首页> 美国卫生研究院文献>Analytical Cellular Pathology : the Journal of the European Society for Analytical Cellular Pathology >Microarray Analysis of Suppression Subtracted Hybridisation Libraries Identifies Genes Associated with Breast Cancer Progression
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Microarray Analysis of Suppression Subtracted Hybridisation Libraries Identifies Genes Associated with Breast Cancer Progression

机译:抑制扣除的杂交文库的微阵列分析确定与乳腺癌进展相关的基因

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摘要

Background: 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. Methods: 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. Results: 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. Conclusions: 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.
机译:背景:癌症研究的主要挑战是确定导致恶性转移表型发展的关键分子,而恶性转移表型是癌症死亡的主要原因。方法:构建四个消减的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微观解剖的乳腺癌和浸润性癌之间差异表达的mRNA。对来自该文库的数百个差异表达的cDNA进行微阵列,并用来自人乳腺肿瘤细胞系和临床标本的mRNA进行筛选。基因产物通过RT-PCR进一步检查,并与临床数据相关。结果:消减杂交和微阵列分析相结合已鉴定出一组15个cDNA,它们与雌激素受体状态,恶性肿瘤或复发密切相关。该组包括S100P,其与细胞系中的非整倍性和患者的复发/死亡有关,以及与雌激素受体和患者的复发有关的AGR2。 X-box结合蛋白1也是雌激素依赖性基因,与乳腺癌患者的更好生存相关。结论:减去的cDNA文库和微阵列分析相结合,从而确定了潜在的诊断/预后生物标志物和癌症治疗靶标,但尚未从常见的预后基因特征中鉴定出这些标志物。

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