Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53
Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53
批准号:
9902384
负责人:
Wenyi Wang
金额:
$42.02万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2023-03-31
关键词:
AccountingAffectAssessment toolBRCA1 geneBioinformaticsCancer CenterCancer EtiologyClinicClinicalClinical ManagementComputer softwareCounselingCountryDataData SetDecision MakingDiseaseEarly DiagnosisEducationEpidemiologistEpithelialEpitheliumEvaluationExtended FamilyFamilyFamily history ofFamily memberFrequenciesFutureGeneticGenetic CounselingGerm-Line MutationHereditary Breast and Ovarian Cancer SyndromeHigh-Risk CancerHumanIndividualInheritedInternationalLi-Fraumeni SyndromeLifeMalignant NeoplasmsMedicalModelingMutationNational Cancer InstituteOncogenesOrganOutcomeOutcomes ResearchPatternPediatricsPenetrancePhysiciansPopulationProbabilityPublic HealthRecording of previous eventsResearchRiskRisk AssessmentScreening for cancerSiteSoftware ToolsStatistical MethodsSyndromeTP53 geneTestingTissuesTumor Suppressor GenesUniversity of Texas M D Anderson Cancer Centercancer diagnosiscancer geneticscancer riskcancer sitecancer typeclinical practiceearly onsetgenetic counselorimprovedindexinglarge datasetslifetime riskmalignant breast neoplasmmathematical modelmembermortalitymutation carrieropen sourceprogramsreceptorrisk prediction modelscreeningscreening programsoftware developmenttool
中文摘要
项目摘要
复杂的风险预测模型极大地改进了对遗传性癌症的筛查和检测
乳腺癌中的BRCA1/2突变等症状。这样一种定量的风险预测模型迫在眉睫
早期发现LI-Fraumeni综合征(LFS)所需的
死亡率和对该综合征的监测测试。LFS主要由TP53的种系突变引起
肿瘤抑制基因,其特征是癌症发生在生命的相对早期,通常反复发生在
,并影响与其他癌症综合征重叠的多个部位,特别是
遗传性乳腺癌和卵巢癌综合征。我们的目标是提高临床管理水平。
有早发性癌症家族史的个人,通过建立数学模型来评估1)
在进行TP53检测之前的生殖系突变携带者概率和2)发病的绝对终生风险
携带TP53突变个体的癌症。我们的理念是,我们的先进型号将使
对遗传性TP53突变家系进行系统全面的风险评估,使基因
咨询师和医生可以为携带TP53的个体提供更有效的咨询和筛查
生殖系突变,考虑到这些人的高频率和不同的癌症类型结果。我们会
通过以下具体目标完成我们的研究目标。1)描述特定事件的开始
LFS高危个体的癌症类型:a)通过以下方式估计TP53突变相关癌症的外显率
癌症类型,使用MD Anderson癌症中心(MDACC)和外部诊所的大家庭数据;
B)开发LFSPROCS以纳入癌症类型特定的渗透率,并在#年验证这些模型
预测未来的风险;c)用癌症风险的其他修饰物来丰富LFSPRO,例如HER2状态
乳腺癌;2)表征有LFS风险的个人的原发癌症的数量:a)估计
利用大家庭数据对原发癌症数量的外显率;c)开发LFSPROMP和
LFSPROMP CS纳入新的渗透并验证这些模型;以及3)开发软件和
在癌症基因诊所中传播。我们的重大贡献将是开发一种先进的
量化风险评估工具,将提供更准确的风险量化,并提供一般
为将来的风险评估纳入更多的癌症部位和癌症基因的统计框架。
相关的软件套件LFSPRO将很快传播到MDACC Li-Fraumeni Education
和早期检测(Lead)筛查计划,以及全国的其他筛查研究。LFSPRO是
已经集成在BayesMendel和Cancergene包中,这两个包广泛用于风险评估和
在高危癌症诊所,特别是乳腺癌诊所进行咨询。随着我们先进的
这些软件工具将继续为临床环境下的新人群提供LFS咨询
并接触到更多受TP53突变影响的家庭。
英文摘要
Project Summary
Sophisticated risk prediction modeling has greatly improved screening and testing for inheritable cancer
syndromes such as BRCA1/2 mutations in breast cancer. Such a quantitative risk prediction model is urgently
needed for the early detection of the Li-Fraumeni syndrome (LFS) following the demonstration of reduced
mortality with surveillance testing for that syndrome. LFS primarily arises from germline mutations in the TP53
tumor suppressor gene and is characterized by cancer occurring relatively early in life, often repeatedly over a
lifetime, and affecting multiple sites that overlap with those of other cancer syndromes, in particular the
hereditary breast and ovarian cancer syndrome. Our objective is to improve the clinical management of
individuals with a family history of early-onset cancers by developing mathematical models to assess 1)
germline mutation carrier probability prior to TP53 testing and 2) the absolute lifetime risk of developing
cancers in individuals with TP53 mutations. Our rationale is that our advanced models will enable the
systematic and comprehensive risk evaluation of families with inherited TP53 mutations so that genetic
counselors and physicians can provide more effective counseling and screening of individuals who carry TP53
germline mutations, given the high frequency and varied cancer-type outcomes in these individuals. We will
accomplish our research objective through the following Specific Aims. 1) Characterize the onset of specific
cancer types for individuals at risk of LFS: a) Estimate the penetrance of TP53 mutation-associated cancers by
cancer type, using extended-family data from MD Anderson Cancer Center (MDACC) and from external clinics;
b) Develop LFSPROCS to incorporate cancer-type-specific penetrances, and validate these models in
predicting future risk; c) Enrich LFSPRO with additional modifiers of cancer risk, such as HER2 status for
breast cancer; 2) Characterize the number of primary cancers for individuals at risk of LFS: a) estimate the
penetrance for the number of primary cancers using extended-family data; c) Develop LFSPROMP and
LFSPROMP+CS to incorporate new penetrances and validate these models; and 3) Develop software and
disseminate it among cancer genetic clinics. Our significant contribution will be to develop an advanced
quantitative risk assessment tool that will provide more accurate risk quantification, and to provide a general
statistical framework for including additional cancer sites and cancer genes for risk assessment in the future.
The associated software suite LFSPRO will be quickly disseminated into the MDACC Li-Fraumeni Education
and Early Detection (LEAD) screening program, as well as other screening studies in the nation. LFSPRO is
already integrated in BayesMendel and CancerGene packages, which are widely used for risk assessment and
counseling at high-risk cancer clinics, in particular breast cancer clinics. With the addition of our advanced
models, these software tools will continue to bring LFS counseling to new populations under clinical settings
and reach more families that are affected by TP53 mutations.
期刊论文(0)
专著(0)
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会议论文
Statistical methods for genomic analysis of heterogeneous tumors
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批准号:10662552
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项目类别:
-
资助金额:$45.93万
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财政年份:2022
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负责人:Wenyi Wang
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依托单位:
Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53
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批准号:10370406
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项目类别:
-
资助金额:$35.15万
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财政年份:2019
-
负责人:Wenyi Wang
-
依托单位:
Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53
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批准号:9755176
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项目类别:
-
资助金额:$35.98万
-
财政年份:2019
-
负责人:Wenyi Wang
-
依托单位:
Statistical methods for genomic analysis of heterogeneous tumors
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批准号:8932668
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项目类别:
-
资助金额:$29.62万
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财政年份:2014
-
负责人:Wenyi Wang
-
依托单位:
Statistical methods for genomic analysis of heterogeneous tumors
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批准号:8817368
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项目类别:
-
资助金额:$40.95万
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财政年份:2014
-
负责人:Wenyi Wang
-
依托单位:
Statistical methods for genomic analysis of heterogeneous tumors
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批准号:9118900
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项目类别:
-
资助金额:$29.62万
-
财政年份:2014
-
负责人:Wenyi Wang
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依托单位:
海外基金