Multiple immunoenzyme staining: methods and visualizations for the observation with spectral imaging

Elevated antibody binding to striatal cholinergic interneurons in patients with pediatric acute-onset neuropsychiatric syndrome

Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is characterized by the abrupt onset of significant obsessive-compulsive symptoms (OCS) and/or severe food restriction, together with other neuropsychiatric manifestations. An autoimmune pathogenesis triggered by infection has been proposed for at least a subset of PANS. The older diagnosis of Pediatric Autoimmune Neuropsychiatric Disorder Associated with Streptococcus (PANDAS) describes rapid onset of OCD and/or tics associated with infection with Group A Streptococcus. The pathophysiology of PANS and PANDAS remains incompletely understood. We recently found serum antibodies from children with rigorously defined PANDAS to selectively bind to cholinergic interneurons (CINs) in the striatum. Here we examine this binding in children with relapsing and remitting PANS, a more heterogeneous condition, collected in a distinct clinical context from those examined in our previous work, from children with a clinical history of Streptococcus infection. IgG from PANS cases showed elevated binding to striatal CINs in both mouse and human brain. Patient plasma collected during symptom flare decreased a molecular marker of CIN activity, phospho-riboprotein S6, in ex vivo brain slices; control plasma did not. Neither elevated antibody binding to CINs nor diminished CIN activity was seen with plasma collected from the same children during remission. These findings replicate what we have seen previously in PANDAS and support the hypothesis that at least a subset of PANS cases have a neuroimmune pathogenesis. Given the critical role of CINs in modulating basal ganglia function, these findings confirm striatal CINs as a locus of interest in the pathophysiology of both PANS and PANDAS.

Multi-Tissue Controls and Multiplex Immunocytochemistry in Pulmonary Cytology

INTRODUCTION

The World Health Organization 2021 lung cancer classification highlights the central role of immunohistochemistry (IHC) in diagnostic pathology. Despite traditional IHC being essential, its limitation to one marker per tissue section brings challenges, particularly when facing cytological limitedly sized samples. To overcome these challenges, multiplex immunocytochemistry (mICC) techniques offer the simultaneous detection of multiple markers from a single section. These advances complement the highly complex imaging techniques that enable additional analyses of cellular interactions.

METHODS

The present study outlines a comprehensive mICC methodology of an automated multiplex immunoperoxidase staining method and multiple tissue hybrid controls for ICC/mICC. Protocols are presented in detail and demonstrate a careful approach to optimizing various markers for diagnostic workup including immunotherapy.

CONCLUSION

Multiplex IHC/ICC emerges as a transformative force in biomedical diagnostics and research. Beyond simultaneous marker detection, it unravels complexities within tissues - unveiling co-localization nuances, deciphering expression patterns, and enhancing understanding of cellular populations. As personalized treatments gain prominence, the study emphasizes the heightened importance of diagnostic tools and sample adequacy. The present methodological study, encapsulating an automated multiplex immunoperoxidase staining method, symbolizes a stride towards precision in pulmonary carcinoma diagnosis. Multi-tissue controls represent a key element in quality assurance in pathology laboratories.

Color Standardization and Stain Intensity Calibration for Whole Slide Image-Based Immunohistochemistry Assessment

Automated quantification of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) using whole slide imaging (WSI) is expected to eliminate subjectivity in visual assessment. However, the color intensity in WSI varies depending on the staining process and scanner device. Such variations affect the image analysis results. This paper presents methods to diminish the influence of color variation produced in the staining process using a calibrator slide consisting of peptide-coated microbeads. The calibrator slide is stained along with tissue sample slides, and the 3,3'-diaminobenzidine (DAB) color intensities of the microbeads are used for calibrating the color variation of the sample slides. An off-the-shelf image analysis tool is employed for the automated assessment, in which cells are classified by the thresholds for the membrane staining. We have adopted two methods for calibrating the color variation based on the DAB color intensities obtained from the calibrator slide: (1) thresholds for classifying the DAB membranous intensity are adjusted, and (2) the color intensity of WSI is corrected. In the experiment, the calibrator slides and tissue of breast cancer slides were stained together on different days and used to test our protocol. With the proposed protocol, the discordance in the HER2 evaluation was reduced to one slide out of 120 slides.

Immunohistochemical double nuclear staining for cell-specific automated quantification of the proliferation index - A promising diagnostic aid for melanocytic lesions

AIMS

Pathologists often use immunohistochemical staining of the proliferation marker Ki67 in their diagnostic assessment of melanocytic lesions. However, the interpretation of Ki67 can be challenging. We propose a new workflow to improve the diagnostic utility of the Ki67-index. In this workflow, Ki67 is combined with the melanocytic tumour-cell marker SOX10 in a Ki67/SOX10 double nuclear stain. The Ki67-index is then quantified automatically using digital image analysis (DIA). The aim of this study was to optimise and test three different multiplexing methods for Ki67/SOX10 double nuclear staining.

METHODS

Multiplex immunofluorescence (mIF), multiplex immunohistochemistry (mIHC), and multiplexed immunohistochemical consecutive staining on single slide (MICSSS) were optimised for Ki67/SOX10 double nuclear staining. DIA applications were designed for automated quantification of the Ki67-index. The methods were tested on a pilot case-control cohort of benign and malignant melanocytic lesions (n = 23).

RESULTS

Using the Ki67/SOX10 double nuclear stain, malignant melanocytic lesions could be completely distinguished from benign lesions by the Ki67-index. The Ki67-index cut-offs were 1.8% (mIF) and 1.5% (mIHC and MICSSS). The AUC of the automatically quantified Ki67-index based on double nuclear staining was 1.0 (95% CI: 1.0;1.0), whereas the AUC of conventional Ki67 single-stains was 0.87 (95% CI: 0.71;1.00).

CONCLUSIONS

The novel Ki67/SOX10 double nuclear stain highly improved the diagnostic precision of Ki67 interpretation. Both mIHC and mIF were useful methods for Ki67/SOX10 double nuclear staining, whereas the MICSSS method had challenges in the current setting. The Ki67/SOX10 double nuclear stain shows potential as a valuable diagnostic aid for melanocytic lesions.

Canine bufavirus (Carnivore protoparvovirus-3) infection in dogs with respiratory disease

Canine bufavirus (CBuV) or Carnivore protoparvovirus-3, a nonenveloped DNA virus belonging to the genus Protoparvovirus, family Parvoviridae, has been identified in dogs with respiratory and enteric diseases. Although CBuV detection has been reported in multiple countries, descriptions of pathologic findings associated with infection have not yet been provided. In this study, the authors necropsied 14 dogs (12 puppies and 2 adult dogs) from a breeding colony that died during multiple outbreaks of respiratory diseases. Postmortem investigations revealed extensive bronchointerstitial pneumonia with segmental type II pneumocyte hyperplasia in all necropsied puppies but less severe lesions in adults. With negative results of common pathogen detection by ancillary testing, CBuV DNA was identified in all investigated dogs using a polymerase chain reaction (PCR). Quantitative PCR demonstrated CBuV DNA in several tissues, and in situ hybridization (ISH) indicated CBuV tissue localization in the lung, tracheobronchial lymph node, and spinal cord, suggesting hematogenous spread. Dual CBuV ISH and cellular-specific immunohistochemistry were used to determine the cellular tropism of the virus in the lung and tracheobronchial lymph node, demonstrating viral localization in various cell types, including B-cells, macrophages, and type II pneumocytes, but not T-cells. Three complete CBuV sequences were successfully characterized and revealed that they clustered with the CBuV sequences obtained from dogs with respiratory disease in Hungary. No additional cases were identified in small numbers of healthy dogs. Although association of the bufavirus with enteric disease remains to be determined, a contributory role of CBuV in canine respiratory disease is possible.

A Robust Method for the Unsupervised Scoring of Immunohistochemical Staining

Immunohistochemistry is a powerful technique that is widely used in biomedical research and clinics; it allows one to determine the expression levels of some proteins of interest in tissue samples using color intensity due to the expression of biomarkers with specific antibodies. As such, immunohistochemical images are complex and their features are difficult to quantify. Recently, we proposed a novel method, including a first separation stage based on non-negative matrix factorization (NMF), that achieved good results. However, this method was highly dependent on the parameters that control sparseness and non-negativity, as well as on algorithm initialization. Furthermore, the previously proposed method required a reference image as a starting point for the NMF algorithm. In the present work, we propose a new, simpler and more robust method for the automated, unsupervised scoring of immunohistochemical images based on bright field. Our work is focused on images from tumor tissues marked with blue (nuclei) and brown (protein of interest) stains. The new proposed method represents a simpler approach that, on the one hand, avoids the use of NMF in the separation stage and, on the other hand, circumvents the need for a control image. This new approach determines the subspace spanned by the two colors of interest using principal component analysis (PCA) with dimension reduction. This subspace is a two-dimensional space, allowing for color vector determination by considering the point density peaks. A new scoring stage is also developed in our method that, again, avoids reference images, making the procedure more robust and less dependent on parameters. Semi-quantitative image scoring experiments using five categories exhibit promising and consistent results when compared to manual scoring carried out by experts.

Strategies for studying immune and non-immune human and canine mammary gland cancer tumour infiltrate

The tumour microenvironment (TME) is usually defined as a cell environment associated with tumours or cancerous stem cells where conditions are established affecting tumour development and progression through malignant cell interaction with non-malignant cells. The TME is made up of endothelial, immune and non-immune cells, extracellular matrix (ECM) components and signalling molecules acting specifically on tumour and non-tumour cells. Breast cancer (BC) is the commonest malignant neoplasm worldwide and the main cause of mortality in women globally; advances regarding BC study and understanding it are relevant for acquiring novel, personalised therapeutic tools. Studying canine mammary gland tumours (CMGT) is one of the most relevant options for understanding BC using animal models as they share common epidemiological, clinical, pathological, biological, environmental, genetic and molecular characteristics with human BC. In-depth, detailed investigation regarding knowledge of human BC-related TME and in its canine model is considered extremely relevant for understanding changes in TME composition during tumour development. This review addresses important aspects concerned with different methods used for studying BC- and CMGT-related TME that are important for developing new and more effective therapeutic strategies for attacking a tumour during specific evolutionary stages.

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.

Triple enzymatic immunochemistry for interneuron populations in postmortem human cerebral cortex

Immunostaining is an antibody-based tool used to visualize proteins in tissue. Enzymes or fluorochromes conjugated to antibodies are used to detect proteins of interests. Fluorescent immunostaining can be used in human tissue, however due to the high autofluorescence of non-perfused human tissue, enzymatic immunostaining is better suited. Enzymes produce a colored product that is detectable by light microscopes. Here we describe a successful triple immunochemistry protocol to enzymatically label three distinct populations of interneurons (Parvalbumin+, Calbindin+, and Calretinin + interneurons) in non-perfused formalin fixed human brain cerebral cortex. Signal was achieved using a combination of horseradish peroxidase (HRP) and Alkaline Phosphatase (AP) enzymes and color was generated using the insoluble chromogens: 3,3'- Diaminobenzidine (DAB, Brown), Vector Blue (Blue), and Vector VIP (Pink). There were no noticeable background and minimal signal overlap between the different colors. We were able to successfully stain human cortical tissue and distinguish morphological properties of the three interneuron (IN) populations.

Nuclei segmentation with point annotations from pathology images via self-supervised learning and co-training

Nuclei segmentation is a crucial task for whole slide image analysis in digital pathology. Generally, the segmentation performance of fully-supervised learning heavily depends on the amount and quality of the annotated data. However, it is time-consuming and expensive for professional pathologists to provide accurate pixel-level ground truth, while it is much easier to get coarse labels such as point annotations. In this paper, we propose a weakly-supervised learning method for nuclei segmentation that only requires point annotations for training. First, coarse pixel-level labels are derived from the point annotations based on the Voronoi diagram and the k-means clustering method to avoid overfitting. Second, a co-training strategy with an exponential moving average method is designed to refine the incomplete supervision of the coarse labels. Third, a self-supervised visual representation learning method is tailored for nuclei segmentation of pathology images that transforms the hematoxylin component images into the H&E stained images to gain better understanding of the relationship between the nuclei and cytoplasm. We comprehensively evaluate the proposed method using two public datasets. Both visual and quantitative results demonstrate the superiority of our method to the state-of-the-art methods, and its competitive performance compared to the fully-supervised methods. Codes are available at https://github.com/hust-linyi/SC-Net.

Histological and immunohistochemical guide to tendon tissue

Tendons are unique dense connective tissues with discrete zones having specific structure and function. They are juxtaposed with other tissues (e.g., bone, muscle, and fat) with different compositional, structural, and mechanical properties. Additionally, tendon properties change drastically with growth and development, disease, aging, and injury. Consequently, there are unique challenges to performing high quality histological assessment of this tissue. To address this need, histological assessment was one of the breakout session topics at the 2022 Orthopaedic Research Society (ORS) Tendon Conference hosted at the University of Pennsylvania. The purpose of the breakout session was to discuss needs from members of the ORS Tendon Section related to histological procedures, data presentation, knowledge dissemination, and guidelines for future work. Therefore, this review provides a brief overview of the outcomes of this discussion and provides a set of guidelines, based on the perspectives from our laboratories, for histological assessment to assist researchers in their quest to utilize these techniques to enhance the outcomes and interpretations of their studies.

Standardizing HER2 immunohistochemistry assessment: calibration of color and intensity variation in whole slide imaging caused by staining and scanning

In the evaluation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) - one of the standard biomarkers for breast cancer- visual assessment is laborious and subjective. Image analysis using whole slide image (WSI) could produce more consistent results; however, color variability in WSIs due to the choice of stain and scanning processes may impact image analysis. We therefore developed a calibration protocol to diminish the staining and scanning variations of WSI using two calibrator slides. The IHC calibrator slide (IHC-CS) contains peptide-coated microbeads with different concentrations. The color distribution obtained from the WSI of stained IHC-CS reflects the staining process and scanner characteristics. A color chart slide (CCS) is also useful for calibrating the color variation due to the scanner. The results of the automated HER2 assessment were compared to confirm the effectiveness of two calibration slides. The IHC-CS and HER2 breast cancer cases were stained on different days. All stained slides and CCS were digitized by two different WSI scanners. Results revealed 100% concordance between automated evaluation and the pathologist's assessment with both the scanner and staining calibration. The proposed method may enable consistent evaluation of HER2.

Citrullinated fibrinogen-SAAs complex causes vascular metastagenesis

Primary tumor cells metastasize to a distant preferred organ. However, the most decisive host factors that determine the precise locations of metastases in cancer patients remain unknown. We have demonstrated that post-translational citrullination of fibrinogen creates a metastatic niche in the vulnerable spots. Pulmonary endothelial cells mediate the citrullination of fibrinogen, changing its conformation, surface charge, and binding properties with serum amyloid A proteins (SAAs), to make it a host tissue-derived metastatic pathogen. The human-specific SAAs-citrullinated fibrinogen (CitFbg) complex recruits cancer cells to form a protein-metastatic cell aggregation in humanized SAA cluster mice. Furthermore, a CitFbg peptide works as a competitive inhibitor to block the homing of metastatic cells into the SAAs-CitFbg sites. The potential metastatic sites in the lungs of patients are clearly visualized by our specific antibody for CitFbg. Thus, CitFbg deposition displays metastatic risks for cancer patients, and the citrullinated peptide is a new type of metastasis inhibitor.

Pharmacological modulation of TSPO in microglia/macrophages and neurons in a chronic neurodegenerative model of prion disease

Neuroinflammation is an important component of many neurodegenerative diseases, whether as a primary cause or a secondary outcome. For that reason, either as diagnostic tools or to monitor progression and/or pharmacological interventions, there is a need for robust biomarkers of neuroinflammation in the brain. Mitochondrial TSPO (18 kDa Translocator protein) is one of few available biomarkers of neuroinflammation for which there are clinically available PET imaging agents. In this study, we further characterised neuroinflammation in a mouse model of prion-induced chronic neurodegeneration (ME7) including a pharmacological intervention via a CSF1R inhibitor. This was achieved by autoradiographic binding of the second-generation TSPO tracer, [3H]PBR28, along with a more comprehensive examination of the cellular contributors to the TSPO signal changes by immunohistochemistry. We observed regional increases of TSPO in the ME7 mouse brains, particularly in the hippocampus, cortex and thalamus. This increased TSPO signal was detected in the cells of microglia/macrophage lineage as well as in astrocytes, endothelial cells and neurons. Importantly, we show that the selective CSF1R inhibitor, JNJ-40346527 (JNJ527), attenuated the disease-dependent increase in TSPO signal, particularly in the dentate gyrus of the hippocampus, where JNJ527 attenuated the number of Iba1+ microglia and neurons, but not GFAP+ astrocytes or endothelial cells. These findings suggest that [3H]PBR28 quantitative autoradiography in combination with immunohistochemistry are important translational tools for detecting and quantifying neuroinflammation, and its treatments, in neurodegenerative disease. Furthermore, we demonstrate that although TSPO overexpression in the ME7 brains was driven by various cell types, the therapeutic effect of the CSF1R inhibitor was primarily to modulate TSPO expression in microglia and neurons, which identifies an important route of biological action of this particular CSF1R inhibitor and provides an example of a cell-specific effect of this type of therapeutic agent on the neuroinflammatory process.

Galactosidase-catalyzed fluorescence amplification method (GAFAM): sensitive fluorescent immunohistochemistry using novel fluorogenic β-galactosidase substrates and its application in multiplex immunostaining

Multiplex immunohistochemistry/multiplex immunofluorescence (mIHC/mIF) enables the simultaneous detection of multiple markers in a single tissue section by visualizing the markers in different colors. Currently, tyramide signal amplification (TSA) is the most commonly used method because it is heat resistant to multiplexing. SPiDER-βGal (6'-(diethylamino)-4'-(fluoromethyl)spiro[isobenzofuran-1(3H),9'-[9H]xanthen]-3'-yl β-D-galactopyranoside), a novel fluorogenic substrate of β-galactosidase (β-gal) was reported recently. Its properties are favorable for application in sensitive mIF based on quinone methide chemistry. Combining SPiDER-βGal with its related substrates, a novel, sensitive fluorescent IHC method for formalin-fixed paraffin-embedded (FFPE) sections was developed, named the galactosidase-catalyzed fluorescence amplification method (GAFAM). Evaluation of GAFAM indicated the following characteristics: (1) the entire GAFAM procedure was complete within a few hours; (2) the optimal working concentration of the substrates was 20 μM; (3) the fluorescent product was heat resistant; (4) the GAFAM exhibited sensitivity comparable with that of TSA, which was higher than that of conventional IF; and (5) the GAFAM was applicable to mIF and multispectral imaging. GAFAM is expected to be applicable to IF (or mIF in combination with TSA), and is a promising tool for facilitating morphological research in various fields of life science.

Companion diagnostic requirements for spatial biology using multiplex immunofluorescence and multispectral imaging

Immunohistochemistry has long been held as the gold standard for understanding the expression patterns of therapeutically relevant proteins to identify prognostic and predictive biomarkers. Patient selection for targeted therapy in oncology has successfully relied upon standard microscopy-based methodologies, such as single-marker brightfield chromogenic immunohistochemistry. As promising as these results are, the analysis of one protein, with few exceptions, no longer provides enough information to draw effective conclusions about the probability of treatment response. More multifaceted scientific queries have driven the development of high-throughput and high-order technologies to interrogate biomarker expression patterns and spatial interactions between cell phenotypes in the tumor microenvironment. Such multi-parameter data analysis has been historically reserved for technologies that lack the spatial context that is provided by immunohistochemistry. Over the past decade, technical developments in multiplex fluorescence immunohistochemistry and discoveries made with improving image data analysis platforms have highlighted the importance of spatial relationships between certain biomarkers in understanding a patient's likelihood to respond to, typically, immune checkpoint inhibitors. At the same time, personalized medicine has instigated changes in both clinical trial design and its conduct in a push to make drug development and cancer treatment more efficient, precise, and economical. Precision medicine in immuno-oncology is being steered by data-driven approaches to gain insight into the tumor and its dynamic interaction with the immune system. This is particularly necessary given the rapid growth in the number of trials involving more than one immune checkpoint drug, and/or using those in combination with conventional cancer treatments. As multiplex methods, like immunofluorescence, push the boundaries of immunohistochemistry, it becomes critical to understand the foundation of this technology and how it can be deployed for use as a regulated test to identify the prospect of response from mono- and combination therapies. To that end, this work will focus on: 1) the scientific, clinical, and economic requirements for developing clinical multiplex immunofluorescence assays; 2) the attributes of the Akoya Phenoptics workflow to support predictive tests, including design principles, verification, and validation needs; 3) regulatory, safety and quality considerations; 4) application of multiplex immunohistochemistry through lab-developed-tests and regulated in vitro diagnostic devices.

Extracellular Vesicle Antibody Microarray for Multiplexed Inner and Outer Protein Analysis

Proteins are found both outside and inside of extracellular vesicles (EVs) and govern the properties and functions of EVs, while also constituting a signature of the cell of origin and of biological function and disease. Outer proteins on EVs can be directly bound by antibodies to either enrich EVs, or probe the expression of a protein on EVs, including in a combinatorial manner. However, co-profiling of inner proteins remains challenging. Here, we present the high-throughput, multiplexed analysis of EV inner and outer proteins (EVPio). We describe the optimization of fixation and heat-induced protein epitope retrieval for EVs, along with oligo-barcoded antibodies and branched DNA signal amplification for sensitive, multiplexed, and high-throughput assays. We captured four subpopulations of EVs from colorectal cancer (CRC) cell lines HT29 and SW403 based on EpCAM, CD9, CD63, and CD81 expression, and quantified the co-expression of eight outer [integrins (ITGs) and tetraspanins] and four inner (heat shock, endosomal, and inner leaflet) proteins. The differences in co-expression patterns were consistent with the literature and known biological function. In conclusion, EVPio analysis can simultaneously detect multiple inner and outer proteins in EVs immobilized on a surface, opening the way to extensive combinatorial protein profiles for both discovery and clinical translation.

An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons

The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.

Validation of a color deconvolution method to quantify MSC tri-lineage differentiation across species

Mesenchymal stem cells (MSCs) are a promising candidate for both human and veterinary regenerative medicine applications because of their abundance and ability to differentiate into several lineages. Mesenchymal stem cells are however a heterogeneous cell population and as such, it is imperative that they are unequivocally characterized to acquire reproducible results in clinical trials. Although the tri-lineage differentiation potential of MSCs is reported in most veterinary studies, a qualitative evaluation of representative histological images does not always unambiguously confirm tri-lineage differentiation. Moreover, potential differences in differentiation capacity are not identified. Therefore, quantification of tri-lineage differentiation would greatly enhance proper characterization of MSCs. In this study, a method to quantify the tri-lineage differentiation potential of MSCs is described using digital image analysis, based on the color deconvolution plug-in (ImageJ). Mesenchymal stem cells from three species, i.e., bovine, equine, and porcine, were differentiated toward adipocytes, chondrocytes, and osteocytes. Subsequently, differentiated MSCs were stained with Oil Red O, Alcian Blue, and Alizarin Red S, respectively. Next, a differentiation ratio (DR) was obtained by dividing the area % of the differentiation signal by the area % of the nuclear signal. Although MSCs isolated from all donors in all species were capable of tri-lineage differentiation, differences were demonstrated between donors using this quantitative DR. Our straightforward, simple but robust method represents an elegant approach to determine the degree of MSC tri-lineage differentiation across species. As such, differences in differentiation potential within the heterogeneous MSC population and between different MSC sources can easily be identified, which will support further optimization of regenerative therapies.

Dissecting Tumor-Immune Microenvironment in Breast Cancer at a Spatial and Multiplex Resolution

The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of spatial information and histopathological evaluation of tumor infiltrating lymphocytes exhibits interobserver variability. Towards improved understanding of the complex interactions in TIME, several emerging multiplex in situ methods are being developed and gaining much attention for protein detection. They enable the simultaneous evaluation of multiple targets in situ, detection of cell densities/subpopulations as well as estimations of functional states of immune infiltrate. Furthermore, they can characterize spatial organization of TIME—by cell-to-cell interaction analyses and the evaluation of distribution within different regions of interest and tissue compartments—while digital imaging and image analysis software allow for reproducibility of the various assays. In this review, we aim to provide an overview of the different multiplex in situ methods used in cancer research with special focus on breast cancer TIME at the neoadjuvant, adjuvant and metastatic setting. Spatial heterogeneity of TIME and importance of longitudinal evaluation of TIME changes under the pressure of therapy and metastatic progression are also addressed.

A Method for Unsupervised Semi-Quantification of Inmunohistochemical Staining with Beta Divergences

In many research laboratories, it is essential to determine the relative expression levels of some proteins of interest in tissue samples. The semi-quantitative scoring of a set of images consists of establishing a scale of scores ranging from zero or one to a maximum number set by the researcher and assigning a score to each image that should represent some predefined characteristic of the IHC staining, such as its intensity. However, manual scoring depends on the judgment of an observer and therefore exposes the assessment to a certain level of bias. In this work, we present a fully automatic and unsupervised method for comparative biomarker quantification in histopathological brightfield images. The method relies on a color separation method that discriminates between two chromogens expressed as brown and blue colors robustly, independent of color variation or biomarker expression level. For this purpose, we have adopted a two-stage stain separation approach in the optical density space. First, a preliminary separation is performed using a deconvolution method in which the color vectors of the stains are determined after an eigendecomposition of the data. Then, we adjust the separation using the non-negative matrix factorization method with beta divergences, initializing the algorithm with the matrices resulting from the previous step. After that, a feature vector of each image based on the intensity of the two chromogens is determined. Finally, the images are annotated using a systematically initialized k-means clustering algorithm with beta divergences. The method clearly defines the initial boundaries of the categories, although some flexibility is added. Experiments for the semi-quantitative scoring of images in five categories have been carried out by comparing the results with the scores of four expert researchers yielding accuracies that range between 76.60% and 94.58%. These results show that the proposed automatic scoring system, which is definable and reproducible, produces consistent results.

Significance of Single-cell Level Dual Expression of BCL2 and MYC Determined With Multiplex Immunohistochemistry in Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a fatal heterogenous neoplasm. Recent clinical trials have failed partly due to nebulous criteria for defining high-risk patients. Patients with double-expresser lymphoma (DEL) have a poor prognosis and are resistant to conventional treatment. However, many diagnostic and clinical controversies still surround DEL partly due to the arbitrariness of criteria for the diagnosis of DEL. In this study, we suggest a refined method for diagnosing DEL by evaluating the concurrent expression of BCL2 and MYC at the single-cell level (dual-protein-expressing lymphoma [DUEL]). For the proof of concept, a multiplex immunofluorescence assay for CD20, BCL2, and MYC was performed and quantitatively analyzed using spectral image analysis in patients. The analysis results and clinical applicability were verified by using dual-color immunohistochemistry performed on 353 independent multicenter patients who had been uniformly treated with standard therapy. DUEL showed significantly worse overall survival (OS) and event-free survival (EFS) (P=0.00011 and 0.00035, respectively). DUEL status remained an independent adverse prognostic variable with respect to the International Prognostic Index risk and the cell of origin. Moreover, the advantage of determining DUEL status by dual-color immunohistochemistry was shown by more robust classification and more homogeneous high-risk subgroup patient identification in both training (n=271) (OS: P<0.0001; EFS: P<0.0001) and validation sets (n=82) (OS: P=0.0087; EFS: P<0.0001). This concept of DUEL is more consistent with carcinogenesis and has greater practical utility, hence it may provide a better basis for both basic and clinical research for the development of new therapeutics.

High-Throughput Strategy for Profiling Sequential Section With Multiplex Staining of Mouse Brain

The brain modulates specific functions in its various regions. Understanding the organization of different cells in the whole brain is crucial for investigating brain functions. Previous studies have focused on several regions and have had difficulty analyzing serial tissue samples. In this study, we introduced a pipeline to acquire anatomical and histological information quickly and efficiently from serial sections. First, we developed a serial brain-slice-staining method to stain serial sections and obtained more than 98.5% of slices with high integrity. Subsequently, using the self-developed analysis software, we registered and quantified the signals of imaged sections to the Allen Mouse Brain Common Coordinate Framework, which is compatible with multimodal images and slant section planes. Finally, we validated the pipeline with immunostaining by analyzing the activity variance in the whole brain during acute stress in aging and young mice. By removing the problems resulting from repeated manual operations, this pipeline is widely applicable to serial brain slices from multiple samples in a rapid and convenient manner, which benefits to facilitate research in life sciences.

Multiplexing and Spectral Microscopy

Visualization of proteins within a tissue sample via immunohistochemistry (IHC) is a central aspect of pathology. However, such methods are limited to the detection of one or two proteins, due to the overlapping absorption/emission spectra of chromogens and fluorescent dyes. The advent of spectral microscopy has enabled improved visualization of multiple proteins by allowing for the specific light wavelengths/spectral signatures of individual fluorophores and chromogens to be unmixed and analyzed, thus detecting signals that would be indistinguishable with conventional microscopy. Combined with improvements to multiplexed immunohistochemistry (mIHC) protocols, spectral microscopy facilitates the interrogation of spatial relationships between four (enzymatic mIHC) or seven (fluorescent mIHC) proteins, unlocking the wealth of information contained within a single tissue section. Furthermore, the application of linear unmixing for image analysis allows for a reduction in background signal associated with tissue autofluorescence and can distinguish chromogens with similar absorption spectra to identify protein colocalization in brightfield spectral microscopy. While many mIHC protocols have been optimized for spectral microscopy, this chapter will focus in detail on two common methods: enzymatic mIHC and manual fluorescent mIHC using tyramide signal amplification and microwave technology.

The effects of exercise training on cardiac matrix metalloproteinases activity and cardiac function in mice with diabetic cardiomyopathy

AIM

To evaluate the effects of exercise training (ET) on cardiac extracellular matrix (ECM) proteins homeostasis and cardiac dysfunction in mice with diabetic cardiomyopathy.

METHODS

Thirty-six male C57BL/6 mice were randomized into 3 groups for 8 weeks (12mice/group): Diabetic control-DC: Diabetes was induced by single streptozotocin injection (200 mg/kg i.p.); Diabetic exercise-DE: Diabetic mice underwent ET program on motorized-treadmill (6-times/week, 60min/session); Non-diabetic control-NDC: Vehicle-treated, sedentary, non-diabetic mice served as controls. Before euthanasia, all groups underwent transthoracic echocardiography (TTE). Post-mortem, left-ventricle (LV) samples were histologically analysed for ECM proteins (collagen, elastin), matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs).

RESULTS

DC group showed significantly higher cardiac contents of collagen and MMP-9 and lower elastic concentration than NDC (p < 0.001). The implementation of ET completely outweighed those diabetes-induced changes (DE vs NDC, p > 0.05). TIMP-1 levels significantly increased across all groups (DC: 18.98 ± 3.47%, DE: 24.24 ± 2.36%, NDC: 46.36 ± 5.91%; p < 0.05), while MMP-9/TIMP-1 ratio followed a reverse pattern. ET tended to increase MMP-2 concentrations versus DC (p = 0.055), but did not achieve non-diabetic levels (p < 0.05). TIMP-2 cardiac concentrations remained unaltered throughout the study (p > 0.05). Importantly, ET ameliorated both LV end-systolic internal diameter (LVESD) (p < 0.001) and the percentage of LV fractional shortening (FS%) (p = 0.006) compared to DC. Despite that favorable effect, the cardiac function level of DE group remained worse than NDC group (%FS: p = 0.002; LVESD: p < 0.001).

CONCLUSION

Systemic ET may favorably change ECM proteins, MMP-9 and TIMP-1 cardiac concentrations in mice with diabetic cardiomyopathy. Those results were associated with partial improvement of echocardiography-assessed cardiac function, indicating a therapeutic effect of ET in diabetic cardiomyopathy.

Fluorescent Immunohistochemistry

Immunofluorescence is an important immunochemical technique that utilizes fluorescence-labeled antibodies to detect specific target antigens. It is used widely in both scientific research and clinical laboratories. Immunofluorescence allows for excellent sensitivity and amplification of signal in comparison to immunohistochemistry. However, analysis of samples labeled with fluorescence-labeled antibodies has to be performed using a fluorescence microscope or other type of fluorescence imaging. There are two methods available: direct (primary) and indirect (secondary) immunofluorescence. Here, we describe the principle of immunofluorescence methods as well as the preparation of fresh-frozen and formalin-fixed, paraffin embedded tissues for both direct and indirect immunofluorescence labeling.

Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry

Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue sections. However, it suffers from several disadvantages, including its lack of objectivity and the fact that it is a time-consuming process. Our aim was to test a recently established artificial intelligence (AI)-aided digital image analysis platform, Pathronus, and to compare it to conventional scoring by five observers on chromogenic IHC-stained slides belonging to three experimental groups. Because Pathronus operates on grayscale 0-255 values, we transformed the data to a seven-point scale for use by pathologists and scientists. The accuracy of these methods was evaluated by comparing statistical significance among groups with quantitative fluorescent IHC reference data on subsequent tissue sections. The pairwise inter-rater reliability of the scoring and converted Pathronus data varied from poor to moderate with Cohen’s kappa, and overall agreement was poor within every experimental group using Fleiss’ kappa. Only the original and converted that were obtained from Pathronus original were able to reproduce the statistical significance among the groups that were determined by the reference method. In this study, we present an AI-aided software that can identify cells of interest, differentiate among organelles, protein specific chromogenic labelling, and nuclear counterstaining after an initial training period, providing a feasible and more accurate alternative to semi-quantitative scoring.

Mesenchymal type neuroblastoma cells escape ALK inhibitors

Cancer therapy frequently fails due to the emergence of resistance. Many tumors include phenotypically immature tumor cells, which have been implicated in therapy resistance. Neuroblastoma cells can adopt a lineage committed adrenergic (ADRN) or an immature mesenchymal (MES) state. They differ in epigenetic landscape and transcription factors, and MES cells are more resistant to chemotherapy. Here we analyzed the response of MES cells to targeted drugs. Activating ALK mutations are frequently found in neuroblastoma and ALK inhibitors (ALKi) are in clinical trials. ALKi treatment of ADRN neuroblastoma cells with a tumor-driving ALK mutation induced cell death. Conversely, MES cells did not express either mutant or wild-type ALK and were resistant to ALKi, and MES cells formed tumors that progressed under ALKi therapy. In assessing the role of MES cells in relapse development, TRAIL was identified to specifically induce apoptosis in MES cells and suppress MES tumor growth. Addition of TRAIL to ALKi treatment of neuroblastoma xenografts delayed relapses in a subset of the animals, suggesting a role for MES cells in relapse formation. While ADRN cells resembled normal embryonal neuroblasts, MES cells resembled immature precursor cells which also lacked ALK expression. Resistance to targeted drugs can therefore be an intrinsic property of immature cancer cells based on their resemblance to developmental precursors.

Fibrocytes in early and long-standing rheumatoid arthritis: a 6-month trial with repeated synovial biopsy, imaging and lung function test

Objectives

To correlate the level of fibrocytes in peripheral blood, synovial tissue and in vitro culture in rheumatoid arthritis (RA) with changes in disease activity, imaging and pulmonary function.

Methods

Twenty patients with early RA (ERA) and 20 patients with long-standing RA (LRA) were enrolled in a 6-month prospective study. Sixteen patients undergoing wrist arthroscopy were healthy controls. Patients with RA underwent pulmonary function tests, ultrasound and synovial ultrasound-guided needle biopsy of the same wrist at baseline and 6 months. Wrist MRI was performed at baseline (all) and 6 months (ERA). Circulating fibrocytes were measured by flow cytometry, in vitro by the number of monocytes that were differentiated to fibrocytes and in synovial biopsies by counting in histological sections.

Results

Fibrocytes were primarily located around vessels and in the subintimal area in the synovium. Fibrocyte levels did not decline during the trial despite effective RA treatment. In the ERA group, increased synovitis assessed by ultrasound was moderate and strongly correlated with an increase in circulating and synovial fibrocyte levels, respectively. Increased synovitis assessed by MRI during the trial in the ERA group was moderately correlated with both increased numbers of circulating and cultured fibrocytes. Absolute diffusion capacity level was overall weakly negatively correlated with the level of circulating and synovial fibrocytes. The decline in diffusion capacity during the trial was moderately correlated with increased levels of synovial fibrocytes.

Conclusion

Our findings suggest that fibrocytes are involved in RA pathogenesis, both in the synovium and the reduction in lung function seen in a part of patients with RA.

Trial registration number

NCT02652299.

Quantitative measurement of the histological features of alpha-1 antitrypsin deficiency-associated liver disease in biopsy specimens

Background

Pathological mutations in Alpha-1 Antitrypsin (AAT) protein cause retention of toxic polymers in the hepatocyte endoplasmic reticulum. The risk for cirrhosis in AAT deficiency is likely directly related to retention of these polymers within the liver. Polymers are classically identified on liver biopsy as inclusion bodies by periodic acid schiff staining after diastase treatment and immunohistochemistry. However, characterization of the polymer burden within a biopsy sample is limited to a semi-quantitative scale as described by a pathologist. Better methods to quantify polymer are needed to advance our understanding of pathogenesis of disease. Therefore, we developed a method to quantify polymer aggregation from standard histologic specimens. In addition, we sought to understand the relationship of polymer burden and other histologic findings to the presence of liver fibrosis.

Methods

Liver samples from a well-categorized AATD cohort were used to develop histo-morphometric tools to measure protein aggregation.

Results

Whole-slide morphometry reliably quantifies aggregates in AATD individuals. Despite very low levels of inclusions present (0–0.41%), accumulation of globules is not linear and is associated with higher fibrosis stages. Immunohistochemistry demonstrates that fibrosis is associated with polymer accumulation and not total AAT. A proportion of patients were found to be “heavy accumulators” with a polymer burden above the upper 25% of normal distribution. Males had significantly more liver inclusions and polymer than females. These measurements also highlight interrelated phenotypes of hepatocellular degeneration and autophagy in AATD liver disease.

Conclusion

Quantitative inclusion analysis measures AAT accumulation in liver biopsy specimens. Quantification of polymer may identify individuals at risk for progressive disease and candidates for therapeutic interventions. Furthermore, these methods may be useful for evaluating efficacy of drugs targeting accumulation of AAT.

Sympathetic nerve distribution in human lymph nodes

Various lymph node functions are regulated by the sympathetic nervous system as shown in rodent studies. If human lymph nodes show a comparable neural regulation, their afferent nerves could represent a potential therapeutic target to treat, for example, infectious or autoimmune disease. Little information is available on human lymph node innervation and the aim of this study is to establish a comprehensive and accurate representation of the presence and location of sympathetic nerves in human lymph nodes. Since previous studies mention sympathetic paravascular nerves to occasionally extent into T cell‐rich regions, the relation of these nerves with T cells was studied as well. A total number of 15 inguinal lymph nodes were resected from six donated human cadavers. Lymph node sections were stained with HE and a double T/B cell staining for evaluation of their morphology and to screen for general pathologies. A triple stain was used to identify blood vessels, sympathetic nerves and T cells, and, to study the presence and location of sympathetic nerves and their relation to T cells. To evaluate whether the observed nerves were en route to other structures or were involved in local processes, adjacent slides were stained with a marker for varicosities (synaptophysin), which presence is suggestive for synaptic activity. All lymph nodes contained sympathetic nerves, both as paravascular and discrete structures. In 15/15 lymph nodes, nerves were observed in their capsule, medulla and hilum, whereas only 13/15 lymph nodes contained nerves in their cortex. The amount of sympathetic nerves varied between compartments and between and within individuals. In general, if a lymph node contained more paravascular nerves in a specific compartment, more discrete nerves were observed as well. Occasionally, discrete nerves were observed in relation to T cells in lymphoid tissues of the cortex and medulla. Furthermore, discrete nerves were frequently present in the capsule and hilum. The presence of varicosities in a portion of these nerves, independently to their compartment, suggested a local regulatory function for these nerves. Human lymph nodes contain sympathetic nerves in their capsule, trabeculae, cortex, medulla and hilum, both as paravascular or as discrete structures. Discrete nerves were observed in relation to T cells and non‐T cell‐rich areas such as the hilar and capsular connective tissue. The presence of discrete structures suggests neural regulation of structures other than blood vessels, which was further supported by the presence of varicosities in a portion of these nerves. These observations are of relevance in further understanding neural regulation of lymph node immune responses and in the development of neuromodulatory immune therapies.

An adaptive digital stain separation method for deep learning-based automatic cell profile counts

BACKGROUND

Quantifying cells in a defined region of biological tissue is critical for many clinical and preclinical studies, especially in the fields of pathology, toxicology, cancer and behavior. As part of a program to develop accurate, precise and more efficient automatic approaches for quantifying morphometric changes in biological tissue, we have shown that both deep learning-based and hand-crafted algorithms can estimate the total number of histologically stained cells at their maximal profile of focus in Extended Depth of Field (EDF) images. Deep learning-based approaches show accuracy comparable to manual counts on EDF images but significant enhancement in reproducibility, throughput efficiency and reduced error from human factors. However, a majority of the automated counts are designed for single-immunostained tissue sections.

NEW METHOD

To expand the automatic counting methods to more complex dual-staining protocols, we developed an adaptive method to separate stain color channels on images from tissue sections stained by a primary immunostain with secondary counterstain.

COMPARISON WITH EXISTING METHODS

The proposed method overcomes the limitations of the state-of-the-art stain-separation methods, like the requirement of pure stain color basis as a prerequisite or stain color basis learning on each image.

RESULTS

Experimental results are presented for automatic counts using deep learning-based and hand-crafted algorithms for sections immunostained for neurons (Neu-N) or microglial cells (Iba-1) with cresyl violet counterstain.

CONCLUSION

Our findings show more accurate counts by deep learning methods compared to the handcrafted method. Thus, stain-separated images can function as input for automatic deep learning-based quantification methods designed for single-stained tissue sections.

Towards Automatic Protein Co-Expression Quantification in Immunohistochemical TMA Slides

Immunohistochemical (IHC) analysis of tissue biopsies is currently used for clinical screening of solid cancers to assess protein expression. The large amount of image data produced from these tissue samples requires specialized computational pathology methods to perform integrative analysis. Even though proteins are traditionally studied independently, the study of protein co-expression may offer new insights towards patients' clinical and therapeutic decisions. To explore protein co-expression, we constructed a modular image analysis pipeline to spatially align tissue microarray (TMA) image slides, evaluate alignment quality, define tumor regions, and ultimately quantify protein expression, before and after tumor segmentation. The pipeline was built with open-source tools that can manage gigapixel slides. To evaluate the consensus between pathologist and computer, we characterized a cohort of 142 gastric cancer (GC) cases regarding the extent of E-cadherin and CD44v6 expression. We performed IHC analysis in consecutive TMA slides and compared the automated quantification with the pathologists' manual assessment. Our results show that automated quantification within tumor regions improves agreement with the pathologists' classification. A co-expression map was created to identify the cores co-expressing both proteins. The proposed pipeline provides not only computational tools forwarding current pathology practices to explore co-expression, but also a framework for merging data and transferring information in learning-based approaches to pathology.

Specialized Histological and Histomorphometrical Analytical Methods for Biocompatibility Testing of Biomaterials for Maxillofacial Surgery in (Pre-) Clinical Studies

Both preclinical in vivo experiments and clinical trials are indispensable for analysis of tissue reactions in evaluating the compatibility of biomaterials or medical devices, i.e. the cell types interacting with the material, integration or degradation behavior, implant bed vascularization and immunological response. In particular, both the histological workup (including the processes such as embedding, cutting, histochemical and immunohistochemical staining methods), as well as qualitative and quantitative analysis are crucial steps enabling the final evaluation of biocompatibility. We present a short overview of the most important steps of the different workup and analytical methods used in preclinical and clinical biopsies for both novice and experienced researchers in the field of biomaterial science.

Detecting Oxidative Stress Biomarkers in Neurodegenerative Disease Models and Patients

Oxidative stress is prominent in many neurodegenerative diseases. Along with mitochondrial dysfunction and pathological protein aggregation, increased levels of reactive oxygen and nitrogen species, together with impaired antioxidant defense mechanisms, are frequently observed in Alzheimer's, Parkinson's, Huntington's disease and amyotrophic lateral sclerosis. The presence of oxidative stress markers in patients' plasma and cerebrospinal fluid may aid early disease diagnoses, as well as provide clues regarding the efficacy of experimental disease-modifying therapies in clinical trials. In preclinical animal models, the detection and localization of oxidatively damaged lipids, proteins and nucleic acids helps to identify most vulnerable neuronal populations and brain areas, and elucidate the molecular pathways and the timeline of pathology progression. Here, we describe the protocol for the detection of oxidative stress markers using immunohistochemistry on formaldehyde-fixed, paraffin-embedded tissue sections, applicable to the analysis of postmortem samples and tissues from animal models. In addition, we provide a simple method for the detection of malondialdehyde in tissue lysates and body fluids, which is useful for screening and the identification of tissues and structures in the nervous system which are most affected by oxidative stress.

Stain Color Adaptive Normalization (SCAN) algorithm: Separation and standardization of histological stains in digital pathology

BACKGROUND AND OBJECTIVE

The diagnosis of histopathological images is based on the visual analysis of tissue slices under a light microscope. However, the histological tissue appearance may assume different color intensities depending on the staining process, operator ability and scanner specifications. This stain variability affects the diagnosis of the pathologist and decreases the accuracy of computer-aided diagnosis systems. In this context, the stain normalization process has proved to be a powerful tool to cope with this issue, allowing to standardize the stain color appearance of a source image respect to a reference image.

METHODS

In this paper, novel fully automated stain separation and normalization approaches for hematoxylin and eosin stained histological slides are presented. The proposed algorithm, named SCAN (Stain Color Adaptive Normalization), is based on segmentation and clustering strategies for cellular structures detection. The SCAN algorithm is able to improve the contrast between histological tissue and background and preserve local structures without changing the color of the lumen and the background.

RESULTS

Both stain separation and normalization techniques were qualitatively and quantitively validated on a multi-tissue and multiscale dataset, with highly satisfactory results, outperforming the state-of-the-art approaches. SCAN was also tested on whole-slide images with high performances and low computational times.

CONCLUSIONS

The potential contribution of the proposed standardization approach is twofold: the improvement of visual diagnosis in digital histopathology and the development of powerful pre-processing strategies to automated classification techniques for cancer detection.

Expression and Cellular Distribution of P-Glycoprotein and Breast Cancer Resistance Protein in Amyotrophic Lateral Sclerosis Patients

For amyotrophic lateral sclerosis (ALS), achieving and maintaining effective drug levels in the brain is challenging due to the activity of ATP-binding cassette (ABC) transporters which efflux drugs that affect drug exposure and response in the brain. We investigated the expression and cellular distribution of the ABC transporters P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) using immunohistochemistry in spinal cord (SC), motor cortex, and cerebellum from a large cohort of genetically well characterized ALS patients (n = 25) and controls (n = 14). The ALS group included 17 sporadic (sALS) and 8 familial (fALS) patients. Strong P-gp expression was observed in endothelial cells in both control and ALS specimens. Immunohistochemical analysis showed higher P-gp expression in reactive astroglial cells in both gray (ventral horn) and white matter of the SC, as well as in the motor cortex of all ALS patients, as compared with controls. BCRP expression was higher in glia in the SC and in blood vessels and glia in the motor cortex of ALS patients, as compared with controls. P-gp and BCRP immunoreactivity did not differ between sALS and fALS cases. The upregulation of both ABC transporters in the brain may explain multidrug resistance in ALS patients and has implications for the use of both approved and experimental therapeutics.

Genetic variants in SUSD2 are associated with the risk of ischemic heart disease

BACKGROUND

Genetic factors partly determine the risk for premature myocardial infarction (MI).

OBJECTIVES

We report the identification of a novel rare genetic variant in a kindred with an autosomal dominant trait for premature MI and atherosclerosis and explored the association of a common nonsynonymous variant in the same gene with the risk of ischemic heart disease (IHD) in a population-based study.

METHODS

Next-generation sequencing was performed in a small pedigree with premature MI or subclinical atherosclerosis. A common variant, rs8141797 A>G (p.Asn466Ser), in sushi domain-containing protein 2 (SUSD2) was studied in the prospective Copenhagen General Population Studies (N = 105,408) for association with IHD.

RESULTS

A novel heterozygous nonsense mutation in SUSD2 (c.G583T; p.Glu195Ter) was associated with the disease phenotype in the pedigree. SUSD2 protein was expressed in aortic specimens in the subendothelial cell layer and around the vasa vasorum. Furthermore, the minor G-allele of rs8141797 was associated with per allele higher levels of SUSD2 mRNA expression in the heart and vasculature. In the Copenhagen General Population Study, hazard ratios for IHD were 0.92 (95% CI: 0.87-0.97) in AG heterozygotes and 0.86 (0.62-1.19) in GG homozygotes vs noncarrriers (P-trend = .002). Finally, in meta-analysis including 73,983 IHD cases and 215,730 controls, the odds ratio for IHD per G-allele vs A-allele was 0.93 (0.90-0.96) (P = 4.6 × 10^-7).

CONCLUSIONS

The identification of a truncating mutation in SUSD2, which was associated with premature MI and subclinical atherosclerosis, combined with the finding that a common missense variant in SUSD2 was strongly associated with a lower risk of IHD, suggest that SUSD2 may alter the risk of atherosclerosis.

Virtual multiplex immunohistochemistry: Application on cell block of effusion and aspiration cytology

BACKGROUND

With the continuous development of new antibodies, the use of immunohistochemistry (IHC) is becoming more often a requirement. IHC is frequently necessary for establishing cancer diagnosis and making therapeutic decisions. However, cytology specimens such as effusion fluid and fine-needle aspiration are highly variable in cellularity and contain background inflammatory and mesothelial cells. Compared to biopsy or excision specimens, tissue exhaustion and levels of sections not matching are more commonly encountered. We present a method of integrating whole-slide cell block image of multiple antibodies by digital image processing and reconstructing a virtual multiplex IHC image for enhanced interpretation.

METHODS

Historic archived cell block preparations of carcinomas (n = 19) and melanoma (n = 1) and IHC performed with 3,3'-diaminobenzidine chromogen were reviewed. The slides were digitized by a whole-slide image scanner. Using ImageJ and self-developed code, the slides were aligned by image registration, layered, and recolored to reconstruct a virtual multiplex image, simulating a multiplex preparation with multiple chromogens. To quantity the performance of the image registration, the mean distance between the same cell clusters in aligned images were measured.

RESULTS

All 20 cases were successfully registered. The mean distance between cell clusters after image registration was 8.40 +/- 5.52 μm. The reconstructed images were able to demonstrate coexpression of membranous, cytoplasmic, and nuclear antibodies.

CONCLUSION

With virtual multiplex IHC, we were able to visualize coexpression of multiple antibodies without the added cost of multiplex IHC. Routine and historic slides, without additional tissue consumption, can be retrieved for image reconstruction. This technique is a low-cost adjunct to diagnosis in cytology for more efficient and accurate assessment of antibody coexpression and histochemical stains.

Deficiency in Androgen Receptor Aggravates the Depressive-Like Behaviors in Chronic Mild Stress Model of Depression

While androgen receptor (AR) and stress may influence the development of the major depressive disorder (MDD), the detailed relationship, however, remains unclear. Here we found loss of AR accelerated development of depressive-like behaviors in mice under chronic mild stress (CMS). Mechanism dissection indicated that AR might function via altering the expression of miR-204-5p to modulate the brain-derived neurotrophic factor (BDNF) expression to influence the depressive-like behaviors in the mice under the CMS. Adding the antiandrogen flutamide with the stress hormone corticosterone can additively decrease BDNF mRNA in mouse hippocampus mHippoE-14 cells, which can then be reversed via down-regulating the miR-204-5p expression. Importantly, targeting this newly identified AR-mediated miR-204-5p/BDNF/AKT/MAPK signaling with small molecules including 7,8-DHF and fluoxetine, all led to alter the depressive-like behavior in AR knockout mice under CMS exposure. Together, results from these preclinical studies conclude that decreased AR may accelerate the stress-induced MDD via altering miR-204-5p/BDNF/AKT/MAPK signaling, and targeting this newly identified signaling may help in the development of better therapeutic approaches to reduce the development of MDD.

Empiric Methods to Account for Pre-analytical Variability in Digital Histopathology in Frontotemporal Lobar Degeneration

Digital pathology is increasingly prominent in neurodegenerative disease research, but variability in immunohistochemical staining intensity between staining batches prevents large-scale comparative studies. Here we provide a statistically rigorous method to account for staining batch effects in a large sample of brain tissue with frontotemporal lobar degeneration with tau inclusions (FTLD-Tau, N = 39) or TDP-43 inclusions (FTLD-TDP, N = 53). We analyzed the relationship between duplicate measurements of digital pathology, i.e., percent area occupied by pathology (%AO) for grey matter (GM) and white matter (WM), from two distinct staining batches. We found a significant difference in duplicate measurements from distinct staining batches in FTLD-Tau (mean difference: GM = 1.13 ± 0.44, WM = 1.28 ± 0.56; p < 0.001) and FTLD-TDP (GM = 0.95 ± 0.66, WM = 0.90 ± 0.77; p < 0.001), and these measurements were linearly related (R-squared [Rsq]: FTLD-Tau GM = 0.92, WM = 0.92; FTLD-TDP GM = 0.75, WM = 0.78; p < 0.001 all). We therefore used linear regression to transform %AO from distinct staining batches into equivalent values. Using a train-test set design, we examined transformation prerequisites (i.e., Rsq) from linear-modeling in training sets, and we applied equivalence factors (i.e., beta, intercept) to independent testing sets to determine transformation outcomes (i.e., intraclass correlation coefficient [ICC]). First, random iterations (×100) of linear regression showed that smaller training sets (N = 12–24), feasible for prospective use, have acceptable transformation prerequisites (mean Rsq: FTLD-Tau ≥0.9; FTLD-TDP ≥0.7). When cross-validated on independent complementary testing sets, in FTLD-Tau, N = 12 training sets resulted in 100% of GM and WM transformations with optimal transformation outcomes (ICC ≥ 0.8), while in FTLD-TDP N = 24 training sets resulted in optimal ICC in testing sets (GM = 72%, WM = 98%). We therefore propose training sets of N = 12 in FTLD-Tau and N = 24 in FTLD-TDP for prospective transformations. Finally, the transformation enabled us to significantly reduce batch-related difference in duplicate measurements in FTLD-Tau (GM/WM: p < 0.001 both) and FTLD-TDP (GM/WM: p < 0.001 both), and to decrease the necessary sample size estimated in a power analysis in FTLD-Tau (GM:-40%; WM: -34%) and FTLD-TDP (GM: -20%; WM: -30%). Finally, we tested generalizability of our approach using a second, open-source, image analysis platform and found similar results. We concluded that a small sample of tissue stained in duplicate can be used to account for pre-analytical variability such as staining batch effects, thereby improving methods for future studies.

Sequential Immunofluorescence and Immunohistochemistry on Cryosectioned Zebrafish Embryos

Investigation of intercellular interactions often requires discrete labeling of specific cell populations and precise protein localization. The zebrafish embryo is an excellent tool for examining such interactions with an in vivo model. Whole-mount immunohistochemical and immunofluorescence assays are frequently applied in zebrafish embryos to assess protein expression. However, it can be difficult to achieve accurate mapping of co-localized proteins in three-dimensional space. In addition, some studies may require the use of two antibodies that are not compatible with the same technique (e.g., antibody 1 is only suitable for immunohistochemistry and antibody 2 is only suitable for immunofluorescence). The purpose of the method described herein is to perform sequential immunofluorescence and/or immunohistochemistry on individual cryosections derived from early-stage zebrafish embryos. Here we describe the use of sequential rounds of immunofluorescence, imaging, immunohistochemistry, imaging for a single cryosection in order to achieve precise identification of protein expression at the single-cell level. This methodology is suitable for any study in early-stage zebrafish embryos that requires accurate identification of multiple protein targets in individual cells.

Signature maps for automatic identification of prostate cancer from colorimetric analysis of H&E- and IHC-stained histopathological specimens

Prostate cancer (PCa) is a major cause of cancer death among men. The histopathological examination of post-surgical prostate specimens and manual annotation of PCa not only allow for detailed assessment of disease characteristics and extent, but also supply the ground truth for developing of computer-aided diagnosis (CAD) systems for PCa detection before definitive treatment. As manual cancer annotation is tedious and subjective, there have been a number of publications describing methods for automating the procedure via the analysis of digitized whole-slide images (WSIs). However, these studies have focused only on the analysis of WSIs stained with hematoxylin and eosin (H&E), even though there is additional information that could be obtained from immunohistochemical (IHC) staining. In this work, we propose a framework for automating the annotation of PCa that is based on automated colorimetric analysis of both H&E and IHC WSIs stained with a triple-antibody cocktail against high-molecular weight cytokeratin (HMWCK), p63, and α-methylacyl CoA racemase (AMACR). The analysis outputs were then used to train a regression model to estimate the distribution of cancerous epithelium within slides. The approach yielded an AUC of 0.951, sensitivity of 87.1%, and specificity of 90.7% as compared to slide-level annotations, and generalized well to cancers of all grades.

Overexpression of survivin in pediatric Hodgkin lymphoma tumor cells: Characterization of protein expression and splice-variants transcription profile

Survivin is abundantly expressed during fetal development but absent in most differentiated adult tissues; an exception being components of the immune system, such as B and T lymphocytes. Beyond acting as a master regulator of the cell cycle, survivin acts as an inhibitor of apoptosis and is overexpressed in almost all carcinoma types; however, its expression in lymphomas is lesser-explored. Survivin's role in carcinogenesis was subjected to its sub-cellular localization and splice transcripts expression, namely wild-type survivin, survivin-∆Ex3 and survivin-2B. To assess survivin's expression and sub-cellular localization in Epstein Barr virus positive and negative biopsies from treatment naïve pediatric patients with Hodgkin lymphoma (HL), samples were stained for survivin protein by immunofluorescence. The proportion of survivin+ cells was calculated, survivin sub-cellular localization assessed and its fluorescence intensity quantified. Transcription profile of survivin mRNA variants was studied by RT-qPCR. Survivin was overexpressed in the nucleus of tumor cells, and also in a greater proportion of tumor cells, in comparison with the non-tumoral infiltrating cells. Although a higher expression of survivin was observed in advanced clinical stages, no correlation was found between the expression level of survivin and a proliferation marker, or event-free survival. Instead, survivin was related to apoptosis inhibition in tumor cells. Additionally, survivin's transcriptional variants displayed similar expression levels. Present results suggest that although survivin is overexpressed in Hodgkin's tumor cells, it may not play a central role in the progression of classic HL, or act as a suitable progression biomarker, as suggested for most carcinomas.

Automated digital image quantification of histological staining for the analysis of the trilineage differentiation potential of mesenchymal stem cells

BACKGROUND

Multipotent mesenchymal stem cells (MSCs) have the potential to repair and regenerate damaged tissues and are considered as attractive candidates for the development of cell-based regenerative therapies. Currently, there are more than 200 clinical trials involving the use of MSCs for a wide variety of indications. However, variations in their isolation, expansion, and particularly characterization have made the interpretation of study outcomes or the rigorous assessment of therapeutic efficacy difficult. An unbiased characterization of MSCs is of major importance and essential to guaranty that only the most suitable cells will be used. The development of standardized and reproducible assays to predict MSC potency is therefore mandatory. The currently used quantification methodologies for the determination of the trilineage potential of MSCs are usually based on absorbance measurements which are imprecise and prone to errors. We therefore aimed at developing a methodology first offering a standardized way to objectively quantify the trilineage potential of MSC preparations and second allowing to discriminate functional differences between clonally expanded cell populations.

METHOD

MSCs originating from several patients were differentiated into osteoblasts, adipocytes, and chondroblasts for 14, 17, and 21 days. Differentiated cells were then stained with the classical dyes: Alizarin Red S for osteoblasts, Oil Red O for adipocytes, and Alcian Blue 8GX for chondroblasts. Quantification of differentiation was then performed with our newly developed digital image analysis (DIA) tool followed by the classical absorbance measurement. The results from the two techniques were then compared.

RESULT

Quantification based on DIA allowed highly standardized and objective dye quantification with superior sensitivity compared to absorbance measurements. Furthermore, small differences between MSC lines in the differentiation potential were highlighted using DIA whereas no difference was detected using absorbance quantification.

CONCLUSION

Our approach represents a novel method that simplifies the laboratory procedures not only for the quantification of histological dyes and the degree of differentiation of MSCs, but also due to its color independence, it can be easily adapted for the quantification of a wide range of staining procedures in histology. The method is easily applicable since it is based on open source software and standard light microscopy.

Spatial resolution enhancement for pushbroom-based microscopic hyperspectral imaging

Hyperspectral imaging (HSI) is a promising tool for microscopic histopathology studies. Pushbroom microscopic hyperspectral imaging systems are widely used because of their low cost and easy implementation. However, the spatial resolution of pushbroom HSI systems is limited by the width of the optical entrance slit. A narrower slit leads to longer exposure time and slower imaging speed. In this paper, we explored several spatial resolution enhancement algorithms, originally designed for remote-sensing hyperspectral imaging, for pushbroom microscopic HSI systems. Our results demonstrate that those algorithms could effectively achieve a higher spatial resolution without sacrificing imaging speed.

Quantification of Tyrosine Hydroxylase and ErbB4 in the Locus Coeruleus of Mood Disorder Patients Using a Multispectral Method to Prevent Interference with Immunocytochemical Signals by Neuromelanin

The locus coeruleus (LC) has been studied in major depressive disorder (MDD) and bipolar disorder (BD). A major problem of immunocytochemical studies in the human LC is interference with the staining of the immunocytochemical end-product by the omnipresent natural brown pigment neuromelanin. Here, we used a multispectral method to untangle the two colors: blue immunocytochemical staining and brown neuromelanin. We found significantly increased tyrosine hydroxylase (TH) in the LC of MDD patients-thus validating the method-but not in BD patients, and we did not find significant changes in the receptor tyrosine-protein kinase ErbB4 in the LC in MDD or BD patients. We observed clear co-localization of ErbB4, TH, and neuromelanin in the LC neurons. The different stress-related molecular changes in the LC may contribute to the different clinical symptoms in MDD and BD.

Expression of activating transcription factor 5 (ATF5) is increased in astrocytomas of different WHO grades and correlates with survival of glioblastoma patients

Background

ATF5 suppresses differentiation of neuroprogenitor cells and is overexpressed in glioblastoma (GBM). A reduction of its expression leads to apoptotic GBM cell death. Data on ATF5 expression in astrocytoma WHO grade II (low-grade astrocytoma [LGA]) are scarce and lacking on recurrent GBM.

Patients and methods

ATF5 mRNA was extracted from frozen samples of patients’ GBM (n=79), LGA (n=40), and normal brain (NB, n=10), quantified by duplex qPCR and correlated with retrospectively collected clinical data. ATF5 protein expression was evaluated by measuring staining intensity on immunohistochemistry.

Results

ATF5 mRNA was overexpressed in LGA (sevenfold, P<0.001) and GBM (tenfold, P<0.001) compared to NB, which was confirmed on protein level. Although ATF5 mRNA expression in GBM showed a considerable fluctuation range, groups of varying biological behavior, that is, local/multifocal growth or primary tumor/relapse and the tumor localization at diagnosis, were not significantly different. ATF5 mRNA correlated with the patients’ age (r=0.339, P=0.028) and inversely with Ki67-staining (r=−0.421, P=0.007). GBM patients were allocated to a low and a high ATF5 expression group by the median ATF5 overexpression compared to NB. Kaplan–Meier analysis and Cox regression indicated that ATF5 mRNA expression significantly correlated with short-term survival (t,12 months, median survival 18 vs 13 months, P=0.022, HR 2.827) and progression-free survival (PFS) (12 vs 6 months, P=0.024). This advantage vanished after 24 months (P=0.084).

Conclusion

ATF5 mRNA expression could be identified as an additional, though not independent factor correlating with overall survival and PFS. Since its inhibition might lead to the selective death of glioma cells, it might serve as a potential ubiquitous therapeutic target in astrocytic tumors.

Progressive multiple sclerosis patients show substantial lesion activity that correlates with clinical disease severity and sex: a retrospective autopsy cohort analysis

Multiple sclerosis (MS) is a highly heterogeneous disease with large inter-individual differences in disease course. MS lesion pathology shows considerable heterogeneity in localization, cellular content and degree of demyelination between patients. In this study, we investigated pathological correlates of disease course in MS using the autopsy cohort of the Netherlands Brain Bank (NBB), containing 182 MS brain donors. Using a standardized autopsy procedure including systematic dissection from standard locations, 3188 tissue blocks containing 7562 MS lesions were dissected. Unbiased measurements of lesion load were made using the tissue from standard locations. Lesion demyelinating and innate inflammatory activity were visualized by immunohistochemistry for proteolipid protein and human leukocyte antigen. Lesions were classified into active, mixed active/inactive (also known as chronic active), inactive or remyelinated, while microglia/macrophage morphology was classified as ramified, amoeboid or foamy. The severity score was calculated from the time from first symptoms to EDSS-6. Lesion type prevalence and microglia/macrophage morphology were analyzed in relation to clinical course, disease severity, lesion load and sex, and in relation to each other. This analysis shows for the first time that (1) in progressive MS, with a mean disease duration of 28.6 ± 13.3 years (mean ± SD), there is substantial inflammatory lesion activity at time to death. 57% of all lesions were either active or mixed active/inactive and 78% of all patients had a mixed active/inactive lesion present; (2) patients that had a more severe disease course show a higher proportion of mixed active/inactive lesions (p = 6e-06) and a higher lesion load (p = 2e-04) at the time of death, (3) patients with a progressive disease course show a higher lesion load (p = 0.001), and a lower proportion of remyelinated lesions (p = 0.03) compared to patients with a relapsing disease course, (4) males have a higher incidence of cortical grey matter lesions (p = 0.027) and a higher proportion of mixed active/inactive lesions compared to females across the whole cohort (p = 0.007). We confirm that there is a higher proportion of mixed active/inactive lesions (p = 0.006) in progressive MS compared to relapsing disease. Identification of mixed active/inactive lesions on MRI is necessary to determine whether they can be used as a prognostic tool in living MS patients.