Role of genetic and nongenetic factors for fluorouracil treatment-related severe toxicity: a prospective clinical trial by the German 5-FU Toxicity Study Group

PURPOSE: To assess the predictive value of polymorphisms in dihydropyrimidine dehydrogenase (DPYD ), thymidylate synthase (TYMS ), and methylene tetrahydrofolate reductase (MTHFR ) and of nongenetic factors for severe leukopenia, diarrhea, and mucositis related to fluorouracil (FU) treatment. PATIENTS AND METHODS: A multicenter prospective clinical trial included 683 patients with cancer treated with FU monotherapy. Toxicity was documented according to World Health Organization grades. DPYD, TYMS, and MTHFR genotypes were determined, and DPYD was resequenced in patients with severe toxicity. RESULTS: Grade 3 to 4 toxicity occurred in 16.1% of patients. The sensitivity of DPYD*2A genotyping for overall toxicity was 5.5% (95%CI, 0.02 to 0.11), with a positive predictive value of 0.46 (95% CI, 0.19 to 0.75; P = .01). Inclusion of additional DPYD variants improved prediction only marginally. Analysis according to toxicity type revealed significant association of DPYD with mucositis and leukopenia, whereas TYMS was associated with diarrhea. Genotype, female sex, mode of FU administration, and modulation by folinic acid were identified as independent risk factors by multivariable analysis. A previously unrecognized significant interaction was found between sex and DPYD, which resulted in an odds ratio for toxicity of 41.8 for male patients (95% CI, 9.2 to 190; P < .0001) but only 1.33 (95% CI, 0.34 to 5.2) in female patients. Homozygosity for the TYMS enhancer region double repeat allele increased risk for toxicity 1.6-fold (95% CI, 1.08 to 2.22; P = .02). CONCLUSION: DPYD, TYMS, and MTHFR play a limited role for FU related toxicity but a pronounced DPYD gene/sex-interaction increases prediction rate for male patients. Toxicity risk assessment should include sex, mode of administration, and folinic acid as additional predictive factor

Products of Abiotic U(VI) Reduction by Biogenic Fe(II)-Bearing Minerals

No abstract available

Products of Abiotic U(VI) Reduction by Biogenic Fe(II)-Bearing Minerals

No abstract available

The CYP1B1_1358_GG genotype is associated with estrogen receptor-negative breast cancer.

Cytochrome P450 1B1 (CYP1B1) is a major enzyme in the initial catabolic step of estradiol (E2) metabolism and belongs to the multitude of genes regulated by the estrogen receptor alpha (ERalpha). The common non-synonymous polymorphisms CYP1B1_1358_A&gt;G and CYP1B1_1294_C&gt;G increase CYP1B1 enzymatic activity. Given a relationship between CYP1B1 and breast tumor E2 level as well as E2 level and breast tumor ERalpha expression it is of interest to know whether CYP1B1 polymorphisms have an impact on the ERalpha status of breast cancer. We genotyped the GENICA population-based breast cancer case-control collection (1,021 cases, 1,015 controls) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and investigated in cases the association between genotypes and tumor ERalpha status (739 ERalpha positive cases; 212 ERalpha negative cases) by logistic regression. We observed a significant association between the homozygous variant CYP1B1_1358_GG genotype and negative ERalpha status (P = 0.005; OR 2.82, 95% CI: 1.37-5.82) with a highly significant Ptrend for CYP1B1_1358_A&gt;G and negative ERalpha status (P = 0.003). We also observed an association of CYP1B1_1358_GG and negative PR status (P = 0.015; OR 2.36, 95% CI: 1.18-4.70) and a Ptrend of 0.111 for CYP1B1_1358_A&gt;G and negative progesterone receptor (PR) status. We conclude that the CYP1B1_1358_A&gt;G polymorphism has an impact on ERalpha status in breast cancer in that the CYP1B1_1358_GG genotype known to encode higher CYP1B1 activity is associated with ERalpha negativity

Polymorphic loci of E2F2, CCND1 and CCND3 are associated with HER2 status of breast tumors.

Overexpression of the human epidermal growth factor receptor 2 (HER2) in breast tumors is associated with bad prognosis. Therefore, it is highly relevant to further improve understanding of the regulatory mechanisms of HER2 expression. In addition to gene amplification, transcriptional regulation plays a crucial role in HER2 overexpression. In this study, we analyzed 3 polymorphisms E2F2_-5368-A&gt;G, CCND1-870-A&gt;G and CCND3_-677_C&gt;T located in genes involved in cell cycle regulation in the GENICA population-based and age-matched breast cancer case-control study from Germany. We genotyped 1,021 cases and 1,015 controls by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Statistical analyses were performed by conditional logistic regression. We observed no differences in genotype frequencies between breast cancer cases and controls. Subgroup analysis showed associations between carriers of the E2F2_-5368_G allele (OR: 0.60, 95% CI: 0.42-0.85), carriers of the (C) over bar CND (1) over bar _870 G allele (OR: 0.66, 95% CI: 0.45-0.96) and carriers of the -CC (N) over bar D3_-677_T allele (OR: 1.72, 95% CI: 1.20-2.49) and HER2 expression in breast tumors. This finding points to an association of an increased expression of these cell cycle regulators with lower expression of HER2. An explanation for this observation might be that low expression of E2F2, CCND1 and CCND3 decrease levels of factors down-regulating HER2. We conclude that the analyzed polymorphisms located in E2F2, CCND1 and CCAID3 are potential markers for HER2 status of breast tumors

Breast cancer: A candidate gene approach across the estrogen metabolic pathway.

Polymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for their potential contribution to breast cancer risk. Of these CYP17A1, CYP19A1, EPHX1, HSD17B1, SRD5A2, and PPARG2 participate in biosynthesis, CYP1A1, CYP1B1, COMT, GSTP1, and SOD2 in catabolism and detoxification. We performed a population-based case-control study with 688 incident breast cancer cases and 724 controls from Germany and genotyped 18 polymorphisms by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR based RFLP (restriction fragment length polymorphism), and TaqMan allelic discrimination. Genotype frequencies were compared between cases and controls and odds ratios were calculated by conditional logistic regression. Further statistical analyses were based on cluster analysis, multifactor dimensionality reduction, logic regression, and global testing. Single factor analyses pointed to CYP1B1_1294_GG as a possible breast cancer risk modulator (OR = 2.57; 95% CI: 1.34-4.93) and two way stratification suggested associations between BMI &gt; or = 30 kg/m(2) and COMT_472_GG (P = 0.0076 and P = 0.0026), BMI &lt; 20 kg/m(2) and HSD17B1_937_GG (P = 0.0082) as well as CYP17A1_-34_CC and HRT use &gt; or =10 years (P = 0.0063). Following correction for multiple testing none of these associations remained significant. No significant association between breast cancer risk and genetic polymorphisms was observed in multifactor analyses. The tested polymorphisms of the estrogen metabolic pathway may not play a direct role in breast cancer risk. Therefore, future association studies should be extended to other polymorphisms and other regulatory pathways