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Systematic Development of Novel, Druggable Cancer Targets

Systematic Development of Novel, Druggable Cancer Targets
新型药物癌症靶标的系统开发
批准号:
9057986
负责人:
MICHAEL E. BERENS
金额:
$79.42万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-05-01 至 2018-04-30

项目摘要

项目成果

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中文摘要
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英文摘要
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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1142/9789814749411_0004
发表时间: 2016
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [G. Speyer;J. Kiefer;Harshil Dhruv;M. Berens;Seungchan Kim]
通讯作者: G. Speyer;J. Kiefer;Harshil Dhruv;M. Berens;Seungchan Kim
Learning contextual gene set interaction networks of cancer with condition specificity.
学习上下文基因设置癌症的相互作用网络具有条件特异性。
DOI: 10.1186/1471-2164-14-110
发表时间: 2013-02-19
期刊: BMC genomics
影响因子: 4.4
作者: [Jung S, Verdicchio M, Kiefer J, Von Hoff D, Berens M, Bittner M, Kim S]
通讯作者: Kim S
RTK inhibition: looking for the right pathways toward a miracle.
RTK抑制:寻找通往奇迹的正确途径。
DOI: 10.2217/fon.12.130
发表时间: 2012
期刊: Future oncology (London, England)
影响因子: --
作者: [Xie,Qian, VandeWoude,GeorgeF, Berens,MichaelE]
通讯作者: Berens,MichaelE
DOI: 10.1142/9789813207813_0046
发表时间: 2017
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [Speyer G, Mahendra D, Tran HJ, Kiefer J, Schreiber SL, Clemons PA, Dhruv H, Berens M, Kim S]
通讯作者: Kim S
Signature-guided treatment of GBM with neddylation inhibitor pevonedistat
Signature-guided treatment of GBM with neddylation inhibitor pevonedistat
Molecular Profiling and Bioinformatics
Molecular Profiling and Bioinformatics
海外基金