Integrative Metabolomics of Prostate Cancer Progression
Integrative Metabolomics of Prostate Cancer Progression
批准号:
7603104
负责人:
Arun Sreekumar
金额:
$32.05万
依托单位:
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:
2008-04-04 至 2013-01-31
关键词:
Animal ModelAreaBenignBiochemical PathwayBiologicalBiological MarkersBiologyCancer DetectionCancer EtiologyCancer ModelCessation of lifeClassificationClinicalClinical PathologyComplexDataData AnalysesDetectionDevelopmentDiagnosisDiagnosticDiseaseDisease ProgressionEarly DiagnosisEventExtraprostaticFamilyGene Expression ProfilingGene FusionGlycineGoalsGrowthIn VitroInvestigationKnowledgeLaboratoriesLeadLightLinkMalignant NeoplasmsMalignant neoplasm of prostateMass Spectrum AnalysisMeasuresMetastatic Prostate CancerMiningModelingMolecularMolecular AnalysisMotivationNeoplasm MetastasisOperative Surgical ProceduresOrganOutcomePathway interactionsPatient SelectionPatientsPhasePlasmaPre-Clinical ModelProcessPrognostic MarkerProgressive DiseaseProstateProstate-Specific AntigenProstatic NeoplasmsProteomicsRadiationRoleSarcosineSpecificitySpecimenStagingSystemTissuesUrineValidationWestern Worldbasecancer initiationcancer microarrayclinically relevantdata miningfallsin vivo ModelinsightmRNA Expressionmenmetabolomicsnovelolder menpre-clinicalprotein functionsuccesstooltranscription factortranscriptomicstumortumor progression
中文摘要
描述(由申请人提供):前列腺癌是西方世界老年男性中非常普遍的疾病。多种复杂的分子事件表征了前列腺癌的起始、不受调节的生长、侵袭和转移。破译区分进行性疾病和非进行性疾病的分子网络,将有助于了解侵袭性前列腺癌的生物学,并有助于识别生物标志物,从而帮助选择应该接受治疗的患者。通过微阵列对前列腺癌进行基因表达谱分析已经做了广泛的研究,但在较小的程度和深度上,也对使用质谱法对前列腺肿瘤进行蛋白质组学分析进行了探索。相比之下,在前列腺癌代谢组学分析领域的研究很少,这可能提供传统转录组学和蛋白质组学之外的额外信息内容。mRNA表达或蛋白质功能/活性的细微变化可能表现为特定代谢物浓度的巨大变化,从而更敏感地检测到扰动。前列腺癌代谢物的全局分析将增强我们对疾病进展过程中发生的通路改变的理解,并可能导致开发新的生物标志物和靶向通路。目前的建议是建立一个丰富的前列腺组织代谢组学概况纲要,以确定前列腺癌进展的类别特异性以及致命或侵袭性代谢组学标志物。因此,本提案的总体目标是定义和验证前列腺癌进展的临床相关代谢组学标志物的子集,并确定其在预测侵袭性疾病中的效用。有鉴于此,目标如下:
英文摘要
DESCRIPTION (provided by applicant): Prostate cancer is a highly prevalent disease in older men of the Western world. Multiple complex molecular events characterize prostate cancer initiation, unregulated growth, invasion, and metastasis. Deciphering the molecular networks that distinguish progressive disease from non-progressive disease will shed light into the biology of aggressive prostate cancer as well as lead to the identification of biomarkers that will aid in the selection of patients that should be treated. Gene expression profiling of prostate cancer by microarrays has been done extensively and to a lesser extent and depth, proteomic profiling of prostate tumors using mass spectrometry has also been explored. By contrast, very little has been done in the area of metabolomic profiling of prostate cancer, which may provide additional information content beyond that available from conventional transcriptomics and proteomics. Subtle alterations in mRNA expression or protein function/activity may manifest as an enormous change in the concentration of specific metabolites resulting in a more sensitive detection of the perturbation. Global profiling of the metabolites in prostate cancer will enhance our understanding of the pathway alterations occurring during disease progression and could lead to the development of novel biomarkers and pathways to target. The current proposal around a rich compendium of metabolomic profiles of prostate tissues that would be mined to define class-specific as well as lethal or aggressive metabolomic markers of prostate cancer progression. Thus the overarching goal of this proposal is to define and validate a subset of clinically relevant metabolomic markers of prostate cancer progression and determine their utility in predicting aggressive disease. Given this, the aims are as follows:
Specific Aim 1: Delineate Potential Metabolomic Markers of Prostate Cancer Progression.
Specific Aim 2: Establish the Predictive/Causal/Consequential Role for the Lethal Metabolomic Markers of Prostate Cancer Using Preclinical Models of Cancer Invasion.
Specific Aim 3: Clinical Association of Candidate Metabolomic Biomarkers of Prostate Cancer Progression
PUBLIC HEALTH RELEVANCE: Prostate cancer is the second largest cause of cancer-related death in US. The disease is often curable if detected early, while metastatic disease is often fatal. Furthermore, there is an imminent need to define additional biomarkers for prostate cancer detection owing to the low specificity of prostate specific antigen (PSA), the current clinical standard used for its early detection. The long term goal of this proposal is to define a subset of clinically relevant metabolomic markers and define their association with the process of disease progression using validated prostate cancer animal models. Our hope is that such a systematic molecular analysis of prostate cancer metabolites would lead to identification of pathway alterations that could be one day targeted for therapy. Further, with the ultimate objective of transitioning these markers to the clinical setting, we intent to validate them across additional prostate-related clinical biospecimens.
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会议论文
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