Identification of lncRNA–miRNA–mRNA regulatory network associated with epithelial ovarian cancer cisplatin-resistant

To construct a long noncoding RNA (lncRNA)–microRNA (miRNA)–messenger RNA (mRNA) regulatory network related to epithelial ovarian cancer (EOC) cisplatin-resistant, differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) between MDAH and TOV-112D cells lines were identified. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. Downstream mRNAs or upstream lncRNAs for miRNAs were analyzed at miRTarBase 7.0 or DIANA-LncBase V2, respectively. A total of 485 significant DEGs, 85 DELs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs contrains 81 nodes and 141 edges was constructed, and 25 hub genes related to EOC cisplatin-resistant were identified. Subsequently, a lncRNA–miRNA–mRNA regulatory network contains 4 lncRNAs, 4 miRNAs, and 35 mRNAs was established. Taken together, our study provided evidence concerning the alteration genes involved in EOC cisplatin-resistant, which will help to unravel the mechanisms underlying drug resistant.     

Integrated insight into the molecular mechanisms of selenium-modulated,MPP+-induced cytotoxicity in a Parkinson’s disease model

ObjectiveParkinson’s disease (PD) is a neurodegenerative disease that is associated with oxidative stress. Due to the anti-inflammatory and antioxidant functions of Selenium (Se), this molecule may have neuroprotective functions in PD; however, the involvement of Se in such a protective function is unclear.Methods1-methyl-4-phenylpyridinium (MPP⁺), which inhibits mitochondrial respiration, is generally used to produce a reliable cellular model of PD. In this study, a MPP⁺-induced PD model was used to test if Se could modulate cytotoxicity, and we further capture gene expression profiles following PC12 cell treatment with MPP⁺ with or without Se by genome wide high-throughput sequencing.ResultsWe identified 351 differentially expressed genes (DEGs) and 14 differentially expressed long non-coding RNAs (DELs) in MPP⁺-treated cells when compared to controls. We further document 244 DEGs and 27 DELs in cells treated with MPP⁺ and Se vs. cells treated with MPP⁺ only. Functional annotation analysis of DEGs and DELs revealed that these groups were enriched in genes that respond to reactive oxygen species (ROS), metabolic processes, and mitochondrial control of apoptosis. Thioredoxin reductase 1 (Txnrd1) was also identified as a biomarker of Se treatment.ConclusionsOur data suggests that the DEGs Txnrd1, Siglec1 and Klf2, and the DEL AABR07044454.1 which we hypothesize to function in cis on the target gene Cdkn1a, may modulate the underlying neurodegenerative process, and act a protective function in the PC12 cell PD model. This study further systematically demonstrated that mRNAs and lncRNAs induced by Se are involved in neuroprotection in PD, and provides novel insight into how Se modulates cytotoxicity in the MPP⁺-induced PD model.     

Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis

The antiviral treatment efficacy varies among chronic hepatitis B (CHB) patients and the underlying mechanism is unclear. An integrated bioinformatics analysis was performed to investigate the host factors that affect the therapeutic responsiveness in CHB patients. Four GEO data sets (GSE54747, GSE27555, GSE66698 and GSE66699) were downloaded from the Gene Expression Omnibus (GEO) database and analysed to identify differentially expressed genes(DEGs). Enrichment analyses of the DEGs were conducted using the DAVID database. Immune cell infiltration characteristics were analysed by CIBERSORT. Upstream miRNAs and lncRNAs of hub DEGs were identified by miRWalk 3.0 and miRNet in combination with the MNDR platform. As a result, seventy-seven overlapping DEGs and 15 hub genes were identified including CCL5, CXCL9, MYH2, CXCR4, CD74, CCL4, HLA-DRB1, ACTA1, CD69, CXCL10, HLA-DRB5, HLA-DQB1, CXCL13, STAT1 and CKM. The enrichment analyses revealed that the DEGs were mainly enriched in immune response and chemokine signalling pathways. Investigation of immune cell infiltration in liver samples suggested significantly different infiltration between responders and non-responders, mainly characterized by higher proportions of CD8+ T cells and activated NK cells in non-responders. The prediction of upstream miRNAs and lncRNAs led to the identification of a potential mRNA-miRNA-lncRNA regulatory network composed of 2 lncRNAs (H19 and GAS5) and 5 miRNAs (hsa-mir-106b-5p, hsa-mir-17-5p, hsa-mir-20a-5p, hsa-mir-6720-5p and hsa-mir-93-5p) targeting CCL5 mRNA. In conclusion, our study suggested that host genetic factors could affect therapeutic responsiveness in CHB patients. The antiviral process might be associated with the chemokine-mediated immune response and immune cell infiltration in the liver microenvironment.     

Understanding pathogen–host interplay by expression profiles of lncRNA and mRNA in the liver of Echinococcus multilocularis-infected mice

Almost all Echinococcus multilocularis (Em) infections occur in the liver of the intermediate host, causing a lethal zoonotic helminthic disease, alveolar echinococcosis (AE). However, the long non-coding RNAs (lncRNAs) expression profiles of the host and the potential regulatory function of lncRNA during Em infection are poorly understood. In this study, the profiles of lncRNAs and mRNAs in the liver of mice at different time points after Em infection were explored by microarray. Thirty-one differentially expressed mRNAs (DEMs) and 68 differentially expressed lncRNAs (DELs) were found continuously dysregulated. These DEMs were notably enriched in “antigen processing and presentation”, “Th1 and Th2 cell differentiation” and “Th17 cell differentiation” pathways. The potential predicted function of DELs revealed that most DELs might influence Th17 cell differentiation and TGF-β/Smad pathway of host by trans-regulating SMAD3, STAT1, and early growth response (EGR) genes. At 30 days post-infection (dpi), up-regulated DEMs were enriched in Toll-like and RIG-I-like receptor signaling pathways, which were validated by qRT-PCR, Western blotting and downstream cytokines detection. Furthermore, flow cytometric analysis and serum levels of the corresponding cytokines confirmed the changes in cell-mediated immunity in host during Em infection that showed Th1 and Th17-type CD4⁺ T-cells were predominant at the early infection stage whereas Th2-type CD4⁺ T-cells were significantly higher at the middle/late stage. Collectively, our study revealed the potential regulatory functions of lncRNAs in modulating host Th cell subsets and provide novel clues in understanding the influence of Em infection on host innate and adaptive immune response.     

Identification of potential biomarkers associated with immune infiltration in the esophageal carcinoma tumor microenvironment

Tumor immune cell infiltration was significantly correlated with the progression and the effect of immunotherapy in cancers including esophageal carcinoma (ESCA). However, no biomarkers were identified which were associated with immune infiltration in ESCA. In the present study, a total of 128 common differentially expressed genes (DEGs) were identified between esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinomas (EAC). The results of gene ontology (GO) enrichment and Reactome pathway analysis displayed that the up-regulated DEGs were mainly involved in the regulation of extracellular matrix (ECM), while the down-regulated DEGs were mainly involved in the regulation of cornification and keratinocyte differentiation. The most significant module of up-regulated DEGs was selected by Molecular Complex Detection (MCODE). Top ten similar genes of COL1A2 were explored, then validation and the prognostic analysis of these genes displayed that COL1A2, COL1A1, COL3A1, ZNF469 and Periostin (POSTN) had the prognostic value which were up-regulated in ESCA. The expressions of COL1A2 and its four similar genes were mainly correlated with infiltrating levels of macrophages and dendritic cells (DCs) and showed strong correlations with diverse immune marker sets in ESCA. To summarize, COL1A2 and its four similar genes were identified as the potential biomarkers associated with immune infiltration in ESCA. These genes might be applied to immunotherapy for ESCA.     

EA15, MIR22, LINC00472 as diagnostic markers for diabetic kidney disease

This study aimed to investigate the molecular mechanisms of diabetic kidney disease (DKD) and to explore new potential therapeutic strategies and biomarkers for DKD. First we analyzed the differentially expressed changes between patients with DKD and the control group using the chip data in Gene Expression Omnibus (GEO) database. Then the gene chip was subjected to be annotated again, so as to screen long noncoding RNAs (lncRNAs) and study expression differences of these lncRNAs in DKD and controlled samples. At last, the function of the differential lncRNAs was analyzed. A total of 252 lncRNAs were identified, and 14 were differentially expressed. In addition, there were 1,629 differentially expressed messenger RNAs (mRNAs) genes, and proliferation and apoptosis adapter protein 15 (PEA15), MIR22, and long intergenic nonprotein coding RNA 472 ( LINC00472) were significantly differentially expressed in DKD samples. Through functional analysis of the encoding genes coexpressed by the three lncRNAs, we found these genes were mainly enriched in type 1 diabetes and autoimmune thyroid disease pathways, whereas in Gene Ontology (GO) function classification, they were also mainly enriched in the immune response, type I interferon signaling pathways, interferon-γ mediated signaling pathways, and so forth. To summary, we identified EA15, MIR22, and LINC00472 may serve as the potential diagnostic markers of DKD.     

基于转录组的瑶药半枫荷根和叶的差异分析

为了探究半枫荷(Semiliquidambar cathayensis)根和叶的基因表达差异和关键活性成分合成通路中关键基因的表达规律,本研究对半枫荷的根和叶进行转录组测序和生物信息分析。59378个差异表达基因归类到在GO分类的3个大类中,主要与生物学过程有关(50.59%)。626个差异表达基因注释KOG数据库的24个分类中。81个差异表达基因参与苯丙烷类化合物的生物合成,110个差异表达基因参与黄酮类化合物的生物合成,211个差异表达基因参与萜类化合物的生物合成。本研究获得了半枫荷根和叶的转录组信息特征,为今后半枫荷基因功能鉴定、次生代谢途径解析及调控机制的研究提供依据。