Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer.
Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer.
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DOI：
10.1371/journal.pcbi.1004820
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发表时间：
2016-04
影响因子：
4.3
通讯作者：
Huttenhower C
中科院分区：
文献类型：
--
作者：
Börnigen D;Tyekucheva S;Wang X;Rider JR;Lee GS;Mucci LA;Sweeney C;Huttenhower C
癌症的分子研究是生物信息学研究的最大领域之一，但从高通量基因组数据中了解癌症相关途径的生物分子机制仍然是一个挑战。其中包括核因子 kappa-B (NFκB) 通路，该通路对于前列腺癌发生和进展中的炎症反应和细胞增殖至关重要。尽管对其许多成员的生物分子活动进行了仔细审查和深入了解，但目前的途径成员列表以及对其相互作用的系统级理解仍然不完整。在这里，我们提供了计算重建前列腺癌中 NFκB 通路相互作用机制的第一步。我们确定了 ATF3、CXCL2、DUSP5、JUNB、NEDD9、SELE、TRIB1 和 ZFP36 在此通路中的新作用，以及这些基因与 10 个已知 NFκB 通路成员之间的新机制相互作用。新预测的 NEDD9 和 ZFP36 之间的相互作用尤其通过免疫共沉淀得到了验证，NEDD9 在前列腺癌细胞生长调节中的潜在生物学作用也是如此。我们将 651 个基因表达数据集与 140 万个基因产物相互作用相结合，以预测该通路中是否包含 40 个其他基因。利用贝叶斯数据集成的最新进展来推断通路成员之间相互作用的分子机制，以同时提供特定于生物背景和个体生物分子活动的信息，从而在完全重建的 NFκB 通路中总共产生 112 种相互作用：13 种 (11%) 先前已知，29 种 (26%) 得到现有文献支持，70 种 (63%) 是新颖的。该方法可推广到其他组织类型、癌症和生物体，并且有关 NFκB 通路的新信息将使我们能够进一步了解前列腺癌并制定更有效的预防和治疗策略。在癌症分子研究中，从高通量基因组数据（包括核因子 kappa-B (NFκB) 通路）揭示癌症相关通路中的生物分子机制仍然具有挑战性。尽管对许多 NFκB 通路成员的生物分子活性进行了仔细审查和深入了解，但目前的通路成员列表以及对其相互作用的系统级理解仍然不完整。在这项研究中，我们迈出了计算重建前列腺癌中 NFκB 通路相互作用机制的第一步。我们确定了该通路中 8 个基因的新作用以及这些基因与 10 个已知通路成员之间的新机制相互作用。我们将 651 个基因表达数据集与 140 万个相互作用相结合，预测该通路中是否包含 40 个额外基因。利用贝叶斯数据集成的最新进展来推断相互作用的分子机制，以同时提供特定于生物背景和个体生物分子活动的信息，从而在完全重建的 NFκB 通路中产生 112 种相互作用。这种方法具有普适性，有关 NFκB 通路的新信息将使我们能够进一步了解前列腺癌。
Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer-related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFκB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members’ biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFκB pathway members. A newly predicted interaction between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9's potential biological role in prostate cancer cell growth regulation. We combined 651 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFκB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFκB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies. In molecular research in cancer it remains challenging to uncover biomolecular mechanisms in cancer-related pathways from high-throughput genomic data, including the Nuclear-factor-kappa-B (NFκB) pathway. Despite close scrutiny and a deep understanding of many of the NFκB pathway members’ biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. In this study, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for 8 genes in this pathway and new mechanistic interactions between these genes and 10 known pathway members. We combined 651 gene expression datasets with 1.4M interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in 112 interactions in the fully reconstructed NFκB pathway. This method is generalizable, and this new information about the NFκB pathway will allow us to further understand prostate cancer.