OncoProteomics Laboratory, Department of Medical Oncology, VU University Medical Center (VUmc)-Cancer Center Amsterdam, The Netherlands.
Mol Cell Proteomics. 2010 May;9(5):988-1005. doi: 10.1074/mcp.M900546-MCP200. Epub 2010 Jan 20.
Abnormalities in nuclear phenotype and chromosome structure are key features of cancer cells. Investigation of the protein determinants of nuclear subfractions in cancer may yield molecular insights into aberrant chromosome function and chromatin organization and in addition may yield biomarkers for early cancer detection. Here we evaluate a proteomics work flow for profiling protein constituents in subnuclear domains in colorectal cancer tissues and apply this work flow to a comparative analysis of the nuclear matrix fraction in colorectal adenoma and carcinoma tissue samples. First, we established the reproducibility of the entire work flow. In a reproducibility analysis of three nuclear matrix fractions independently isolated from the same colon tumor homogenate, 889 of 1,047 proteins (85%) were reproducibly identified at high confidence (minimally two peptides per protein at 99% confidence interval at the protein level) with an average coefficient of variance for the number of normalized spectral counts per protein of 30%. This indicates a good reproducibility of the entire work flow from biochemical isolation to nano-LC-MS/MS analysis. Second, using spectral counting combined with statistics, we identified proteins that are significantly enriched in the nuclear matrix fraction relative to two earlier fractions (the chromatin-binding and intermediate filament fractions) isolated from six colorectal tissue samples. The total data set contained 2,059 non-redundant proteins. Gene ontology mining and protein network analysis of nuclear matrix-enriched proteins revealed enrichment for proteins implicated in "RNA processing" and "mRNA metabolic process." Finally, an explorative comparison of the nuclear matrix proteome in colorectal adenoma and carcinoma tissues revealed many proteins previously implicated in oncogenesis as well as new candidates. A subset of these differentially expressed proteins also exhibited a corresponding change at the mRNA level. Together, the results show that subnuclear proteomics of tumor tissue is feasible and a promising avenue for exploring oncogenesis.
核表型和染色体结构的异常是癌细胞的关键特征。研究癌症中核亚区的蛋白质决定因素，可以深入了解异常染色体功能和染色质组织，并为早期癌症检测提供生物标志物。在这里，我们评估了一种用于分析结直肠癌组织核亚区蛋白成分的蛋白质组学工作流程，并将该工作流程应用于结直肠腺瘤和癌组织样本中核基质部分的比较分析。首先，我们确定了整个工作流程的可重复性。在对从同一结肠癌组织匀浆中独立分离的三个核基质部分的重复性分析中，在高可信度（在蛋白质水平上置信区间为 99%时，每个蛋白质至少有两个肽）下可重复性地鉴定出 1047 种蛋白质中的 889 种（85%），每个蛋白质的归一化光谱计数的平均系数方差为 30%。这表明从生化分离到纳升液相色谱-串联质谱分析的整个工作流程具有良好的可重复性。其次，使用光谱计数结合统计学方法，我们鉴定出了在核基质部分中相对两个早期部分（染色质结合部分和中间丝部分）显著富集的蛋白质，这六个结直肠组织样本中分离得到。总数据集包含 2059 种非冗余蛋白质。对核基质富集蛋白的基因本体挖掘和蛋白质网络分析显示，富含参与“RNA 加工”和“mRNA 代谢过程”的蛋白质。最后，对结直肠腺瘤和癌组织的核基质蛋白质组进行探索性比较，发现了许多先前与致癌作用有关的蛋白质以及新的候选蛋白。这些差异表达蛋白中的一部分在 mRNA 水平也表现出相应的变化。总之，结果表明肿瘤组织的亚核蛋白质组学是可行的，是探索致癌作用的一个很有前途的途径。
