Expression and prognostic analysis of STAT6(YE361) in Hodgkin lymphoma.

This study aimed to investigate the expression and prognostic significance of the signal transducer and activator of transcription protein 6 (STAT6YE361) and EB virus encoding a small molecule RNA (EBER) in Hodgkin lymphoma (HL), as well as their correlation with clinical parameters. The expression of STAT6YE361 and EBER was investigated in HL via immunohistochemistry and in situ hybridization. Patient clinical data were retrospectively collected from archival libraries, and statistical analysis was performed. Overall, the nuclear positive expression rate of STAT6YE361 was 46%, and the EBER positive expression rate was 57%. STAT6YE361 was specifically expressed on the nucleus in cHL tissues. EBER was overexpressed in HL and had correlations with several clinical data, including age, gender, ethnicity, and primary cancer site. Interestingly, nuclear STAT6YE361 expression was correlated with EBER expression. Based on survival analysis, the nuclear expression of STAT6YE361 and female patients were associated with poor prognosis and were independent prognostic factors for five-year OS. These findings suggest that STAT6YE361 is a potential valuable index in the differential diagnosis and prognosis of HL. The mechanism of STAT6YE361 is related to Epstein-Barr virus infection.

Screening and identification of differentially expressed microRNAs in diffuse large B-cell lymphoma based on microRNA microarray.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of B-cell non-Hodgkin lymphoma in adults and the pathogenesis of DLBCL is multifactorial and complex. Understanding the molecular mechanisms involved in DLBCL is important to identify new therapeutic targets. The present study aimed to screen and identify differentially expressed microRNAs (miRNAs/miRs) between diffuse large B-cell lymphoma (DLBCL) and control [lymph node reactive hyperplasia (LRH)] groups, and to investigate whether miRNAs associated with DLBCL could serve as potential therapeutic targets. In total, 5 DLBCL experimental samples and 5 control samples were obtained from fresh patient tissues. Firstly, the fresh samples were analyzed using miRNA microarray to identify differentially expressed miRNAs. Next, three databases (TargetScan, microRNA.org and PITA) were used to predict by intersection the potential target genes of the 204 differential miRNAs identified, and a Venn diagram of the results was performed. Subsequently, the target genes of differential miRNAs were analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Finally, to validate the miRNA microarray data, reverse transcription-quantitative PCR (RT-qPCR) was performed for 8 differentially expressed miRNAs (miR-193a-3p, miR-19a-3p, miR-19b-3p, miR-370-3p, miR-1275, miR-490-5p, miR-630 and miR-665) using DLBCL and LRH fresh samples. In total, 204 miRNAs exhibited differential expression, including 105 downregulated and 54 upregulated miRNAs. The cut-off criteria were set as P≤0.05 and fold-change ≥2. A total of 7,522 potential target genes for the 204 miRNAs were predicted. Potential target genes were enriched in the following pathways: 'Cancer', 'MAPK signaling pathway', 'regulation of actin cytoskeleton', 'focal adhesion', 'endocytosis', 'Wnt signaling pathway', 'axon guidance', 'calcium signaling pathway' and 'PI3K/AKT signaling pathway'. A total of 8 miRNAs were validated by RT-qPCR, and 4 miRNAs (miR-19b-3p, miR-193a-3p, miR-370-3p and miR-490-5p) exhibited low expression levels in DLBCL (P<0.05), while miR-630 was highly expressed in DLBCL (P<0.05). Overall, the present study screened 204 differentially expressed miRNAs and analyzed the expression levels of 8 differentially expressed miRNAs in DLBCL. These differentially expressed miRNAs may serve as therapeutic targets for improvement of therapeutic efficacy in DLBCL in the future.

Network strategy to investigate differential pathways in sporadic amyotrophic lateral sclerosis.

OBJECTIVE: The objective of this paper was to investigate differential pathways in sporadic amyotrophic lateral sclerosis (SALS) based on pathway network analysis. MATERIALS AND METHODS: To achieve this goal, first, differentially expressed genes (DEGs) between SALS and normal controls were identified, and a target network was defined as DEGs correlated interactions from the search tool for the retrieval of interacting genes/proteins (STRING). Second, topological centrality analysis was conducted on the target network to identify hub genes and hub network. Third, pathway network was constructed by taking intersections of Reactome database and STRING protein-protein interaction network. Finally, based on extracting the common interactions between target network, hub network and pathway network, we built randomized network, performed randomization test, and denoted differential pathways and hub differential pathways with P < 0.05. RESULTS: There were 485 DEGs and 627 interactions in the target network. The pathway network was comprised 117,370 interactions. What was more, we found that 217 pathways had intersections with the target network. By accessing randomization test and removing the intersected count <10, 21 differential pathways with P values were nearly to be 0 were obtained, of which 6 rightly were the hub differential pathways, such as gene expression, mRNA Splicing, and mRNA splicing-major pathway. CONCLUSION: We have investigated 217 differential pathways and 21 significant differential pathways between SALS and normal controls based on network strategy. The findings might provide potential biomarkers for detection and therapy of SALS clinically and give great insights to reveal molecular mechanism underlying this disease. However, how these pathways cooperated with each other is still not clear, and future study should focus on this aspect.