基于多维基因组学的卵巢癌亚型分析

Ovarian Cancer Subtype Analysis Based on Multi-dimensional Genomics and Pathway Activity

卵巢癌预后较差且个体差异很大,有必要从多维基因组学的角度来理解卵巢癌复杂的致癌机制,以期获得导致卵巢癌亚型间预后差异的分子机制.鉴于从基因组学数据中所识别的预后特征往往不具备较好的一致性,提出一种多维基因组学中应用通路活性对卵巢癌亚型进行区分的方法.首先,通过DNA拷贝数、DNA甲基化及miRNA等基因表达调控因素与基因表达变化相结合的方法来识别卵巢癌预后相关的14个通路.其次,基于卵巢癌预后相关的通路活性在不同亚型中有不同的模式,得到4种存在着生存差别的稳定亚型,并提取了其中预后最差的亚型区别于其它亚型的TGF-β等显著差异通路.最后,独立数据验证显示,该组显著差异通路的活性在验证集预后最差的亚型中也发生了一致地改变.识别预后显著差别的亚型及其内在一致的分子机制可以对卵巢癌的预后预测及治疗提供一定的参考.

The outcome of ovarian cancer was poor and varied greatly among patients.To reveal the molecular mechanisms underlying the differences in subtype prognosis,it＇s necessary to understand the complicated carcinogenic mechanisms of ovarian cancer from the perspective of multi-dimensional genomics.Considered prognosis related markers identified from one-dimensional genomics often lack of consistency,a subtype identification method based on pathway activity which obtained from multi-dimensional genomics was proposed in this article.Firstly,by integrating such factors which regulate gene expression as DNA copy number,DNA methylation and microRNA with expression changes,14prognosis-related pathways were identified for ovarian cancer.Then,4stable subtypes with significant differences in survival were obtained and significant pathways such as the TGF-βpathway between the poorest prognosis subtype and others were selected by the knowledge that activity of prognosis-related pathway shows a different pattern among different subtypes.Finally,it showed that the poor prognosis subgroups exhibited a reproducible relationship between pathway activity pattern and their prognosis in independent validation.Identification of subtypes with significant differences of prognosis and consistent molecular mechanism underlying it intrinsically may provide a reference to prognosis prediction and treatment of ovarian cancer.