Anti-IL17A Monoclonal antibody, Alexa Fluor® 488

Interleukin 17 (IL-17) plays important roles in the progression of asthma. Genetic variants in the 11-17 may influence the immunopathogenesis of many diseases. Many studies have investigated the relevance of IL-17 polymorphism with cancers or immune diseases, including asthma. In this study, single nucleotide polymorphisms (SNPs) of IL-17 were explored by PCR-RFLP and verified by sequencing method. The frequencies of genotypes and alleles were analyzed. Haplotypes were analyzed with the SHEsis online program. The relationship between the genotypes of SNPs and IgE level was also investigated. The False Discovery Rate (FDR) correction was performed (P-adjusted < 0.05). The frequencies of A allele, GA and (GA + AA) genotype of rs3748067 were significantly higher in asthma patients. As for rs763780, the C allele in patients was more frequent than healthy controls. In addition, we found C carriers (CT + CC) were significantly higher in asthma patients. We further found that the haplotype CT for IL-17F (rs763780/rs2397084) was associated with an increased susceptibility of asthma, but this association did not survive after FDR correction. The level of serum total IgE in mutant group (GA + AA) of rs3748067 was significantly higher than the wild genotype (GG) group and control group. These results suggested that IL-17 SNPs, but not haplotypes may be associated with the susceptibility of asthma in Chinese Han population from central China.

Objective To evaluate the predictive value of genetic polymorphisms in the context of bacille Calmette-Guerin (BCG) immunotherapy outcome and create a predictive profile that may allow discrimination of the risk of recurrence. Patients and Methods In a dataset of 204 patients treated with BCG, we evaluated 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY (R) technology. Stepwise multivariate Cox regression was used for data mining. Results In agreement with previous studies we found that gender, age, tumour multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules [single nucleotide polymorphisms in tumour necrosis factor a (TNFA)-1031T/C (rs1799964), interleukin 2 receptor a (IL2RA) rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, intercellular adhesion molecule 1 (ICAM-1) K469E (rs5498), Fas ligand (FASL)-844T/C (rs763110) and TNF-related apoptosis-inducing ligand receptor 1 (TRAILR1)-397T/G (rs79037040)] in association with clinicopathological variables. This risk score allows the categorisation of patients into risk groups: patients within the low-risk group have a 90% chance of successful treatment, whereas patients in the high-risk group present a 75% chance of recurrence after BCG treatment. Conclusion We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.