Gene Networks Essential to Colon Cancer Phenotype

摘要 现在有一个广泛的共识，即不可能理解和合理地干预 癌症的发展和进展，而不了解和具体扰乱网络， 支持癌细胞的功能。在这里，我们制定了一个新的方法，合理和有效的 发现癌细胞特异性药物靶点的基础上，我们有能力重建基因网络， 遗传实验与基因组学、数学和计算/生物信息学的整合 工具.我们的方法的新奇在于具体考虑和利用的概念， 癌细胞表型的特征仅作为多种共- 操作致癌突变通过分析癌基因的分子机制， 协同性我们已经确定了对两种致癌突变的联合作用有反应的基因， 协同改变其表达。重要的是，我们发现，这种监管 “合作反应基因”（CRG）对癌症表型的关键作用高得惊人（14 在24个测试的基因中），表明致癌突变通过协同调节 下游基因网络值得注意的是，相关的基因可以作为调节剂，控制多个 以及多种细胞过程，如细胞信号传导、存活、运动、侵袭和自我更新 这表明协同致癌突变可以同时影响多个平行的癌细胞， 性状值得注意的是，恶性细胞转化过程的复杂特征强烈地 在鼠和人结肠细胞中保守。因此，对这些特征的分析变得可行， 研究策略利用遗传学上易于处理的小鼠恶性转化模型， 结合人类结肠癌细胞的数据验证。根据我们的观察 因此，我们假设（I）CRG是恶性细胞转化所必需的一类基因 协同致癌突变的下游此外，我们有初步证据显示， CRG表达的调控通过协同致癌突变不是独立的，而是基于 强大的等级组织。因此，我们预测（II）CRG网络结构的研究 提供了一个合理的途径来识别癌细胞的脆弱性，从而一类新的药物靶点。 我们还发现，组蛋白脱乙酰酶抑制剂（HDACi）的抗癌活性至少在20%以上。 部分通过CRG表达模式的逆转介导。因此，我们假设（III）CRG 表达模式可以作为选择具有潜在癌症用途的有效药物的指标 干预我们的方法来测试这些假设将直接导致识别和验证 真正的癌细胞特异性药物靶点和药物通过合理的手段。

Abstract There is now broad consensus that it will be impossible to understand and rationally intervene with the development and progression of cancer without understanding and specifically perturbing the networks that support the functioning of cancer cells. Here we formulate a novel approach for rational and efficient discovery of cancer cell-specific drug targets based on our capability to reconstruct gene networks through the integration of genetic experimentation with genomic, mathematical and computational/bioinformatics tools. The novelty of our approach lies in specifically considering and exploiting the notion that many features of the cancer cell phenotype only emerge as a result of the interplay between multiple co- operating oncogenic mutations. Through analysis of the molecular mechanisms underlying oncogene cooperativity we have identified genes that respond to the combined effect of two oncogenic mutations with synergistic alterations in their expression. Importantly, we have discovered that the regulation of such `cooperation response genes' (CRG) is critical for the cancer phenotype at surprisingly high frequency (14 out of 24 genes tested), indicating that oncogenic mutations cooperate through synergistic regulation of downstream gene networks. Remarkably, the genes involved can act as mediators in the control of multiple and diverse cellular processes, such as cell signaling, survival, motility, invasiveness and self-renewal indicating that cooperating oncogenic mutations simultaneously can affect multiple parallel cancer cell traits. Notably, the complex features underlying the malignant cell transformation process are strongly conserved in murine and human colon cells. Analysis of these features thus becomes feasible through a research strategy utilizing both a genetically tractable murine model of malignant transformation derived from colonic crypts combined with data validation in human colon cancer cells. Based on our observations we thus hypothesize (I) that CRGs are a class of genes essential for malignant cell transformation downstream of cooperating oncogenic mutations. In addition, we have preliminary evidence to show that regulation of CRG expression by cooperating oncogenic mutations is not independent but rather underlies strong hierarchical organization. We thus predict that (II) investigation of CRG network architecture provides a rational path to identification of cancer cell vulnerabilities and thus a novel class of drug targets. We also have discovered that the anti-cancer activity of histone deacetylase inhibitors (HDACi) is at least in part mediated through reversion of CRG expression patterns. We thus hypothesize (III) that CRG expression patterns can serve as indicators for selection of efficacious drugs with potential use in cancer intervention. Our approaches to test these hypotheses will lead directly to identification and validation of bona fide cancer cell-specific drug targets and drugs by rational means.