Background: A substantial proportion of patients with non-small cell lung cancer (NSCLC) derive limited clinical benefit from immunotherapy. Monitoring of peripheral blood immune markers (PBIMs) may emerge as a useful tool to predict treatment outcomes with immune checkpoint inhibitors (ICIs). Patients/Methods: We prospectively measured several PBIMs in a PD-L1 high (TPS ≥ 50%) NSCLC cohort of patients treated with first-line pembrolizumab monotherapy. Kinetics over the first year of treatment were assessed at baseline (T0) and at 21 days (T1), 3 months (T2), 6 months (T3) and at 1 year (T4) post-treatment initiation. Associations with clinical outcomes were explored after a 2-year follow-up period. Results: In total, 31 patients with PD-L1 high locally advanced or metastatic NSCLC were prospectively enrolled. Over the first year of treatment, levels of CRP, IL-17α, IL-6, and IL-8 were significantly decreased. Early kinetics analysis showed significant decrease in total leukocytes, neutrophils, CRP, and MIP-3α/CCL20, as well as significant transient elevation of ITAC/CXCL11, IL-1β, IL-7, and TNFα, during the first 3 months of treatment. Early percent changes (Δ% at T1 and at T2) of ‘low’ vs. ‘high’ pretreatment levels showed significant differences for LDH, ITAC/CXCL11, GM-CSF, MIP-1α/CCL3, IL-2, IL-4, IL-5, and sPD-L1. Longitudinal analysis, stratified per responders and for pre-progression fluctuations, did not reveal significant findings. Among markers with acceptable discriminative performance, higher baseline CRP, complement C4, and IL-6 levels were associated with poorer clinical outcomes. In multivariable analysis, only C4 retained independent prognostic significance; however, integration of these PBIMs into composite indices improved prognostic performance. Conclusions: In this prospective study, longitudinal monitoring of PBIMs provided descriptive insights into immune and inflammatory dynamics during pembrolizumab treatment; however, no significant associations were observed between in-treatment biomarker kinetics and clinical outcomes. In exploratory analyses, baseline CRP, complement C4, and IL-6 levels were associated with clinical outcomes, and their integration into composite indices improved prognostic performance. These findings suggest that specific baseline PBIMs may carry prognostic relevance, while the role of in-treatment monitoring remains to be further clarified in larger prospective studies.

Severe respiratory infections such as COVID-19 are characterized by excessive inflammation leading to the development of pneumonia and acute respiratory distress syndrome. Bioactive lipid mediators (LMs) derived from ω6 and ω3 polyunsaturated fatty acids are central to the regulation of inflammation, controlling both its initiation and resolution. Still, their role in viral infections remains underexplored. By employing a holistic approach involving the analysis of white blood cell transcriptomes, targeted lipidomics, cytokine and immune cell profiling, we now show that LM patterns around hospital admission are profoundly altered in COVID-19, correlate with inflammatory responses, and stratify patients according to disease severity. Central to this are CYP450-derived LMs, such as 20-HETE, and lipoxygenase- or nonenzymatic-associated LMs such as 15-HETE, both exhibiting vasoactive function, along with lipid peroxidation metabolites such as 10-HDOHE. Among them, increased 20-HETE appears to be a promising prognostic biomarker for ICU admission and a potential therapeutic target for severe COVID-19 disease. Our study emphasizes the importance of LM patterns in COVID-19 pathophysiology and sheds light into the broader immune mechanisms beyond cytokines driving viral pneumonia in humans.

Autoantibodies neutralizing type-I interferons (AAN-I-IFNs) emerge as global, common, and strong determinants of a growing number of severe viral diseases. We report that AAN-I-IFNs+ patients with life-threatening COVID-19 pneumonia harbor circulating type-I IFN-specific B cells indistinguishable from patients bearing T cell tolerance defects of genetic origin. This autoimmune response mobilizes a highly diverse and stable circulating B cell response that is detected prior to severe viral infection and acquires high affinity and neutralization potential to type-I IFNs through extended somatic hypermutation. X-ray crystallography and AlphaFold3 structural analysis of hundreds of patient-derived monoclonal antibodies reveals the extended breadth of this response, targeting three major B cell epitopes covering all facets of type-I IFNs. These findings support a model in which a germinal-center-derived memory B cell response directed against type-I IFNs is established before severe viral infection, providing a core mechanism linking T cell tolerance defect to pathogenic AAN-I-IFNs underlying severe viral diseases.

Five years ago, we launched the COVID Human Genetic Effort. Our goal was to explain the clinical variability among SARS-CoV-2-exposed individuals by searching for monogenic inborn errors of immunity (IEI) and their phenocopies. We deciphered the pathogenesis of critical COVID-19 pneumonia and multisystemic inflammatory syndrome in children (MIS-C) in ~15% and 2% of cases, respectively, thereby revealing general mechanisms of severe disease. We also defined neuro-COVID-19 genetically and immunologically in one child, while we delineated the immunological mechanisms of COVID-toes in healthy children and young adults, paving the way for their genetic study. Understanding the human genetic and immunological basis of resistance to SARS-CoV-2 infection, long COVID, and myocarditis post mRNA vaccination, has been challenging and investigations remain ongoing. This work highlights the power of patient-based basic research and large-scale international collaborative efforts to discover human genetic and immunological drivers of infectious disease phenotypes, with implications for the timely development of new medical strategies before the next pandemic arrives.

Andreakos et al. report the progress of the COVID Human Genetic Effort since its launch 5 years ago, with the aim to understand clinical variability, from resistance to severe outcomes, among individuals exposed to SARS-CoV-2. Their work revealed key mechanisms of pneumonia, MIS-C, and other manifestations, informing diagnostics, therapeutics, and preparedness for future pandemics.

Introduction:Giant Cell Arteritis (GCA) and Polymyalgia Rheumatica (PMR) are autoimmune/autoinflammatory disorders presenting as acute inflammatory responses and are highly responsive to steroids. In this report, we aim to decipher the immune landscape including immune cell subpopulations, plasma cytokines, and small lipid mediators (LMs) at the very early stages of steroid treatment initiation in 4 distinct time points at: 0h (T1), 48h (T2), 96h (T3), and 24 weeks (T4). Patients and methods:Serum, plasma and peripheral blood mononuclear cells (PBMCs) were collected prospectively from 8 GCA and 6 PMR newly diagnosed patients. Sixteen healthy individuals served as controls (HC). Deep immunophenotyping by CyTOF was performed in PBMCs at T1-T3. A multiplex Luminex assay measured serum levels of 21 cytokines at T1 and T3. Levels of lipid mediators (LMs) were evaluated at T1, T3 and T4 with the LC-MS/MS method. Results:Total CD8+ T cells and DCs were decreased within 48-96 hours, following steroid treatment, while B-cells were increased at 48 hours. Further analysis of immune subpopulations containing the major cell types revealed different frequencies of distinct CD8+, CD4+, DCs, and B cell subtypes. Out of 21 cytokines/chemokines evaluated, only ITAC levels were decreased at T3. The ratio of pro/anti-inflammatory LMs was high at T1 in patients with either PMR or GCA. However, 6 months after steroid treatment it returned to normal in PMR patients, but remained high in GCA patients, providing the only discriminatory element between the two diseases. Conclusion:The rapid clinical improvement of GCA and PMR patients, following steroid treatment, is associated with immune cell type alterations, but it is poorly associated with plasma cytokine levels. Small lipid mediators can differentiate GCA and PMR patients. The persistently elevated levels of pro-inflammatory LMs might be related to the underlying residual tissue inflammation described in GCA. These preliminary results suggest that further studies in a larger patient cohort are required to validate these findings.

While most respiratory viral infections resolve with little harm to the host, severe symptoms arise when infection triggers an aberrant inflammatory response that damages lung tissue. Host regulators of virally induced lung inflammation have not been well defined. Here, we show that enrichment for sialylated, but not asialylated immunoglobulin G (IgG), predicted mild influenza disease in humans and was broadly protective against heterologous influenza viruses in a murine challenge model. Mechanistic studies show that sialylated IgG mediated this protection by inducing the transcription factor repressor element-1 silencing transcription factor (REST), which repressed nuclear factor κB (NF-κB)-driven responses, preventing severe lung inflammation and protecting lung function during influenza infection. Therapeutic administration of a recombinant, sialylated Fc molecule in clinical development similarly activated REST and protected against severe influenza disease, demonstrating that this pathway could be clinically harnessed. Overall, induction of REST through sialylated IgG signaling is a strategy to limit inflammatory disease sequelae in infections caused by antigenically distinct influenza strains.

We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-α2 in 10 patients: IFN-α2 only in three, IFN-α2 plus IFN-ω in five, and IFN-α2, IFN-ω plus IFN-β in two; IFN-ω only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-α2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-ω in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-α2 only (OR [95% CI] = 67.6 [5.7–9,196.6]) than for auto-Abs neutralizing IFN-ω only (OR [95% CI] = 2.6 [1.2–5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6–35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1–9.6]) of IFN-ω and/or IFN-α2.

In the majority of downstream analysis pipelines for single-cell RNA sequencing (scRNA-seq), techniques like dimensionality reduction and feature selection are employed to address the problem of high-dimensional nature of the data. These approaches involve mapping the data onto a lower-dimensional space, eliminating less informative genes, and pinpointing the most pertinent features. This process ultimately leads to a reduction in the number of dimensions used for downstream analysis, which in turn speeds up the computation of large-scale scRNA-seq data. Most approaches are directed to isolate from biological background the genes characterizing different cells and or the condition under study by establishing lists of differentially expressed or coexpressed genes. Herein, we present scRNA-Explorer an open-source online tool for simplified and rapid scRNA-seq analysis designed with the end user in mind. scRNA-Explorer utilizes: i) Filtering out uninformative cells in an interactive manner via a web interface, ii) Gene correlation analysis coupled with an extra step of evaluating the biological importance of these correlations, and iii) Gene enrichment analysis of correlated genes in order to find gene implication in specific functions. We developed a pipeline to address the above problem. The scRNA-Explorer pipeline allows users to interrogate in an interactive manner scRNA-sequencing data sets to explore via gene expression correlations possible function(s) of a gene of interest. scRNA-Explorer can be accessed at https://bioinformatics.med.uoc.gr/shinyapps/app/scrnaexplorer

Giant cell arteritis (GCA) is an autoimmune disease affecting large vessels in patients over 50 years old. It is an exemplary model of a classic inflammatory disorder with IL-6 playing the leading role. The main comorbidities that may appear acutely or chronically are vascular occlusion leading to blindness and thoracic aorta aneurysm formation, respectively. The tissue inflammatory bulk is expressed as acute or chronic delayed-type hypersensitivity reactions, the latter being apparent by giant cell formation. The activated monocytes/macrophages are associated with pronounced Th1 and Th17 responses. B-cells and neutrophils also participate in the inflammatory lesion. However, the exact order of appearance and mechanistic interactions between cells are hindered by the lack of cellular and molecular information from early disease stages and accurate experimental models. Recently, senescent cells and neutrophil extracellular traps have been described in tissue lesions. These structures can remain in tissues for a prolonged period, potentially favoring inflammatory responses and tissue remodeling. In this review, current advances in GCA pathogenesis are discussed in different inflammatory phases. Through the description of these—often overlapping—phases, cells, molecules, and small lipid mediators with pathogenetic potential are described.

Lambda interferons (IFNλs), also termed type III interferons (IFNs) or interleukins-28/29, have been in the shadow of type I IFNs for a long time. Their common induction mechanisms and signalling cascades with type I IFNs have made difficult the unwinding of their unique nonredundant functions. However, this is now changing with mounting evidence supporting a major role of IFNλs as a specialized antiviral defense system in the body, mediating protection at mucosal barrier surfaces while limiting immunopathology.Here, we review the latest progress on the complex activities of IFNλs in the respiratory tract, focusing on their multiple effects in IFNλ receptor-expressing cells, the modulation of innate and adaptive immune responses in the context of infections and respiratory diseases, and their similarities and differences with type I IFNs. We also discuss their potential in therapeutic applications and the most recent developments in that direction.

The process of navigating through the landscape of biomedical literature and performing searches or combining them with bioinformatics analyses can be daunting, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related repositories. Herein, we present BioTextQuest v2.0, a tool for biomedical literature mining.BioTextQuest v2.0 is an open-source online web portal for document clustering based on sets of selected biomedical terms, offering efficient management of information derived from PubMed abstracts. Employing established machine learning algorithms, the tool facilitates document clustering while allowing users to customize the analysis by selecting terms of interest. BioTextQuest v2.0 streamlines the process of uncovering valuable insights from biomedical research articles, serving as an agent that connects the identification of key terms like genes/proteins, diseases, chemicals, Gene Ontology (GO) terms, functions, and others through named entity recognition, and their application in biological research.Instead of manually sifting through articles, researchers can enter their PubMed-like query and receive extracted information in two user-friendly formats, tables and word clouds, simplifying the comprehension of key findings. The latest update of BioTextQuest leverages the EXTRACT named entity recognition tagger, enhancing its ability to pinpoint various biological entities within text.BioTextQuest v2.0 acts as a research assistant, significantly reducing the time and effort required for researchers to identify and present relevant information from the biomedical literature.

The importance of macrophages in adipose tissue (AT) homeostasis and inflammation is well established. However, the potential cues that regulate their function remain incompletely understood. To bridge this important gap, we sought to characterize novel pathways involved using a mouse model of diet-induced obesity. By performing transcriptomics analysis of AT macrophages (ATMs), we found that late-stage ATMs from high-fat diet mice presented with perturbed Notch signaling accompanied by robust proinflammatory and metabolic changes. To explore the hypothesis that the deregulated Notch pathway contributes to the development of AT inflammation and diet-induced obesity, we employed a genetic approach to abrogate myeloid Notch1 and Notch2 receptors. Our results revealed that the combined loss of Notch1 and Notch2 worsened obesity-related metabolic dysregulation. Body and AT weight gain was higher, blood glucose levels increased and metabolic parameters were substantially worsened in deficient mice fed high-fat diet. Moreover, serum insulin and leptin were elevated as were triglycerides. Molecular analysis of ATMs showed that deletion of Notch receptors escalated inflammation through the induction of an M1-like pro-inflammatory phenotype. Our findings thus support a protective role of myeloid Notch signaling in adipose tissue inflammation and metabolic dysregulation.

Apolipoprotein E-knockout (Apoe-/-) mice constitute the most widely employed animal model of atherosclerosis. Deletion of Apoe induces profound hypercholesterolemia and promotes the development of atherosclerosis. However, despite its widespread use, the Apoe-/- mouse model remains incompletely characterized, especially at late time points and advanced disease stages. Thus, it is unclear how late atherosclerotic plaques compare to earlier ones in terms of lipid deposition, calcification, macrophage accumulation, smooth muscle cell presence, or plaque necrosis. Additionally, it is unknown how cardiac function and hemodynamic parameters are affected at late disease stages. Here, we used a comprehensive analysis based on histology, fluorescence microscopy, and Doppler ultrasonography to show that in normal chow diet-fed Apoe-/- mice, atherosclerotic lesions at the level of the aortic valve evolve from a more cellular macrophage-rich phenotype at 26 weeks to an acellular, lipid-rich, and more necrotic phenotype at 52 weeks of age, also marked by enhanced lipid deposition and calcification. Coronary artery atherosclerotic lesions are sparse at 26 weeks but ubiquitous and extensive at 52 weeks; yet, left ventricular function was not significantly affected. These findings demonstrate that atherosclerosis in Apoe-/- mice is a highly dynamic process, with atherosclerotic plaques evolving over time. At late disease stages, histopathological characteristics of increased plaque vulnerability predominate in combination with frequent and extensive coronary artery lesions, which nevertheless may not necessarily result in impaired cardiac function.

Severe COVID-19 is characterized by excessive inflammation leading to the development of pneumonia and acute respiratory distress syndrome. Bioactive lipid mediators (LMs) derived from ω6 and ω3 polyunsaturated fatty acids are central to the regulation of inflammation, controlling both its initiation and resolution. Still, their role in COVID-19 remains underexplored. By employing a holistic approach involving the analysis of white blood cell transcriptomes, targeted lipidomics, cytokine and immune cell profiling, across the spectrum of disease severity groups, we now show that LM networks are profoundly altered in COVID-19, correlate with inflammatory patterns, and stratify patients according to disease severity. Central to this are CYP450-derived LMs such as 20-HETE, lipid peroxidation metabolites such as iPF2a-VI, and lipoxygenase-derived LMs such as 12-HETE, all of which are major vasoactive mediators of inflammation. Among them, 20-HETE appears to be a promising prognostic biomarker for ICU admission and a potential therapeutic target for severe COVID-19 disease. Our study thus underscores the significance of LM networks in COVID-19 pathophysiology and sheds light into the broader mechanisms driving viral pneumonia in humans. ### Competing Interest Statement The authors have declared no competing interest.

The continuous evolution of SARS-CoV-2 and possible future pandemics have risen concerns relevant to the effectiveness of the vaccines which are currently available. To this direction, new computational tools based on artificial intelligence (AI) and machine learning (ML) methods are incorporated, focusing on revealing hidden patterns and behaviors from, oftentimes, a great number of parameters that may affect (or not) the evolution of the pandemic. In this study, we developed and validated prediction models of COVID-19 in-hospital mortality among vaccinated patients by applying Symbolic Regression (SR)-based, ML algorithms. Considering the key role of cytokines and chemokines in the modulation of the immune response, we employed a dataset combining several of the aforementioned biomolecules with commonly used laboratory markers as well as demographic and clinical data. Starting from a forty-four features dataset, we managed to restrict the total number of employed variables between 6–8 and ended up in four possible equations accurately predicting data behavior. The feature ‘Days with symptoms from onset until admission’ appeared in every equation, while interleukins (ILs)-17A and -6 in 3 out of 4 models. The parameters ‘IL-6’ and ‘IL-17A’, wherever combined led in a different survival effect on patients, compared to those cases where they solely appeared in an equation. Our method is presented for the first time and aims to be part of a broader computational and statistical framework that could aid in medical decision-making applications.

Type I and type III interferons (IFNs) constitute a key antiviral defense systems of the body, inducing viral resistance to cells and mediating diverse innate and adaptive immune functions. Defective type I and type III IFN responses have recently emerged as the 'Achilles heel' in COVID-19, with such patients developing severe disease and exhibiting a high risk for critical pneumonia and death. Here, we review the biology of type I and type III IFNs, their similarities and important functional differences, and their roles in SARS-CoV-2 infection. We also appraise the various mechanisms proposed to drive defective IFN responses in COVID-19 with particular emphasis to the ability of SARS-CoV-2 to suppress IFN production and activities, the genetic factors involved and the presence of autoantibodies neutralizing IFNs and accounting for a large proportion of individuals with severe COVID-19. Finally, we discuss the long history of the type I IFN therapeutics for the treatment of viral diseases, cancer and multiple sclerosis, the various efforts to use them in respiratory infections, and the newly emerging type III IFN therapeutics, with emphasis to the more recent studies on COVID-19 and their potential use as broad spectrum antivirals for future epidemics or pandemics.