Cancer Genomics Branch, Research Institute, National Cancer Center, Goyang, Korea.
PLoS One. 2012;7(4):e31685. doi: 10.1371/journal.pone.0031685. Epub 2012 Apr 9.
Colorectal cancer (CRC) has one of the highest incidences among all cancers. The majority of CRCs are sporadic cancers that occur in individuals without family histories of CRC or inherited mutations. Unfortunately, whole-genome expression studies of sporadic CRCs are limited. A recent study used microarray techniques to identify a predictor gene set indicative of susceptibility to early-onset CRC. However, the molecular mechanisms of the predictor gene set were not fully investigated in the previous study. To understand the functional roles of the predictor gene set, in the present study we applied a subpathway-based statistical model to the microarray data from the previous study and identified mechanisms that are reasonably associated with the predictor gene set. Interestingly, significant subpathways belonging to 2 KEGG pathways (focal adhesion; natural killer cell-mediated cytotoxicity) were found to be involved in the early-onset CRC patients. We also showed that the 2 pathways were functionally involved in the predictor gene set using a text-mining technique. Entry of a single member of the predictor gene set triggered a focal adhesion pathway, which confers anti-apoptosis in the early-onset CRC patients. Furthermore, intensive inspection of the predictor gene set in terms of the 2 pathways suggested that some entries of the predictor gene set were implicated in immunosuppression along with epithelial-mesenchymal transition (EMT) in the early-onset CRC patients. In addition, we compared our subpathway-based statistical model with a gene set-based statistical model, MIT Gene Set Enrichment Analysis (GSEA). Our method showed better performance than GSEA in the sense that our method was more consistent with a well-known cancer-related pathway set. Thus, the biological suggestion generated by our subpathway-based approach seems quite reasonable and warrants a further experimental study on early-onset CRC in terms of dedifferentiation or differentiation, which is underscored in EMT and immunosuppression.
结直肠癌（CRC）是所有癌症中发病率最高的一种。大多数 CRC 是散发性癌症，发生在没有 CRC 家族史或遗传突变的个体中。不幸的是，散发性 CRC 的全基因组表达研究有限。最近的一项研究使用微阵列技术鉴定了一个预示易感性的预测基因集。然而，之前的研究并没有充分研究预测基因集的分子机制。为了了解预测基因集的功能作用，本研究应用基于子通路的统计模型对之前研究的微阵列数据进行了分析，并鉴定了与预测基因集合理相关的机制。有趣的是，属于 2 个 KEGG 途径（粘着斑；自然杀伤细胞介导的细胞毒性）的显著子途径被发现与早发性 CRC 患者有关。我们还使用文本挖掘技术表明，这 2 个途径与预测基因集在功能上有关。预测基因集的单个成员的进入会触发粘着斑途径，从而赋予早发性 CRC 患者抗凋亡作用。此外，从 2 个途径的角度对预测基因集进行深入检查表明，预测基因集的某些条目与早发性 CRC 患者的免疫抑制以及上皮-间充质转化（EMT）有关。此外，我们将我们的基于子通路的统计模型与基于基因集的统计模型（MIT Gene Set Enrichment Analysis，GSEA）进行了比较。我们的方法在性能上优于 GSEA，因为我们的方法与一个著名的癌症相关途径集更一致。因此，我们基于子通路的方法所产生的生物学建议似乎是合理的，并需要进一步研究 EMT 和免疫抑制中的去分化或分化与早发性 CRC 的关系。
