Anti-FCGR2A monoclonal antibody [FITC]

We aimed to investigate whether the PTPRC rs10919563 A/G and Fc gamma receptor 2A (FCGR2A) R131H polymorphisms can predict the response to anti-TNF therapy in rheumatoid arthritis (RA) patients. We conducted a meta-analysis of studies on the association between the PTPRC rs10919563 A/G or the FCGR2A R131H polymorphism and responsiveness to anti-TNF therapy in RA patients. Eighteen studies (twelve on PTPRC and six on FCGR2A) from eight articles involving 3058 patients were considered in this meta-analysis. The meta-analysis showed a significant association between the PTPRC rs10919563 A allele and response to TNF-alpha blockers in RA. The OR of the PTPRC A allele was significantly lower in responders (OR = 0.584, 95 % CI = 0.409-0.835, P = 0.003). Meta-analysis revealed no association between the FCGR2A HH + HR genotype and responsiveness to TNF blockers in all study subjects (OR = 0.762, 95 % CI = 0.543-1.068, P = 0.115). However, stratification by TNF inhibitor type showed that the FCGR2A HH + HR genotype was associated with responsiveness to adalimumab (OR = 0.591, 95 % CI = 0.369-0.947, P = 0.029), but not infliximab and etanercept (OR = 0.929, 95 % CI = 0.354-2.440, P = 0.881; OR = 0.804, 95 % CI = 0.293-2.207, P = 0.673). The PTPRC rs10919563 A allele shows a poor response to anti-TNF therapy, and the FCGR2A HH + HR genotype shows a poor response to adalimumab for RA. Genotyping for these polymorphisms may be useful for predicting the response to TNF-alpha blockers with respect to personalized medicine.

Background: In recent studies, microRNAs have been demonstrated as stable detectable biomarkers in blood for cancer. In addition, computer-aided biomarker discovery has now become an attractive paradigm for precision diagnosis. Methods: In this study, we identified and evaluated miR-139-3p as a biomarker for screening of esophageal squamous cell carcinoma using the Cancer Genome Atlas and Gene Expression Omnibus database analyses. We identified possible miR-139-3p target genes through the predicted database and esophageal squamous cell carcinoma upregulated genes from the Cancer Genome Atlas and Gene. Bioinformatics analysis was performed to determine key miR-139-3p targets and pathways associated with esophageal carcinoma. Finally, the expression and expected significance of hub genes were evaluated via the Genotype-Tissue Expression project. Results: MiR-139-3p was significantly downregulated in patients with esophageal squamous cell carcinoma/esophageal carcinoma. In GSE 122497, the area under the curve-receiver operating characteristic value, sensitivity, and specificity for serum miR-139-3p were 0.754, 67.49%, and 80.00%, respectively. The pattern specification process, skeletal system development, and regionalization process were the most enriched interactions in esophageal carcinoma. In addition, Epstein-Barr virus infection, human T-cell leukemia virus 1 infection, and human cytomegalovirus infection were identified as crucial pathways. Six hub genes (CD1A, FCGR2A, ANPEP, CD1B, membrane metalloendopeptidase, and TWIST1) were found, and FCGR2A and membrane metalloendopeptidase were further confirmed by genotype-tissue expression. High expression of membrane metalloendopeptidase correlated with a better overall survival but not with disease-free survival of patients with esophageal carcinoma. Conclusions: MiR-139-3p was identified as a candidate biomarker for predicting esophageal squamous cell carcinoma based on network analysis. MiR-139-3p acted as a tumor suppressor by targeting membrane metalloendopeptidase in esophageal carcinoma, and low expression of membrane metalloendopeptidase may indicate a better prognosis of patients with esophageal carcinoma.