Deep immune phenotyping reveals similarities between aging, Down syndrome, and autoimmunity

Permutational analysis of the immune system reveals advanced immune aging in individuals with Down syndrome and in individuals with type 1 diabetes.

Role and Relevance of Cerebrospinal Fluid Cells in Diagnostics and Research: State-of-the-Art and Underutilized Opportunities

Cerebrospinal fluid (CSF) has recently experienced a revival in diagnostics and research. However, little progress has been made regarding CSF cell analysis. For almost a century, CSF cell count and cytomorphological examination have been central diagnostic parameters, with CSF pleocytosis as a hallmark finding of neuroinflammation and cytology offering valuable clues regarding infectious, autoimmune, and malignant aetiologies. A great deal of information, however, remains unattended as modern immune phenotyping technologies have not yet been broadly incorporated into routine CSF analysis. This is a serious deficit considering the central role of CSF cells as effectors in central nervous system (CNS) immune defence and autoimmune CNS processes, and the diagnostic challenges posed by clinically overlapping infectious and immune-mediated CNS diseases. Here, we summarize historical, specimen-intrinsic, methodological, and technical issues determining the state-of-the-art diagnostics of CSF cells and outline future perspectives for this underutilized window into meningeal and CNS immunity.

Spontaneous Physical Activity in Obese Condition Favours Antitumour Immunity Leading to Decreased Tumour Growth in a Syngeneic Mouse Model of Carcinogenesis

Our goal was to evaluate the effect of spontaneous physical activity on tumour immunity during aging. Elderly (n = 10/group, 33 weeks) ovariectomized C57BL/6J mice fed a hyperlipidic diet were housed in standard (SE) or enriched (EE) environments. After 4 weeks, orthotopic implantation of syngeneic mammary cancer EO771 cells was performed to explore the immune phenotyping in the immune organs and the tumours, as well as the cytokines in the tumour and the plasma. EE lowered circulating myostatin, IL-6 and slowed down tumour growth. Spleen and inguinal lymph node weights reduced in relation to SE. Within the tumours, EE induced a lower content of lymphoid cells with a decrease in Th2, Treg and MDCS; and, conversely, a greater quantity of Tc and TAMs. While no change in tumour NKs cells occurred, granzyme A and B expression increased as did that of perforin 1. Spontaneous physical activity in obese conditions slowed tumour growth by decreasing low-grade inflammation, modulating immune recruitment and efficacy within the tumour.

Immunomonitoring of Monocyte and Neutrophil Function in Critically Ill Patients: From Sepsis and/or Trauma to COVID-19

Immune cells and mediators play a crucial role in the critical care setting but are understudied. This review explores the concept of sepsis and/or injury-induced immunosuppression and immuno-inflammatory response in COVID-19 and reiterates the need for more accurate functional immunomonitoring of monocyte and neutrophil function in these critically ill patients. in addition, the feasibility of circulating and cell-surface immune biomarkers as predictors of infection and/or outcome in critically ill patients is explored. It is clear that, for critically ill, one size does not fit all and that immune phenotyping of critically ill patients may allow the development of a more personalized approach with tailored immunotherapy for the specific patient. In addition, at this point in time, caution is advised regarding the quality of evidence of some COVID-19 studies in the literature.

Multiplexed high-throughput immune cell imaging reveals molecular health-associated phenotypes

SummaryPhenotypic plasticity is essential to the immune system, yet the factors that shape it are not fully understood. Here, we comprehensively analyze immune cell phenotypes including morphology across human cohorts by single-round multiplexed immunofluorescence, automated microscopy, and deep learning. Using the uncertainty of convolutional neural networks to cluster the phenotypes of 8 distinct immune cell subsets, we find that the resulting maps are influenced by donor age, gender, and blood pressure, revealing distinct polarization and activation-associated phenotypes across immune cell classes. We further associate T-cell morphology to transcriptional state based on their joint donor variability, and validate an inflammation-associated polarized T-cell morphology, and an age-associated loss of mitochondria in CD4+ T-cells. Taken together, we show that immune cell phenotypes reflect both molecular and personal health information, opening new perspectives into the deep immune phenotyping of individual people in health and disease.

821 Machine learning models can quantify CD8 positivity in lymphocytes in melanoma clinical trial samples

BackgroundAn accurate histological characterization of immune cells in the tumor microenvironment is essential for developing novel immune oncology targeted therapies and can assist in guiding patient treatment decisions. However, immune phenotyping is subject to challenges of manual scoring and inter-pathologist scoring variability. To support pathologist-scored immune phenotyping across tumor types, we are developing machine learning (ML)-based models that can identify and quantify CD8+ lymphocytes within the stromal and parenchyma regions of tumors from non-small cell lung cancer, renal cell carcinoma, breast cancer, gastric cancer, head and neck squamous cell carcinoma, urothelial carcinoma, and melanoma. Here, we focus on the ML model for melanoma showing recent results for ML-based identification and quantification of CD8+ lymphocytes and concordance with manual pathologic assessment in data derived from clinical trials.MethodsML algorithms were developed to quantify CD8+ lymphocytes in melanoma using 200 samples from a commercial dataset containing both primary and metastatic melanoma cases. Models were trained using the PathAI research platform on digitized whole slide images (WSI) stained for CD8 using clone C8/144b (Dako), and annotations were provided by the PathAI network of expert pathologists. Training included identification of slide artifacts, parenchyma, cancer stroma, and necrosis, as well as CD8+ lymphocytes and other CD8– cell types. Examples of melanin, such as pigmented macrophages, were added to non-CD8+ cell types. To evaluate the performance of the ML model, model-predicted CD8+ counts were compared to a consensus count from five independent pathologists for representative regions (“frames”) using the Pearson correlation. This was done in 112 held-out test frames from 90 WSI baseline samples from three clinical trials of immunotherapy treatment in individuals with metastatic melanoma. Inter-pathologist agreement among the five pathologists was also calculated.ResultsML-based quantitation of CD8 positivity in lymphocytes showed high concordance with manual pathologist consensus counts. In frames validation of CD8+ counts on the test set of WSI, there was high correlation between the ML model and pathologist consensus counts (r=0.92 [95% CI 0.88–0.94]). This correlation was comparable to the agreement among the five expert pathologists (r=0.88 [95% CI 0.85–0.91]).ConclusionsML model-predicted CD8+ cell counts are highly concordant with pathologist scores on WSI samples from melanoma-focused clinical trials. These data demonstrate the capability of AI-powered digital pathology for accurate and reproducible quantitation of CD8+ lymphocytes in clinical trial samples, contributing to improved evaluation of the tumor microenvironment and targeted development of therapeutics.

Modeling the relevance of immune and metabolic cues in the macrophage/fibroblast interplay during fibrosis

Fibrosis is a progressive biological process leading to organ dysfunction in different clinical settings. As fibroblasts and macrophages are known as key cellular players for fibrosis development, we adopted an in vitro model to define the functional effects of inflammation, hypoxia, and the adaptive immune context on their functional interplay with respect to fibrosis development. Transcriptomic analysis defined the impact of each parameter, acting alone or in combination, on functional properties of both cell types, exposed individually or in a cell-cell contact. These in vitro signatures were matched with transcriptomic profiles generated on laser-captured glomeruli and cortical tubulointerstitial area isolated from human transplanted kidneys with advanced stages of glomerulosclerosis and interstitial fibrosis/tubular atrophy, two clinically relevant conditions associated with organ failure in renal allografts. In vitro signatures were also used to instruct the development of a mathematical model predicting the relevance of each parameter in fibrosis development scenario, which indicated tolerance to inflammatory infiltrates under otherwise favorable conditions and defined an operative window in which hypoxia exerts a crucial role, supported by the degree of inflammation. Observed signatures and model-based predictions strongly suggested that irreversible fibrosis development is the result of specific combinations of metabolic and inflammatory cues, which drive distinct profibrotic paths in the glomeruli and the tubulointerstitial compartments. These findings, which found confirmation in tissue-based quantitative immune-phenotyping of transplanted kidney biopsies, indicate that the combination of in vitro and in silico modeling represents a powerful systems medicine approach to dissect fibrosis pathogenesis and develop coordinated targeted approaches.

The CXCL13/CXCR5-chemokine axis in neuroinflammation: evidence of CXCR5+CD4 T cell recruitment to CSF

Background C-X-C chemokine ligand 13 (CXCL13) is frequently elevated in cerebrospinal fluid (CSF) in a variety of inflammatory central nervous system (CNS) diseases, has been detected in meningeal B cell aggregates in brain tissues of multiple sclerosis patients, and proposedly recruits B cells into the inflamed CNS. Besides B cells also follicular helper T (Tfh) cells express the cognate receptor C-X-C chemokine receptor type 5 (CXCR5) and follow CXCL13 gradients in lymphoid tissues. These highly specialized B cell helper T cells are indispensable for B cell responses to infection and vaccination and involved in autoimmune diseases. Phenotypically and functionally related circulating CXCR5+CD4 T cells occur in blood. Their co-recruitment to the inflamed CSF is feasible but unresolved. Methods We approached this question with a retrospective study including data of all patients between 2017 and 2019 of whom immune phenotyping data of CXCR5 expression and CSF CXCL13 concentrations were available. Discharge diagnoses and CSF laboratory parameters were retrieved from records. Patients were categorized as pyogenic/aseptic meningoencephalitis (ME, n = 29), neuroimmunological diseases (NIMM, n = 22), and non-inflammatory neurological diseases (NIND, n = 6). ANOVA models and Spearman’s Rank-Order correlation were used for group comparisons and associations of CXCL13 levels with immune phenotyping data. Results In fact, intrathecal CXCL13 elevations strongly correlated with CXCR5+CD4 T cell frequencies in the total cohort (p < 0.0001, r = 0.59), and ME (p = 0.003, r = 0.54) and NIMM (p = 0.043, r = 0.44) patients. Moreover, the ratio of CSF-to-peripheral blood (CSF/PB) frequencies of CXCR5+CD4 T cells strongly correlated with CXCL13 levels both in the total cohort (p = 0.001, r = 0.45) and ME subgroup (p = 0.005, r = 0.50), indicating selective accumulation. ME, NIMM and NIND groups differed with regard to CSF cell counts, albumin quotient, intrathecal IgG, CXCL13 elevations and CXCR5+CD4 T cells, which were higher in inflammatory subgroups. Conclusion The observed link between intrathecal CXCL13 elevations and CXCR5+CD4 T cell frequencies does not prove but suggests recruitment of possible professional B cell helpers to the inflamed CSF. This highlights CSF CXCR5+CD4 T cells a key target and potential missing link to the poorly understood phenomenon of intrathecal B cell and antibody responses with relevance for infection control, chronic inflammation and CNS autoimmunity.

Establishing standardized immune phenotyping of metastatic melanoma by digital pathology

CD8+ tumor-infiltrating T cells can be regarded as one of the most relevant predictive biomarkers in immune-oncology. Highly infiltrated tumors, referred to as inflamed (clinically “hot”), show the most favorable response to immune checkpoint inhibitors in contrast to tumors with a scarce immune infiltrate called immune desert or excluded (clinically “cold”). Nevertheless, quantitative and reproducible methods examining their prevalence within tumors are lacking. We therefore established a computational diagnostic algorithm to quantitatively measure spatial densities of tumor-infiltrating CD8+ T cells by digital pathology within the three known tumor compartments as recommended by the International Immuno-Oncology Biomarker Working Group in 116 prospective metastatic melanomas of the Swiss Tumor Profiler cohort. Workflow robustness was confirmed in 33 samples of an independent retrospective validation cohort. The introduction of the intratumoral tumor center compartment proved to be most relevant for establishing an immune diagnosis in metastatic disease, independent of metastatic site. Cut-off values for reproducible classification were defined and successfully assigned densities into the respective immune diagnostic category in the validation cohort with high sensitivity, specificity, and precision. We provide a robust diagnostic algorithm based on intratumoral and stromal CD8+ T-cell densities in the tumor center compartment that translates spatial densities of tumor-infiltrating CD8+ T cells into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”. The consideration of the intratumoral tumor center compartment allows immune phenotyping in the clinically highly relevant setting of metastatic lesions, even if the invasive margin compartment is not captured in biopsy material.