DR. EPS: Drug Repurposing for Extended Patient Survival

项目摘要 人类癌症是一种复杂的疾病，表现出巨大的异质性，导致不同的存活率。 结果。因此，迫切需要可操作的、稳健的癌症预后预测模型 个性化治疗和疾病管理。然而，一直严重缺乏 治疗上可操作的计算方法，这些方法明确地将患者存活率差异建模为 目的整合多维高通量基因组学数据。为了解决这个问题，我们提出了一个 一种新的可操作的癌症药物再利用框架，称为Dr.EPS(药物再利用扩展 患者生存)。为了实现这一目标，我们将制定以下策略：(1)构建和验证 一种新的基于混合学习的多组学预后建模方法，使用七种不同的肝脏 癌症人群队列。(2)开发和实验验证可操作的计算药物- 重新定位框架，以提高高危肝癌患者的生存率，使用大套 药物基因组学和药物遗传学数据。(3)建立一个用户友好的网络工具，以加快这一进程 用于肝癌治疗的从板凳到床的过渡。我们预计这个项目将在许多方面具有开创性 方面，包括在多组学数据集上建立新的预后模型，确定新的再利用药物 延长高危肝癌患者生命周期，为肝脏提供第一手药物再定位资源 癌症治疗学研究社区。

Project Summary Human cancers are complex diseases that present vast heterogeneity, leading to widely different survival outcomes. Thus actionable and robust predictive models for cancer prognosis are much needed for more personalized treatment and disease management. However, There has been severely lacking of therapeutically actionable computational methods, which explicitly model patient survival difference as the objective while integrating multi-dimension high-throughput genomics data. To solve this issue, we propose a novel actionable framework for caner drug repurposing, called DR. EPS (Drug Repurposing for Extended Patient Survival). Towards this goal, we will develop the following strategies: (1) Constructing and validating a new class of hybrid-learning based, multi-omics prognosis modeling approach, using seven diverse liver cancer population cohorts. (2) Developing and experimentally validating an actionable computational drug- repurposing framework to improve the survival of high-risk liver cancer patients, using big sets of pharmacogenomics and pharmacogenetics data. (3) Building a user-friendly webtool that accelerates such bench-to-bed transition for liver cancer treatment. We expect that this project will be groundbreaking in many aspects, including building new prognostic models on multi-omics data sets, identifying new repurposed drugs to extend high-risk liver cancer patient life-spans, and providing a first-hand drug reposition resource for liver cancer therapeutics research community.