The MTDH (-470G>A) polymorphism is associated with ovarian cancer susceptibility.

The MTDH (-470G>A) polymorphism is associated with ovarian cancer susceptibility.
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DOI:
10.1371/journal.pone.0051561
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Kong B
Kong B
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Yuan C;Li X;Yan S;Yang Q;Liu X;Kong B

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MTDH(metadherin)是一种重要的癌基因,在多种肿瘤中广泛表达,是肿瘤恶性程度的潜在生物标志物。MTDH的变异与乳腺癌的易感性有关。然而,没有研究评估MTDH基因多态性及其与卵巢癌易感性的潜在关系的报道。因此,我们使用序列分析研究了MTDH(− 470 G>A)多态性与145名卵巢癌患者和254名匹配对照受试者卵巢癌发生的相关性。我们发现MTDH(− 470 G>A)多态性与卵巢癌风险在统计学上相关(在加性遗传模型下,GG vs. GA vs. AA,P = 0.042)。  与G等位基因型(GG和GA)相比,AA基因型可能降低卵巢癌的发病风险(P = 0.0198,OR = 0.33,95% CI [0.12 <$0.78])。    与G等位基因相比,A等位基因对卵巢癌的风险具有保护作用(P = 0.01756,OR = 0.66,95%CI [0.46 ~ 0.93])。    此外,GG和GA+AA基因型与临床分期之间存在统计学显著相关性(P = 0.038)。  这些数据表明,MTDH(− 470 G>A)可能是评估卵巢癌风险和预测卵巢癌患者预后的有用分子标志物。
MTDH(metadherin), an important oncogene that is widely overexpressed in various cancers, is a potential biomarker of tumor malignancy. Variants in MTDH have been associated with susceptibility to breast cancer. However, no studies assessing MTDH gene polymorphisms and their potential relationship to ovarian cancer susceptibility have been reported. Thus, we investigated the association of MTDH (−470G>A) polymorphism with ovarian cancer development in 145 ovarian cancer patients and 254 matched control subjects, using sequence analysis. We found that the MTDH (−470G>A) polymorphism was statistically correlated with ovarian cancer risk (under the additive genetic model, GG vs. GA vs AA, P = 0.042). Compared with genotypes containing the G allele (GG and GA), the AA genotype may decrease the risk of ovarian cancer (P = 0.0198, OR = 0.33, 95% CI [0.12∼0.78]). Compared with the G allele, the A allele is protective against ovarian cancer risk (P = 0.01756, OR = 0.66, 95% CI [0.46∼0.93]). Furthermore, a statistically significant association between the GG and GA+AA genotypes and the clinical stage was observed (P = 0.038). These data suggest that MTDH (−470G>A) could be a useful molecular marker for assessing ovarian cancer risk and for predicting ovarian cancer patient prognosis.
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