Molecular Genetics of HNPCC
HNPCC 的分子遗传学
基本信息
- 批准号:8067773
- 负责人:
- 金额:$ 53.08万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:1997
- 资助国家:美国
- 起止时间:1997-06-01 至 2013-04-30
- 项目状态:已结题
- 来源:
- 关键词:AbbreviationsAgeAge of OnsetAreaAspirinBase Excision RepairsBudgetsCDK4 geneCHEK2 geneCancer ModelCandidate Disease GeneCell CycleCell Cycle CheckpointCell Cycle ProgressionCellsClassificationClinicalClinical TrialsColorectal CancerComplexCyclin D1DataDatabasesDefectDevelopmentDiseaseEarly DiagnosisEthnic OriginFoundationsGenderGene MutationGene OrderGenesGenetic PolymorphismGenetic RiskGenomeGenotypeGerm-Line MutationGoalsHealthHereditary Nonpolyposis Colorectal NeoplasmsIndividualLarge Intestine CarcinomaLearningLeukocytesLinkage DisequilibriumMDM2 geneMachine LearningMaintenanceMalignant NeoplasmsMediatingMicrosatellite InstabilityMismatch RepairModelingMolecular GeneticsMutateNational Cancer InstituteNonhomologous DNA End JoiningNucleotide Excision RepairObesityPathway interactionsPhasePlayPreventiveProteolysisResearch DesignResourcesRiskRoleSTK6 geneSingle Nucleotide PolymorphismSmokingSpecimenTechniquesTestingTreesUbiquitinationValidationWorkaurora-A kinasebasecancer sitecdc Genesearly onsetforestgene interactiongenetic varianthomologous recombinationmutation carriernovelperipheral bloodprotein protein interactiontool
项目摘要
DESCRIPTION (provided by applicant): The overall goal of this application is to elucidate genetic risk modifiers influencing age of onset of hereditary nonpolyposis colorectal cancer (HNPCC) using a pathway-based approach. The overall hypothesis of this proposal is that SNPs in cell cycle pathways influence the efficiency of the finely tuned mechanisms of cell cycle progression. We will continue to build and expand upon our unique clinical and specimen resource of mismatch repair gene mutation carriers in order to accomplish this goal. In aim 1, we will determine the role that genetic variants in cell cycle genes have on risk for development of early onset HNPCC. We will use the Illumina Golden Gate platform to genotype SNPs from 153 cell cycle genes. We will evaluate the main effects of SNPs in these genes using a two-phase study design in order to determine if there are differences in age-associated risk for development of HNPCC between carriers of the wild type genotype vs. those carrying one or two copies of the SNP. In aim 2, we will use novel machine learning analytic tools to determine if we can identify combinations of cell cycle SNPs that work together to influence risk for development of early onset HNPCC. Two approaches will be used to accomplish this goal. A focused candidate gene approach, and the second is an exploratory, pathways based approach. In the focused candidate approach, we have selected 12 candidate genes because they are known to interact with each other in the cell cycle pathways and there is evidence that SNPs in these genes influence risk for HNPCC or other cancers. We will determine if combinations of these SNPs work together to influence development of HNPCC at an early age. In the second approach we will investigate SNPs in all 153 of the genes, including the 12 candidate genes. We hypothesize that there are many possible combinations of cell cycle genes that work together and under the influence of SNPS, contribute to development of HNPCC at an early age. We will use Random Forests (RF) modeling to rank all of the SNPs from these genes. RF can handle large numbers of predictor variables such as SNPs and provides estimates of variable importance. We will then use CART to build age-to-onset trees using the SNPs ranked the highest from RF. The proposed studies will contribute to our long-term goal to develop a risk model for early onset HNPCC by defining the role that SNPs in cell cycle genes play in risk for HNPCC. They will also provide important information regarding novel gene-gene interactions contributing to risk for development of HNPCC at an earlier age. The National Cancer Institute in its 2006 budget proposal cited risk prediction as an area of extraordinary opportunity. Risk prediction models for cancer could provide valuable tools for identifying individuals who may benefit from preventive treatments or increased surveillance or who are good candidates to participate in clinical trials. PUBLIC HEALTH REVELANCE: The proposed studies will contribute to our long-term goal to develop a risk model for HNPCC, which may also have important implications for sporadic colorectal cancer as well as other cancer sites.
描述(由申请人提供):本申请的总体目标是使用基于途径的方法阐明影响遗传性非息肉病性结直肠癌(HNPCC)发病年龄的遗传风险调节因子。该提议的总体假设是细胞周期途径中的SNP影响细胞周期进展的精细调节机制的效率。我们将继续建立和扩大我们独特的错配修复基因突变携带者的临床和标本资源,以实现这一目标。在目标1中,我们将确定细胞周期基因中的遗传变异对早发性HNPCC发展风险的作用。我们将使用Illumina Golden Gate平台对来自153个细胞周期基因的SNP进行基因分型。我们将使用两阶段研究设计评估这些基因中SNP的主要影响,以确定野生型基因型携带者与携带一个或两个SNP拷贝的携带者之间是否存在HNPCC发展的年龄相关风险差异。在目标2中,我们将使用新的机器学习分析工具来确定我们是否可以识别细胞周期SNP的组合,这些组合共同影响早发性HNPCC的发展风险。将采用两种方法来实现这一目标。一种是集中的候选基因方法,第二种是探索性的,基于途径的方法。在重点候选方法中,我们选择了12个候选基因,因为已知它们在细胞周期途径中相互作用,并且有证据表明这些基因中的SNP会影响HNPCC或其他癌症的风险。我们将确定这些SNP的组合是否共同影响HNPCC在早期的发展。在第二种方法中,我们将研究所有153个基因中的SNP,包括12个候选基因。我们推测,有许多可能的细胞周期基因的组合,一起工作,并在SNPS的影响下,有助于HNPCC在早期的发展。我们将使用随机森林(RF)建模来对来自这些基因的所有SNP进行排名。RF可以处理大量的预测变量,如SNP,并提供变量重要性的估计。然后,我们将使用CART来使用RF中排名最高的SNP构建年龄至发病树。这些研究将有助于我们的长期目标,即通过确定细胞周期基因中SNP在HNPCC风险中的作用,建立早发性HNPCC的风险模型。他们还将提供有关新的基因-基因相互作用的重要信息,有助于在较早的年龄HNPCC的发展风险。国家癌症研究所在其2006年预算提案中将风险预测列为一个具有非凡机会的领域。癌症风险预测模型可以提供有价值的工具,用于识别可能从预防性治疗或增加监测中受益的个体,或者是参与临床试验的良好候选人。公共卫生部门:拟议的研究将有助于我们建立HNPCC风险模型的长期目标,这也可能对散发性结直肠癌以及其他癌症部位具有重要意义。
项目成果
期刊论文数量(29)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Association of the CpG island methylator phenotype with family history of cancer in patients with colorectal cancer.
- DOI:
- 发表时间:2003-08
- 期刊:
- 影响因子:11.2
- 作者:M. Frazier;Lixuan Xi;J. Zong;Nancy Viscofsky;A. Rashid;E. Wu;P. Lynch;C. Amos;J. Issa
- 通讯作者:M. Frazier;Lixuan Xi;J. Zong;Nancy Viscofsky;A. Rashid;E. Wu;P. Lynch;C. Amos;J. Issa
Microsatellite instability in saliva from patients with hereditary non-polyposis colon cancer and siblings carrying germline mismatch repair gene mutations.
- DOI:
- 发表时间:2011-09
- 期刊:
- 影响因子:0.8
- 作者:Peter Hu;C. W. Lee;J. Xu;Crystal M. Simien;Chuan Li Fan;M. Tam;L. Ramagli;B. Brown;P. Lynch;M. Frazier;M. Siciliano;Mary Coolbaugh-Murphy
- 通讯作者:Peter Hu;C. W. Lee;J. Xu;Crystal M. Simien;Chuan Li Fan;M. Tam;L. Ramagli;B. Brown;P. Lynch;M. Frazier;M. Siciliano;Mary Coolbaugh-Murphy
Changes in screening behaviors and attitudes toward screening from pre-test genetic counseling to post-disclosure in Lynch syndrome families.
- DOI:10.1111/cge.12091
- 发表时间:2013-03
- 期刊:
- 影响因子:3.5
- 作者:Burton-Chase AM;Hovick SR;Peterson SK;Marani SK;Vernon SW;Amos CI;Frazier ML;Lynch PM;Gritz ER
- 通讯作者:Gritz ER
Interactions between cigarette smoking and selected polymorphisms in xenobiotic metabolizing enzymes in risk for colorectal cancer: A case-only analysis.
- DOI:10.1002/mc.20682
- 发表时间:2010-11
- 期刊:
- 影响因子:4.6
- 作者:Pande, Mala;Amos, Christopher I.;Eng, Cathy;Frazier, Marsha L.
- 通讯作者:Frazier, Marsha L.
Genetic variants in the cell cycle control pathways contribute to early onset colorectal cancer in Lynch syndrome.
- DOI:10.1007/s10552-009-9416-x
- 发表时间:2009-11
- 期刊:
- 影响因子:2.3
- 作者:Chen, Jinyun;Etzel, Carol J.;Amos, Christopher I.;Zhang, Qing;Viscofsky, Nancy;Lindor, Noralane M.;Lynch, Patrick M.;Frazier, Marsha L.
- 通讯作者:Frazier, Marsha L.
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MARSHA L. FRAZIER其他文献
MARSHA L. FRAZIER的其他文献
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Mouse Model of Pancreatic Tumorigenesis with Dysregulation of mTOR
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7535942 - 财政年份:2008
- 资助金额:
$ 53.08万 - 项目类别:
Biomarkers for the Early Detection of Pancreatic Cancer
用于早期检测胰腺癌的生物标志物
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8289475 - 财政年份:2004
- 资助金额:
$ 53.08万 - 项目类别:
Biomarkers for the Early Detection of Pancreatic Cancer
用于早期检测胰腺癌的生物标志物
- 批准号:
8515943 - 财政年份:2004
- 资助金额:
$ 53.08万 - 项目类别:
Biomarkers for the Early Detection of Pancreatic Cancer
用于早期检测胰腺癌的生物标志物
- 批准号:
7983177 - 财政年份:2004
- 资助金额:
$ 53.08万 - 项目类别:
Biomarkers for the Early Detection of Pancreatic Cancer
用于早期检测胰腺癌的生物标志物
- 批准号:
8130791 - 财政年份:2004
- 资助金额:
$ 53.08万 - 项目类别:
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