Auranofin (AF) is an FDA-approved antirheumatic drug with anticancer properties that acts as a thioredoxin reductase 1 (TrxR) inhibitor. The exact mechanisms through which AF targets cancer cells ...remain elusive. To shed light on the mode of action, this study provides an in-depth analysis on the molecular mechanisms and immunogenicity of AF-mediated cytotoxicity in the non-small cell lung cancer (NSCLC) cell line NCI–H1299 (p53 Null) and its two isogenic derivates with mutant p53 R175H or R273H accumulation.
TrxR is highly expressed in a panel of 72 NSCLC patients, making it a valid druggable target in NSCLC for AF. The presence of mutant p53 overexpression was identified as an important sensitizer for AF in (isogenic) NSCLC cells as it was correlated with reduced thioredoxin (Trx) levels in vitro. Transcriptome analysis revealed dysregulation of genes involved in oxidative stress response, DNA damage, granzyme A (GZMA) signaling and ferroptosis. Although functionally AF appeared a potent inhibitor of GPX4 in all NCI–H1299 cell lines, the induction of lipid peroxidation and consequently ferroptosis was limited to the p53 R273H expressing cells. In the p53 R175H cells, AF mainly induced large-scale DNA damage and replication stress, leading to the induction of apoptotic cell death rather than ferroptosis. Importantly, all cell death types were immunogenic since the release of danger signals (ecto-calreticulin, ATP and HMGB1) and dendritic cell maturation occurred irrespective of (mutant) p53 expression. Finally, we show that AF sensitized cancer cells to caspase-independent natural killer cell-mediated killing by downregulation of several key targets of GZMA.
Our data provides novel insights on AF as a potent, clinically available, off-patent cancer drug by targeting mutant p53 cancer cells through distinct cell death mechanisms (apoptosis and ferroptosis). In addition, AF improves the innate immune response at both cytostatic (natural killer cell-mediated killing) and cytotoxic concentrations (dendritic cell maturation).
Display omitted
As the hepatitis B virus is widely spread and responsible for considerable morbidity and mortality, WHO recommends vaccination from infancy to reduce acute infection and chronic carriers. However, ...current subunit vaccines are not 100% efficacious and leave 5–10% of recipients unprotected.
To evaluate immune responses after Engerix-B vaccination, we determined, using mRNA-sequencing, whole blood early gene expression signatures before, at day 3 and day 7 after the first dose and correlated this with the resulting antibody titer after two vaccine doses.
Our results indicate that immune related genes are differentially expressed in responders mostly at day 3 and in non-responders mostly at day 7. The most remarkable difference between responders and non-responders were the differentially expressed genes before vaccination. The granulin precursor gene (GRN) was significantly downregulated in responders while upregulated in non-responders at day 0. Furthermore, absolute granulocytes numbers were significantly higher in non-responders at day 0.
The non-responders already showed an activated state of the immune system before vaccination. Furthermore, after vaccination, they exhibited a delayed and partial immune response in comparison to the responders. Our data may indicate that the baseline and untriggered immune system can influence the response upon hepatitis B vaccination.
Antigen recognition through the T cell receptor (TCR) αβ heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naïve T cells with high specificity to ...expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts. In this study, we use high-throughput sequencing of memory CD4 TCRβ repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCRβ sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination.
The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and ...controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.
Display omitted
•T cell phenotypes did not significantly differ between HZ patients and controls•CD4+ TCR diversity against VZV gE and IE63 after culture was broader in controls•T cell activation pathways after VZV peptide stimulation were lower in HZ patients•TCRs from HZ patients co-clustered more often together than TCRs from controls
Boeren et al. demonstrate that susceptibility for shingles, caused by varicella-zoster virus (VZV) reactivation, correlates with reduced T cell receptor (TCR) diversity against several VZV proteins. Their results indicate that reduced T cell activation correlates with reduced affinity between VZV proteins and the VZV-specific TCR repertoire in shingles patients.
The immune system acts as an intricate apparatus that is dedicated to mounting a defense and ensures host survival from microbial threats. To engage this faceted immune response and provide ...protection against infectious diseases, vaccinations are a critical tool to be developed. However, vaccine responses are governed by levels that, when interrogated, separately only explain a fraction of the immune reaction. To address this knowledge gap, we conducted a feasibility study to determine if multi-view modeling could aid in gaining actionable insights on response markers shared across populations, capture the immune system's diversity, and disentangle confounders. We thus sought to assess this multi-view modeling capacity on the responsiveness to the Hepatitis B virus (HBV) vaccination. Seroconversion to vaccine-induced antibodies against the HBV surface antigen (anti-HBs) in early converters (
= 21; <2 months) and late converters (
= 9; <6 months) and was defined based on the anti-HBs titers (>10IU/L). The multi-view data encompassed bulk RNA-seq, CD4+ T-cell parameters (including T-cell receptor data), flow cytometry data, and clinical metadata (including age and gender). The modeling included testing single-view and multi-view joint dimensionality reductions. Multi-view joint dimensionality reduction outperformed single-view methods in terms of the area under the curve and balanced accuracy, confirming the increase in predictive power to be gained. The interpretation of these findings showed that age, gender, inflammation-related gene sets, and pre-existing vaccine-specific T-cells could be associated with vaccination responsiveness. This multi-view dimensionality reduction approach complements clinical seroconversion and all single modalities. Importantly, this modeling could identify what features could predict HBV vaccine response. This methodology could be extended to other vaccination trials to identify the key features regulating responsiveness.
Despite the general agreement on the significance of T cells during SARS-CoV-2 infection, the clinical impact of specific and cross-reactive T-cell responses remains uncertain. Understanding this ...aspect could provide insights for adjusting vaccines and maintaining robust long-term protection against continuously emerging variants. To characterize CD8+ T-cell response to SARS-CoV-2 epitopes unique to the virus (SC2-unique) or shared with other coronaviruses (CoV-common), we trained a large number of T-cell receptor (TCR) - epitope recognition models for MHC-I-presented SARS-CoV-2 epitopes from publicly available data. These models were then applied to longitudinal CD8+ TCR repertoires from critical and non-critical COVID-19 patients. In spite of comparable initial CoV-common TCR repertoire depth and CD8+ T-cell depletion, the temporal dynamics of SC2-unique TCRs differed depending on the disease severity. Specifically, while non-critical patients demonstrated a large and diverse SC2-unique TCR repertoire by the second week of the disease, critical patients did not. Furthermore, only non-critical patients exhibited redundancy in the CD8+ T-cell response to both groups of epitopes, SC2-unique and CoV-common. These findings indicate a valuable contribution of the SC2-unique CD8+ TCR repertoires. Therefore, a combination of specific and cross-reactive CD8+ T-cell responses may offer a stronger clinical advantage. Besides tracking the specific and cross-reactive SARS-CoV-2 CD8+ T cells in any TCR repertoire, our analytical framework can be expanded to more epitopes and assist in the assessment and monitoring of CD8+ T-cell response to other infections.
Meningitis can be caused by several viruses and bacteria. Identifying the causative pathogen as quickly as possible is crucial to initiate the most optimal therapy, as acute bacterial meningitis is ...associated with a significant morbidity and mortality. Bacterial meningitis requires antibiotics, as opposed to enteroviral meningitis, which only requires supportive therapy. Clinical presentation is usually not sufficient to differentiate between viral and bacterial meningitis, thereby necessitating cerebrospinal fluid (CSF) analysis by PCR and/or time-consuming bacterial cultures. However, collecting CSF in children is not always feasible and a rather invasive procedure.
In 12 Belgian hospitals, we obtained acute blood samples from children with signs of meningitis (49 viral and 7 bacterial cases) (aged between 3 months and 16 years). After pathogen confirmation on CSF, the patient was asked to give a convalescent sample after recovery. 3' mRNA sequencing was performed to determine differentially expressed genes (DEGs) to create a host transcriptomic profile.
Enteroviral meningitis cases displayed the largest upregulated fold change enrichment in type I interferon production, response and signaling pathways. Patients with bacterial meningitis showed a significant upregulation of genes related to macrophage and neutrophil activation. We found several significantly DEGs between enteroviral and bacterial meningitis. Random forest classification showed that we were able to differentiate enteroviral from bacterial meningitis with an AUC of 0.982 on held-out samples.
Enteroviral meningitis has an innate immunity signature with type 1 interferons as key players. Our classifier, based on blood host transcriptomic profiles of different meningitis cases, is a possible strong alternative for diagnosing enteroviral meningitis.
Background Transcriptome profiling of blood cells is an efficient tool to study the gene expression signatures of rheumatic diseases. This study aims to improve the early diagnosis of pediatric ...rheumatic diseases by investigating patients' blood gene expression and applying machine learning on the transcriptome data to develop predictive models. Methods RNA sequencing was performed on whole blood collected from children with rheumatic diseases. Random Forest classification models were developed based on the transcriptome data of 48 rheumatic patients, 46 children with viral infection, and 35 controls to classify different disease groups. The performance of these classifiers was evaluated by leave-one-out cross-validation. Analyses of differentially expressed genes (DEG), gene ontology (GO), and interferon-stimulated gene (ISG) score were also conducted. Results Our first classifier could differentiate pediatric rheumatic patients from controls and infection cases with high area-under-the-curve (AUC) values (AUC = 0.8 + or - 0.1 and 0.7 + or - 0.1, respectively). Three other classifiers could distinguish chronic recurrent multifocal osteomyelitis (CRMO), juvenile idiopathic arthritis (JIA), and interferonopathies (IFN) from control and infection cases with AUC greater than or equal to 0.8. DEG and GO analyses reveal that the pathophysiology of CRMO, IFN, and JIA involves innate immune responses including myeloid leukocyte and granulocyte activation, neutrophil activation and degranulation. IFN is specifically mediated by antibacterial and antifungal defense responses, CRMO by cellular response to cytokine, and JIA by cellular response to chemical stimulus. IFN patients particularly had the highest mean ISG score among all disease groups. Conclusion Our data show that blood transcriptomics combined with machine learning is a promising diagnostic tool for pediatric rheumatic diseases and may assist physicians in making data-driven and patient-specific decisions in clinical practice. Keywords: Pediatric rheumatic diseases, RNA sequencing, Blood transcriptomics, Classification model
Varicella zoster virus (VZV) typically causes chickenpox upon primary infection. In rare cases, VZV can give rise to life-threatening disease in otherwise healthy people, but the immunological basis ...for this remains unexplained. We report 4 cases of acute severe VZV infection affecting the central nervous system or the lungs in unrelated, otherwise healthy children who are heterozygous for rare missense mutations in POLR3A (one patient), POLR3C (one patient), or both (two patients). POLR3A and POLR3C encode subunits of RNA polymerase III. Leukocytes from all 4 patients tested exhibited poor IFN induction in response to synthetic or VZV-derived DNA. Moreover, leukocytes from 3 of the patients displayed defective IFN production upon VZV infection and reduced control of VZV replication. These phenotypes were rescued by transduction with relevant WT alleles. This work demonstrates that monogenic or digenic POLR3A and POLR3C deficiencies confer increased susceptibility to severe VZV disease in otherwise healthy children, providing evidence for an essential role of a DNA sensor in human immunity.
Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large amount of patient cells. To maximize information ...from and minimize the need of precious samples in cancer research, prediction models have been developed to identify in silico epitope-specific TCRs. In this chapter, we provide a step-by-step protocol to train a prediction model using the user-friendly TCRex webtool for the nearly universal tumor-associated antigen Wilms' tumor 1 (WT1)-specific TCR repertoire. WT1 is a self-antigen overexpressed in numerous solid and hematological malignancies with a high clinical relevance. Training of computational models starts from a list of known epitope-specific TCRs which is often not available for new cancer epitopes. Therefore, we describe a workflow to assemble a training data set consisting of TCR sequences obtained from WT1
-reactive CD8 T cell clones expanded and sorted from healthy donor peripheral blood mononuclear cells.
PDF
