INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE
批准号:
8738408
负责人:
TIMOTHY J YEATMAN
金额:
$48.15万
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:
2012-09-19 至 2017-08-31
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
中文摘要
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特征,并通过新型突变评估来改进其活性。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。
英文摘要
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.
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