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利用基因表达微阵列预测卵巢癌的生物标志物。

Predicting biomarkers for ovarian cancer using gene-expression microarrays.

作者信息

Adib T R, Henderson S, Perrett C, Hewitt D, Bourmpoulia D, Ledermann J, Boshoff C

机构信息

Cancer Research UK Viral Oncology Group, Wolfson Institute for Biomedical Research, University College London, Cruciform Building, Gower Street, London WC1E 6BT, UK.

出版信息

Br J Cancer. 2004 Feb 9;90(3):686-92. doi: 10.1038/sj.bjc.6601603.

Abstract

Ovarian cancer has the highest mortality rate of gynaecological cancers. This is partly due to the lack of effective screening markers. Here, we used oligonucleotide microarrays complementary to approximately 12 000 genes to establish a gene-expression microarray (GEM) profile for normal ovarian tissue, as compared to stage III ovarian serous adenocarcinoma and omental metastases from the same individuals. We found that the GEM profiles of the primary and secondary tumours from the same individuals were essentially alike, reflecting the fact that these tumours had already metastasised and acquired the metastatic phenotype. We have identified a novel biomarker, mammaglobin-2 (MGB2), which is highly expressed specific to ovarian cancer. MGB2, in combination with other putative markers identified here, could have the potential for screening.

摘要

卵巢癌是妇科癌症中死亡率最高的。部分原因是缺乏有效的筛查标志物。在此,我们使用与约12000个基因互补的寡核苷酸微阵列,建立了正常卵巢组织的基因表达微阵列(GEM)图谱,并与同一患者的III期卵巢浆液性腺癌及网膜转移灶进行比较。我们发现,同一患者原发肿瘤和继发肿瘤的GEM图谱基本相似,这反映出这些肿瘤已经发生转移并获得了转移表型。我们鉴定出一种新型生物标志物——乳腺珠蛋白-2(MGB2),它在卵巢癌中高度特异性表达。MGB2与本文鉴定出的其他假定标志物相结合,可能具有筛查潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/656a/2409606/bfd3ba352412/90-6601603f1.jpg

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