Systematic Development of Novel, Druggable Cancer Targets

描述（由申请人提供）：我们是一个多学科团队，在生物信息学，临床前癌症建模，高通量遗传和化学文库筛选方面具有明显的能力，在大型多机构研究计划中具有参与和领导的传统。 我们的提案描述了系统地识别、验证和评估胶质母细胞瘤和其他癌症中新靶点的可药性的工作流程，这些工作流程将由癌症靶点发现和开发（CTD 2）网络转发。 特别是在这个应用程序中，TGen的电子卓越研究中心（ISRCE）提供了关于多形性胶质母细胞瘤（GBM）的癌症基因组图谱（TCGA）的工作知识，并为肿瘤亚组和目标识别的数据库挖掘带来了生物信息学工具和工作计划。 系统生物学专业知识由货车安德尔研究所（瓦里）和汤普森路透社（GeneGO）提供。通过信息学策略（目的1）鉴定的候选靶标使用54个分子特征的人原位原代GBM异种移植物进一步获知。 这些信息平台及其注释的工作流程管理系统指导Sanford-Burnham医学研究所（SBMRI）的目标和途径验证（目标2）和易处理性（目标3）的功能工作。 SBMRI的化学基因组学中心（NIH分子库探针生产中心网络（MLPCN）和NCI化学生物学联盟的综合中心）能够实现强大的RNAi和基于小分子的高通量检测开发和筛选，以有效地对靶标和途径进行大规模功能验证。 结果将用于迭代增强分类和预测算法，我们改进的生物信息学工具可用于识别CTD 2网络转发的其他肿瘤类型中的生物学重要靶标。 因此，该提案的重要性源于领先的生物医学研究组织对计算机和实验室技术的独特整合，用于在癌症分子亚群中进行易于处理的靶标识别和验证。项目的创新 我们的多学科团队反复询问胶质母细胞瘤和其他癌症的良好表征，临床相关的临床前模型。总体而言，我们描述了一种系统的方法，该方法利用了胶质母细胞瘤生物学和建模方面的顶级人才，生物信息学方法来识别肿瘤亚组以及靶标和途径，以及一系列广泛的高通量检测方法，这些方法专注于癌症的关键特征，适合在相关临床前模型中进行有效的靶标验证。此外，我们使用的小分子化合物屏幕对确定的目标和途径提供了一个潜在的快速通道的新的“干扰素”对验证的目标。因此，所描述的项目将通过展示一种用于易处理的靶标识别和验证的有效方法来影响信息学、癌症生物学和药物发现领域，从而加速基因组发现转化为新的治疗方法。

DESCRIPTION (provided by applicant): We are a multidisciplinary team with demonstrated competencies in bioinformatics, preclinical cancer modeling, high throughput genetic and chemical library screening, with a legacy of participation as well as leadership in large, multi-institutional research initiatives. Our proposal depicts workflows that systematically identify, validate, and assess druggability of novel targets in glioblastoma and other cancers to be forwarded by the Cancer Target Discovery and Development (CTD2) Network. Specifically in this application, TGen's In Silico Research Center of Excellence (ISRCE) provides working knowledge of The Cancer Genome Atlas (TCGA) on Glioblastoma Multiforme (GBM), and brings bioinformatic tools and workplans for database mining for tumor subgrouping and target identification. Systems biology expertise is provided by the Van Andel Research Institute (VARI) and Thompson Reuters (GeneGO). Candidate targets identified by informatics strategies (Aim 1) are further informed using 54 molecularly profiled human orthotopic primary GBM xenografts. These informatic platforms and their annotated Workflow Management Systems guide functional work in target and pathway validation (Aim 2) and tractability (Aim 3) at Sanford-Burnham Medical Research Institute (SBMRI). SBMRI's Center for Chemical Genomics [a Comprehensive Center in NIH's Molecular Libraries Probe Production Centers Network (MLPCN) and NCI's Chemical Biology Consortium] enable robust RNAi and small-molecule-based high-throughput assay development and screening for efficient large-scale functional validation of targets and pathways. Results will be utilized to iteratively enhance classification and prediction algorithms~ our refined bioinformatic tools are then available for identification of biologically significant targets in other tumor types forwarded by the CTD2 Network. Thus, the significance of this proposal stems from the unique integration of incisive in silico and laboratory technologies by leading biomedical research organizations for tractable target identification and validation in molecular subsets of cancers. The innovation of the project is underscored by our multi-disciplinary team iteratively interrogating well-characterized, clinically-relevant preclinical models of glioblastoma and other cancers. Overall, we describe a systematic approach that leverages top-tiered talent in the biology and modeling of glioblastoma, bioinformatic methodologies to identify tumor subgroups as well as targets and pathways, and an expansive repertoire of high throughput assays focused on key hallmarks of cancer suitable for efficient target validation in relevant preclinical models. Furthermore, our us of small-molecule compound screens against identified targets and pathways provides a potential fast-track for novel "perturbagens" against the validated targets. As such, the described project will impact the fields of informatics, cancer biology and drug discovery by demonstrating an efficient approach for tractable target identification and validation, thereby accelerating the translation of genomic discoveries into new treatments.