minimizes the odds of cross-reactivity while preserving tissue adhesion and antigen integrity in human postmortem tissue.

COMPARISON WITH EXISTING METHODS

Our proposed method is optimal for standard lab settings and shows consistent efficacy despite the intricacies of suboptimal human postmortem tissue and the need to strip markers bound to highly aggregated proteins. Additionally, it incorporates quality control steps to validate antibody stripping.

CONCLUSIONS

Multiplex immunofluorescence methods for studying neurodegenerative diseases in human postmortem tissue are feasible even in standard laboratories. Nevertheless, evaluation of stripping parameters during optimization and validation phases of experiments is prudent.

Development and applications of computer image analysis algorithms for scoring of PD-L1 immunohistochemistry

Immune checkpoint inhibitors targeting programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) have rapidly become integral to standard-of-care therapy for non-small cell lung cancer and other cancers. Immunohistochemical (IHC) staining of PD-L1 is currently the accepted and approved diagnostic assay for selecting patients for PD-L1/PD-1 axis therapies in certain indications. However, the inherent biological complexity of PD-L1 and the availability of several PD-L1 assays – each with different detection systems, platforms, scoring algorithms and cut-offs – have created challenges to ensure reliable and reproducible results based on subjective visual assessment by pathologists. The increasing adoption of computer technologies into the daily workflow of pathology provides an opportunity to leverage these tools towards improving the clinical value of PD-L1 IHC assays. This review describes several image analysis software programs of computer-aided PD-L1 scoring in the hope of driving further discussion and technological advancement in digital pathology and artificial intelligence approaches, particularly as precision medicine evolves to encompass accurate simultaneous assessment of multiple features of cancer cells and their interactions with the tumor microenvironment.

The Generation and Identity of Human Myeloid-Derived Suppressor Cells

Myeloid-derived suppressor cells (MDSCs) are cells of myeloid lineage with a potent immunosuppressive capacity. They are present in cancer patients as well as in patients with severe inflammatory conditions and infections. MDSCs exist as two main subtypes, the granulocytic (G-MDSCs) and the monocytic (Mo-MDSCs) type, as defined by their surface phenotype and functions. While the functions of MDSCs have been investigated in depth, the origin of human MDSCs is less characterized and even controversial. In this review, we recapitulate theories on how MDSCs are generated in mice, and whether this knowledge is translatable into human MDSC biology, as well as on problems of defining MDSCs by their immature cell surface phenotype in relation to the plasticity of myeloid cells. Finally, the challenge of pharmacological targeting of MDSCs in the future is envisioned.

Transcription factor MafB is a marker of tumor-associated macrophages in both mouse and humans

The transcription factor MafB is specifically expressed in macrophages. We have recently demonstrated that MafB is expressed in anti-inflammatory alternatively activated M2 macrophages in vitro. Tumor-associated macrophages (TAMs) are a subset of M2 type macrophages that can promote immunosuppressive activity, induce angiogenesis, and promote tumor cell proliferation. To examine whether MafB express in TAMs, we analyzed green fluorescent protein (GFP) expression in Lewis lung carcinoma tumors of MafB-GFP knock-in heterozygous mice. FACS analysis demonstrated GFP fluorescence in cells positive for macrophage-markers (F4/80, CD11b, CD68, and CD204). Moreover, quantitative RT-PCR analysis with F4/80⁺GFP⁺ and F4/80⁺GFP^- sorted cells showed that the GFP-positive macrophages express IL-10, Arg-1, and TNF-α, which were known to be expressed in TAMs. These results indicate that MafB is expressed in TAMs. Furthermore, immunostaining analysis using an anti-MAFB antibody revealed that MAFB is expressed in CD204-and CD68-positive macrophages in human lung cancer samples. In conclusion, MafB can be a suitable marker of TAMs in both mouse and human tumor tissues.

Macrophage spatial heterogeneity in gastric cancer defined by multiplex immunohistochemistry

Tumor-associated macrophages (TAMs), one of the most abundant immune components in gastric cancer (GC), are difficult to characterize due to their heterogeneity. Multiple approaches have been used to elucidate the issue, however, due to the tissue-destructive nature of most of these methods, the spatial distribution of TAMs in situ remains unclear. Here we probe the relationship between tumor context and TAM heterogeneity by multiplex immunohistochemistry of 56 human GC cases. Using distinct expression marker profiles on TAMs, we report seven predominant populations distributed between tumor and non-tumor tissue. TAM population-associated gene signatures reflect their heterogeneity and polarization in situ. Increased density of CD163+ (CD206-) TAMs with concurrent high CD68 expression is associated with upregulated immune-signaling and improved patient survival by univariate, but not multivariate analysis. CD68-only and CD206+ TAMs are correlated with high PDL1 expression.

Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach

BACKGROUND

For analysis of the tumor microenvironment in diffuse large B-cell lymphoma (DLBCL) tissue samples, it is desirable to obtain information about counts and distribution of different macrophage subtypes. Until now, macrophage counts are mostly inferred from gene expression analysis of whole tissue sections, providing only indirect information. Direct analysis of immunohistochemically (IHC) fluorescence stained tissue samples is confronted with several difficulties, e.g. high variability of shape and size of target macrophages and strongly inhomogeneous intensity of staining. Consequently, application of commercial software is largely restricted to very rough analysis modes, and most macrophage counts are still obtained by manual counting in microarrays or high power fields, thus failing to represent the heterogeneity of tumor microenvironment adequately.

METHODS

We describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies.

RESULTS

Among all tested methods, the novel approach is best correlated with manual count (0.9297). Automated detection of evaluation subregions proved to be fully reliable. Comparison with gene expression data obtained for the same tissue samples reveals only moderate to low correlation levels. Subsampling within tumor subregions is possible with results almost identical to full sampling. Mean macrophage size in tumor subregions is 152.5±111.3 μm2.

CONCLUSIONS

ROF based approach is successfully applied to detection of IHC stained macrophages in DLBCL tissue samples. The method competes well with existing commercial software kits. In difference to them, it is fully automated, externally repeatable, independent on training data and completely documented. Comparison with gene expression data indicates that image morphometry constitutes an independent source of information about antibody-polarized macrophage occurence and distribution.

State-of-the-Art of Profiling Immune Contexture in the Era of Multiplexed Staining and Digital Analysis to Study Paraffin Tumor Tissues

Multiplexed platforms for multiple epitope detection have emerged in the last years as very powerful tools to study tumor tissues. These revolutionary technologies provide important visual techniques for tumor examination in formalin-fixed paraffin-embedded specimens to improve the understanding of the tumor microenvironment, promote new treatment discoveries, aid in cancer prevention, as well as allowing translational studies to be carried out. The aim of this review is to highlight the more recent methodologies that use multiplexed staining to study simultaneous protein identification in formalin-fixed paraffin-embedded tumor tissues for immune profiling, clinical research, and potential translational analysis. New multiplexed methodologies, which permit the identification of several proteins at the same time in one single tissue section, have been developed in recent years with the ability to study different cell populations, cells by cells, and their spatial distribution in different tumor specimens including whole sections, core needle biopsies, and tissue microarrays. Multiplexed technologies associated with image analysis software can be performed with a high-quality throughput assay to study cancer specimens and are important tools for new discoveries. The different multiplexed technologies described in this review have shown their utility in the study of cancer tissues and their advantages for translational research studies and application in cancer prevention and treatments.