Barraclough Dong Liu, Sewart Susan, Rudland Philip S, Shoker Balvinder S, Sibson D Ross, Barraclough Roger, Davies Michael P A
Cancer Tissue Bank Research Centre, University of Liverpool, Liverpool, UK School of Biological Sciences, University of Liverpool, Liverpool, UK.
Cell Oncol. 2010;32(1-2):87-99. doi: 10.3233/CLO-2009-0499.
A major challenge of cancer research is to identify key molecules which are responsible for the development of the malignant metastatic phenotype, the major cause of cancer death.
Four subtracted cDNA libraries were constructed representing mRNAs differentially expressed between benign and malignant human breast tumour cells and between micro-dissected breast carcinoma in situ and invasive carcinoma. Hundreds of differentially expressed cDNAs from the libraries were micro-arrayed and screened with mRNAs from human breast tumor cell lines and clinical specimens. Gene products were further examined by RT-PCR and correlated with clinical data.
The combination of subtractive hybridisation and microarray analysis has identified a panel of 15 cDNAs which shows strong correlations with estrogen receptor status, malignancy or relapse. This panel included S100P, which was associated with aneuploidy in cell lines and relapse/death in patients, and AGR2 which was associated with estrogen receptor and with patient relapse. X-box binding protein-1 is also an estrogen-dependent gene and is associated with better survival for breast cancer patients.
The combination of subtracted cDNA libraries and microarray analysis has thus identified potential diagnostic/prognostic biomarkers and targets for cancer therapy, which have not been identified from common prognostic gene signatures.
癌症研究的一项重大挑战是识别导致恶性转移表型(癌症死亡的主要原因)发展的关键分子。
构建了四个消减cDNA文库,分别代表在良性和恶性人乳腺肿瘤细胞之间以及在显微切割的原位乳腺癌和浸润性癌之间差异表达的mRNA。从这些文库中挑选出数百个差异表达的cDNA进行微阵列分析,并用来自人乳腺肿瘤细胞系和临床标本的mRNA进行筛选。通过逆转录聚合酶链反应(RT-PCR)进一步检测基因产物,并将其与临床数据相关联。
消减杂交和微阵列分析相结合,鉴定出一组15个cDNA,它们与雌激素受体状态、恶性程度或复发密切相关。该组包括S100P,它与细胞系中的非整倍体以及患者的复发/死亡相关;还有AGR2,它与雌激素受体以及患者复发相关。X盒结合蛋白1也是一个雌激素依赖性基因,与乳腺癌患者的较好生存率相关。
因此,消减cDNA文库和微阵列分析相结合,已鉴定出潜在的诊断/预后生物标志物以及癌症治疗靶点,这些是从常见的预后基因特征中未发现的。