Nibbe Rod K, Chance Mark R
Case Center for Proteomics & Bioinformatics, 10900 Euclid Avenue, Cleveland, OH, USA, Tel.: +1 216 368 5868.
Biomark Med. 2009 Aug 1;3(4):385-396. doi: 10.2217/BMM.09.33.
Like all human cancers, colorectal cancer is a complicated disease. While a mature body of research involving colorectal cancer has implicated the putative sequence of genetic alterations that trigger the disease and sustain its progression, there is a surprising paucity of well-validated, clinically useful diagnostic markers of this disease. For prognosis or guiding therapy, single gene-based markers of colorectal cancer often have limited specificity and sensitivity. Genome-wide analyses (microarrays) have been used to propose candidate patterns of gene expression that are prognostic of outcome or predict the tumor's response to a therapy regimen; however, these patterns frequently do not overlap, and this has raised questions concerning their use as biomarkers. The limitation of gene-expression approaches to marker discovery occurs because the change in mRNA expression across tumors is highly variable and, alone, accounts for a limited variability of the phenotype, such as with cancer. More robust and accurate markers of cancer will result from integrating all the information we have about the cell: genomics, proteomics and interactomics. This article will discuss traditional markers in colorectal cancer, both genomic and proteomic, including their respective approaches and limitations, then conclude with examples of systems biology-based approaches for candidate marker discovery, and discuss how this approach is reshaping our view of a biomarker.
与所有人类癌症一样，结直肠癌是一种复杂的疾病。虽然关于结直肠癌的大量成熟研究已表明引发该疾病并维持其进展的假定基因改变序列，但令人惊讶的是，针对这种疾病的经过充分验证且具有临床实用性的诊断标志物却非常匮乏。对于预后或指导治疗而言，基于单个基因的结直肠癌标志物通常特异性和敏感性有限。全基因组分析（微阵列）已被用于提出可预测预后或肿瘤对治疗方案反应的候选基因表达模式；然而，这些模式常常并不重叠，这引发了关于它们作为生物标志物用途的质疑。基因表达方法在标志物发现方面存在局限性，原因在于肿瘤间mRNA表达的变化高度可变，且单独来看，它仅能解释有限的表型变异性，比如癌症相关的表型变异性。整合我们所拥有的关于细胞的所有信息（基因组学、蛋白质组学和相互作用组学），将产生更强大、准确的癌症标志物。本文将讨论结直肠癌中的传统标志物，包括基因组和蛋白质组标志物，阐述它们各自的方法及局限性，接着以基于系统生物学的候选标志物发现方法为例进行总结，并讨论这种方法如何重塑我们对生物标志物的看法。
