Differential gene expression in ovarian carcinoma - Identification of potential biomarkers
Differential gene expression in ovarian carcinoma - Identification of potential biomarkers
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DOI：
10.1016/s0002-9440(10)63306-8
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发表时间：
2004-08-01
影响因子：
6
通讯作者：
Skubitz, APN
中科院分区：
文献类型：
--
作者：
Hibbs, K;Skubitz, KM;Skubitz, APN
卵巢癌仍然是美国妇女癌症死亡的第五大原因。在这项研究中，基因逻辑公司使用Affymetrix基因芯片HU_95阵列检测了20例卵巢癌、17例转移到网膜的卵巢癌和50例正常卵巢的基因表达，该阵列含有相似的12,000个已知基因。与正常卵巢和卵巢癌转移相比，卵巢癌中基因表达的差异被量化为基因表达的倍数变化。与300多个其他正常和病变组织样本相比，卵巢癌组织样本中的基因上调被确定。选择7个基因进行免疫组化进一步筛选，以确定蛋白的存在和定位。这7个基因分别是：β 8整合素亚基、骨形态发生蛋白-7、claudin-4、IX型胶原α 2、细胞维甲酸结合蛋白-1、叉头盒J1、S100钙结合蛋白A1。统计分析表明，beta8整合素亚基、claudin-4和S100A1对卵巢癌和正常卵巢组织的区分效果最好，可能是研究的7个基因中最好的候选肿瘤标志物。这些结果表明，进一步探索其他上调基因可能会在卵巢癌中发现新的诊断、治疗和/或预后生物标志物。
Ovarian cancer remains the fifth leading cause of cancer death for women in the United States. In this study, the gene expression of 20 ovarian carcinomas, 17 ovarian carcinomas metastatic to the omentum, and 50 normal ovaries was determined by Gene Logic Inc. using Affymetrix GeneChip HU_95 arrays containing similar to12,000 known genes. Differences in gene expression were quantified as fold changes in gene expression in ovarian carcinomas compared to normal ovaries and ovarian carcinoma metastases. Genes up-regulated in ovarian carcinoma tissue samples compared to more than 300 other normal and diseased tissue samples were identified. Seven genes were selected for further screening by immunohistochemistry to determine the presence and localization of the proteins. These seven genes were: the beta8 integrin subunit, bone morphogenetic protein-7, claudin-4, collagen type IX alpha2, cellular retinoic acid binding protein-1, forkhead box J1, and S100 calcium-binding protein A1. Statistical analyses showed that the beta8 integrin subunit, claudin-4, and S100A1 provided die best distinction between ovarian carcinoma and normal ovary tissues, and may serve as the best candidate tumor markers among the seven genes studied. These results suggest that further exploration into other up-regulated genes may identify novel diagnostic, therapeutic, and/or prognostic biomarkers in ovarian carcinoma.