INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
利用混合 RNA 和 DNA 分子特征进行个体化结肠癌治疗
基本信息
- 批准号:8547787
- 负责人:
- 金额:$ 46.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-09-19 至 2017-08-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAlgorithmsAllelesBRAF geneBiological AssayCancer PatientCetuximabCharacteristicsClinicalClinical DataClinical TrialsCollaborationsColon CarcinomaColorectal CancerComplexDNADataDevelopmentDiagnosticEnsureEnvironmentEpidermal Growth Factor ReceptorExperimental DesignsFailureFormalinFreezingFutureGene Expression ProfileGene MutationGenesGeneticGenetic DeterminismGenomeGenomicsGoalsHealth Care CostsHealthcareHybridsInvestigational TherapiesLaboratoriesMeasuresMolecularMolecular ProfilingMutateMutationNatureOutcomeParaffin EmbeddingPathway interactionsPatientsPharmaceutical PreparationsPharmacologic SubstancePopulationPrevalenceProgression-Free SurvivalsProtocols documentationRNAReadingRegimenReproducibilityResistanceRiskRoleSamplingSeasonsSensitivity and SpecificitySequence AnalysisSignal TransductionSpecimenSystemTestingToxic effectTrainingTranslationsValidationbasecancer carecancer therapyclinical applicationclinical phenotypecohortcostcost effectiveexome sequencingimprovedmutantnoveloncologypublic health relevanceresponsesuccesstherapeutic targettumortumor progression
项目摘要
DESCRIPTION (provided by applicant): Predicting which cancer patients will best respond to therapy is an enormous health care issue. It has been recently suggested, based on early reads of whole exome sequencing data, that there may only be ~12 molecular pathways that drive the development and progression of cancer. Many experimental therapies are now targeting these pathways. We believe that gene expression signatures may be one of the best ways to judge the activation of a particular molecular pathway, by providing a "molecular summary" of the activity of many genes. Moreover, we believe that the selective addition of mutational assessment may improve the resolving power of a hybrid, multi-analyte (DNA + RNA) test that may be used to guide patients to the most effective drugs. We have recently developed gene expression signatures to measure the activation of two of the most important pathways in colon cancer, RAS and PI3K, for which there is an increasing availability of pathway targeted therapeutics. Due to the complex nature of these pathways, simple analysis of canonical single gene mutations only identifies the response characteristics of a proportion (<30%) of the population. Here, we propose to technically validate the existing RAS and PI3K signatures and to refine their activity through novel mutational assessment. Multi-analyte signatures/ algorithms will be clinically validated in a CLIA environment with a cohort of colorectal cancer patients treated with cetuximab therapy. This approach will prepare signatures for clinical application in the near future.
描述(由申请人提供):预测哪些癌症患者对治疗的反应最好是一个巨大的卫生保健问题。最近有人提出,基于全外显子组测序数据的早期读数,可能只有约12种分子途径驱动癌症的发展和进展。许多实验性疗法现在都针对这些途径。我们相信,基因表达的签名可能是最好的方式来判断一个特定的分子途径的激活,通过提供一个“分子总结”的活动,许多基因。此外,我们认为,选择性地增加突变评估可以提高杂交多分析物(DNA + RNA)测试的分辨率,该测试可用于指导患者使用最有效的药物。我们最近开发了基因表达特征来测量结肠癌中两个最重要的通路RAS和PI 3 K的激活,对于这两个通路,靶向治疗的可用性越来越高。由于这些途径的复杂性,对典型单基因突变的简单分析只能确定一部分(<30%)人群的反应特征。在这里,我们建议从技术上验证现有的RAS和PI 3 K签名,并通过新的突变评估来完善它们的活性。多分析物特征/算法将在CLIA环境中使用接受西妥昔单抗治疗的结直肠癌患者队列进行临床验证。这种方法将在不久的将来为临床应用准备签名。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
TIMOTHY J YEATMAN其他文献
TIMOTHY J YEATMAN的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('TIMOTHY J YEATMAN', 18)}}的其他基金
CLINCIAL VALIDATION OF APC AND TP53 AS BIOMARKERS FOR CETUXIMAB RESPONSE
APC 和 TP53 作为西妥昔单抗反应生物标志物的临床验证
- 批准号:
10789666 - 财政年份:2023
- 资助金额:
$ 46.83万 - 项目类别:
APC + TP53 Combinatorial Mutations Emerging as Biomarkers to Predict EGFRI Sensitivity
APC TP53 组合突变作为预测 EGFRI 敏感性的生物标志物
- 批准号:
10610600 - 财政年份:2022
- 资助金额:
$ 46.83万 - 项目类别:
Detection of Colorectal Cancer Adaptive Mutability May Justify Combination of Targeted- and Immune-Therapies
结直肠癌适应性突变的检测可能证明靶向治疗和免疫治疗相结合的合理性
- 批准号:
10289627 - 财政年份:2021
- 资助金额:
$ 46.83万 - 项目类别:
Detection of Colorectal Cancer Adaptive Mutability May Justify Combination of Targeted- and Immune-Therapies
结直肠癌适应性突变的检测可能证明靶向治疗和免疫治疗相结合的合理性
- 批准号:
10613171 - 财政年份:2021
- 资助金额:
$ 46.83万 - 项目类别:
APC + TP53 Combinatorial Mutations Emerging as Biomarkers to Predict EGFRI Sensitivity
APC TP53 组合突变作为预测 EGFRI 敏感性的生物标志物
- 批准号:
10289625 - 财政年份:2021
- 资助金额:
$ 46.83万 - 项目类别:
CLINCIAL VALIDATION OF APC AND TP53 AS BIOMARKERS FOR CETUXIMAB RESPONSE
APC 和 TP53 作为西妥昔单抗反应生物标志物的临床验证
- 批准号:
10373564 - 财政年份:2019
- 资助金额:
$ 46.83万 - 项目类别:
CLINCIAL VALIDATION OF APC AND TP53 AS BIOMARKERS FOR CETUXIMAB RESPONSE
APC 和 TP53 作为西妥昔单抗反应生物标志物的临床验证
- 批准号:
10381742 - 财政年份:2019
- 资助金额:
$ 46.83万 - 项目类别:
INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
利用混合 RNA 和 DNA 分子特征进行个体化结肠癌治疗
- 批准号:
8738408 - 财政年份:2012
- 资助金额:
$ 46.83万 - 项目类别:
INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
利用混合 RNA 和 DNA 分子特征进行个体化结肠癌治疗
- 批准号:
9133794 - 财政年份:2012
- 资助金额:
$ 46.83万 - 项目类别:
INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
利用混合 RNA 和 DNA 分子特征进行个体化结肠癌治疗
- 批准号:
8918486 - 财政年份:2012
- 资助金额:
$ 46.83万 - 项目类别:
相似海外基金
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
- 批准号:
EP/Y029089/1 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
- 批准号:
2337776 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
- 批准号:
2338816 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
- 批准号:
2338846 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
- 批准号:
2348261 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
- 批准号:
2348457 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
- 批准号:
2404989 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
- 批准号:
2339310 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
- 批准号:
2339669 - 财政年份:2024
- 资助金额:
$ 46.83万 - 项目类别:
Continuing Grant