Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational
使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析
基本信息
- 批准号:8104025
- 负责人:
- 金额:$ 12.32万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:11qAfrican AmericanAlgorithmsAmerican Cancer SocietyBiologyCaliforniaCancer CenterCancer EtiologyCancer PatientCessation of lifeCharacteristicsChromosome ArmChromosomesChromosomes, Human, Pair 11Chromosomes, Human, Pair 8ClassificationClinicalComplexComputer softwareComputing MethodologiesDataData AnalysesData SetDetectionDevelopmentDiagnosisDiseaseDistalGenesGenomeGenomicsGoalsHybridization ArrayIndividualInternetKnowledgeLeadMachine LearningMalignant NeoplasmsMalignant neoplasm of lungMentorsMethodsMinority GroupsNoiseNumerical valuePatientsPhenotypePhysiologyPopulationPrincipal InvestigatorPublishingRecommendationRecurrenceResearchResearch Project GrantsResolutionSamplingSan FranciscoStratificationSubgroupSurvival RateTechniquesTechnologyThe University of California San Francisco Cancer CenterUnderrepresented MinorityUniversitiesWomanabstractingbasecancer diagnosiscancer recurrencecohortcomparative genomic hybridizationdesigneffective therapyethnic minority populationimprovedmalignant breast neoplasmmeetingsnovelnovel strategiesoutcome forecastprofessorsoftware developmenttreatment planningtreatment responsetumortumor progression
项目摘要
COLLABORATIVE RESEARCH PROJECT #3
MULTISCALE ANALYSIS OF CGH ARRAYS FROM BREAST CANCER PATIENTS
USING COMPUTATIONAL ALGEBRAIC TOPOLOGY
Javier Arsuaga, Principal Investigator
San Francisco State University
Mariel Vazquez, Principal Investigator
San Francisco State University
Daniel Pinkel, Mentor/Collaborator
UCSF Cancer Center
Abstract
Breast cancer, the most common cancer in women worldwide, is one of the leading causes
of cancer deaths, second only to lung cancer. The American Cancer Society has estimated
that in the US alone almost 200,000 new cases of breast cancer will be diagnosed during
2008. In order to improve the survival rates from this disease, there is a need for new
approaches to facilitate a more effective stratification of patients into distinct clinical
subgroups likely to benefit from different treatment regimes. To meet this need, Drs.
Arsuaga and Vazquez propose to develop a computational method for analyzing DMA copy
number changes. These changes, which are known to be associated with the progression of
cancer, can be detected through array Comparative Genomic Hybridization (CGH);
however, the application of this technology for the prediction of recurrence remains a
challenge due to the complexity of the data involved. The goal of the proposed project is to
develop a novel computational method, based on computational algebraic homology, to
analyze CGH profiles at multiple levels of resolution in order to predict recurrence of breast
cancer. The Pis will first determine the chromosome regions which contain genes
associated with breast cancer recurrence, and then establish the contribution of the overall
characteristics of the CGH profile to the recurrence. The study will involve the examination
not just of independent interchromosomal regions but also of relationships between proximal
and distal intrachromosomal regions. Software developed for the project will be made
publicly available through the web. The Pis will be supported through a mentoring
relationship with Professor Daniel Pinkel from the University of California, San Francisco
(UCSF), an expert on CGH array development and analysis as well as on breast cancer.
合作研究项目#3
乳腺癌患者CGH序列的多尺度分析
使用抽象代数拓扑
Javier Arsuaga,主要研究者
旧金山弗朗西斯科州立大学
Mariel Vazquez,主要研究者
旧金山弗朗西斯科州立大学
丹尼尔平克尔,导师/合作者
加州大学旧金山分校癌症中心
摘要
乳腺癌是全球女性最常见的癌症,
癌症死亡率仅次于肺癌美国癌症协会估计,
仅在美国,2015年将有近20万例新的乳腺癌病例被诊断出来。
2008.为了提高这种疾病的存活率,需要新的治疗方法。
有助于更有效地将患者分层为不同临床
亚组可能受益于不同的治疗方案。为了满足这一需求,博士。
Arsuaga和Vazquez提出了一种分析DMA拷贝的计算方法
数字变化。这些变化,这是已知的,与进展,
癌症,可以通过阵列比较基因组杂交(CGH)检测;
然而,应用这项技术预测复发仍然是一个问题。
由于所涉及的数据的复杂性,这是一个挑战。拟议项目的目标是
发展一种新的计算方法,基于计算代数同调,
分析多个分辨率水平的CGH曲线,以预测乳腺癌的复发
癌PI将首先确定包含基因的染色体区域
与乳腺癌复发相关,然后建立整体的贡献,
CGH曲线的特征与复发的关系。这项研究将包括检查
不仅是独立的染色体间区域,
和远端染色体内区域。为该项目开发的软件将由
可通过网络公开获取。私人侦探将通过指导得到支持,
与弗朗西斯科加州大学丹尼尔平克尔教授的关系
(UCSF),CGH阵列开发和分析以及乳腺癌专家。
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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Francisco Javier Arsuaga其他文献
Francisco Javier Arsuaga的其他文献
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{{ truncateString('Francisco Javier Arsuaga', 18)}}的其他基金
Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational
使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析
- 批准号:
8377834 - 财政年份:2012
- 资助金额:
$ 12.32万 - 项目类别:
Computer Modeling of DNA Double-Strand Break Repair (pilot)
DNA 双链断裂修复的计算机建模(试点)
- 批准号:
7568890 - 财政年份:2008
- 资助金额:
$ 12.32万 - 项目类别:
Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational
使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析
- 批准号:
7649882 - 财政年份:2008
- 资助金额:
$ 12.32万 - 项目类别:
Computer Modeling of DNA Double-Strand Break Repair (pilot)
DNA 双链断裂修复的计算机建模(试点)
- 批准号:
7229133 - 财政年份:2007
- 资助金额:
$ 12.32万 - 项目类别:
Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational
使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析
- 批准号:
7892389 - 财政年份:
- 资助金额:
$ 12.32万 - 项目类别:
Computer Modeling of DNA Double-Strand Break Repair (pilot)
DNA 双链断裂修复的计算机建模(试点)
- 批准号:
8015305 - 财政年份:
- 资助金额:
$ 12.32万 - 项目类别:
Multiscale Analysis of CGH Arrays from Breast Cancer Patients Using Computational
使用计算对乳腺癌患者的 CGH 阵列进行多尺度分析
- 批准号:
8294466 - 财政年份:
- 资助金额:
$ 12.32万 - 项目类别:
Computer Modeling of DNA Double-Strand Break Repair (pilot)
DNA 双链断裂修复的计算机建模(试点)
- 批准号:
7751325 - 财政年份:
- 资助金额:
$ 12.32万 - 项目类别:
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