Enhancing Global Diversity in Cancer Clinical Genetics
增强癌症临床遗传学的全球多样性
基本信息
- 批准号:10164921
- 负责人:
- 金额:$ 17.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-18 至 2022-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAfrica South of the SaharaAgeBRCA1 geneBRCA2 geneBreastBreast Cancer Risk FactorCaucasiansCessation of lifeChemopreventionClinicalClinical ManagementColorectalCounselingDNA Sequence AlterationDataDevelopmentDiagnosisEndometrialEuropeanEvaluationEvaluation ResearchFeasibility StudiesGeneticGenetic CounselingGenetic Predisposition to DiseaseGenetic ProcessesGenetic ResearchGenetic RiskGoalsGuidelinesHealthHealth systemHereditary Malignant NeoplasmHereditary Nonpolyposis Colorectal NeoplasmsIncidenceIndividualInheritedInterventionMalignant NeoplasmsMalignant neoplasm of prostateMedical GeneticsMilitary HospitalsMutateMutationNigerianOperative Surgical ProceduresOvarianPathogenicityPatientsPersonal CommunicationPoly(ADP-ribose) PolymerasesPopulationPopulation HeterogeneityPrevalencePreventionProstateProtocols documentationResearchResourcesRiskRwandaSystems IntegrationTP53 geneTeaching HospitalsTestingTreatment ProtocolsUniversitiesactionable mutationcancer geneticscancer riskclinical translationethnic diversityevidence basegenetic informationgenetic testinghealth care settingshealth disparityimprovedinhibitor/antagonistinterestmalignant breast neoplasmmortalitymutation carrierracial diversityresponsetooltumor
项目摘要
PROJECT SUMMARY/ABSTRACT
This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA-
20-032.
Inherited genetic information can reduce cancer risk and mortality using protocols for patient
ascertainment, testing, counseling, prevention, and treatment. There is growing evidence that inherited genetic
mutations represent a large proportion of cancer cases in sub-Saharan Africa (SSA). Nigerian breast cancer
cases have a 2.5-fold higher rate of inherited susceptibility mutations than US Whites, with BRCA2 being the
most commonly mutated in Nigerian breast cancer, and higher rates of BRCA and TP53 mutations compared
to observations made in Caucasians in Rwanda. These preliminary observations highlight the need for further
large studies to better define the inheritance of breast cancer risk in SSA.
Most cancer genetic testing data does not represent the racial and ethnic diversity of the US or global
population. This deficit of diverse populations in cancer genetics research limits the application of these data to
all populations. In addition, it has been demonstrated that genetic misdiagnoses can arise when diverse
populations and their mutational spectrum is not included when making inferences about pathogenicity and risk
and can exacerbate health disparities. Thus, studies that include a broader spectrum of individuals in cancer
genetics research will benefit all populations.
In order to develop and evaluate the potential for genetic testing in SSA, we propose a proof of concept
feasibility study of hereditary cancer that will contribute data on the prevalence of hereditary cancer mutations
in SSA and inform the development of SSA-specific guidelines for cancer genetic testing. We will address
these goals by undertaking the following specific aims: Specific Aim 1: Develop and evaluate a set of
essential cancer genetic protocols for cancer genetic testing, counseling, and management in low resource
settings; and Specific Aim 2: Undertake a pilot evaluation of research genetic testing and counseling in 100
breast and prostate cancer cases in Rwanda.
The proposed pilot research will not only enhance cancer genetics research and clinical translation in SSA
but will address the critical need for increased ethnic diversity in cancer genetics data, which to date has been
dominated by European ancestry data. Ethnically diverse genetic data will aid in the appropriate development
and implementation of cancer genetic testing for all populations, and in particular will reduce the potential for
genetic misdiagnoses and improved interpretation of cancer genetic risk in US populations.
项目概要/摘要
本申请是为了响应被识别为 NOT-CA- 的特殊利益通知 (NOSI) 而提交的
20-032。
使用针对患者的方案,遗传遗传信息可以降低癌症风险和死亡率
确定、检测、咨询、预防和治疗。越来越多的证据表明遗传性基因
撒哈拉以南非洲 (SSA) 的癌症病例中,突变占很大比例。尼日利亚乳腺癌
病例的遗传易感性突变率比美国白人高 2.5 倍,其中 BRCA2 是
尼日利亚乳腺癌中最常见的突变,且 BRCA 和 TP53 突变率较高
对卢旺达白人的观察。这些初步观察结果强调需要进一步
大型研究,以更好地确定 SSA 中乳腺癌风险的遗传。
大多数癌症基因检测数据并不代表美国或全球的种族和民族多样性
人口。癌症遗传学研究中不同人群的这种缺陷限制了这些数据的应用
所有人群。此外,已经证明,当基因多样化时,可能会出现遗传误诊。
在推断致病性和风险时,不包括人群及其突变谱
并可能加剧健康差距。因此,研究包括更广泛的癌症个体
遗传学研究将使所有人群受益。
为了开发和评估 SSA 基因检测的潜力,我们提出了概念验证
遗传性癌症的可行性研究将提供有关遗传性癌症突变发生率的数据
参与 SSA 并为制定 SSA 特定癌症基因检测指南提供信息。我们将解决
通过实现以下具体目标来实现这些目标: 具体目标 1:制定并评估一套
用于癌症基因检测、咨询和资源匮乏管理的基本癌症基因方案
设置;具体目标 2:在 100 个国家开展研究基因检测和咨询试点评估
卢旺达的乳腺癌和前列腺癌病例。
拟议的试点研究不仅将加强 SSA 的癌症遗传学研究和临床转化
但将解决增加癌症遗传学数据种族多样性的迫切需求,迄今为止,这一需求已
以欧洲血统数据为主。种族多样化的遗传数据将有助于适当的发展
对所有人群进行癌症基因检测,特别是会减少癌症的可能性
遗传误诊和改进对美国人群癌症遗传风险的解释。
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)
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Jinbo Chen的其他文献
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{{ truncateString('Jinbo Chen', 18)}}的其他基金
Data and Information Integration for Risk Prediction in the Era of Big Data
大数据时代的数据与信息融合风险预测
- 批准号:
10021609 - 财政年份:2019
- 资助金额:
$ 17.77万 - 项目类别:
Data and Information Integration for Risk Prediction in the Era of Big Data
大数据时代的数据与信息融合风险预测
- 批准号:
10480872 - 财政年份:2019
- 资助金额:
$ 17.77万 - 项目类别:
Data and Information Integration for Risk Prediction in the Era of Big Data
大数据时代的数据与信息融合风险预测
- 批准号:
10249251 - 财政年份:2019
- 资助金额:
$ 17.77万 - 项目类别:
Precision Assessment and Delivery of Cancer Risks in BRCA 1/2 Mutation Cancers
BRCA 1/2 突变癌症的癌症风险的精确评估和传递
- 批准号:
10228006 - 财政年份:2017
- 资助金额:
$ 17.77万 - 项目类别:
Precision Assessment and Delivery of Cancer Risks in BRCA 1/2 Mutation Cancers
BRCA 1/2 突变癌症的癌症风险的精确评估和传递
- 批准号:
9762870 - 财政年份:2017
- 资助金额:
$ 17.77万 - 项目类别:
Precision Assessment and Delivery of Cancer Risks in BRCA 1/2 Mutation Cancers
BRCA 1/2 突变癌症的癌症风险的精确评估和传递
- 批准号:
9381396 - 财政年份:2017
- 资助金额:
$ 17.77万 - 项目类别:
Precision Assessment and Delivery of Cancer Risks in BRCA 1/2 Mutation Cancers
BRCA 1/2 突变癌症的癌症风险的精确评估和传递
- 批准号:
9567099 - 财政年份:2017
- 资助金额:
$ 17.77万 - 项目类别:
Statistical Methods for Cancer Absolute Risk Prediction
癌症绝对风险预测的统计方法
- 批准号:
8503712 - 财政年份:2013
- 资助金额:
$ 17.77万 - 项目类别:
Statistical Methods for Cancer Absolute Risk Prediction
癌症绝对风险预测的统计方法
- 批准号:
8619604 - 财政年份:2013
- 资助金额:
$ 17.77万 - 项目类别:
Statistical Methods for Cancer Absolute Risk Prediction
癌症绝对风险预测的统计方法
- 批准号:
9052041 - 财政年份:2013
- 资助金额:
$ 17.77万 - 项目类别:
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