Background Exportin 1 (XPO1), a nuclear export protein, participates in many biological processes, including mRNA transport, nucleocytoplasmic transport, nuclear protein export, regulation of mRNA stability, and drug response. XPO1 plays key roles in many cancer types and may serve as a potential biomarker. It is significant to systematically elucidate the roles of XPO1 in various cancer types in terms of function, molecular biology, immunology, and clinical relevance. Methods Data from UCSC Xena, CCLE, and CBioPortal were analyzed for the investigation of the differential expression of XPO1 across multiple cancer types. Clinical data were acquired to analyze the influence of XPO1 on the clinical characteristics of patients, such as survival outcome and clinical stage. The roles of XPO1 in the onset and progression of multiple cancers were expounded in terms of genetic changes at the molecular level [including tumor mutational burden (TMB), microsatellite instability (MSI), copy number variation (CNV), methylation, and gene co-expression], biological pathway changes, and the immune microenvironment. Results XPO1 was overexpressed in various tumor types, which may be related to CNV. Clinical data analysis revealed that XPO1 may serve as a risk factor in tumors, such as adrenocortical carcinoma, liver hepatocellular carcinoma, and low-grade glioma, thereby affecting patient prognosis. XPO1 in multiple tumor types was also substantially correlated with clinical stage, patient gender, and patient age. In certain tumors, the expression level of XPO1 exerted a greater influence on TMB and MSI. It was also found that XPO1 inhibited the activity of immune cells in the tumor immune microenvironment, such as CD8+ T cells, and affected biological pathways, such as the cell cycle and oxidative phosphorylation, and drove the expression of cancer driver genes, immune checkpoint genes, and highly mutated genes. Conclusions XPO1 is a potential pan-cancer risk factor as it may jointly promote tumor onset and progression by inhibiting the immune response, influencing relevant biological pathways, and promoting mutations in other genes.

MicroRNAs(miRNAs) have emerged as key regulators that control and influence gene expression as well as multiple biological processes depending on their potential binding sites in human-protein coding genes and other unconventional patterns, including coding for peptides, activating Toll-like receptors as a ligand, and other manners. Accumulating evidence has demonstrated that microRNA expression is tightly regulated during phases of development, differentiation, and effector functions of immune cells, immunological disorders of systemic lupus erythematosus (SLE). This review outlines the biogenesis of miRNAs and their unconventional functions as well as underlying cellular and molecular mechanisms. It then summarizes our current knowledge about how the biogenesis of miRNAs is regulated. Moreover, an overview was provided concerning the role of abnormal expression of miRNAs in lupus immune cells. In particular, we will shed some light on the recent advances in the role of miRNAs and exosome-derived miRNAs in immunological and epigenetic pathways in the pathogenesis of SLE.

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The morbidity rate of ulcerative colitis (UC) in the world is increasing year by year, recurrent episodes of diarrhea, mucopurulent and bloody stools, and abdominal pain are the main symptoms, reducing the quality of life of the patient and affecting the productivity of the society. In this study, we sought to develop robust diagnostic biomarkers for UC, to uncover potential targets for anti-TNF-ɑ drugs, and to investigate their associated pathway mechanisms. We collected single-cell expression profile data from 9 UC or healthy samples and performed cell annotation and cell communication analysis. Revealing the possible pathogenesis of ulcerative colitis by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analysis. Based on the disease-related modules obtained from weighted correlation network analysis (WGCNA) analysis, we used Lasso regression analysis and random forest algorithm to identify the genes with the greatest impact on disease (EPB41L3, HSD17B3, NDRG1, PDIA5, TRPV3) and further validated the diagnostic value of the model genes by various means. To further explore the relationship and mechanism between model genes and drug sensitivity, we collected gene expression profiles of 185 UC patients before receiving anti-tumor necrosis factor drugs, and we performed functional analysis based on the results of differential analysis between NR tissues and R tissues, and used single-sample GSEA (ssGSEA) and CIBERSORT algorithms to explore the important role of immune microenvironment on drug sensitivity. The results suggest that our model is not only helpful in aiding diagnosis, but also has implications for predicting drug efficacy; in addition, model genes may influence drug sensitivity by affecting immune cells. We suggest that this study has developed a diagnostic model with higher specificity and sensitivity, and also provides suggestions for clinical administration and drug efficacy prediction.