51 research outputs found

    The significance of c.690G>T polymorphism (rs34529039) and expression of the CEBPA gene in ovarian cancer outcome

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    The CEBPA gene is known to be mutated or abnormally expressed in several cancers. This is the first study assessing the clinical impact of CEBPA gene status and expression on the ovarian cancer outcome. The CEBPA gene sequence was analyzed in 118 ovarian cancer patients (44 platinum/cyclophosphamide (PC)-treated and 74 taxane/platinum (TP)-treated), both in tumors and blood samples, and in blood from 236 healthy women, using PCR-Sanger sequencing and Real-Time quantitative PCR (qPCR)-based genotyping methods, respectively. The CEBPA mRNA level was examined with Reverse Transcription quantitative PCR (RT-qPCR). The results were correlated to different clinicopathological parameters. Thirty of 118 (25.4%) tumors harbored the CEBPA synonymous c.690G>T polymorphism (rs34529039), that we showed to be related to up-regulation of CEBPA mRNA levels (p=0.0059). The presence of the polymorphism was significantly associated with poor prognosis (p=0.005) and poor response to the PC chemotherapy regimen (p=0.024). In accordance, elevated CEBPA mRNA levels negatively affected patient survival (pT, p.(Thr230Thr) (rs34529039) polymorphism of the CEBPA gene, together with up-regulation of its mRNA expression, are negative factors worsening ovarian cancer outcome. Their adverse clinical effect depends on a therapeutic regimen used, which might make them potential prognostic and predictive biomarkers for response to DNA-damaging chemotherapy

    Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

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    Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR=1.33, p=4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR=1.07, p=0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR=0.90, p=0.00033; rs927062, OR =0.94, p=0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations

    Evaluating the ovarian cancer gonadotropin hypothesis: a candidate gene study

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    OBJECTIVE: Ovarian cancer is a hormone-related disease with a strong genetic basis. However, none of its high-penetrance susceptibility genes and GWAS-identified variants to date are known to be involved in hormonal pathways. Given the hypothesized etiologic role of gonadotropins, an assessment of how variability in genes involved in the gonadotropin signaling pathway impacts disease risk is warranted.METHODS: Genetic data from 41 ovarian cancer study sites were pooled and unconditional logistic regression was used to evaluate whether any of the 2185 SNPs from 11 gonadotropin signaling pathway genes was associated with ovarian cancer risk. A burden test using the admixture likelihood (AML) method was also used to evaluate gene-level associations.RESULTS: We did not find any genome-wide significant associations between individual SNPs and ovarian cancer risk. However, there was some suggestion of gene-level associations for four gonadotropin signaling pathway genes: INHBB (p=0.045, mucinous), LHCGR (p=0.046, high-grade serous), GNRH (p=0.041, high-grade serous), and FSHB (p=0.036, overall invasive). There was also suggestive evidence for INHA (p=0.060, overall invasive).CONCLUSIONS: Ovarian cancer studies have limited sample numbers, thus fewer genome-wide susceptibility alleles, with only modest associations, have been identified relative to breast and prostate cancers. We have evaluated the majority of ovarian cancer studies with biological samples, to our knowledge, leaving no opportunity for replication. Using both our understanding of biology and powerful gene-level tests, we have identified four putative ovarian cancer loci near INHBB, LHCGR, GNRH, and FSHB that warrant a second look if larger sample sizes and denser genotype chips become available<br/
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