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Expression Patterns of Xenobiotic-Metabolizing Enzymes in Tumor and Adjacent Normal Mucosa Tissues among Patients with Colorectal Cancer: The ColoCare Study.
Beyerle, J, Holowatyj, AN, Haffa, M, Frei, E, Gigic, B, Schrotz-King, P, Boehm, J, Habermann, N, Stiborova, M, Scherer, D, et al
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2020;(2):460-469
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Abstract
BACKGROUND Xenobiotic-metabolizing enzymes (XME) play a critical role in the activation and detoxification of several carcinogens. However, the role of XMEs in colorectal carcinogenesis is unclear. METHODS We investigated the expression of XMEs in human colorectal tissues among patients with stage I-IV colorectal cancer (n = 71) from the ColoCare Study. Transcriptomic profiling using paired colorectal tumor and adjacent normal mucosa tissues of XMEs (GSTM1, GSTA1, UGT1A8, UGT1A10, CYP3A4, CYP2C9, GSTP1, and CYP2W1) by RNA microarray was compared using Wilcoxon rank-sum tests. We assessed associations between clinicopathologic, dietary, and lifestyle factors and XME expression with linear regression models. RESULTS GSTM1, GSTA1, UGT1A8, UGT1A10, and CYP3A4 were all statistically significantly downregulated in colorectal tumor relative to normal mucosa tissues (all P ≤ 0.03). Women had significantly higher expression of GSTM1 in normal tissues compared with men (β = 0.37, P = 0.02). By tumor site, CYP2C9 expression was lower in normal mucosa among patients with rectal cancer versus colon cancer cases (β = -0.21, P = 0.0005). Smokers demonstrated higher CYP2C9 expression levels in normal mucosa (β = 0.17, P = 0.02) when compared with nonsmokers. Individuals who used NSAIDs had higher GSTP1 tumor expression compared with non-NSAID users (β = 0.17, P = 0.03). Higher consumption of cooked vegetables (>1×/week) was associated with higher CYP3A4 expression in colorectal tumor tissues (β = 0.14, P = 0.007). CONCLUSIONS XMEs have lower expression in colorectal tumor relative to normal mucosa tissues and may modify colorectal carcinogenesis via associations with clinicopathologic, lifestyle, and dietary factors. IMPACT Better understanding into the role of drug-metabolizing enzymes in colorectal cancer may reveal biological differences that contribute to cancer development, as well as treatment response, leading to clinical implications in colorectal cancer prevention and management.
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Genome-Wide Prioritization and Transcriptomics Reveal Novel Signatures Associated With Thiazide Diuretics Blood Pressure Response.
Shahin, MH, Sá, AC, Webb, A, Gong, Y, Langaee, T, McDonough, CW, Riva, A, Beitleshees, AL, Chapman, AB, Gums, JG, et al
Circulation. Cardiovascular genetics. 2017;(1)
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Abstract
BACKGROUND Thiazide diuretics are among the most commonly prescribed antihypertensives. However, <50% of thiazide-treated patients achieve blood pressure (BP) control. Herein, we used different omics (genomics and transcriptomics) to identify novel biomarkers of thiazide diuretics BP response. METHODS AND RESULTS Genome-wide analysis included 228 white hypertensives with BP determined at baseline and after 9 weeks of hydrochlorothiazide. Single-nucleotide polymorphisms with P <5×10-5 were prioritized according to their biological function, using RegulomeDB, haploreg, and Genome-Wide Annotation of Variants. The results from the prioritization approach revealed rs10995 as the most likely functional single-nucleotide polymorphism, among single-nucleotide polymorphisms tested, that has been associated with hydrochlorothiazide BP response. The rs10995 G-allele was associated with better BP response to hydrochlorothiazide versus noncarriers (Δ systolic BP/Δ diastolic BP: -12.3/-8.2 versus -6.8/-3.5 mm Hg, respectively, Δ systolic BP P=3×10-4, Δ diastolic BP P=5×10-5). This association was replicated in independent participants treated with chlorthalidone. In addition, rs10995 G-allele was associated with increased mRNA expression of VASP (vasodilator-stimulated phosphoprotein). Moreover, baseline expression of the VASP mRNA was significantly higher in 25 good responders to hydrochlorothiazide compared with 25 poor responders (P=0.01). This finding was replicated in independent participants treated with chlorthalidone (P=0.04). Last, allelic-specific expression analysis revealed a significant but modest imbalance with rs10995 and rs10156, a single-nucleotide polymorphism in high linkage disequilibrium (r2=0.7) with rs10995, which both could contribute to the observed genetic effects by affecting VASP mRNA expression. CONCLUSIONS This study highlights the strength of using different omics to identify novel biomarkers of drug response and suggests VASP as a potential determinant of thiazide diuretics BP response. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00246519 and NCT01203852.
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A distinct metabolic signature of human colorectal cancer with prognostic potential.
Qiu, Y, Cai, G, Zhou, B, Li, D, Zhao, A, Xie, G, Li, H, Cai, S, Xie, D, Huang, C, et al
Clinical cancer research : an official journal of the American Association for Cancer Research. 2014;(8):2136-46
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Abstract
PURPOSE Metabolic phenotyping has provided important biomarker findings, which, unfortunately, are rarely replicated across different sample sets due to the variations from different analytical and clinical protocols used in the studies. To date, very few metabolic hallmarks in a given cancer type have been confirmed and validated by use of a metabolomic approach and other clinical modalities. Here, we report a metabolomics study to identify potential metabolite biomarkers of colorectal cancer with potential theranostic value. EXPERIMENTAL DESIGN Gas chromatography-time-of-flight mass spectrometry (GC-TOFMS)-based metabolomics was used to analyze 376 surgical specimens, which were collected from four independent cohorts of patients with colorectal cancer at three hospitals located in China and City of Hope Comprehensive Cancer Center in the United States. Differential metabolites were identified and evaluated as potential prognostic markers. A targeted transcriptomic analysis of 29 colorectal cancer and 27 adjacent nontumor tissues was applied to analyze the gene expression levels for key enzymes associated with these shared metabolites. RESULTS A panel of 15 significantly altered metabolites was identified, which demonstrates the ability to predict the rate of recurrence and survival for patients after surgery and chemotherapy. The targeted transcriptomic analysis suggests that the differential expression of these metabolites is due to robust metabolic adaptations in cancer cells to increased oxidative stress as well as demand for energy, and macromolecular substrates for cell growth and proliferation. CONCLUSIONS These patients with colorectal cancer, despite their varied genetic background, mutations, pathologic stages, and geographic locations, shared a metabolic signature that is of great prognostic and therapeutic potential.
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The impact of self-identified race on epidemiologic studies of gene expression.
Sharma, S, Murphy, A, Howrylak, J, Himes, B, Cho, MH, Chu, JH, Hunninghake, GM, Fuhlbrigge, A, Klanderman, B, Ziniti, J, et al
Genetic epidemiology. 2011;(2):93-101
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Abstract
Although population differences in gene expression have been established, the impact on differential gene expression studies in large populations is not well understood. We describe the effect of self-reported race on a gene expression study of lung function in asthma. We generated gene expression profiles for 254 young adults (205 non-Hispanic whites and 49 African Americans) with asthma on whom concurrent total RNA derived from peripheral blood CD4(+) lymphocytes and lung function measurements were obtained. We identified four principal components that explained 62% of the variance in gene expression. The dominant principal component, which explained 29% of the total variance in gene expression, was strongly associated with self-identified race (P<10(-16)). The impact of these racial differences was observed when we performed differential gene expression analysis of lung function. Using multivariate linear models, we tested whether gene expression was associated with a quantitative measure of lung function: pre-bronchodilator forced expiratory volume in one second (FEV(1)). Though unadjusted linear models of FEV(1) identified several genes strongly correlated with lung function, these correlations were due to racial differences in the distribution of both FEV(1) and gene expression, and were no longer statistically significant following adjustment for self-identified race. These results suggest that self-identified race is a critical confounding covariate in epidemiologic studies of gene expression and that, similar to genetic studies, careful consideration of self-identified race in gene expression profiling studies is needed to avoid spurious association.