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DESCRIPTION (provided by applicant): Most human tumors, particularly those derived from epithelial cancers, exhibit global genomic alterations that make it difficult to identify mutations critical for cell transformation and to define the consequences of specific cancer-associated mutations. Recent advances in technologies to identify structural changes in human cancers now make it possible to consider enumerating all of the genetic alterations harbored by a particular tumor. Despite these advances in annotating structural alterations in cancer genomes, identifying the genes targeted by specific amplification or deletion events and deciphering the function of targeted gene mutations remains a major challenge. Indeed, the parallel development of efficient methods to annotate the function of cancer-associated genes is necessary to distill validated cancer targets from this structural description of cancer genomes. This proposal focuses on the integration of newly developed, high throughput methods to functionally annotate the cancer genome. Specifically, methods to perform large scale loss-of function, gain-of-function, and protein-protein network analyses will be combined in a novel integrated program to identify and validate functionally important cancer genes. Specifically, these studies build upon prior work by our laboratories to develop and implement genome scale RNA interference libraries, complete collections of human open reading frames (ORFs) and comprehensive protein-protein interaction maps. Although the basic tools required to perform large-scale studies are now available, the integration of such whole genome approaches represents an entirely new endeavor that requires the further development of these nascent technologies, the fabrication of comprehensive reagents and the creation of new ways to connect these datasets to achieve a scale beyond what has been previously performed. As such, the overarching goals of this R33 application is to apply these technologies in an integrated manner while simultaneously identifying and validating genes of particular promise for therapeutic targeting. The long-term goal of these studies is to provide a foundation for the expansion of these efforts at genome scale.
期刊论文(4)
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会议论文
DOI: 10.1158/2159-8290.cd-11-0110
发表时间: 2011-09
期刊: Cancer discovery
影响因子: 28.2
作者: [MacConaill LE, Van Hummelen P, Meyerson M, Hahn WC]
通讯作者: Hahn WC
DOI: 10.1038/onc.2010.493
发表时间: 2011-02-10
期刊: ONCOGENE
影响因子: 8
作者: [Shen, R. R., Hahn, W. C.]
通讯作者: Hahn, W. C.
DOI: 10.1038/nmeth.1638
发表时间: 2011-06-26
期刊: NATURE METHODS
影响因子: 48
作者: [Yang, Xiaoping, Boehm, Jesse S., Yang, Xinping, Salehi-Ashtiani, Kourosh, Hao, Tong, Shen, Yun, Lubonja, Rakela, Thomas, Sapana R., Alkan, Ozan, Bhimdi, Tashfeen, Green, Thomas M., Johannessen, Cory M., Silver, Serena J., Cindy Nguyen, Murray, Ryan R., Hieronymus, Haley, Balcha, Dawit, Fan, Changyu, Lin, Chenwei, Ghamsari, Lila, Vidal, Marc, Hahn, William C., Hill, David E., Root, David E.]
通讯作者: Root, David E.
DOI: 10.1158/0008-5472.can-09-1704
发表时间: 2009-10-15
期刊: Cancer research
影响因子: 11.2
作者: [Firestein R, Hahn WC]
通讯作者: Hahn WC
Development of p300/CBP histone acetyltransferase inhibitors for oncogene-driven cancers
  • 批准号:
    10627744
  • 项目类别:
  • 资助金额:
    $65.12万
  • 财政年份:
    2022
  • 负责人:
    William C. Hahn
  • 依托单位:
Novel genetic dependencies in VRK2 methylated glioblastoma multiforme
  • 批准号:
    10046375
  • 项目类别:
  • 资助金额:
    $17.8万
  • 财政年份:
    2020
  • 负责人:
    William C. Hahn
  • 依托单位:
Development and implementation of multiplex methods to understand the biology and heterogeneity of patient-derived cancer models
  • 批准号:
    10004385
  • 项目类别:
  • 资助金额:
    $100.49万
  • 财政年份:
    2020
  • 负责人:
    William C. Hahn
  • 依托单位:
Systematic interrogation of the pancreatic cancer microenvironment in patient-derived specimens
  • 批准号:
    10250566
  • 项目类别:
  • 资助金额:
    $56.84万
  • 财政年份:
    2017
  • 负责人:
    William C. Hahn
  • 依托单位:
海外基金