Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

Nuclear apoptotic volume decrease in individual cells: Confocal microscopy imaging and kinetic modeling.

The dynamics of nuclear morphology changes during apoptosis remains poorly investigated and understood. Using 3D time-lapse confocal microscopy we performed a study of early-stage apoptotic nuclear morphological changes induced by etoposide in single living HepG2 cells. These observations provide a definitive evidence that nuclear apoptotic volume decrease (AVD) is occurring simultaneously with peripheral chromatin condensation (so called "apoptotic ring"). In order to describe quantitatively the dynamics of nuclear morphological changes in the early stage of apoptosis we suggest a general molecular kinetic model, which fits well the obtained experimental data in our study. Results of this work may clarify molecular mechanisms of nuclear morphology changes during apoptosis.

Transcriptional reprogramming of infiltrating neutrophils drives lung pathology in severe COVID-19 despite low viral load.

Troubling disparities in COVID-19-associated mortality emerged early, with nearly 70% of deaths confined to Black/African American (AA) patients in some areas. However, targeted studies on this vulnerable population are scarce. Here, we applied multiomics single-cell analyses of immune profiles from matching airways and blood samples of Black/AA patients during acute SARS-CoV-2 infection. Transcriptional reprogramming of infiltrating IFITM2+/S100A12+ mature neutrophils, likely recruited via the IL-8/CXCR2 axis, leads to persistent and self-sustaining pulmonary neutrophilia with advanced features of acute respiratory distress syndrome (ARDS) despite low viral load in the airways. In addition, exacerbated neutrophil production of IL-8, IL-1ß, IL-6, and CCL3/4, along with elevated levels of neutrophil elastase and myeloperoxidase, were the hallmarks of transcriptionally active and pathogenic airway neutrophilia. Although our analysis was limited to Black/AA patients and was not designed as a comparative study across different ethnicities, we present an unprecedented in-depth analysis of the immunopathology that leads to acute respiratory distress syndrome in a well-defined patient population disproportionally affected by severe COVID-19.

Acetylation-dependent nuclear arrangement and recruitment of BMI1 protein to UV-damaged chromatin.

Polycomb group (PcG) proteins, organized into Polycomb bodies, are important regulatory components of epigenetic processes involved in the heritable transcriptional repression of target genes. Here, we asked whether acetylation can influence the nuclear arrangement and function of the BMI1 protein, a core component of the Polycomb group complex, PRC1. We used time-lapse confocal microscopy, micro-irradiation by UV laser (355 nm) and GFP technology to study the dynamics and function of the BMI1 protein. We observed that BMI1 was recruited to UV-damaged chromatin simultaneously with decreased lysine acetylation, followed by the recruitment of heterochromatin protein HP1ß to micro-irradiated regions. Pronounced recruitment of BMI1 was rapid, with half-time τ = 15 sec; thus, BMI1 is likely involved in the initiation step leading to the recognition of UV-damaged sites. Histone hyperacetylation, stimulated by HDAC inhibitor TSA, suppression of transcription by actinomycin D, and ATP-depletion prevented increased accumulation of BMI1 to γH2AX-positive irradiated chromatin. Moreover, BMI1 had slight ability to recognize spontaneously occurring DNA breaks caused by other pathophysiological processes. Taken together, our data indicate that the dynamics of recognition of UV-damaged chromatin, and the nuclear arrangement of BMI1 protein can be influenced by acetylation and occur as an early event prior to the recruitment of HPß to UV-irradiated chromatin.

Arrangement of nuclear structures is not transmitted through mitosis but is identical in sister cells.

Although it is well known that chromosomes are non-randomly organized during interphase, it is not completely clear whether higher-order chromatin structure is transmitted from mother to daughter cells. Therefore, we addressed the question of how chromatin is rearranged during interphase and whether heterochromatin pattern is transmitted after mitosis. We additionally tested the similarity of chromatin arrangement in sister interphase nuclei. We noticed a very active cell rotation during interphase, especially when histone hyperacetylation was induced or transcription was inhibited. This natural phenomenon can influence the analysis of nuclear arrangement. Using photoconversion of Dendra2-tagged core histone H4 we showed that the distribution of chromatin in daughter interphase nuclei differed from that in mother cells. Similarly, the nuclear distribution of heterochromatin protein 1ß (HP1ß) was not completely identical in mother and daughter cells. However, identity between mother and daughter cells was in many cases evidenced by nucleolar composition. Moreover, morphology of nucleoli, HP1ß protein, Cajal bodies, chromosome territories, and gene transcripts were identical in sister cell nuclei. We conclude that the arrangement of interphase chromatin is not transmitted through mitosis, but the nuclear pattern is identical in naturally synchronized sister cells. It is also necessary to take into account the possibility that cell rotation and the degree of chromatin condensation during functionally specific cell cycle phases might influence our view of nuclear architecture.

A nonfitting method using a spatial sine window transform for inhomogeneous effective-diffusion measurements by FRAP.

Determining averaged effective diffusion constants from experimental measurements of fluorescent proteins in an inhomogeneous medium in the presence of ligand-receptor interactions poses problems of analytical tractability. Here, we introduced a nonfitting method to evaluate the averaged effective diffusion coefficient of a region of interest (which may include a whole nucleus) by mathematical processing of the entire cellular two-dimensional spatial pattern of recovered fluorescence. Spatially and temporally resolved measurements of protein transport inside cells were obtained using the fluorescence recovery after photobleaching technique. Two-dimensional images of fluorescence patterns were collected by laser-scanning confocal microscopy. The method was demonstrated by applying it to an estimation of the mobility of green fluorescent protein-tagged heterochromatin protein 1 in the nuclei of living mouse embryonic fibroblasts. This approach does not require the mathematical solution of a corresponding system of diffusion-reaction equations that is typical of conventional fluorescence recovery after photobleaching data processing, and is most useful for investigating highly inhomogeneous areas, such as cell nuclei, which contain many protein foci and chromatin domains.

Distribution function approach to the study of the kinetics of IgM antibody binding to FcγRIIIb (CD16b) receptors on neutrophils by flow cytometry.

Though flow cytometry provides the entire distribution of cellular fluorescence (i.e., "fluorescence profile"), only mean fluorescence data are usually considered in studies of ligand-receptor binding. In this study, we presented a method of the treatment of the temporal evolution of the whole fluorescence profile with a comprehensive statistical approach extended to the reversible binding case. The method was demonstrated in the study of the 1D3 IgM monoclonal antibodies binding to FcγRIIIb receptors (CD16b) on neutrophils. Kinetic experiments were carried out using a FACSCalibur (Becton Dickinson, USA) flow cytometer. For each of four donors, we obtained the distribution of the number of FcγRIIIb surface receptors for neutrophils and the rate constants per receptor: the association rate constant of (2.7±0.4)×10(7) M(-1) min(-1), and the dissociation rate constant of (1.3±0.4)×10(-1) min(-1). Based on the obtained values, the size of the receptor reaction site was estimated at approximately 1 nm. It was found, that cell receptors distributions differed sufficiently between donors in mean and the skewness values, whereas the coefficient of variation (i.e., the ratio of the standard deviation to the mean) did not vary significantly.

Automated subset identification and characterization pipeline for multidimensional flow and mass cytometry data clustering and visualization.

When examining datasets of any dimensionality, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. The ubiquity of multidimensional data has motivated the replacement of user-guided clustering with fully automated clustering. The fully automated methods are designed to make clustering more accurate, standardized and faster. However, the adoption of these methods is still limited by the lack of intuitive visualization and cluster matching methods that would allow users to readily interpret fully automatically generated clusters. To address these issues, we developed a fully automated subset identification and characterization (SIC) pipeline providing robust cluster matching and data visualization tools for high-dimensional flow/mass cytometry (and other) data. This pipeline automatically (and intuitively) generates two-dimensional representations of high-dimensional datasets that are safe from the curse of dimensionality. This new approach allows more robust and reproducible data analysis,+ facilitating the development of new gold standard practices across laboratories and institutions.

Light scattering by neutrophils: model, simulation, and experiment.

We studied the elastic light-scattering properties of human blood neutrophils, both experimentally and theoretically. The experimental study was performed with a scanning flow cytometer measuring the light-scattering patterns (LSPs) of individual cells over an angular range of 5-60 deg. We determined the absolute differential light-scattering cross sections of neutrophils. We also proposed an optical model for a neutrophil as a sphere filled by small spheres and prolate spheroids that correspond to granules and segmented nucleus, respectively. This model was used in simulations of LSPs using the discrete dipole approximation and different compositions of internal organelles. A comparison of experimentally measured and simulated LSPs gives a good qualitative agreement in LSP shape and quantitative agreement in overall magnitude of the differential light-scattering cross section.

QFMatch: multidimensional flow and mass cytometry samples alignment.

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples.

Earth Mover's Distance (EMD): A True Metric for Comparing Biomarker Expression Levels in Cell Populations.

Changes in the frequencies of cell subsets that (co)express characteristic biomarkers, or levels of the biomarkers on the subsets, are widely used as indices of drug response, disease prognosis, stem cell reconstitution, etc. However, although the currently available computational "gating" tools accurately reveal subset frequencies and marker expression levels, they fail to enable statistically reliable judgements as to whether these frequencies and expression levels differ significantly between/among subject groups. Here we introduce flow cytometry data analysis pipeline which includes the Earth Mover's Distance (EMD) metric as solution to this problem. Well known as an informative quantitative measure of differences between distributions, we present three exemplary studies showing that EMD 1) reveals clinically-relevant shifts in two markers on blood basophils responding to an offending allergen; 2) shows that ablative tumor radiation induces significant changes in the murine colon cancer tumor microenvironment; and, 3) ranks immunological differences in mouse peritoneal cavity cells harvested from three genetically distinct mouse strains.

AutoGate: automating analysis of flow cytometry data.

Nowadays, one can hardly imagine biology and medicine without flow cytometry to measure CD4 T cell counts in HIV, follow bone marrow transplant patients, characterize leukemias, etc. Similarly, without flow cytometry, there would be a bleak future for stem cell deployment, HIV drug development and full characterization of the cells and cell interactions in the immune system. But while flow instruments have improved markedly, the development of automated tools for processing and analyzing flow data has lagged sorely behind. To address this deficit, we have developed automated flow analysis software technology, provisionally named AutoComp and AutoGate. AutoComp acquires sample and reagent labels from users or flow data files, and uses this information to complete the flow data compensation task. AutoGate replaces the manual subsetting capabilities provided by current analysis packages with newly defined statistical algorithms that automatically and accurately detect, display and delineate subsets in well-labeled and well-recognized formats (histograms, contour and dot plots). Users guide analyses by successively specifying axes (flow parameters) for data subset displays and selecting statistically defined subsets to be used for the next analysis round. Ultimately, this process generates analysis "trees" that can be applied to automatically guide analyses for similar samples. The first AutoComp/AutoGate version is currently in the hands of a small group of users at Stanford, Emory and NIH. When this "early adopter" phase is complete, the authors expect to distribute the software free of charge to .edu, .org and .gov users.

Structure and epigenetics of nucleoli in comparison with non-nucleolar compartments.

The nucleolus is a nuclear compartment that plays an important role in ribosome biogenesis. Some structural features and epigenetic patterns are shared between nucleolar and non-nucleolar compartments. For example, the location of transcriptionally active mRNA on extended chromatin loop species is similar to that observed for transcriptionally active ribosomal DNA (rDNA) genes on so-called Christmas tree branches. Similarly, nucleolus organizer region-bearing chromosomes located a distance from the nucleolus extend chromatin fibers into the nucleolar compartment. Specific epigenetic events, such as histone acetylation and methylation and DNA methylation, also regulate transcription of both rRNA- and mRNA-encoding loci. Here, we review the epigenetic mechanisms and structural features that regulate transcription of ribosomal and mRNA genes. We focus on similarities in epigenetic and structural regulation of chromatin in nucleoli and the surrounding non-nucleolar region and discuss the role of proteins, such as heterochromatin protein 1, fibrillarin, nucleolin, and upstream binding factor, in rRNA synthesis and processing.