Department of Pathology, Johns Hopkins University, Baltimore, MD 21231, USA.
Mol Cell Proteomics. 2013 Feb;12(2):356-68. doi: 10.1074/mcp.M112.019521. Epub 2012 Nov 19.
While ovarian cancer remains the most lethal gynecological malignancy in the United States, there are no biomarkers available that are able to predict therapeutic responses to ovarian malignancies. One major hurdle in the identification of useful biomarkers has been the ability to obtain enough ovarian cancer cells from primary tissues diagnosed in the early stages of serous carcinomas, the most deadly subtype of ovarian tumor. In order to detect ovarian cancer in a state of hyperproliferation, we analyzed the implications of molecular signaling cascades in the ovarian cancer cell line OVCAR3 in a temporal manner, using a mass-spectrometry-based proteomics approach. OVCAR3 cells were treated with EGF(1), and the time course of cell progression was monitored based on Akt phosphorylation and growth dynamics. EGF-stimulated Akt phosphorylation was detected at 12 h post-treatment, but an effect on proliferation was not observed until 48 h post-exposure. Growth-stimulated cellular lysates were analyzed for protein profiles between treatment groups and across time points using iTRAQ labeling and mass spectrometry. The protein response to EGF treatment was identified via iTRAQ analysis in EGF-stimulated lysates relative to vehicle-treated specimens across the treatment time course. Validation studies were performed on one of the differentially regulated proteins, lysosomal-associated membrane protein 1 (LAMP-1), in human tissue lysates and ovarian tumor tissue sections. Further, tissue microarray analysis was performed to demarcate LAMP-1 expression across different stages of epithelial ovarian cancers. These data support the use of this approach for the efficient identification of tissue-based markers in tumor development related to specific signaling pathways. LAMP-1 is a promising biomarker for studies of the progression of EGF-stimulated ovarian cancers and might be useful in predicting treatment responses involving tyrosine kinase inhibitors or EGF receptor monoclonal antibodies.
尽管卵巢癌仍然是美国最致命的妇科恶性肿瘤,但目前尚无能够预测卵巢恶性肿瘤治疗反应的生物标志物。在鉴定有用的生物标志物方面的一个主要障碍是,从早期浆液性癌(卵巢肿瘤最致命的亚型)诊断的原发性组织中获得足够的卵巢癌细胞的能力。为了在过度增殖的状态下检测卵巢癌,我们采用基于质谱的蛋白质组学方法,从时间上分析了 OVCAR3 卵巢癌细胞系中分子信号级联反应的意义。用 EGF(1)处理 OVCAR3 细胞,并根据 Akt 磷酸化和生长动力学监测细胞进展的时间过程。EGF 刺激的 Akt 磷酸化在处理后 12 小时检测到,但直到暴露后 48 小时才观察到对增殖的影响。使用 iTRAQ 标记和质谱法,在治疗组之间和不同时间点分析生长刺激的细胞裂解物的蛋白质图谱。通过 iTRAQ 分析,在 EGF 刺激的裂解物中相对于载体处理的标本,鉴定出对 EGF 处理的蛋白质反应,跨越整个治疗时间过程。在人类组织裂解物和卵巢肿瘤组织切片中对一种差异调节蛋白,溶酶体相关膜蛋白 1(LAMP-1)进行了验证研究。此外,还进行了组织微阵列分析,以确定 LAMP-1 在不同上皮性卵巢癌阶段的表达。这些数据支持使用这种方法来有效地鉴定与特定信号通路相关的肿瘤发展中的组织标志物。LAMP-1 是研究 EGF 刺激的卵巢癌进展的有前途的生物标志物,并且可能有助于预测涉及酪氨酸激酶抑制剂或 EGF 受体单克隆抗体的治疗反应。