Fátima Marín

Aromatic DNA adducts and polymorphisms in metabolic genes in healthy adults: findings from the EPIC-Spain cohort.

Aromatic compounds such as polycyclic aromatic hydrocarbons, arylamines and heterocyclic amines require metabolic activation to form metabolites able to bind to DNA, a process mediated by polymorphic enzymes. We measured aromatic DNA adducts in white blood cells by the (32)P-post-labelling assay in a sample of 296 healthy adults (147 men and 149 women) from five regions of Spain. We also analyzed functional polymorphisms in the metabolic genes CYP1A1, CYP1A2, EPHX1, GSTM1, GSTT1, NAT2 and SULT1A1. A significant increased level of DNA aromatic adducts was found related to the fast oxidation-hydrolysis phenotype defined by the polymorphism I462V in CYP1A1, the allele A in IVS1-154C>A of CYP1A2 and the combination Tyrosine-Arginine for Y113H and H139R of EPHX1. Geometric means (adducts per 10(-9) normal nucleotides) were 2.17, 4.04 and 6.30 for slow, normal and fast phenotypes, respectively (P-trend = 0.01). Slow acetylation by NAT2 was associated with a significant decrease in adduct level; subjects with slow alleles *5A and *7A/B had in average 1.56 x 10(-9)adducts, as compared with 5.60 for those with normal NAT2 activity (P-value = 0.01). No association was seen with polymorphisms of other metabolic genes such as GSTM1, GSTT1 or SULT1A1. We concluded that the metabolic pathways of oxidation, hydrolysis and acetylation are relevant to the formation of bulky DNA adducts. This could suggest a potential involvement of aromatic compounds in the formation of such adducts; however, given lack of specificity of the post-labeling assay, a firm conclusion cannot be drawn.

Simultaneous genotyping of GSTT1 and GSTM1 null polymorphisms by melting curve analysis in presence of SYBR Green I.

Due to their ability to metabolize xenobiotics, glutathione S-transferases (GSTs) play an important role in cellular protection. GST family members mu (GSTM1) and theta (GSTT1) exhibit a common polymorphism that results in the complete deletion of the gene (null allele). Homozygous deletions, which result in the absence of the enzyme, are considered a risk factor for several diseases, including cancer. We report a simple, low cost, and high throughput assay for the simultaneous analysis of the GSTM1 and GSTT1 null polymorphisms in a single step. The assay is based on multiplex real-time PCR in the presence of SYBR Green I and genotype discrimination by melting curve analysis in a LightCycler. We have genotyped 792 samples to compare this new approach with conventional PCR followed by gel electrophoresis. Comparison of the methods gave a good agreement, with kappa values of 0.88 for GSTM1 and 0.64 for GSTT1. Reanalysis of discrepant samples indicated that absence of amplification of the larger GSTT1 fragment by conventional PCR accounted for most of the discrepancies. Moreover, the improved amplification efficiency of the real-time PCR results in a significant reduction of missing values. Due to its simplicity and low cost, this assay is well suited for the rapid analysis of GST-null genotypes in studies that involve large number of samples.

Nanofluidic Digital PCR and Extended Genotyping of RAS and BRAF for Improved Selection of Metastatic Colorectal Cancer Patients for Anti-EGFR Therapies.

The clinical significance of low-frequent RAS pathway–mutated alleles and the optimal sensitivity cutoff value in the prediction of response to anti-EGFR therapy in metastatic colorectal cancer (mCRC) patients remains controversial. We aimed to evaluate the added value of genotyping an extended RAS panel using a robust nanofluidic digital PCR (dPCR) approach. A panel of 34 hotspots, including RAS (KRAS and NRAS exons 2/3/4) and BRAF (V600E), was analyzed in tumor FFPE samples from 102 mCRC patients treated with anti-EGFR therapy. dPCR was compared with conventional quantitative PCR (qPCR). Response rates, progression-free survival (PFS), and overall survival (OS) were correlated to the mutational status and the mutated allele fraction. Tumor response evaluations were not available in 9 patients and were excluded for response rate analysis. Twenty-two percent of patients were positive for one mutation with qPCR (mutated alleles ranged from 2.1% to 66.6%). Analysis by dPCR increased the number of positive patients to 47%. Mutated alleles for patients only detected by dPCR ranged from 0.04% to 10.8%. An inverse correlation between the fraction of mutated alleles and radiologic response was observed. ROC analysis showed that a fraction of 1% or higher of any mutated alleles offered the best predictive value for all combinations of RAS and BRAF analysis. In addition, this threshold also optimized prediction both PFS and OS. We conclude that mutation testing using an extended gene panel, including RAS and BRAF with a threshold of 1% improved prediction of response to anti-EGFR therapy. Mol Cancer Ther; 15(5); 1106–12. ©2016 AACR.