Human Anti-Human TNFRSF17 monoclonal Antibody, clone SFB426 [Biotin]

We previously found that the haplotypes of TNFRSF17 single nucleotide polymorphisms (SNPs) were associated with the susceptibility to inflammatory bowel disease on Korean population. The present study aimed to investigate whether the polymorphisms in the TNFRSF17 gene are associated with susceptibility to colorectal cancer (CRC). Genotype analysis in the TNFRSF17 SNPs was performed by high-resolution melting and TaqMan probe analysis, and the genotype and allele frequencies of TNFRSF17 SNPs were compared between the CRC patients and the healthy controls. The haplotype frequencies of TNFRSF17 for multiple loci were estimated using the expectation maximization algorithm. Although, the genotype and allelic frequencies of these SNPs, in the colon cancer and rectal cancer patients, were not significantly different from those in the healthy controls, the genotype and allele frequency of g.2493G > A was significantly different between the healthy controls and the right colon cancer patients (P = 0.014 and 0.004, respectively). Moreover, the haplotypes frequencies in the healthy controls were significantly different from those in the colon cancer patients. Our results suggest that TNFRSF17 may be a candidate gene associated with the pathogenesis of colon cancer, and the haplotypes of the TNFRSF17 polymorphisms might be one of the markers for colon cancer susceptibility.

Objective. Production of pathogenic autoantibodies by self-reactive plasma cells (PCs) is a hallmark of autoimmune diseases. We undertook this study to investigate the prevalence of PCs and their relationship to known pathogenic pathways to increase our understanding of the role of PCs in disease progression and treatment response. Methods. We developed a sensitive gene expression-based method to overcome the challenges of measuring PCs using flow cytometry. Whole-genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA1, IGJ, IGKC, IGKV4-1, and TNFRSF17, expressed predominantly in PCs. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy, for evaluating the relationship between PCs and other autoimmune disease-related genes, and for estimating PC levels in affected blood and tissue from patients with multiple autoimmune diseases. Results. The PC signature was highly sensitive and capable of detecting a change in as few as 360 PCs. The PC signature was reduced more than 90% in scleroderma patients following anti-CD19 treatment, and this reduction was highly correlated (r = 0.80) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed that 30-35% of lupus and rheumatoid arthritis patients had increased levels of PCs. Conclusion. This newly developed PC signature provides a robust and accurate method of measuring PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases who may benefit from PC-depleting therapy.