Immune effector process

Abstract: The pathogenesis of diabetic nephropathy is not completely understood, and the effects of existing treatments are not satisfactory. Various public platforms already contain extensive data for deeper bioinformatics analysis. From the GSE30529 dataset based on diabetic nephropathy tubular samples, we identified 345 genes through differential expression analysis and weighted gene coexpression correlation network analysis. GO annotations mainly included neutrophil activation, regulation of immune effector process, positive regulation of cytokine production and neutrophil-mediated immunity. KEGG pathways mostly included phagosome, complement and coagulation cascades, cell adhesion molecules and the AGE-RAGE signalling pathway in diabetic complications. Additional datasets were analysed to understand the mechanisms of differential gene expression from an epigenetic perspective. Differentially expressed miRNAs were obtained to construct a miRNA-mRNA network from the miRNA profiles in the GSE57674 dataset. The miR-1237-3p/SH2B3, miR-1238-5p/ZNF652 and miR-766-3p/TGFBI axes may be involved in diabetic nephropathy. The methylation levels of the 345 genes were also tested based on the gene methylation profiles of the GSE121820 dataset. The top 20 hub genes in the PPI network were discerned using the CytoHubba tool. Correlation analysis with GFR showed that SYK, CXCL1, LYN, VWF, ANXA1, C3, HLA-E, RHOA, SERPING1, EGF and KNG1 may be involved in diabetic nephropathy. Eight small molecule compounds were identified as potential therapeutic drugs using Connectivity Map.

Abstract: The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD. The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts. A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design. Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

Abstract: The objectives of the present study were to identify key genes and biological pathways associated with thermal stress in Chinese Holstein dairy cattle. Hence, we constructed a cell-model, applied various molecular biology experimental techniques and bioinformatics analysis. A total of 55 candidate genes were screened from published literature and the IPA database to examine its regulation under cold (25°C) or heat (42°C) stress in PBMCs. We identified 29 (3 up-regulated and 26 down-regulated) and 41 (15 up-regulated and 26 down-regulated) significantly differentially expressed genes (DEGs) (fold change ≥ 1.2-fold and P < 0.05) after cold and heat stress treatments, respectively. Furthermore, bioinformatics analyses confirmed that major biological processes and pathways associated with thermal stress include protein folding and refolding, protein phosphorylation, transcription factor binding, immune effector process, negative regulation of cell proliferation, autophagy, apoptosis, protein processing in endoplasmic reticulum, estrogen signaling pathway, pathways related to cancer, PI3K- Akt signaling pathway, and MAPK signaling pathway. Based on validation at the cellular and individual levels, the mRNA expression of the HIF1A gene showed upregulation during cold stress and the EIF2A, HSPA1A, HSP90AA1, and HSF1 genes showed downregulation after heat exposure. The RT-qPCR and western blot results revealed that the HIF1A after cold stress and the EIF2A, HSPA1A, HSP90AA1, and HSF1 after heat stress had consistent trend changes at the cellular transcription and translation levels, suggesting as key genes associated with thermal stress response in Holstein dairy cattle. The cellular model established in this study with PBMCs provides a suitable platform to improve our understanding of thermal stress in dairy cattle. Moreover, this study provides an opportunity to develop simultaneously both high-yielding and thermotolerant Chinese Holstein cattle through marker-assisted selection.