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首页> 外文期刊>BMC Medical Genomics >Integrative network analysis identifies potential targets and drugs for ovarian cancer
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Integrative network analysis identifies potential targets and drugs for ovarian cancer

机译：综合网络分析识别卵巢癌的潜在目标和药物

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Though accounts for 2.5% of all cancers in female, the death rate of ovarian cancer is high, which is the fifth leading cause of cancer death (5% of all cancer death) in female. The 5-year survival rate of ovarian cancer is less than 50%. The oncogenic molecular signaling of ovarian cancer are complicated and remain unclear, and there is a lack of effective targeted therapies for ovarian cancer treatment. In this study, we propose to investigate activated signaling pathways of individual ovarian cancer patients and sub-groups; and identify potential targets and drugs that are able to disrupt the activated signaling pathways. Specifically, we first identify the up-regulated genes of individual cancer patients using Markov chain Monte Carlo (MCMC), and then identify the potential activated transcription factors. After dividing ovarian cancer patients into several sub-groups sharing common transcription factors using K-modes method, we uncover the up-stream signaling pathways of activated transcription factors in each sub-group. Finally, we mapped all FDA approved drugs targeting on the upstream signaling. The 427 ovarian cancer samples were divided into 3 sub-groups (with 100, 172, 155 samples respectively) based on the activated TFs (with 14, 25, 26 activated TFs respectively). Multiple up-stream signaling pathways, e.g., MYC, WNT, PDGFRA (RTK), PI3K, AKT TP53, and MTOR, are uncovered to activate the discovered TFs. In addition, 66 FDA approved drugs were identified targeting on the uncovered core signaling pathways. Forty-four drugs had been reported in ovarian cancer related reports. The signaling diversity and heterogeneity can be potential therapeutic targets for drug combination discovery. The proposed integrative network analysis could uncover potential core signaling pathways, targets and drugs for ovarian cancer treatment.
机译：虽然占女性所有癌症的2.5％，但卵巢癌的死亡率很高，这是女性癌症死亡率的第五个主要原因（癌症死亡的5％）。卵巢癌的5年生存率小于50％。卵巢癌的致癌分子信号是复杂的并且仍然尚不清楚，缺乏有效的卵巢癌治疗靶向疗法。在这项研究中，我们建议调查个体卵巢癌患者和子组的活性信号通路;并识别能够破坏激活的信号通路的潜在目标和药物。具体而言，我们首先使用Markov链蒙特卡罗（MCMC）鉴定单个癌症患者的上调基因，然后鉴定潜在的活化转录因子。将卵巢癌患者分成几个子组使用K-MODES方法分享常见转录因子后，我们发现每个子组中的活化转录因子的上游信号通路。最后，我们映射了所有FDA批准的药物，针对上游信号。将427个卵巢癌样品分为3个子组（分别有100,172,155个样品），基于活化的TFS（分别为14,25,26个活化的TFS）。多个向上流信令路径，例如MYC，WNT，PDGFRA（RTK），PI3K，AKT TP53和MTOR被揭示以激活发现的TFS。此外，鉴定了66个FDA批准的药物靶向未覆盖的核心信号通路。卵巢癌相关报告报告了四十四种药物。信号传导多样性和异质性可以是药物组合发现的潜在治疗靶标。拟议的综合网络分析可以揭示潜在的核心信号通路，针对卵巢癌治疗的目标和药物。

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