Statistical Methods for Identifying Clonal Tumors
Statistical Methods for Identifying Clonal Tumors
批准号:
7743500
负责人:
Colin B Begg
金额:
$35.41万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-12-01 至 2011-11-30
关键词:
AffectBody partChromosome ArmCrossbreedingDataDevelopmentDiagnosisDiagnostic testsDistantEvaluationEventFingerprintGenesGeneticGenomeHybridization ArrayIndividualLoss of HeterozygosityMalignant NeoplasmsMedicalMethodsMicroscopicModelingMolecularMolecular DiagnosisMolecular ProfilingMutationNeoplasm MetastasisOperative Surgical ProceduresPaired ComparisonPathologicPathologistPatientsPatternPoint MutationProceduresProcessPropertyRelative (related person)ResearchResearch PersonnelResourcesSecond Primary CancersSideSiteSomatic MutationStatistical MethodsTechniquesTestingWorkbasecandidate markerclinically relevantcomparativecomputerized toolsexperiencegenome-widepublic health relevancesoftware developmentstatisticstumor
中文摘要
描述(由申请人提供):癌症的定义特征是转移,即肿瘤定植于身体远处部位的能力。然而,独立的(第二原发性)癌症也经常发生。区分第二原发灶与转移灶的能力通常具有很大的临床相关性,因为它可以影响局部(手术)与全身(药物)治疗的适当性。历史上,病理学家根据肉眼和显微镜病理标准区分这些。近年来,癌症研究人员已经开始比较成对肿瘤的分子谱,以期在分子水平上区分独立的癌症与共享克隆起源(例如转移)的癌症。这些研究涉及基于体细胞突变模式(如等位基因获得或丢失,或在肿瘤中经常经历体细胞突变的基因中的点突变)对肿瘤对(来自同一患者)进行并排比较。在这一领域中,用于将肿瘤分类为独立与克隆的统计方法最近才开始开发并评估其有效性。建立在我们最近开发的用于比较杂合性缺失的候选标记集的方法上的研究的基础上,我们现在计划开发用于比较来自两个肿瘤的阵列CGH谱的正式程序,以确定它们是克隆的(转移的)还是独立的起源。我们的策略包括对肿瘤上明显的等位基因损失和增益的相关性进行全局评估,以及对染色体臂内的个体、潜在克隆体细胞事件进行更精确的比较。根据研究结果,我们将开发软件,为研究人员提供计算工具,以达到这些分子诊断。公共卫生相关性:癌症可以通过手术治愈,也可能随后扩散到身体的其他部位。后一个过程被称为转移。已经治愈的患者也有可能发展出新的独立癌症。当一个新的肿瘤发展时,病理学家检查肿瘤以确定它是转移还是新的原发性癌症。然而,在某些情况下,病理学家很难区分新的原发癌和转移癌,但这种诊断对于决定适当的治疗过程可能非常重要。我们相信,病理学家在这些情况下的困境可以通过比较两种肿瘤的“遗传指纹”来解决。我们提出的研究涉及开发统计技术,用于检查这些遗传指纹中的信息,代表肿瘤发展过程中发生的突变,以提供准确的病理诊断。
英文摘要
DESCRIPTION (provided by applicant): The defining feature of cancer is metastasis, the ability of tumors to colonize distant sites of the body. However, independent (second primary) cancers also occur frequently. The ability to distinguish a second primary from a metastasis is often of great clinical relevance, as it can affect the appropriateness of local (surgical) versus systemic (medical) treatment. Historically pathologists have distinguished these on the basis of gross and microscopic pathologic criteria. In recent years cancer investigators have begun to compare the molecular profiles of pairs of tumors with a view to distinguishing independent cancers from those that share a clonal origin (e.g. metastases) at the molecular level. These studies involve the side-by-side comparison of pairs of tumors (from the same patient) on the basis of patterns of somatic mutations, such as allelic gains or losses, or point mutations in genes that frequently experience somatic mutations in tumors. Statistical methods for classifying the tumors as independent versus clonal in this field have only recently begun to be developed and evaluated for validity. Building on research on methods for comparing sets of candidate markers of loss of heterozygosity that we have recently developed, we now plan to develop formal procedures for comparing array CGH profiles from two tumors to determine if they are of clonal (metastatic) or independent origin. Our strategy involves a global evaluation of the correlation of apparent allelic losses and gains on the tumors, and a much more precise comparison of individual, potentially clonal somatic events within chromosome arms. Based on the results of the research we will develop software t provide investigators with the computational tools to arrive at these molecular diagnoses. PUBLIC HEALTH RELEVANCE: Cancers can be cured by surgery or they may spread subsequently to other parts of the body. This latter process is known as metastasis. It is also possible for a patient who has been cured to develop a new, independent occurrence of cancer. When a new tumor develops pathologists examine the tumor to determine if it is a metastasis or a new primary cancer. However, in some circumstances it is difficult for the pathologist to distinguish a new primary cancer from a metastasis, and yet this diagnosis may be very important for deciding upon the appropriate course of treatment. We believe that the pathologist's dilemma in these circumstances can be resolved by comparing the "genetic fingerprints" of the two tumors. Our proposed research involves developing statistical techniques for examining the information in these genetic fingerprints, representing the mutations that have occurred during the development of the tumors, in order to provide accurate pathological diagnoses.
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会议论文
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Statistical Methods for Identifying Clonal Tumors
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海外基金