CD8+ tissue-resident memory T cells induce oral lichen planus erosion via cytokine network

Unraveling the immunological landscape in acute pancreatitis progression to sepsis: insights from a Mendelian randomization study on immune cell traits

Background

Acute pancreatitis (AP) is a severe digestive system disorder with a significant risk of progressing to sepsis, a major cause of mortality. Unraveling the immunological pathways in AP is essential for developing effective treatments, particularly understanding the role of specific immune cell traits in this progression.

Methods

Employing a bidirectional two-sample Mendelian Randomization (MR) approach, this study first examined the causal relationship between AP and 731 immune cell traits to identify those significantly associated with AP. Subsequently, we explored the causal associations between 731 immune cell traits and sepsis. The analysis utilized extensive genome-wide association studies (GWAS) summary datasets, with a focus on identifying common immune cell traits with statistically significant causal associations between AP and sepsis.

Results

Our investigation identified 44 immune cell traits unidirectionally associated with AP and 36 traits unidirectionally associated with sepsis. Among these, CD127 on CD28+ CD45RA- CD8+ T cells emerged as a common mediator, accounting for 5.296% of the increased risk of sepsis in AP patients. This finding highlights the significant role of specific memory CD8+ T cells in the pathophysiology of AP and its progression to sepsis.

Conclusion

This study elucidates the critical role of specific immune cell traits, particularly CD127hi memory CD8+ T cells, in the progression of AP to sepsis. Our findings provide a foundation for future research into targeted immune-modulatory therapies, potentially improving patient outcomes in AP-related sepsis and offering new insights into the complex immunological dynamics of this condition.

Development of an immune-related diagnostic predictive model for oral lichen planus

Oral lichen planus (OLP) was a chronic inflammatory disease of unknown etiology with a 1.4% chance of progressing to malignancy. However, it has been suggested in several studies that immune system disorders played a dominant role in the onset and progression of OLP. Therefore, this experiment aimed to develop a diagnostic prediction model for OLP based on immunopathogenesis to achieve early diagnosis and treatment and prevent cancer. In this study, 2 publicly available OLP datasets from the gene expression omnibus database were filtered. In the experimental group (GSE52130), the level of immune cell infiltration was assessed using MCPcounter and ssGSEA algorithms. Subsequently, differential expression analysis and gene set enrichment analysis were performed between the OLP and control groups. The resulting differentially expressed genes were intersected with immunologically relevant genes provided on the immunology database and analysis portal database (ImmPort) website to obtain differentially expressed immunologically relevant genes (DEIRGs). Furthermore, the gene ontology and kyoto encyclopedia of genes and genomes analyses were carried out. Finally, protein-protein interaction network and least absolute shrinkage and selection operator regression analyses constructed a model for OLP. Receiver operating characteristic curves for the experimental and validation datasets (GSE38616) were plotted separately to validate the model's credibility. In addition, real-time quantitative PCR experiment was performed to verify the expression level of the diagnostic genes. Immune cell infiltration analysis revealed a more significant degree of inflammatory infiltration in the OLP group compared to the control group. In addition, the gene set enrichment analysis results were mainly associated with keratinization, antibacterial and immune responses, etc. A total of 774 differentially expressed genes was obtained according to the screening criteria, of which 65 were differentially expressed immunologically relevant genes. Ultimately, an immune-related diagnostic prediction model for OLP, which was composed of 5 hub genes (BST2, RNASEL, PI3, DEFB4A, CX3CL1), was identified. The verification results showed that the model has good diagnostic ability. There was a significant correlation between the 5 hub diagnostic biomarkers and immune infiltrating cells. The development of this model gave a novel insight into the early diagnosis of OLP.

A novel "prime and pull" strategy mediated by the combination of two dendritic cell-targeting designs induced protective lung tissue-resident memory T cells against H1N1 influenza virus challenge

Vaccination is still the most promising strategy for combating influenza virus pandemics. However, the highly variable characteristics of influenza virus make it difficult to develop antibody-based universal vaccines, until now. Lung tissue-resident memory T cells (TRM), which actively survey tissues for signs of infection and react rapidly to eliminate infected cells without the need for a systemic immune reaction, have recently drawn increasing attention towards the development of a universal influenza vaccine. We previously designed a sequential immunization strategy based on orally administered Salmonella vectored vaccine candidates. To further improve our vaccine design, in this study, we used two different dendritic cell (DC)-targeting strategies, including a single chain variable fragment (scFv) targeting the surface marker DC-CD11c and DC targeting peptide 3 (DCpep3). Oral immunization with Salmonella harboring plasmid pYL230 (S230), which displayed scFv-CD11c on the bacterial surface, induced dramatic production of spleen effector memory T cells (TEM). On the other hand, intranasal boost immunization using purified DCpep3-decorated 3M2e-ferritin nanoparticles in mice orally immunized twice with S230 (S230inDC) significantly stimulated the differentiation of lung CD11b+ DCs, increased intracellular IL-17 production in lung CD4+ T cells and elevated chemokine production in lung sections, such as CXCL13 and CXCL15, as determined by RNAseq and qRT‒PCR assays, resulting in significantly increased percentages of lung TRMs, which could provide efficient protection against influenza virus challenge. The dual DC targeting strategy, together with the sequential immunization approach described in this study, provides us with a novel "prime and pull" strategy for addressing the production of protective TRM cells in vaccine design.