Fetal microchimerism cells suppress arthritis progression by inducing CD14+ IL-10+ cells in pregnant experimental mice.

BACKGROUND: Fetal microchimerism occurs in the mother after a pregnancy. To investigate the role of fetal microchimerism cells (FMCs) in rheumatoid arthritis, we analyzed the population of fetal cells in pregnant experimental arthritis mice. METHODS: We used EGFP+ fetuses, which were mated with either healthy female mice or CIA mice, and male C57BL/6J-Tg (Pgk1-EGFP)03Narl mice, to detect the population of FMCs in maternal circulation. The disease progression was determined by measuring the clinical score and histological stains during pregnancy. The fetal cells have been analyzed if expressing EGFP, CD45, and Scal by flow cytometry. We also detected the expression of CD14+ IL-10+ cells in vivo and in vitro. RESULTS: Our data showed that the pregnancy ameliorated the arthritis progression of CIA mice. The IHC stains showed the CD45 -Sca-1+ EGFP+ FMCs were expressed in the bone marrow and peripheral blood mononuclear cells (PBMC) at 14 gestation days. However, Treg and Tc cell populations showed no significant change in the bone marrow. The data showed the H2Kb + fetal cells induced CD14+ IL10+ cell populations increased in the bone marrow in vitro and in vivo. CONCLUSION: Our investigations demonstrated that the FMCs protected the CIA mice from cartilage damage and triggered an immunosuppressive response in them by increasing the number of CD14+ IL10+ cells. In conclusion, the FMCs could potentially exhibit protective properties within the context of inflammatory arthritis that arises during pregnancy.

Integrated multiomics revealed adenosine signaling predict immunotherapy response and regulate tumor ecosystem of melanoma.

Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy.

Neural and immune roles in osteoarthritis pain: Mechanisms and intervention strategies.

Pain is the leading symptom for most individuals with osteoarthritis (OA), a complex condition marked by joint discomfort. Recently, the dynamic interplay between the nervous and immune systems has become a focal point for understanding pain regulation. Despite this, there is still a substantial gap in our comprehensive understanding of the neuroimmune interactions and their effects on pain in OA. This review examines the bidirectional influences between immune cells and nerves in OA progression. It explores current approaches that target neuroimmune pathways, including promoting M2 macrophage polarization and specific neuronal receptor targeting, for effective pain reduction. Translational potential statement: This review provides a comprehensive overview of the mechanisms underlying the interplay between the immune system and nervous system during the progression of OA, as well as their contributions to pain. Additionally, it compiles existing intervention strategies targeting neuroimmunity for the treatment of OA pain. This information offers valuable insights for researchers seeking to address the challenge of OA pain.

Targeting tumour metabolism in melanoma to enhance response to immune checkpoint inhibition: A balancing act.

Immune checkpoint inhibition has transformed the treatment landscape of advanced melanoma and long-term survival of patients is now possible. However, at least half of the patients do not benefit sufficiently. Metabolic reprogramming is a hallmark of cancer cells and may contribute to both tumour growth and immune evasion by the tumour. Preclinical studies have indeed demonstrated that modulating tumour metabolism can reduce tumour growth while improving the functionality of immune cells. Since metabolic pathways are commonly shared between immune and tumour cells, it is essential to understand how modulating tumour metabolism in patients influences the intricate balance of pro-and anti-tumour immune effects in the tumour microenvironment. The key question is whether modulating tumour metabolism can inhibit tumour cell growth as well as facilitate an anti-tumour immune response. Here, we review current knowledge on the effect of tumour metabolism on the immune response in melanoma. We summarise metabolic pathways in melanoma and non-cancerous cells in the tumour microenvironment and discuss models and techniques available to study the metabolic-immune interaction. Finally, we discuss clinical use of these techniques to improve our understanding of how metabolic interventions can tip the balance towards a favourable, immune permissive microenvironment in melanoma patients.

An in vitro model system for testing chemical effects on microbiome-immune interactions - examples with BPX and PFAS mixtures.

Introduction: More than 350,000 chemicals make up the chemical universe that surrounds us every day. The impact of this vast array of compounds on our health is still poorly understood. Manufacturers are required to carry out toxicological studies, for example on the reproductive or nervous systems, before putting a new substance on the market. However, toxicological safety does not exclude effects resulting from chronic exposure to low doses or effects on other potentially affected organ systems. This is the case for the microbiome-immune interaction, which is not yet included in any safety studies. Methods: A high-throughput in vitro model was used to elucidate the potential effects of environmental chemicals and chemical mixtures on microbiome-immune interactions. Therefore, a simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species was cultured in vitro in a bioreactor that partially mimics intestinal conditions. The bacteria were continuously exposed to mixtures of representative and widely distributed environmental chemicals, i.e. bisphenols (BPX) and/or per- and polyfluoroalkyl substances (PFAS) at concentrations of 22 µM and 4 µM, respectively. Furthermore, changes in the immunostimulatory potential of exposed microbes were investigated using a co-culture system with human peripheral blood mononuclear cells (PBMCs). Results: The exposure to BPX, PFAS or their mixture did not influence the community structure and the riboflavin production of SIHUMIx in vitro. However, it altered the potential of the consortium to stimulate human immune cells: in particular, activation of CD8+ MAIT cells was affected by the exposure to BPX- and PFAS mixtures-treated bacteria. Discussion: The present study provides a model to investigate how environmental chemicals can indirectly affect immune cells via exposed microbes. It contributes to the much-needed knowledge on the effects of EDCs on an organ system that has been little explored in this context, especially from the perspective of cumulative exposure.

Hybridizing mechanistic mathematical modeling with deep learning methods to predict individual cancer patient survival after immune checkpoint inhibitor therapy.

We present a study where predictive mechanistic modeling is used in combination with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) therapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models (but may not be directly measurable in the clinic) and easily measurable quantities or characteristics (that are not always readily incorporated into predictive mechanistic models). The mechanistic model we have applied here can predict tumor response from CT or MRI imaging based on key mechanisms underlying checkpoint inhibitor therapy, and in the present work, its parameters were combined with readily-available clinical measures from 93 patients into a hybrid training set for a deep learning time-to-event predictive model. Analysis revealed that training an artificial neural network with both mechanistic modeling-derived and clinical measures achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when only mechanistic model-derived values or only clinical data were used. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in neural network decision making, and in increasing prediction accuracy, further supporting the advantage of our hybrid approach. We anticipate that many existing mechanistic models may be hybridized with deep learning methods in a similar manner to improve predictive accuracy through addition of additional data that may not be readily implemented in mechanistic descriptions.

Metabolic reprogramming and signalling cross-talks in tumour-immune interaction: a system-level exploration.

Tumour-immune microenvironment (TIME) is pivotal in tumour progression and immunoediting. Within TIME, immune cells undergo metabolic adjustments impacting nutrient supply and the anti-tumour immune response. Metabolic reprogramming emerges as a promising approach to revert the immune response towards a pro-inflammatory state and conquer tumour dominance. This study proposes immunomodulatory mechanisms based on metabolic reprogramming and employs the regulatory flux balance analysis modelling approach, which integrates signalling, metabolism and regulatory processes. For the first time, a comprehensive system-level model is constructed to capture signalling and metabolic cross-talks during tumour-immune interaction and regulatory constraints are incorporated by considering the time lag between them. The model analysis identifies novel features to enhance the immune response while suppressing tumour activity. Particularly, altering the exchange of succinate and oxaloacetate between glioma and macrophage enhances the pro-inflammatory response of immune cells. Inhibition of glutamate uptake in T-cells disrupts the antioxidant mechanism of glioma and reprograms metabolism. Metabolic reprogramming through adenosine monophosphate (AMP)-activated protein kinase (AMPK), coupled with glutamate uptake inhibition, was identified as the most impactful combination to restore T-cell function. A comprehensive understanding of metabolism and gene regulation represents a favourable approach to promote immune cell recovery from tumour dominance.

Kill rates by immune cells: Ratio-dependent, or mass action?

We describe a cell-based fixed-lattice model to simulate immune cell and tumor cell interaction involving MHC recognition, and FasL vs perforin lysis. We are motivated by open questions about the mechanisms behind observed kill rates of tumor cells by different types of effector cells. These mechanisms play a big role in the effectiveness of many cancer immunotherapies. The model is a stochastic cellular automaton on a hexagonal grid.

A novel computational tool for tracking cancer energy hijacking from immune cells.

Recent studies revealed a new biological process that malignant cancer cells hijack mitochondria from nearby T cells, providing another potential mechanism for immune evasion. We further confirmed this process at the single-cell genomic level through MERCI, a novel algorithm for tracking mitochondrial (MT) transfer. Applied to human cancer samples, MERCI identified a new cancer phenotype linked to MT hijacking, correlating with rapid tumour proliferation and poor patient survival. This discovery offers insights into the limitations of current cancer immunotherapies and suggests new therapeutic avenues targeting MT transfer to enhance cancer treatment efficacy.

Galectin-3's Complex Interactions in Pancreatic Ductal Adenocarcinoma: From Cellular Signaling to Therapeutic Potential.

Galectin-3 (Gal-3) plays a multifaceted role in the development, progression, and prognosis of pancreatic ductal adenocarcinoma (PDAC). This review offers a comprehensive examination of its expression in PDAC, its interaction with various immune cells, signaling pathways, effects on apoptosis, and therapeutic resistance. Additionally, the prognostic significance of serum levels of Gal-3 is discussed, providing insights into its potential utilization as a biomarker. Critical analysis is also extended to the inhibitors of Gal-3 and their potential therapeutic applications in PDAC, offering new avenues for targeted treatments. The intricate nature of Gal-3's role in PDAC reveals a complex landscape that demands a nuanced understanding for potential therapeutic interventions and monitoring.

Single-cell transcriptomic architecture and cellular communication circuits of parametrial adipose tissue in pregnant mice.

AIMS: The activity and interactions of cellular subpopulations in the adipose tissue microenvironment are critical for the coordination of local and systemic adaptation during pregnancy. With a particular interest in parametrial adipose tissue (PmAT), single-cell RNA-sequencing (scRNA-seq) was utilized to unveil the gestative cellular composition and functional shift. MATERIALS AND METHODS: To identify cell-type-enriched transcriptome profiles, a total of 18,074 cells in adipose tissue were studied. The cell populations were cataloged, and signaling crosstalk between adipocytes and other composition factions via soluble and membrane-bound factors were evaluated. KEY FINDINGS: A marked decline of pregnancy adipocytes and relative elevation of non-adipocyte fractions were observed. A subpopulation of adipocytes, Adipo_5, with unique properties in the response to estrogen and the embryonic processes involved in pregnancy, was defined. Interactome analysis revealed the potential contribution of PmAT to the establishment of maternal-fetal immune tolerance. During gestation, adipocytes shut down outgoing signaling, resulting in deterioration of the resistin-related incoming signaling network in B cells, which would therefore benefit tissue-specific maternal-fetal tolerance. Furthermore, a subpopulation of adipocytes, Aipo_2, was also considered to take part in a paradigm shift in the process of pregnancy-induced chemical stiffness-triggered vesicular remodeling via the THBS signaling pathway network. SIGNIFICANCE: These data-derived findings will encourage investigation into the role of pregnant PmTA in pregnancy-related immunological, hypertensive and metabolic disorders, with the ultimate goal of establishing preventive strategies to mitigate these pregnancy-related health challenges. This translational aspect of our work holds significant promise for improving maternal and fetal well-being.

Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution.

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

Exploring probiotic effector molecules and their mode of action in gut-immune interactions.

Probiotics, live microorganisms that confer health benefits when consumed in adequate amounts, have gained significant attention for their potential therapeutic applications. The beneficial effects of probiotics are believed to stem from their ability to enhance intestinal barrier function, inhibit pathogens, increase beneficial gut microbes, and modulate immune responses. However, clinical studies investigating the effectiveness of probiotics have yielded conflicting results, potentially due to the wide variety of probiotic species and strains used, the challenges in controlling the desired number of live microorganisms, and the complex interactions between bioactive substances within probiotics. Bacterial cell wall components, known as effector molecules, play a crucial role in mediating the interaction between probiotics and host receptors, leading to the activation of signaling pathways that contribute to the health-promoting effects. Previous reviews have extensively covered different probiotic effector molecules, highlighting their impact on immune homeostasis. Understanding how each probiotic component modulates immune activity at the molecular level may enable the prediction of immunological outcomes in future clinical studies. In this review, we present a comprehensive overview of the structural and immunological features of probiotic effector molecules, focusing primarily on Lactobacillus and Bifidobacterium. We also discuss current gaps and limitations in the field and propose directions for future research to enhance our understanding of probiotic-mediated immunomodulation.

A study on fractional tumor-immune interaction model related to lung cancer via generalized Laguerre polynomials.

BACKGROUND: Cancer, a complex and deadly health concern today, is characterized by forming potentially malignant tumors or cancer cells. The dynamic interaction between these cells and their environment is crucial to the disease. Mathematical models can enhance our understanding of these interactions, helping us predict disease progression and treatment strategies. METHODS: In this study, we develop a fractional tumor-immune interaction model specifically for lung cancer (FTIIM-LC). We present some definitions and significant results related to the Caputo operator. We employ the generalized Laguerre polynomials (GLPs) method to find the optimal solution for the FTIIM-LC model. We then conduct a numerical simulation and compare the results of our method with other techniques and real-world data. RESULTS: We propose a FTIIM-LC model in this paper. The approximate solution for the proposed model is derived using a series of expansions in a new set of polynomials, the GLPs. To streamline the process, we integrate Lagrange multipliers, GLPs, and operational matrices of fractional and ordinary derivatives. We conduct a numerical simulation to study the effects of varying fractional orders and achieve the expected theoretical results. CONCLUSION: The findings of this study demonstrate that the optimization methods used can effectively predict and analyze complex phenomena. This innovative approach can also be applied to other nonlinear differential equations, such as the fractional Klein-Gordon equation, fractional diffusion-wave equation, breast cancer model, and fractional optimal control problems.

Basophils in pruritic skin diseases.

Basophils are rare cells in the peripheral blood which have the capability to infiltrate into the skin. Invasion of basophils has been detected in pruritic skin diseases, including atopic dermatitis, bullous pemphigoid, chronic spontaneous urticaria and contact dermatitis. In the skin, basophils are important players of the inflammatory immune response, as they release Th2 cytokines, including interleukin (IL)-4 and IL-13, subsequently inducing the early activation of T-cells. Further, basophils release a multitude of mediators, such as histamine and IL-31, which both play an important role in the initiation of the pruritic response via activation of sensory nerves. Chronic pruritus significantly affects the quality of life and the working capability of patients, though its mechanisms are not fully elucidated yet. Since basophils and neurons share many receptors and channels, bidirectional interaction mechanisms, which drive the sensation of itch, are highlighted in this review.

In-vitro model to mimic T cell subset change in human PDAC organoid co-culture.

PURPOSE: Immunotherapies have largely failed as treatment options for pancreatic ductal adenocarcinoma (PDAC). In this field, clinical translational studies into personalized treatment are of fundamental importance. In our study, we model tumor-cell immune-cell interactions in a co-culture of primary human PDAC organoids and matched peripheral blood mononuclear cells (PBMCs). METHODS: Using flow cytometry, we evaluated changes in T cell subtypes upon co-culture of patient-derived PDAC organoids and matched PBMCs. RESULTS: After co-culturing PDAC organoids with PBMCs, we observed changes in CD4+, CD8+ and Treg cell populations. We observed favorable clinical outcome in patients whose PBMCs reacted to the co-culture with organoids. CONCLUSION: This experimental model allows to investigate interactions between patient derived PDAC organoids and their PBMCs. This co-culture system could serve as a preclinical platform to guide personalized therapeutic strategies in the future.

Caudal DMN neurons innervate the spleen and release CART peptide to regulate neuroimmune function.

BACKGROUND: Inflammation is a fundamental biological response to injury and infection, which if unregulated can contribute to the pathophysiology of many diseases. The vagus nerve, which primarily originates from the dorsal motor nucleus (DMN), plays an important role in rapidly dampening inflammation by regulating splenic function. However, direct vagal innervation of the spleen, which houses the majority of immune and inflammatory cells, has not been established. As an alternative to direct innervation, an anti-inflammatory reflex pathway has been proposed which involves the vagus nerve, the sympathetic celiac ganglion, and the neurotransmitter norepinephrine. Although sympathetic regulation of inflammation has been shown, the interaction of the vagus nerve and the celiac ganglia requires a unique interaction of parasympathetic and sympathetic inputs, making this putative mechanism of brain-spleen interaction controversial. BODY: As neuropeptides can be expressed at relatively high levels in neurons, we reasoned that DMN neuropeptide immunoreactivity could be used to determine their target innervation. Employing immunohistochemistry, subdiaphragmatic vagotomy, viral tract tracing, CRISPR-mediated knock-down, and functional assays, we show that cocaine and amphetamine-regulated transcript (CART) peptide-expressing projection neurons in the caudal DMN directly innervate the spleen. In response to lipopolysaccharide (LPS) stimulation, CART acts to reduce inflammation, an effect that can be augmented by intrasplenic administration of a synthetic CART peptide. These in vivo effects could be recapitulated in cultured splenocytes, suggesting that these cells express the as yet unidentified CART receptor(s). CONCLUSION: Our results provide evidence for direct connections between the caudal DMN and spleen. In addition to acetylcholine, these neurons express the neuropeptide CART that, once released, acts to suppress inflammation by acting directly upon splenocytes.

Methods for assessment of the tumour microenvironment and immune interactions in non-small cell lung cancer. A narrative review.

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer death worldwide. Immunotherapy with immune checkpoint inhibitors (ICI) has significantly improved outcomes in some patients, however 80-85% of patients receiving immunotherapy develop primary resistance, manifesting as a lack of response to therapy. Of those that do have an initial response, disease progression may occur due to acquired resistance. The make-up of the tumour microenvironment (TME) and the interaction between tumour infiltrating immune cells and cancer cells can have a large impact on the response to immunotherapy. Robust assessment of the TME with accurate and reproducible methods is vital to understanding mechanisms of immunotherapy resistance. In this paper we will review the evidence of several methodologies to assess the TME, including multiplex immunohistochemistry, imaging mass cytometry, flow cytometry, mass cytometry and RNA sequencing.

Regulatory T cells in peripheral tissue tolerance and diseases.

Maintenance of peripheral tolerance by CD4+Foxp3+ regulatory T cells (Tregs) is essential for regulating autoreactive T cells. The loss of function of Foxp3 leads to autoimmune disease in both animals and humans. An example is the rare, X-linked recessive disorder known as IPEX (Immune Dysregulation, Polyendocrinopathy, Enteropathy X-linked) syndrome. In more common human autoimmune diseases, defects in Treg function are accompanied with aberrant effector cytokines such as IFNγ. It has recently become appreciated that Tregs plays an important role in not only maintaining immune homeostasis but also in establishing the tissue microenvironment and homeostasis of non-lymphoid tissues. Tissue resident Tregs show profiles that are unique to their local environments which are composed of both immune and non-immune cells. Core tissue-residence gene signatures are shared across different tissue Tregs and are crucial to homeostatic regulation and maintaining the tissue Treg pool in a steady state. Through interaction with immunocytes and non-immunocytes, tissue Tregs exert a suppressive function via conventional ways involving contact dependent and independent processes. In addition, tissue resident Tregs communicate with other tissue resident cells which allows Tregs to adopt to their local microenvironment. These bidirectional interactions are dependent on the specific tissue environment. Here, we summarize the recent advancements of tissue Treg studies in both human and mice, and discuss the molecular mechanisms that maintain tissue homeostasis and prevent pathogenesis.

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data.

BACKGROUND: The Human Leukocyte Antigen (HLA) genes are a group of highly polymorphic genes that are located in the Major Histocompatibility Complex (MHC) region on chromosome 6. The HLA genotype affects the presentability of tumour antigens to the immune system. While knowledge of these genotypes is of utmost importance to study differences in immune responses between cancer patients, gold standard, PCR-derived genotypes are rarely available in large Next Generation Sequencing (NGS) datasets. Therefore, a variety of methods for in silico NGS-based HLA genotyping have been developed, bypassing the need to determine these genotypes with separate experiments. However, there is currently no consensus on the best performing tool. RESULTS: We evaluated 13 MHC class I and/or class II HLA callers that are currently available for free academic use and run on either Whole Exome Sequencing (WES) or RNA sequencing data. Computational resource requirements were highly variable between these tools. Three orthogonal approaches were used to evaluate the accuracy on several large publicly available datasets: a direct benchmark using PCR-derived gold standard HLA calls, a correlation analysis with population-based allele frequencies and an analysis of the concordance between the different tools. The highest MHC-I calling accuracies were found for Optitype (98.0%) and arcasHLA (99.4%) on WES and RNA sequencing data respectively, while for MHC-II HLA-HD was the most accurate tool for both data types (96.2% and 99.4% on WES and RNA data respectively). CONCLUSION: The optimal strategy for HLA genotyping from NGS data depends on the availability of either WES or RNA data, the size of the dataset and the available computational resources. If sufficient resources are available, we recommend Optitype and HLA-HD for MHC-I and MHC-II genotype calling respectively.