Background Human B-cell lymphoma 6 (BCL6) gene, usually coding protein of 706 amino acids, is closely associated with large B cell lymphoma. Researches showed that protein mutation or change of expression levels usually happened in the mounting non-hodgkin lymphoma (NHL). Thus BCL6 is considered to be involved in germinal center (GC)-derived lymphoma. Results The BCL6 1-350 gene codons were optimized for prokaryotic system. After expression of BCL6 1-350 in E . coli , the BCL6 1-350 protein was purified with Ni column. Then the BCL6 1-350 protein, mixing with QuickAntibody-Mouse5W adjuvant, was injected into Balb/c mice. After immunization and cell fusion, a stable cell line named 1E6A4, which can secrete anti-BCL6 antibody, was obtained. The isotype of 1E6A4 mAb was determined as IgG 2a , and the affinity constant reached 5.12×10 10 L/mol. Furthermore, the specificity of the mAb was determined with ELISA, western blot and immunohistochemistry. Results indicated that the 1E6A4 mAb was able to detect BCL6 specifically and sensitively. Conclusions BCL6 1-350 antigen has been successfully generated with an effective and feasible method, and a highly specific antibody named 1E6A4 against BCL6 has been screened and characterized in this study, which was valuable in clinical diagnosis.

Background: Prostate cancer is one of the most common malignancies among men worldwide currently. However, specific mechanisms of prostate cancer were still not fully understood due to lack of integrated molecular analyses. We performed this study to establish an mRNA-single nucleotide polymorphism (SNP)-microRNA (miRNA) interaction network by comprehensive bioinformatics analysis, and search for novel biomarkers for prostate cancer.Materials and methods: mRNA, miRNA, and SNP data were acquired from Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify differentially expressed genes (DEGs) and miRNAs (DEMs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) analysis and expression quantitative trait loci (eQTL) analysis of DEGs were conducted. SNPs related to DEMs (miRSNPs) were downloaded from the open-source website MirSNP and PolymiRTS 3.0. TargetScan and miRDB databases were used for the target mRNA prediction of miRNA. The mRNA-SNP-miRNA interaction network was then constructed and visualized by Cytoscape 3.9.0. Selected key biomarkers were further validated using the Cancer Genome Atlas (TCGA) database. A nomogram model was constructed to predict the risk of prostate cancer.Results: In our study, 266 DEGs and 11 DEMs were identified. KEGG pathway analysis showed that DEGs were strikingly enriched in focal adhesion and PI3K-Akt signaling pathway. A total of 60 mRNA-SNP-miRNAs trios were identified to establish the mRNA-SNP-miRNA interaction network. Seven mRNAs in mRNA-SNP-miRNA network were consistent with the predicted target mRNAs of miRNA. These results were largely validated by the TCGA database analysis. A nomogram was constructed that contained four variables (ITGB8, hsa-miR-21, hsa-miR-30b and prostate-specific antigen (PSA) value) for predicting the risk of prostate cancer.Conclusion: Our study established the mRNA-SNP-miRNA interaction network in prostate cancer. The interaction network showed that hsa-miR-21, hsa-miR-30b, and ITGB8 may be utilized as new biomarkers for prostate cancer.

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