Identification, Functional Analysis and Preliminary Validation of Differentially Expressed Genes in Hyperacute Cerebral Infarction Patients

Background/AimsAt present, most studies on ischemic stroke and micro RNA are focused on 24h after stroke. Therefore, our experiment intends to analyze the differentially expressed genes in hyperacute cerebral infarction patients, and to analyze the relationship between the most significantly differentially expressed miRNA and clinical characteristics. MethodsDownload miRNA expression microarray and gene expression microarray from GEO database, screen differentially expressed genes and miRNA by bioinformatics method, and analyze their biological functions. The peripheral plasma of patients with hyperacute stroke was collected, the related miRNAs were extracted, and the relationship between them and clinical characteristics was analyzed. ResultsThe microarray included 39 hyperacute cerebral infarction patients patients and 33 healthy volunteers and 5 differentially expressed miRNAs and 1107 differentially expressed genes were obtained by analysis. MiR-3156-5p was selected to further analyze and verify the correlation with the clinical characteristics of patients. The results showed that the expression level of miR-3156-5p was significantly positively correlated with triglyceride level, and had a significant negative impact on stroke. The low level of miR-3156-5p in hyperacute cerebral infarction patients may be one of the initiating factors of neuroinflammation induced by ischemic stroke, and functional analysis and some existing experimental results also support this view. ConclusionsIn our study, a series of differentially expressed genes and differentially expressed miRNAs were screened by analyzing GEO data sets. In addition, the low expression of miR-3156-5p in hyperacute cerebral infarction patients may be one of the initiating factors of neuroinflammation induced by ischemic stroke.

Comprehensive analysis of lncRNA and mRNA based on expression microarray profiling reveals different characteristics of osteoarthritis between Tibetan and Han patients

Background Osteoarthritis (OA) is thought to be the most prevalent chronic joint disease, especially in Tibet of China. Here, we aimed to explore the integrative lncRNA and mRNA landscape between the OA patients of Tibet and Han. Methods The lncRNA and mRNA expression microarray profiling was performed by SurePrint G3 Human Gene Expression 8x60K v2 Microarray in articular cartilage samples from OA patients of Han nationality and Tibetans, followed by GO, KEGG, and trans-regulation and cis-regulation analysis of lncRNA and mRNA. Results We found a total of 117 lncRNAs and 297 mRNAs differently expressed in the cartilage tissues of Tibetans (n = 5) comparing with those of Chinese Han (n = 3), in which 49 lncRNAs and 158 mRNAs were upregulated, and 68 lncRNAs and 139 mRNAs were downregulated. GO and KEGG analysis showed that several unreported biological processes and signaling pathways were particularly identified. LncRNA-mRNA co-expression analysis revealed a remarkable lncRNA-mRNA relationship, in which OTOA may play a critical role in the different mechanisms of the OA progression between Tibetans and Chinese Han. Conclusion This study identified different lncRNA/mRNA expression profiling between OA patients of Tibetans and Han, which were involved in many characteristic biological processes and signaling pathways.

Long-term transcriptomic and proteomic effects in Sprague Dawley rat thyroid and plasma after internal low dose 131I exposure

Background Radioiodide (131I) is commonly used to treat thyroid cancer and hyperthyroidis.131I released during nuclear accidents, have resulted in increased incidence of thyroid cancer in children. Therefore, a better understanding of underlying cellular mechanisms behind 131I exposure is of great clinical and radiation protection interest. The aim of this work was to study the long-term dose-related effects of 131I exposure in thyroid tissue and plasma in young rats and identify potential biomarkers. Materials and methods Male Sprague Dawley rats (5-week-old) were i.v. injected with 0.5, 5.0, 50 or 500 kBq 131I (Dthyroid ca 1–1000 mGy), and killed after nine months at which time the thyroid and blood samples were collected. Gene expression microarray analysis (thyroid samples) and LC-MS/MS analysis (thyroid and plasma samples) were performed to assess differential gene and protein expression profiles in treated and corresponding untreated control samples. Bioinformatics analyses were performed using the DAVID functional annotation tool and Ingenuity Pathway Analysis (IPA). The gene expression microarray data and LC-MS/MS data were validated using qRT-PCR and ELISA, respectively. Results Nine 131I exposure-related candidate biomarkers (transcripts: Afp and RT1-Bb, and proteins: ARF3, DLD, IKBKB, NONO, RAB6A, RPN2, and SLC25A5) were identified in thyroid tissue. Two dose-related protein candidate biomarkers were identified in thyroid (APRT and LDHA) and two in plasma (DSG4 and TGM3). Candidate biomarkers for thyroid function included the ACADL and SORBS2 (all activities), TPO and TG proteins (low activities). 131I exposure was shown to have a profound effect on metabolism, immune system, apoptosis and cell death. Furthermore, several signalling pathways essential for normal cellular function (actin cytoskeleton signalling, HGF signalling, NRF2-mediated oxidative stress, integrin signalling, calcium signalling) were also significantly regulated. Conclusion Exposure-related and dose-related effects on gene and protein expression generated few expression patterns useful as biomarkers for thyroid function and cancer.

Identification of Bioinformatics of the Metastasis of Endometrial Carcinoma Based on Gene Expression Microarray

Objective: We aimed to explore the bioinformatics of endometrial carcinoma (EC) metastasis. Methods: The microarray information of 4 cases of progressive endometrial cancer (PEC) and 4 cases of non-progressive controls (NPC) were collected from the Gene Expression Omnibus Database (GEOD). The Limma package in R was performed to selected the differentially expressed genes (DEGs). Then, the hierarchical clustering of DEGs was carried out. In addition, bioinformatics analysis was carried out. Results: There were 65 DEGs identified between PEC and NPC. Those DEGs were mostly enriched in cell proliferation function, MAPK and TGF-β signaling pathways. Furthermore, those DEGs were related to of the increased contents of IGF2 and PLAG1, and decreased contents of THBS4 and FGF20. Conclusions: There were 65 DEGs identified in endometrial cancer between progressive and non-progressive. Those DEGs were significantly related to tumor metastasis. Increased levels of IGF2 and PLAG1, and decreased levels of THBS4 and FGF20 may have a notable effect on the development of EC.