卵巢癌化疗反应相关基因群的鉴定

Yan-E. Li, Juan Zhang, Bin Han, Lihua Li
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引用次数: 0

摘要

手术配合化疗仍是治疗卵巢癌的主要手段。因此,确定卵巢癌化疗反应(OCCR)相关基因并描述其相互作用是一个重要的问题。然而,微阵列数据的高维性和生物先验的稀缺性使得构建一个完整的OCCR生物网络变得非常困难。为此,我们将液体关联(LA)算法与生物知识库搜索相结合,识别OCCR相关基因团,并描述它们之间的相互作用。我们的方法不是试图建立一个基因网络,而是专注于识别OCCR相关的基因集团,然后将它们修补起来。统计分析和生物学验证表明,所鉴定的基因团在肿瘤发生、免疫、细胞增殖和迁移等方面发挥重要作用,与OCCR显著相关。更重要的是,建立了独立基因集团之间的联系,并描述了基因之间的关联。在方法上,该方法避免了复杂的计算问题,只依赖于现有的生物先验,为构建基因网络提供了一种新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Ovarian Cancer Chemotherapy Response Relevant Gene Cliques
Operation with adjuvant chemotherapy is still the principal means to treat Ovarian cancer. Identifying Ovarian Cancer Chemotherapy Response (OCCR) relevant genes and describe their interactions is thus an important issue. However the problems of high dimensional micro array data and the scarcity of biological priors make building a complete OCCR biological network intractable. To this end, we combine liquid association (LA) algorithm with biological knowledgebase searching to identify OCCR relevant gene clique and describe their interactions. Rather than trying to build a gene network, our approach focus on identifying OCCR relevant gene cliques and then patching them up. Statistical analysis and biological validation show that the identified gene cliques play important roles in tumor genesis, immunity, cells proliferation and migration etc and significantly OCCR relevant. More importantly, the connection of independent gene cliques is established and the associations of genes are described. Methodologically, the proposed method avoids the problem of complex computation, relies only on available biological priors and provides a novel way to build gene network.
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