S100A9 Drives the Chronification of Psoriasiform Inflammation by Inducing IL-23/Type 3 Immunity

Elucidating the pan-oncologic landscape of S100A9: prognostic and therapeutic corollaries from an integrative bioinformatics and Mendelian randomization analysis

The calcium-binding protein S100A9 has emerged as a pivotal biomolecular actor in oncology, implicated in numerous malignancies. This comprehensive bioinformatics study transcends traditional boundaries, investigating the prognostic and therapeutic potential of S100A9 across diverse neoplastic entities. Leveraging a wide array of bioinformatics tools and publicly available cancer genomics databases, such as TCGA, we systematically examined the S100A9 gene. Our approach included differential expression analysis, mutational burden assessment, protein interaction networks, and survival analysis. This robust computational framework provided a high-resolution view of S100A9's role in cancer biology. The study meticulously explored S100A9's oncogenic facets, incorporating comprehensive analyses of its relationship with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration across various tumor types. This study presents a panoramic view of S100A9 expression across a spectrum of human cancers, revealing a heterogeneous expression landscape. Elevated S100A9 expression was detected in malignancies such as BLCA (Bladder Urothelial Carcinoma), CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma), COAD (Colon adenocarcinoma), ESCA (Esophageal carcinoma), and GBM (Glioblastoma multiforme), while reduced expression was noted in BRCA (Breast invasive carcinoma), HNSC (Head and Neck squamous cell carcinoma), and KICH (Kidney Chromophobe). This disparate expression pattern suggests that S100A9's role in cancer biology is multifaceted and context-dependent. Prognostically, S100A9 expression correlates variably with patient outcomes across different cancer types. Furthermore, its expression is intricately associated with TMB and MSI in nine cancer types. Detailed examination of six selected tumors-BRCA, CESC, KIRC (Kidney renal clear cell carcinoma), LUSC (Lung squamous cell carcinoma), SKCM (Skin Cutaneous Melanoma); STAD (Stomach adenocarcinoma)-revealed a negative correlation of S100A9 expression with the infiltration of most immune cells, but a positive correlation with neutrophils, M1 macrophages, and activated NK cells, highlighting the complex interplay between S100A9 and the tumor immune environment. This bioinformatics synthesis posits S100A9 as a significant player in cancer progression, offering valuable prognostic insights. The data underscore the utility of S100A9 as a prognostic biomarker and its potential as a therapeutic target. The therapeutic implications are profound, suggesting that modulation of S100A9 activity could significantly impact cancer management strategies.

The effects of age and dysfunction on meibomian gland population dynamics

PURPOSE

While meibomian gland dysfunction (MGD) is widely recognized as a major cause of evaporative dry eye disease, little is known about normal gland differentiation and lipid synthesis or the mechanism underlying gland atrophy and abnormal lipid secretion. The purpose of this study was to use single-cell and spatial transcriptomics to probe changes in cell composition, differentiation, and gene expression associated with two murine models of MGD: age-related gland atrophy in wild-type mice and altered meibum quality in acyl-CoA wax alcohol acyltransferase 2 (Awat2) knockout (KO) mice.

METHODS

Young (6 month) and old (22 month) wild type, C57Bl/6 mice and young (3 month) and old (13 month) Awat2 KO mice were used in these studies. For single-cell analysis, the tarsal plate was dissected from the upper and lower eyelids, and single cells isolated and submitted to the UCI Genomic Core, while for the spatial analysis frozen tissue sections were shipped to Resolve Biosciences on dry ice and sections probed in duplicate using a meibomian gland specific, 100 gene Molecular Chartography panel.

RESULTS

Analysis of gene expression patterns identified the stratified expression of lipogenic genes during meibocyte differentiation, which may control the progressive synthesis of meibum lipids; an age-related decrease in meibocytes; and increased immune cell infiltration. Additionally, we detected unique immune cell populations in the Awat2 KO mouse suggesting activation of psoriasis-like, inflammatory pathways perhaps caused by ductal dilation and hyperplasia.

CONCLUSION

Together these findings support novel mechanism controlling gland function and dysfunction.

Identification of a shared gene signature and biological mechanism between diabetic foot ulcers and cutaneous lupus erythemnatosus by transcriptomic analysis

Diabetic foot ulcers (DFU) and cutaneous lupus erythematosus (CLE) are both diseases that can seriously affect a patient's quality of life and generate economic pressure in society. Symptomatically, both DLU and CLE exhibit delayed healing and excessive inflammation; however, there is little evidence to support a molecular and cellular connection between these two diseases. In this study, we investigated potential common characteristics between DFU and CLE at the molecular level to provide new insights into skin diseases and regeneration, and identify potential targets for the development of new therapies. The gene expression profiles of DFU and CLE were obtained from the Gene Expression Omnibus (GEO) database and used for analysis. A total of 41 common differentially expressed genes (DEGs), 16 upregulated genes and 25 downregulated genes, were identified between DFU and CLE. GO and KEGG analysis showed that abnormalities in epidermal cells and the activation of inflammatory factors were both involved in the occurrence and development of DFU and CLE. Protein-protein interaction network (PPI) and sub-module analysis identified enrichment in seven common key genes which is KRT16, S100A7, KRT77, OASL, S100A9, EPGN and SAMD9. Based on these seven key genes, we further identified five miRNAs(has-mir-532-5p, has-mir-324-3p,has-mir-106a-5p,has-mir-20a-5p,has-mir-93-5p) and7 transcription factors including CEBPA, CEBPB, GLI1, EP30D, JUN,SP1, NFE2L2 as potential upstream molecules. Functional immune infiltration assays showed that these genes were related to immune cells. The CIBERSORT algorithm and Pearson method were used to determine the correlations between key genes and immune cells, and reverse key gene-immune cell correlations were found between DFU and CLE. Finally, the DGIbd database demonstrated that Paquinimod and Tasquinimod could be used to target S100A9 and Ribavirin could be used to target OASL. Our findings highlight common gene expression characteristics and signaling pathways between DFU and CLE, indicating a close association between these two diseases. This provides guidance for the development of targeted therapies and mutual interactions.

Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics

BACKGROUND

Mounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses are not fully understood. Our study aimed to find potential crucial genes in psoriasis and UC through machine learning and integrated bioinformatics.

METHODS

The overlapping differentially expressed genes (DEGs) of the datasets GSE13355 and GSE87466 were identified. Then the functional enrichment analysis was performed. The overlapping genes in LASSO, SVM-RFE and key module in WGCNA were considered as potential crucial genes. The receiver operator characteristic (ROC) curve was used to estimate their diagnostic confidence. The CIBERSORT was conducted to evaluate immune cell infiltration. Finally, the datasets GSE30999 and GSE107499 were retrieved to validate.

RESULTS

112 overlapping DEGs were identified in psoriasis and UC and the functional enrichment analysis revealed they were closely related to the inflammatory and immune response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, and SLAMF7, were ultimately identified as potential crucial genes. ROC curves showed they all had high confidence in the test and validation datasets. CIBERSORT analysis indicated there was a correlation between infiltrating immune cells and potential crucial genes.

CONCLUSION

In our study, we focused on the comprehensive understanding of pathogeneses in psoriasis and UC. The identification of eight potential crucial genes may contribute to not only understanding the common mechanism, but also identifying occult UC in psoriasis patients, even serving as therapeutic targets in the future.

T cell-specific P2RX7 favors lung parenchymal CD4+ T cell accumulation in response to severe lung infections

CD4+ T cells are key components of the immune response during lung infections and can mediate protection against tuberculosis (TB) or influenza. However, CD4+ T cells can also promote lung pathology during these infections, making it unclear how these cells control such discrepant effects. Using mouse models of hypervirulent TB and influenza, we observe that exaggerated accumulation of parenchymal CD4+ T cells promotes lung damage. Low numbers of lung CD4+ T cells, in contrast, are sufficient to protect against hypervirulent TB. In both situations, lung CD4+ T cell accumulation is mediated by CD4+ T cell-specific expression of the extracellular ATP (eATP) receptor P2RX7. P2RX7 upregulation in lung CD4+ T cells promotes expression of the chemokine receptor CXCR3, favoring parenchymal CD4+ T cell accumulation. Our findings suggest that direct sensing of lung eATP by CD4+ T cells is critical to induce tissue CD4+ T cell accumulation and pathology during lung infections.