Smith Laura, Watson Mark B, O'Kane Sara L, Drew Philip J, Lind Michael J, Cawkwell Lynn
Cancer Biology Proteomics Group, Postgraduate Medical Institute of the University of Hill in association with the Hull-York Medical School, University of Hull, Hull, United Kingdom.
Mol Cancer Ther. 2006 Aug;5(8):2115-20. doi: 10.1158/1535-7163.MCT-06-0190.
Doxorubicin is considered to be the most effective agent in the treatment of breast cancer patients. Unfortunately, resistance to this agent is common, representing a major obstacle to successful treatment. The identification of novel biomarkers that are able to predict treatment response may allow therapy to be tailored to individual patients. Antibody microarrays provide a powerful new technique, enabling the global comparative analysis of many proteins simultaneously. This technology may identify a panel of proteins to discriminate between drug-resistant and drug-sensitive samples. The Panorama Cell Signaling Antibody Microarray was exploited to analyze the MDA-MB-231 breast cancer cell line and a novel derivative, which displays significant resistance to doxorubicin at clinically relevant concentrations. The microarray comprised 224 antibodies selected from a variety of pathways, including apoptotic and cell signaling pathways. A standard >/=2.0-fold cutoff value was used to determine differentially expressed proteins. A decrease in the expression of mitogen-activated protein kinase-activated monophosphotyrosine (phosphorylated extracellular signal-regulated kinase; 2.8-fold decrease), cyclin D2 (2.5-fold decrease), cytokeratin 18 (2.5-fold decrease), cyclin B1 (2.4-fold decrease), and heterogeneous nuclear ribonucleoprotein m3-m4 (2.0-fold decrease) was associated with doxorubicin resistance. Western blotting was exploited to confirm results from the antibody microarray experiment. These results suggest that antibody microarrays can be used to identify novel biomarkers and further validation may reveal mechanisms of chemotherapy resistance and identify potential therapeutic targets. [Mol Cancer Ther 2006;5(8):2115-20].
阿霉素被认为是治疗乳腺癌患者最有效的药物。不幸的是,对这种药物的耐药性很常见,这是成功治疗的主要障碍。鉴定能够预测治疗反应的新型生物标志物可能使治疗能够针对个体患者进行调整。抗体微阵列提供了一种强大的新技术,能够同时对多种蛋白质进行全局比较分析。这项技术可能会识别出一组蛋白质,以区分耐药和药物敏感样本。利用全景细胞信号抗体微阵列分析了MDA-MB-231乳腺癌细胞系和一种新型衍生物,该衍生物在临床相关浓度下对阿霉素表现出显著的耐药性。该微阵列包含从多种途径(包括凋亡和细胞信号传导途径)中选择的224种抗体。使用标准的≥2.0倍截止值来确定差异表达的蛋白质。丝裂原活化蛋白激酶激活的单磷酸酪氨酸(磷酸化细胞外信号调节激酶;降低2.8倍)、细胞周期蛋白D2(降低2.5倍)、细胞角蛋白18(降低2.5倍)、细胞周期蛋白B1(降低2.4倍)和不均一核核糖核蛋白m3-m4(降低2.0倍)的表达降低与阿霉素耐药性相关。利用蛋白质印迹法来确认抗体微阵列实验的结果。这些结果表明,抗体微阵列可用于鉴定新型生物标志物,进一步的验证可能揭示化疗耐药机制并确定潜在的治疗靶点。[《分子癌症治疗》2006年;5(8):2115 - 20]