Anti-SDHC monoclonal antibody, clone FQS22146(C)

Background: Recent findings have shown that up to 60% of pheochromocytomas (PCCs) and paragangliomas (PGLs) are caused by germline or somatic mutations in one of the 11 hitherto known susceptibility genes: SDHA, SDHB, SDHC, SDHD, SDHAF2, VHL, HIF2A (EPAS1), RET, NF1, TMEM127 and MAX. This list of genes is constantly growing and the 11 genes together consist of 144 exons. A genetic screening test is extensively time consuming and expensive. Hence, we introduce next-generation sequencing (NGS) as a time-efficient and cost-effective alternative. Methods: Tumour lesions from three patients with apparently sporadic PCC were subjected to whole exome sequencing utilizing Agilent Sureselect target enrichment system and Illumina Hi seq platform. Bioinformatics analysis was performed in-house using commercially available software. Variants in PCC and PGL susceptibility genes were identified. Results: We have identified 16 unique genetic variants in PCC susceptibility loci in three different PCC, spending less than a 30-min hands-on, in-house time. Two patients had one unique variant each that was classified as probably and possibly pathogenic: NF1 Arg304Ter and RET Tyr791Phe. The RET variant was verified by Sanger sequencing. Conclusions: NGS can serve as a fast and cost-effective method in the clinical genetic screening of PCC. The bioinformatics analysis may be performed without expert skills. We identified process optimization, characterization of unknown variants and determination of additive effects of multiple variants as key issues to be addressed by future studies.

Introduction: Non-small cell lung cancer (NSCLC) is characterized by poor prognosis and only a few molecular markers may be potentially used to predict the outcome. Metabolic reprogramming is a hallmark of cancer, including the alterations of tricarboxylic acid (TCA) cycle key enzymes. However, the significance of single nucleotide polymorphisms (SNPs) in genes encoding these key enzymes has not been investigated in NSCLC. Patients and methods: In this study, we genotyped 18 potentially functional SNPs in 7 genes belonging to 3 TCA cycle enzyme families (SDH, FH and IDH) using Sequenom iPLEX genotyping system in a cohort of 500 NSCLC patients. Multivariate Cox proportional hazards model and Kaplan-Meier curve were used for the survival analysis. Results: Our results showed that SDHC gene: SNP rs12064957, IDH2 gene: SNP rs11540478 and FH gene: SNP rs1414493 were associated with overall survival (OS) and SDHA gene: SNP rs13173911, IDH2 gene: SNP rs4932158 were associated with recurrence-free survival (RFS) of NSCLC patients. Unfavorable genotypes of these SNPs showed a significant cumulative effect on OS and RFS of NSCLC patients (both P < 0.001). Furthermore, survival tree analysis indicated that FH: rs1414493 was the primary risk factor contributing to OS of NSCLC patients and the IDH2: rs4932158 was the primary risk factor contributing to RFS of NSCLC patients. Conclusion: Our data suggest that SNPs in TCA cycle key enzyme genes may serve as potential biomarkers to predict the outcomes of NSCLC. Further studies with different ethnicities are needed to validate our findings and generalize their clinical utility. (C) 2014 Elsevier Ireland Ltd. All rights reserved.