Kim Min-Ji, Choi Na Young, Lee Eun Kyung, Kang Myung-Soo
Samsung Biomedical Research Institute and Samsung Medical Center, Seoul, Korea, 135-718.
Cell Oncol (Dordr). 2014 Aug;37(4):235-43. doi: 10.1007/s13402-014-0178-4. Epub 2014 Jul 8.
Circulating tumor cells (CTCs) can be used to predict the spread of cancer to distant sites, to monitor the clinical response to therapy and to predict patient survival. The currently used EpCAM antibody-mediated identification of CTCs may lead to false negative results due to the low level or absence of EpCAM expression in several types of cancer, thus provoking a need to identify novel CTC markers.
The Cancer Cell Line Encyclopedia (CCLE) microarray dataset, storing 18,915 gene expression profiles across 967 cancer cell lines derived from 25 primary sites, was systematically analyzed. The results obtained were cross-validated using an independent microarray dataset generated from 1,911 clinical cancer specimens derived from 15 different cancers.
Through bioinformatics analyses we identified, categorized and prioritized three classes of novel markers: pan-CTC markers (n = 45), EpCAM((-/low)) CTC markers (n = 16) and single cancer type-specific markers (n = 74). The pan-CTC markers were significantly, uniformly and constitutively over-expressed in most cancer types, except in cancers of hematopoietic and lymphoid origin. The EpCAM((-/low)) CTC markers were over-expressed in cancers with low or undetectable EpCAM expression levels. Among these, 22 markers were validated in an independent microarray dataset. In addition, 74 markers that were over-expressed in only single cancer types were categorized.
The combined use of these novel markers in conjunction with cancer type-specific markers should be able to quantify CTCs that are not captured by EpCAM antibodies, and to enhance the sensitivity and specificity of CTC detection among admixtures containing leucocytes or other types of contaminants.
循环肿瘤细胞(CTC)可用于预测癌症向远处转移、监测治疗的临床反应以及预测患者生存情况。目前使用的EpCAM抗体介导的CTC鉴定方法可能会因几种癌症类型中EpCAM表达水平低或缺失而导致假阴性结果,因此需要鉴定新的CTC标志物。
对癌细胞系百科全书(CCLE)微阵列数据集进行系统分析,该数据集存储了来自25个原发部位的967个癌细胞系的18915个基因表达谱。使用从15种不同癌症的1911份临床癌症标本生成的独立微阵列数据集对所得结果进行交叉验证。
通过生物信息学分析,我们鉴定、分类并优先列出了三类新标志物:泛CTC标志物(n = 45)、EpCAM((-/低))CTC标志物(n = 16)和单一癌症类型特异性标志物(n = 74)。泛CTC标志物在大多数癌症类型中均显著、一致且组成性地过度表达,但造血和淋巴起源的癌症除外。EpCAM((-/低))CTC标志物在EpCAM表达水平低或无法检测到的癌症中过度表达。其中,22种标志物在独立的微阵列数据集中得到验证。此外,还对仅在单一癌症类型中过度表达的74种标志物进行了分类。
这些新标志物与癌症类型特异性标志物联合使用,应能够对未被EpCAM抗体捕获的CTC进行定量,并提高在含有白细胞或其他类型污染物的混合物中CTC检测的灵敏度和特异性。