Background: Endometrial cancer (EC) is one kind of women cancers. Bioinformatic technology could screen out relative genes which made targeted therapy becoming conventionalized. Methods: GSE17025 were downloaded from GEO. The genomic data and clinical data were obtained from TCGA. R software and bioconductor packages were used to identify the DEGs. Clusterprofiler was used for functional analysis. STRING was used to assess PPI information and plug-in MCODE to screen hub modules in Cytoscape. The selected genes were coped with functional analysis. CMap could find EC-related drugs that might have potential effect. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk of each patient. Kaplan-Meier curve analysis could compare the survival time. ROC curve analysis was performed to predict value of the genes. Mutation and survival analysis in TCGA database and UALCAN validation were completed. Immunohistochemistry staining from Human Protein Atlas database. GSEA, ROC curve analysis, Oncomine and qRT-PCR were also performed. Results: Functional analysis showed that the upregulated DEGs were strikingly enriched in chemokine activity, and the down-regulated DEGs in glycosaminoglycan binding. PPI network suggested that NCAPG was the most relevant protein. CMap identified 10 small molecules as possible drugs to treat EC. Cox analysis showed that BCHE, MAL and ASPM were correlated with EC prognosis. TCGA dataset analysis showed significantly mutated BHCE positively related to EC prognosis. MAL and ASPM were further validated in UALCAN. All the results demonstrated that the two genes might promote EC progression. The profile of ASPM was confirmed by the results from immunohistochemistry. ROC curve demonstrated that the mRNA levels of two genes exhibited difference between normal and tumor tissues, indicating their diagnostic efficiency. qRT-PCR results supported the above results. Oncomine results showed that DNA copy number variation of MAL was significantly higher in different EC subtypes than in healthy tissues. GSEA suggested that the two genes played crucial roles in cell cycle. Conclusion: BCHE, MAL and ASPM are tumor-related genes and can be used as potential biomarkers in EC treatment.

Background/Aims: Interleukin (IL)-35 has immunosuppressive functions in autoimmune diseases, infectious diseases, and certain cancers. However, few studies have focused on its immunoregulatory activity in non-small cell lung cancer (NSCLC). Thus, we investigated the role of IL-35 in the pathogenesis of this disease. Methods: A total of 66 NSCLC patients and 21 healthy individuals were enrolled. IL-35 expression in peripheral blood and bronchoalveolar lavage fluid (BALF) was measured. The modulatory functions of IL-35 on purified CD4⁺ and CD8⁺ T cells from NSCLC patients were investigated in direct and indirect coculture systems with NSCLC cell lines. Results: IL-35 expression was significantly increased in BALF from the tumor site, but not in the peripheral blood of NSCLC patients. IL-35 did not affect the bioactivity including proliferation, cytokine production, cell cycle, and cellular invasion of NSCLC cells. It suppressed responses from type 1 T helper (Th1) and Th17 cells but elevated the regulatory T cell response in cultured CD4⁺ T cells from NSCLC patients, and reduced cytokine-mediated CD4⁺ T cells cytotoxicity to NSCLC cells. Moreover, IL-35 also inhibited cytotoxic gene expression in CD8⁺ T cells from NSCLC, reducing their cytolytic and noncytolytic functions. Conclusion: The results of this study suggest that IL-35 contributes to the dysfunction/exhaustion of T cells and limited antitumor immune responses in NSCLC.

No abstract

Background: Previous studies have shown that macrophage migration inhibitory factor (MIF) is involved in the pathogenesis of asthma. This study aimed to investigate whether serum MIF reflects a therapeutic response in allergic asthma. Methods: We enrolled 30 asthmatic patients with mild-to-moderate exacerbations and 20 healthy controls, analyzing the parameter levels of serum MIF, serum total immunoglobulin E (tIgE), peripheral blood eosinophil percentage (EOS% ), and fractional exhaled nitric oxide (FeNO). Lung function indices were used to identify disease severity and therapeutic response. Results: Our study showed that all measured parameters in patients were at higher levels than those of controls. After one week of treatment, most parameter levels decreased significantly except for serum tIgE. Furthermore, we found that serum MIF positively correlated with EOS% as well as FeNO, but negatively correlated with lung function indices. Receiver operator characteristic (ROC) curve analysis indicated that among the parameters, serum MIF exhibited a higher capacity to evaluate therapeutic response. The area under the curve (AUC) of MIF was 0.931, with a sensitivity of 0.967 and a specificity of 0.800. Conclusions: Our results suggested that serum MIF may serve as a potential biomarker for evaluating therapeutic response in allergic asthma with mild-to-moderate exacerbations.