61 research outputs found

    Relationship between intratumoral expression of genes coding for xenobiotic-metabolizing enzymes and benefit from adjuvant tamoxifen in estrogen receptor alpha-positive postmenopausal breast carcinoma

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    INTRODUCTION: Little is known of the function and clinical significance of intratumoral dysregulation of xenobiotic-metabolizing enzyme expression in breast cancer. One molecular mechanism proposed to explain tamoxifen resistance is altered tamoxifen metabolism and bioavailability. METHODS: To test this hypothesis, we used real-time quantitative RT-PCR to quantify the mRNA expression of a large panel of genes coding for the major xenobiotic-metabolizing enzymes (12 phase I enzymes, 12 phase II enzymes and three members of the ABC transporter family) in a small series of normal breast (and liver) tissues, and in estrogen receptor alpha (ERα)-negative and ERα-positive breast tumors. Relevant genes were further investigated in a well-defined cohort of 97 ERα-positive postmenopausal breast cancer patients treated with primary surgery followed by adjuvant tamoxifen alone. RESULTS: Seven of the 27 genes showed very weak or undetectable expression in both normal and tumoral breast tissues. Among the 20 remaining genes, seven genes (CYP2A6, CYP2B6, FMO5, NAT1, SULT2B1, GSTM3 and ABCC11) showed significantly higher mRNA levels in ERα-positive breast tumors than in normal breast tissue, or showed higher mRNA levels in ERα-positive breast tumors than in ERα-negative breast tumors. In the 97 ERα-positive breast tumor series, most alterations of these seven genes corresponded to upregulations as compared with normal breast tissue, with an incidence ranging from 25% (CYP2A6) to 79% (NAT1). Downregulation was rare. CYP2A6, CYP2B6, FMO5 and NAT1 emerged as new putative ERα-responsive genes in human breast cancer. Relapse-free survival was longer among patients with FMO5-overexpressing tumors or NAT1-overexpressing tumors (P = 0.0066 and P = 0.000052, respectively), but only NAT1 status retained prognostic significance in Cox multivariate regression analysis (P = 0.0013). CONCLUSIONS: Taken together, these data point to a role of genes coding for xenobiotic-metabolizing enzymes in breast tumorigenesis, NAT1 being an attractive candidate molecular predictor of antiestrogen responsiveness

    Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family

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    <p>Abstract</p> <p>Background</p> <p>Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.</p> <p>Methods</p> <p>We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.</p> <p>Results</p> <p>We demonstrate that the two separately introduced ER<sup>- </sup>breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.</p> <p>Conclusion</p> <p>We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.</p

    Hypericum sp.: essential oil composition and biological activities

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    Phytochemical composition of Hypericum genus has been investigated for many years. In the recent past, studies on the essential oils (EO) of this genus have been progressing and many of them have reported interesting biological activities. Variations in the EO composition of Hypericum species influenced by seasonal variation, geographic distribution, phenological cycle and type of the organ in which EO are produced and/or accumulated have also been reported. Although many reviews attributed to the characterization as well as biological activities of H. perforatum crude extracts have been published, no review has been published on the EO composition and biological activities of Hypericum species until recently (Crockett in Nat Prod Commun 5(9):1493–1506, 2010; Bertoli et al. in Global Sci Books 5:29–47, 2011). In this article, we summarize and update information regarding the composition and biological activities of Hypericum species EO. Based on experimental work carried out in our laboratory we also mention possible biotechnology approaches envisaging EO improvement of some species of the genus.Fundação para a Ciência e a Tecnologia (FCT) - project PTDC/AGR AAM/70418/2006, SFRH/BD/ 13283/2003
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