Early Cancer Detection & Prognosis through Glycomics
Early Cancer Detection & Prognosis through Glycomics
批准号:
8104031
负责人:
Milos Novotny
金额:
$36.19万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-08-08 至 2012-06-30
关键词:
AftercareAntibodiesBioinformaticsBiologicalBiological MarkersCancer PatientCancer PrognosisCancer RemissionCapillary ElectrophoresisClinicalColon CarcinomaComplexDataDevelopmentDiagnosticDisease ProgressionDisease remissionEvaluationExcisionFemaleHealthHumanIndividualIsomerismLIF geneLaboratoriesLectinLinkMalignant NeoplasmsMalignant neoplasm of lungMalignant neoplasm of ovaryMalignant neoplasm of prostateMapsMeasurementMethodologyMicrofluidicsMonitorPatientsPatternPharmaceutical PreparationsPhasePolysaccharidesProceduresProcessProteinsResearchResearch PersonnelSamplingScreening for cancerScreening procedureSerumStagingStructureTechnologyValidationanalytical toolbasecancer typeclinically relevantcomparativeglycosylationmaleoutcome forecastphase 3 studyphase changeprognosticprogramstooltrendtumor progression
中文摘要
描述(由申请人提供):我们强调未分级生物样品中的定量去糖基化(聚糖的去除),并在定量聚糖图谱中显示去除的聚糖,而不是寻找特定的癌症生物标志物(蛋白质或糖基化蛋白质)。比较来自健康和患病个体的糖组学谱应该允许分配与癌症相关的结构变化。另一方面,患者健康的预后或差异评估则依赖于此类聚糖模式的同位素辅助定量MS测量。在我们拟议研究的前两个阶段,将通过我们完善的程序筛选临床相关样本,同时使用最先进的基于MS的方法和毛细管电泳。在第1阶段,将从健康女性和男性中采集的人血清的糖组学模式与从卵巢癌、前列腺癌、肺癌和结肠癌患者中采集的人血清的糖组学模式进行比较。通过生物信息学和统计学评价,将确定与每种类型的癌症或与待研究的所有类型的癌症相关的聚糖标志物列表。这对于确定糖基化或“糖基化畸变”发生率的定量趋势并将这些测量结果与阳性鉴定的聚糖结构联系起来是必要的。通过CE-LIF获得的相同样品的糖组学图谱将有助于确定由于结构异构体变化而导致的变化,这些变化无法通过MS确定。在第2阶段,将比较特定药物治疗前后的癌症人血清糖组学图谱。在此阶段,将密切监测第1阶段中定义的聚糖组的变化,并评价其因癌症进展或缓解而发生的变化。II期研究结果将证实或反驳将在I期研究中定义为潜在生物标志物的潜在聚糖结构。一旦鉴定出这些特定的聚糖变化或由于疾病进展或缓解而变化的聚糖结构集,将研究更快的筛选方法(如凝集素或抗体微阵列)的潜力。这是本研究第3阶段的目的,重点是确定可用作诊断和预后工具的最佳分析工具。
英文摘要
DESCRIPTION (provided by applicant): Rather than looking for specific cancer biomarkers (proteins or glycosylated proteins), we emphasize quantitative deglycosylation (removal of glycans) in unfractionated biological samples and displaying the removed glycans in quantitative glycan maps. Comparing glycomic profiles originating from healthy and diseased individuals should allow the assignment of structural changes associated with cancer. On the other hand, prognosis or a differential assessment of patients' health then relies on the isotopically-aided quantitative MS measurements of such glycan patterns. In the first two phases of our proposed research, clinically relevant samples will be screened through our well-established procedures while using the state-of- the-art MS-based methodologies and capillary electrophoresis. In Phase 1, the glycomic patterns of human blood serum collected from healthy females and males will be compared to those collected from ovarian, prostate, lung and colon cancer patients. Through bioinformatic and statistical evaluation a list of glycan markers that are associated with each type of cancer or with all types of cancer to be studied will be determined. This is necessary to establish quantitative trends in glycosylation or the occurrence of "glycosylation aberrations" and link these measurements to positively identified glycan structures. Glycomic profiles acquired for the same samples by CE-LIF will aid in determining changes that are due to changes in structural isomers which cannot be determined through MS. In Phase 2, the glycomic maps of human blood serum of cancer before and after treatment with a specific drug will be compared. In this phase, changes in the set of glycans defined in Phase 1 will be closely monitored and their changes as a result of cancer progression or remission will be evaluated. Phase 2 results will confirm or refute the potential glycan structures that will be defined as potential biomarkers in Phase 1. Upon the identification of these specific glycan changes or the set of glycan structures that change as a result of disease progression or remission, the potential of a faster screening approach such as lectin or antibody microarrays will be investigated. This is the aim of Phase 3 of this study which will focus on defining the best analytical tools that could be utilized as diagnostic and prognostic tool.
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DOI:
10.1021/pr201070k
发表时间:
2012-04-06
期刊:
JOURNAL OF PROTEOME RESEARCH
影响因子:
4.4
作者:
[Alley, William R., Jr., Vasseur, Jacqueline A., Goetz, John A., Syoboda, Martin, Mann, Benjamin F., Matei, Daniela E., Menning, Nancy, Hussein, Ahmed, Mechref, Yehia, Novotny, Milos V.]
通讯作者:
Novotny, Milos V.
DOI:
10.1021/ac303274w
发表时间:
2013-02-05
期刊:
Analytical chemistry
影响因子:
7.4
作者:
[Mann BF, Mann AK, Skrabalak SE, Novotny MV]
通讯作者:
Novotny MV
DOI:
10.1007/s10719-012-9444-8
发表时间:
2013-02
期刊:
GLYCOCONJUGATE JOURNAL
影响因子:
3
作者:
[Novotny, Milos V., Alley, William R., Jr., Mann, Benjamin F.]
通讯作者:
Mann, Benjamin F.
DOI:
10.1002/elps.201000461
发表时间:
2011-01
期刊:
ELECTROPHORESIS
影响因子:
2.9
作者:
[Zhuang, Zexi, Mitra, Indranil, Hussein, Ahmed, Novotny, Milos V., Mechref, Yehia, Jacobson, Stephen C.]
通讯作者:
Jacobson, Stephen C.
DOI:
10.1021/ac100131e
发表时间:
2010-06-15
期刊:
ANALYTICAL CHEMISTRY
影响因子:
7.4
作者:
[Alley, William R., Jr., Madera, Milan, Mechref, Yehia, Novotny, Milos V.]
通讯作者:
Novotny, Milos V.
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New Chromatographic Technologies for Resolving Carbohydrate Isomers
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Early Cancer Detection & Prognosis through Glycomics
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