6 research outputs found

    Identification of a three-gene expression signature of poor-prognosis breast carcinoma

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    BACKGROUND: The clinical course of breast cancer is difficult to predict on the basis of established clinical and pathological prognostic criteria. Given the genetic complexity of breast carcinomas, it is not surprising that correlations with individual genetic abnormalities have also been disappointing. The use of gene expression profiles could result in more accurate and objective prognostication. RESULTS: To this end, we used real-time quantitative RT-PCR assays to quantify the mRNA expression of a large panel (n = 47) of genes previously identified as candidate prognostic molecular markers in a series of 100 ERα-positive breast tumor samples from patients with known long-term follow-up. We identified a three-gene expression signature (BRCA2, DNMT3B and CCNE1) as an independent prognostic marker (P = 0.007 by univariate analysis; P = 0.006 by multivariate analysis). This "poor prognosis" signature was then tested on an independent panel of ERα-positive breast tumors from a well-defined cohort of 104 postmenopausal breast cancer patients treated with primary surgery followed by adjuvant tamoxifen alone: although this "poor prognosis" signature was associated with shorter relapse-free survival in univariate analysis (P = 0.029), it did not persist as an independent prognostic factor in multivariate analysis (P = 0.27). CONCLUSION: Our results confirm the value of gene expression signatures in predicting the outcome of breast cancer

    Expression analysis of mitotic spindle checkpoint genes in breast carcinoma: role of NDC80/HEC1 in early breast tumorigenicity, and a two-gene signature for aneuploidy

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    <p>Abstract</p> <p>Background</p> <p>Aneuploidy and chromosomal instability (CIN) are common abnormalities in human cancer. Alterations of the mitotic spindle checkpoint are likely to contribute to these phenotypes, but little is known about somatic alterations of mitotic spindle checkpoint genes in breast cancer.</p> <p>Methods</p> <p>To obtain further insight into the molecular mechanisms underlying aneuploidy in breast cancer, we used real-time quantitative RT-PCR to quantify the mRNA expression of 76 selected mitotic spindle checkpoint genes in a large panel of breast tumor samples.</p> <p>Results</p> <p>The expression of 49 (64.5%) of the 76 genes was significantly dysregulated in breast tumors compared to normal breast tissues: 40 genes were upregulated and 9 were downregulated. Most of these changes in gene expression during malignant transformation were observed in epithelial cells.</p> <p>Alterations of nine of these genes, and particularly <it>NDC80</it>, were also detected in benign breast tumors, indicating that they may be involved in pre-neoplastic processes.</p> <p>We also identified a two-gene expression signature (<it>PLK1 </it>+ <it>AURKA</it>) which discriminated between DNA aneuploid and DNA diploid breast tumor samples. Interestingly, some DNA tetraploid tumor samples failed to cluster with DNA aneuploid breast tumors.</p> <p>Conclusion</p> <p>This study confirms the importance of previously characterized genes and identifies novel candidate genes that could be activated for aneuploidy to occur. Further functional analyses are required to clearly confirm the role of these new identified genes in the molecular mechanisms involved in breast cancer aneuploidy. The novel genes identified here, and/or the two-gene expression signature, might serve as diagnostic or prognostic markers and form the basis for novel therapeutic strategies.</p

    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
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