Making cancer precision medicine real: bottlenecks and opportunities
让癌症精准医疗成为现实:瓶颈与机遇
基本信息
- 批准号:10687086
- 负责人:
- 金额:$ 100.38万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-16 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAddressCell SurvivalCell modelCellsClinicalCommunitiesComplexDNAData SetDiagnosticDrug resistanceGene ExpressionGenetic Predisposition to DiseaseGenomicsImmuneMapsMediatingMethodsMinorityModelingMolecularOrganoidsPatientsPre-Clinical ModelPrimary NeoplasmRNAResearchResearch ProposalsTestingdrug actiondrug response predictiondrug sensitivityin situ sequencinginsightneoplastic cellprecision oncologypublic health relevancetumortumor microenvironment
项目摘要
PROJECT SUMMARY
The concept of cancer precision medicine is simple: patient treatments are guided by the molecular features of
their tumor. In practice, however, the situation is more complex. Only a minority of patients at present benefit
from the approach. A number of scientific challenges must be overcome before cancer precision medicine can
become a reality for all patients. These challenges are the focus on the present research proposal. For
example, we now know that gene expression, not DNA-level aberrations, are the most predictive of drug
response, and yet the entire clinical genomic testing enterprise is focused on DNA. We therefore need to
develop methods suitable for quantitative RNA-based diagnostics, likely using emerging single cell and in situ
sequencing methods. In addition, we must develop comprehensive maps using preclinical models that make it
possible to predict drug sensitivity (and genetic vulnerabilities) given the molecular features of the tumor. This
will require expanding our repertoire of cell models (to include organoids, short-term primary tumor cultures
and models that combine tumor cells and immune cells), developing more sophisticated read-outs of drug
action beyond viability, and also developing new insights into the influence of the tumor microenvironment on
mediating cell survival and drug resistance. The present proposal aims to address these challenges over the 7
years ahead by developing new methods and datasets that will accelerate cancer precision medicine research
throughout the research community.
项目总结
癌症精准医学的概念很简单:患者的治疗是由肿瘤的分子特征来指导的
他们的肿瘤。然而在实践中,情况要复杂得多。目前只有一小部分患者受益
从方法上看。在癌症精准医学能够
成为所有患者的现实。这些挑战是本研究提案的重点。为
例如,我们现在知道,基因表达,而不是DNA水平的异常,是最具预测性的药物
然而,整个临床基因组测试企业都专注于DNA。因此,我们需要
开发适合于基于RNA的定量诊断的方法,可能使用新兴的单细胞和原位
测序方法。此外,我们必须使用临床前模型开发全面的地图,使其
考虑到肿瘤的分子特征,有可能预测药物敏感性(和遗传脆弱性)。这
将需要扩展我们的细胞模型库(包括有机物、短期原发肿瘤培养
以及结合肿瘤细胞和免疫细胞的模型),开发更复杂的药物读出
超越生存能力的行动,并对肿瘤微环境对
调节细胞存活和耐药。本提案旨在应对以下7个方面的挑战
通过开发新的方法和数据集来加速癌症精准医学研究
在整个研究界。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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{{ truncateString('TODD R. GOLUB', 18)}}的其他基金
Discovering existing medicines that abrogate cellular responses to SARS CoV-2 infection
发现消除细胞对 SARS CoV-2 感染反应的现有药物
- 批准号:
10199270 - 财政年份:2020
- 资助金额:
$ 100.38万 - 项目类别:
Making cancer precision medicine real: bottlenecks and opportunities
让癌症精准医疗成为现实:瓶颈与机遇
- 批准号:
10473781 - 财政年份:2019
- 资助金额:
$ 100.38万 - 项目类别:
Making cancer precision medicine real: bottlenecks and opportunities
让癌症精准医疗成为现实:瓶颈与机遇
- 批准号:
10018814 - 财政年份:2019
- 资助金额:
$ 100.38万 - 项目类别:
Making cancer precision medicine real: bottlenecks and opportunities
让癌症精准医疗成为现实:瓶颈与机遇
- 批准号:
9816920 - 财政年份:2019
- 资助金额:
$ 100.38万 - 项目类别:
Making cancer precision medicine real: bottlenecks and opportunities
让癌症精准医疗成为现实:瓶颈与机遇
- 批准号:
10246428 - 财政年份:2019
- 资助金额:
$ 100.38万 - 项目类别:
LINCS Data Coordination and Integration Center
LINCS数据协调与集成中心
- 批准号:
9096857 - 财政年份:2015
- 资助金额:
$ 100.38万 - 项目类别:
LINCS Data Coordination and Integration Center
LINCS数据协调与集成中心
- 批准号:
8825090 - 财政年份:2015
- 资助金额:
$ 100.38万 - 项目类别:
LINCS Data Coordination and Integration Center
LINCS数据协调与集成中心
- 批准号:
9280623 - 财政年份:2015
- 资助金额:
$ 100.38万 - 项目类别:
PQB-3: Discovery and validation of the driving mediators of cancer cachexia
PQB-3:癌症恶病质驱动介质的发现和验证
- 批准号:
8792102 - 财政年份:2014
- 资助金额:
$ 100.38万 - 项目类别:
Broad Institute LINCS Center for Transcriptomics
布罗德研究所 LINCS 转录组学中心
- 批准号:
8787845 - 财政年份:2014
- 资助金额:
$ 100.38万 - 项目类别:
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