Development of ex-vivo tumor culture for systems network biology and personalized medicine

用于系统网络生物学和个性化医疗的离体肿瘤培养的开发

基本信息

  • 批准号:
    10830630
  • 负责人:
  • 金额:
    $ 15.23万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-09-14 至 2027-08-31
  • 项目状态:
    未结题

项目摘要

THE CANCER CELL MAP INITIATIVE v2.0 OVERALL SUMMARY The Cancer Genome Atlas and sister projects have now sequenced over 20,000 tumor genomes, providing a catalog of gene mutations, copy number variants and other genetic alterations associated with cancer. These data have made it clear that every cancer is a distinct genetic disease, with tumors that look physiologically similar often driven by patterns of gene mutations that are strikingly different. Due to this molecular heterogeneity, it is typically unclear what are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. One key observation for interpreting tumor genomes is that the many rare tumor mutations can be shown to converge on common molecular networks. Based on this premise we created the Cancer Cell Map Initiative (CCMI), whose mission is to create comprehensive maps of cancer molecular networks and to use these maps in intelligent systems for personalized therapy. In 2017, the CCMI was funded as an NCI U54 Research Center for Cancer Systems Biology, integrating expertise in network mapping, bioinformatic analysis and cancer research from leading academic laboratories at two University of California campuses (UCSF and UCSD). We have since generated comprehensive networks of protein interactions in breast and head-and-neck tumor cells and, from these data, identified several hundred protein complexes under selective mutational pressure in cancer (NeST v1.0). We have piloted deep learning systems (DCell, DrugCell and TCRP) that can use this protein network information to translate a patient’s tumor mutation profile to a predicted drug response, including FDA-approved and exploratory agents. We have implemented a rich portfolio of training opportunities and, leveraging UC institutional support, expanded the CCMI consortium to include more than a dozen faculty at UC and, most recently, Stanford. In the next five years, the CCMI will seek to: (1) Generate comprehensive protein interaction networks centered on key cancer driver genes in lung squamous cells (in healthy and diseased states) as well as the PIK3CA and TP53 pathways, which are central to many tumor types; (2) Systematically extend the CCMI collection of cancer protein interaction data with protein immunofluorescent imaging and cryo-electron microscopy to formulate multi-scale cancer cell maps; (3) Dissect the functional logic of these networks and maps by systematic genetic screening experiments in the same tumor types and pathways, using a panel of scalable cell proliferation, phenotype and pathway readouts; (4) Significantly advance and harden our DrugCell interpretable deep learning system for cancer precision medicine; (5) Train the current and next generation of scientists in network biology and its applications to cancer research; and (6) Continue to build a cadre of leading investigators to expand CCMI into a global coordinated partnership.
癌症细胞地图倡议v2.0

项目成果

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Trey Ideker其他文献

Trey Ideker的其他文献

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{{ truncateString('Trey Ideker', 18)}}的其他基金

Next generation massively multiplexed combinatorial genetic screens
下一代大规模多重组合遗传筛选
  • 批准号:
    10587354
  • 财政年份:
    2023
  • 资助金额:
    $ 15.23万
  • 项目类别:
The Cancer Cell Map Initiative v2.0
癌细胞图谱计划 v2.0
  • 批准号:
    10525586
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
Core 2: Software Infrastructure for Network Models and Cell Maps
核心 2:网络模型和小区地图的软件基础设施
  • 批准号:
    10704622
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
Project 3: From Networks and Structures to Hierarchical Whole­ Cell Models of Cancer
项目 3:从网络和结构到癌症的分层全细胞模型
  • 批准号:
    10704611
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
Project 3: From Networks and Structures to Hierarchical Whole­ Cell Models of Cancer
项目 3:从网络和结构到癌症的分层全细胞模型
  • 批准号:
    10525590
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
Core 2: Software Infrastructure for Network Models and Cell Maps
核心 2:网络模型和小区地图的软件基础设施
  • 批准号:
    10525593
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
CYTOSCAPE: AN ECOSYSTEM FOR NETWORK GENOMICS
CYTOSCAPE:网络基因组学的生态系统
  • 批准号:
    10411738
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
The Cancer Cell Map Initiative v2.0
癌细胞图谱计划 v2.0
  • 批准号:
    10704587
  • 财政年份:
    2022
  • 资助金额:
    $ 15.23万
  • 项目类别:
Cytoscape: A Modeling Platform for Biomolecular Networks
Cytoscape:生物分子网络建模平台
  • 批准号:
    10415596
  • 财政年份:
    2021
  • 资助金额:
    $ 15.23万
  • 项目类别:
Cytoscape: A Modeling Platform for Biomolecular Networks
Cytoscape:生物分子网络建模平台
  • 批准号:
    10166303
  • 财政年份:
    2020
  • 资助金额:
    $ 15.23万
  • 项目类别:

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