Exome-Driven Characterization of the Cancer Cell Lines at the Proteome Level: The NCI-60 Case Study

Cancer genome deviates significantly from the reference human genome, and thus a search against standard genome databases in cancer cell proteomics fails to identify cancer-specific protein variants. The goal of this Article is to combine high-throughput exome data [Abaan et al. Cancer Res. 2013] and shotgun proteomics analysis [Modhaddas Gholami et al. Cell Rep. 2013] for cancer cell lines from NCI-60 panel to demonstrate further that the cell lines can be effectively recognized using identified variant peptides. To achieve this goal, we generated a database containing mutant protein sequences of NCI-60 panel of cell lines. The proteome data were searched using Mascot and X!Tandem search engines against databases of both reference and mutant protein sequences. The identification quality was further controlled by calculating a fraction of variant peptides encoded by the own exome sequence for each cell line. We found that up to 92.2% peptides identified by both search engines are encoded by the own exome. Further, we used the identified variant peptides for cell line recognition. The results of the study demonstrate that proteome data supported by exome sequence information can be effectively used for distinguishing between different types of cancer cell lines.癌症基因组与人类参考基因组存在显著差异，因此在癌细胞蛋白质组学研究中，仅针对标准基因组数据库进行检索时，无法识别癌症特异性蛋白质变异体。本研究旨在结合NCI-60细胞系组的高通量外显子组（exome）数据[Abaan等, Cancer Res, 2013]与鸟枪法蛋白质组学（shotgun proteomics）分析[Modhaddas Gholami等, Cell Rep, 2013]，进一步验证通过鉴定变异肽段可有效实现细胞系的识别。为达成该研究目标，我们构建了包含NCI-60细胞系组突变蛋白质序列的专用数据库。我们采用Mascot与X!Tandem两款质谱检索引擎，分别针对参考蛋白质序列数据库与突变蛋白质序列数据库，对蛋白质组数据进行检索。通过计算每个细胞系自身外显子组序列编码的变异肽段占比，进一步管控肽段鉴定质量。研究结果显示，经两款检索引擎共同鉴定的肽段中，最高92.2%均由对应细胞系的自身外显子组编码。后续我们将鉴定得到的变异肽段应用于细胞系识别任务。本研究结果证实，结合外显子组序列信息的蛋白质组数据，可有效用于区分不同类型的癌细胞系。