Chen Yet-Ran, Juan Hsueh-Fen, Huang Hsuan-Cheng, Huang Hsin-Hung, Lee Ya-Jung, Liao Mei-Yueh, Tseng Chien-Wei, Lin Li-Ling, Chen Jeou-Yuan, Wang Mei-Jung, Chen Jenn-Han, Chen Yu-Ju
Institute of Chemistry and Genomic Research Center, Academia Sinica, Taipei, Taiwan.
J Proteome Res. 2006 Oct;5(10):2727-42. doi: 10.1021/pr060212g.
Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.
胃癌是全球主要的死亡原因之一，患者的总体5年生存率不到10%。我们运用定量蛋白质组学技术结合微阵列芯片，建立了转移性胃癌TMC-1细胞和非侵袭性胃癌SC-M1细胞的全面蛋白质组和转录组图谱。我们的定性蛋白质谱分析策略首次对胃癌细胞蛋白质组进行了全面分析，分别从SC-M1细胞和TMC-1细胞中鉴定出926种和909种蛋白质。可裂解同位素编码亲和标签分析能够对总共559种蛋白质进行定量分析（蛋白质假阳性率<0.005），并且在SC-M1细胞和TMC-1细胞之间有240种蛋白质差异表达（>1.3倍）。我们鉴定出许多以前与胃癌无关的蛋白质。值得注意的是，大量差异表达的蛋白质与肿瘤转移相关，包括在细胞-细胞和细胞-细胞外基质（细胞-ECM）黏附、细胞运动、增殖和肿瘤免疫中发挥作用的蛋白质。通过DNA微阵列进行的基因表达谱分析显示约1000个基因有差异表达（>2倍）。在蛋白质和mRNA图谱之间观察到的弱相关性突出了DNA微阵列和蛋白质组学方法的重要互补性。这些比较数据使我们能够描绘出疾病扰乱的细胞-细胞和细胞-ECM黏附以及Rho GTPase介导的细胞骨架途径。对一部分基因的进一步验证表明波形蛋白和半乳糖凝集素1有可能作为转移的标志物。我们证明，将蛋白质组学和基因组学方法相结合不仅提供了一个快速、稳健且灵敏的平台来阐明胃癌转移的分子机制，而且还可能识别出候选诊断标志物和治疗靶点。
