Sensitivity of CT-derived radiomic features to extraction libraries and gray-level discretization in the context of immune biomarker discovery.

Objectives: Radiomics can predict patient outcomes by automatically extracting a large number of features from medical images. This study is aimed to investigate the sensitivity of radiomics features extracted from 2 different pipelines, namely, Pyradiomics and RaCat, as well as the impact of gray-level discretization on the discovery of immune checkpoint inhibitors (ICIs) biomarkers.

Methods: A retrospective cohort of 164 non-small cell lung cancer patients administered with ICIs was used in this study.

CXCL13 Positive Cells Localization Predict Response to Anti-PD-1/PD-L1 in Pulmonary Non-Small Cell Carcinoma.

Immune checkpoint inhibitors (ICIs) have revolutionized non-small cell lung cancers (NSCLCs) treatment, but only 20-30% of patients benefit from these treatments. Currently, PD-L1 expression in tumor cells is the only clinically approved predictor of ICI response in lung cancer, but concerns arise due to its low negative and positive predictive value. Recent studies suggest that CXCL13+ T cells in the tumor microenvironment (TME) may be a good predictor of response.

The Cross-Scale Association between Pathomics and Radiomics Features in Immunotherapy-Treated NSCLC Patients: A Preliminary Study.

Background: Recent advances in cancer biomarker development have led to a surge of distinct data modalities, such as medical imaging and histopathology. To develop predictive immunotherapy biomarkers, these modalities are leveraged independently, despite their orthogonality. This study aims to explore the cross-scale association between radiological scans and digitalized pathology images for immunotherapy-treated non-small cell lung cancer (NSCLC) patients.

Multi-institutional prognostic modeling of survival outcomes in NSCLC patients treated with first-line immunotherapy using radiomics.

Background: Immune checkpoint inhibitors (ICIs) have emerged as one of the most promising first-line therapeutics in the management of non-small cell lung cancer (NSCLC). However, only a subset of these patients responds to ICIs, highlighting the clinical need to develop better predictive and prognostic biomarkers. This study will leverage pre-treatment imaging profiles to develop survival risk models for NSCLC patients treated with first-line immunotherapy.

Imaging-Based Biomarkers Predict Programmed Death-Ligand 1 and Survival Outcomes in Advanced NSCLC Treated With Nivolumab and Pembrolizumab: A Multi-Institutional Study.

Background: Although the immune checkpoint inhibitors, nivolumab and pembrolizumab, were found to be promising in patients with advanced NSCLC, some of them either do not respond or have recurrence after an initial response. It is still unclear who will benefit from these therapies, and, hence, there is an unmet clinical need to build robust biomarkers.

Methods: Patients with advanced NSCLC (N = 323) who were treated with pembrolizumab or nivolumab were retrospectively identified from two institutions.

A Radiomics-Clinical Model Predicts Overall Survival of Non-Small Cell Lung Cancer Patients Treated with Immunotherapy: A Multicenter Study.

Background: Immune checkpoint inhibitors (ICIs) are a great breakthrough in cancer treatments and provide improved long-term survival in a subset of non-small cell lung cancer (NSCLC) patients. However, prognostic and predictive biomarkers of immunotherapy still remain an unmet clinical need. In this work, we aim to leverage imaging data and clinical variables to develop survival risk models among advanced NSCLC patients treated with immunotherapy.

Generalization optimizing machine learning to improve CT scan radiomics and assess immune checkpoint inhibitors' response in non-small cell lung cancer: a multicenter cohort study.

Background: Recent developments in artificial intelligence suggest that radiomics may represent a promising non-invasive biomarker to predict response to immune checkpoint inhibitors (ICIs). Nevertheless, validation of radiomics algorithms in independent cohorts remains a challenge due to variations in image acquisition and reconstruction. Using radiomics, we investigated the importance of scan normalization as part of a broader machine learning framework to enable model external generalizability to predict ICI response in non-small cell lung cancer (NSCLC) patients across different centers.

Radiomics approaches to predict PD-L1 and PFS in advanced non-small cell lung patients treated with immunotherapy: a multi-institutional study.

With the increasing use of immune checkpoint inhibitors (ICIs), there is an urgent need to identify biomarkers to stratify responders and non-responders using programmed death-ligand (PD-L1) expression, and to predict patient-specific outcomes such as progression free survival (PFS). The current study is aimed to determine the feasibility of building imaging-based predictive biomarkers for PD-L1 and PFS through systematically evaluating a combination of several machine learning algorithms with different feature selection methods. A retrospective, multicenter study of 385 advanced NSCLC patients amenable to ICIs was undertaken in two academic centers.

Single-cell spatial landscape of immunotherapy response reveals mechanisms of CXCL13 enhanced antitumor immunity.

Background: Immunotherapy has revolutionized clinical outcomes for patients suffering from lung cancer, yet relatively few patients sustain long-term durable responses. Recent studies have demonstrated that the tumor immune microenvironment fosters tumorous heterogeneity and mediates both disease progression and response to immune checkpoint inhibitors (ICI). As such, there is an unmet need to elucidate the spatially defined single-cell landscape of the lung cancer microenvironment to understand the mechanisms of disease progression and identify biomarkers of response to ICI.

Dissecting host cell death programs in the pathogenesis of influenza.

Influenza A virus (IAV) is a pulmonary pathogen, responsible for significant yearly morbidity and mortality. Due to the absence of highly effective antiviral therapies and vaccine, as well as the constant threat of an emerging pandemic strain, there is considerable need to better understand the host-pathogen interactions and the factors that dictate a protective versus detrimental immune response to IAV. Even though evidence of IAV-induced cell death in human pulmonary epithelial and immune cells has been observed for almost a century, very little is known about the consequences of cell death on viral pathogenesis.

Hypertriglyceridemic Waist: A Simple Marker of High-Risk Atherosclerosis Features Associated With Excess Visceral Adiposity/Ectopic Fat.

Background: Subclinical atherosclerosis identification remains challenging; abdominal visceral adiposity may improve risk stratification beyond traditional cardiovascular risk factors. Hypertriglyceridemic waist, a visceral adiposity marker combining elevated triglycerides (≥2 mmol/L) and waist circumference (≥90 cm), has been related to carotid atherosclerosis, although associations with high-risk features, including lipid-rich necrotic core (LRNC), remain unknown. We tested the hypothesis that hypertriglyceridemic waist is an independent marker of high-risk atherosclerosis features.

RIPK3 interacts with MAVS to regulate type I IFN-mediated immunity to Influenza A virus infection.

The type I interferon pathway plays a critical role in both host defense and tolerance against viral infection and thus requires refined regulatory mechanisms. RIPK3-mediated necroptosis has been shown to be involved in anti-viral immunity. However, the exact role of RIPK3 in immunity to Influenza A Virus (IAV) is poorly understood.

The energy sensor AMPK regulates T cell metabolic adaptation and effector responses in vivo.

Naive T cells undergo metabolic reprogramming to support the increased energetic and biosynthetic demands of effector T cell function. However, how nutrient availability influences T cell metabolism and function remains poorly understood. Here we report plasticity in effector T cell metabolism in response to changing nutrient availability.

Targeting eicosanoid pathways in the development of novel anti-influenza drugs.

The constant new emergence of life-threatening human respiratory viral pathogens presents new challenges to clinicians who are left with no available therapeutic interventions. Highly pathogenic strains of influenza A virus (IAV) share an enhanced capacity to propagate to the lower airways and paralyze alveolar macrophage antiviral capacity in order to replicate efficiently and cause pathologic inflammation. Following a century of using NSAIDs for the management of influenza symptoms, a number of studies have interrogated their function in the host response to IAV infection.

NLRX1 prevents mitochondrial induced apoptosis and enhances macrophage antiviral immunity by interacting with influenza virus PB1-F2 protein.

To subvert host immunity, influenza A virus (IAV) induces early apoptosis in innate immune cells by disrupting mitochondria membrane potential via its polymerase basic protein 1-frame 2 (PB1-F2) accessory protein. Whether immune cells have mechanisms to counteract PB1-F2-mediated apoptosis is currently unknown. Herein, we define that the host mitochondrial protein nucleotide-binding oligomerization domain-like receptor (NLR)X1 binds to viral protein PB1-F2, preventing IAV-induced macrophage apoptosis and promoting both macrophage survival and type I IFN signaling.

Targeted prostaglandin E2 inhibition enhances antiviral immunity through induction of type I interferon and apoptosis in macrophages.

Aspirin gained tremendous popularity during the 1918 Spanish Influenza virus pandemic, 50 years prior to the demonstration of their inhibitory action on prostaglandins. Here, we show that during influenza A virus (IAV) infection, prostaglandin E2 (PGE2) was upregulated, which led to the inhibition of type I interferon (IFN) production and apoptosis in macrophages, thereby causing an increase in virus replication. This inhibitory role of PGE2 was not limited to innate immunity, because both antigen presentation and T cell mediated immunity were also suppressed.

Muramyl dipeptide induces NOD2-dependent Ly6C(high) monocyte recruitment to the lungs and protects against influenza virus infection.

Bacterial peptidoglycan-derived muramyl dipeptide (MDP) and derivatives have long-recognized antiviral properties but their mechanism of action remains unclear. In recent years, the pattern-recognition receptor NOD2 has been shown to mediate innate responses to MDP. Here, we show that MDP treatment of mice infected with Influenza A virus (IAV) significantly reduces mortality, viral load and pulmonary inflammation in a NOD2-dependent manner.

Involvement of TLR2 in recognition of acute gammaherpesvirus-68 infection.

Background: Toll-like receptors (TLRs) play a crucial role in the activation of innate immunity in response to many viruses. We previously reported the implication of TLR2 in the recognition of Epstein-Barr virus (EBV) by human monocytes. Because murine gammaherpesvirus-68 (MHV-68) is a useful model to study human gammaherpesvirus pathogenesis in vivo, we evaluated the importance of mouse TLR2 in the recognition of MHV-68.

Epstein-Barr virus interferes with the amplification of IFNalpha secretion by activating suppressor of cytokine signaling 3 in primary human monocytes.

Background: Epstein-Barr virus is recognized to cause lymphoproliferative disorders and is also associated with cancer. Evidence suggests that monocytes are likely to be involved in EBV pathogenesis, especially due to a number of cellular functions altered in EBV-infected monocytes, a process that may affect efficient host defense. Because type I interferons (IFNs) are crucial mediators of host defense against viruses, we investigated the effect of EBV infection on the IFNalpha pathway in primary human monocytes.

Increased NOD2-mediated recognition of N-glycolyl muramyl dipeptide.

Peptidoglycan-derived muramyl dipeptide (MDP) activates innate immunity via the host sensor NOD2. Although MDP is N-acetylated in most bacteria, mycobacteria and related Actinomycetes convert their MDP to an N-glycolylated form through the action of N-acetyl muramic acid hydroxylase (NamH). We used a combination of bacterial genetics and synthetic chemistry to investigate whether N-glycolylation of MDP alters NOD2-mediated immunity.

NOD2, RIP2 and IRF5 play a critical role in the type I interferon response to Mycobacterium tuberculosis.

While the recognition of microbial infection often occurs at the cell surface via Toll-like receptors, the cytosol of the cell is also under surveillance for microbial products that breach the cell membrane. An important outcome of cytosolic recognition is the induction of IFNalpha and IFNbeta, which are critical mediators of immunity against both bacteria and viruses. Like many intracellular pathogens, a significant fraction of the transcriptional response to Mycobacterium tuberculosis infection depends on these type I interferons, but the recognition pathways responsible remain elusive.