Anti-IFNG monoclonal antibody, clone 5T.C4 [PerCP/Cy5.5®]

Background: Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies in urinary system. However, there are still no reliable biomarkers for the diagnosis and prognosis of ccRCC. In this study, we aimed to screen candidate biomarkers and potential therapeutic targets for ccRCC. Methods: Differentially expressed genes (DEGs) were screened using NetworkAnalyst. Protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) were utilized to identify hub genes. Then, we assessed the prognostic and diagnostic values of hub genes to screen candidate biomarkers. Gene Set Enrichment Analysis (GSEA) was applied to reveal potential mechanisms of candidate biomarkers in ccRCC. Oncomine database and The Human Protein Atlas were used to verify the expression of candidate biomarkers online. In addition, qRT-PCR, Enzyme linked immunosorbent assay (ELISA) and Immunohistochemistry (IHC) assays were performed to validate the expression level of candidate biomarkers in ccRCC cells and tissues. Results: A total of 771 genes were identified as DEGs. GO function analysis showed that DEGs were mostly enriched in excretion, apical part of cell and monovalent inorganic cation transmembrane transporter activity. KEGG pathway analysis demonstrated that DEGs were mostly involved in Neuroactive ligand-receptor interaction. After utilizing PPI network and WGCNA, nine genes (IFNG, CXCR3, PMCH, CD2, FASLG, CXCL13, CD8A, CD3D and GZMA) were identified as the hub genes. Moreover, survival analysis exhibited that high expression of CXCL13 predicted poor survival in both overall survival (OS) and disease free survival (DFS). The ROC curves indicated that CXCL13 could distinguish ccRCC samples from normal kidney samples. High expression of CXCL13 group was mostly associated with RB and MEL18 pathways by GSEA. Furthermore, qRT-PCR, ELISA and IHC results showed that the expression of CXCL13 was elevated in ccRCC. Conclusions: Our study illustrated that CXCL13 had good diagnostic and prognostic value, which may become a candidate biomarker and therapeutic target for ccRCC.

BackgroundTreatments for autoimmune diseases aim to dampen autoreactivity while preserving normal immune function. In CD4(+) T cells, the transcription factor Oct1/Pou2f1 is a dispensable transcription factor for T cell development and response to primary infection, but promotes expression of target genes, including Il2 and Ifng, under conditions of antigen reencounter. As a result, they are more strongly expressed upon secondary stimulation. Such repeated antigen encounters occur in memory recall responses, in autoimmunity where self-antigen can be recognized multiple times, and in chronic infection where foreign antigen is persistent. Based on these previous findings, we hypothesized that Oct1 loss would protect animals from autoimmunity but maintain normal responses to pathogens in the CNS.ObjectiveWe used a conditional mouse Oct1 (Pou2f1) allele and a CD4-Cre driver to determine the effect of T cell-specific Oct1 loss on autoimmune- and viral-induced neuroinflammation using an autoantigen-driven EAE model of autoimmunity and a JHMV model of viral infection.ResultsOct1 conditional deletion mitigated clinical scores and reduced infiltrating T cells and cytokine production in the EAE model. Consistently, Oct1-deficient CD4(+) T cells stimulated in vitro showed increased expression of markers associated with T cell anergy, particularly in the absence of co-stimulatory signals. In contrast, anti-viral T cell effector functions are intact in the absence of Oct1, with no changes in neuroinflammation, infiltrating T cells or cytokine production.ConclusionOur findings uncover a significant difference between the effect of Oct1 loss on autoimmune and anti-pathogen responses, which potentially could be exploited for therapeutic benefit.