课题基金 / 基金详情

Quantitative Spectroscopic Imaging of Cancer Metabolites in Live Cells and Intact

Quantitative Spectroscopic Imaging of Cancer Metabolites in Live Cells and Intact
活细胞和完整细胞中癌症代谢物的定量光谱成像
批准号:
8884566
负责人:
Ji-Xin Cheng
金额:
$23.45万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-20 至 2017-08-31

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):虽然改变的细胞代谢是癌症的一个新的标志,但迫切需要新的代谢物定量工具。虽然NMR光谱、质谱和拉曼光谱被广泛用于组织提取物或完整组织中的分子检测,但这些工具不能告诉细胞内分析物的空间位置。我们通过开发多重受激拉曼散射(SRS)显微镜来解决这一未满足的需求,以实现活肿瘤细胞和完整活检组织中代谢物的定量振动成像。最近开发的SRS显微镜允许在活细胞中的单个拉曼带的高速、高灵敏度成像。然而,单频SRS成像技术具有有限的能力,因为它不能分辨经常具有重叠的拉曼带的分子种类。我们建议通过一个自制的调谐放大器阵列,使光谱分散的SRS信号的并行检测,以克服这一技术障碍。在一项初步研究中,我们展示了活胰腺癌细胞的多重SRS成像,像素停留时间为40 μs。在目标1中,我们将开发多重受激拉曼损耗(SRL)显微镜和多变量分析算法,使活细胞中的脂质代谢物的定量振动成像。在目标2中,我们将开发epi检测的多重SRL显微镜,以实现肿瘤活检的高速,大面积光谱成像。通过这两个目标的实现,我们将建立一个高灵敏度、高速度、亚微米空间分辨率的活细胞分子分析光谱成像平台。该平台将允许在活细胞中无标记地可视化代谢转化,这是蛋白质组学工具不可能实现的。这种能力对于癌症代谢的机制理解和靶向癌症代谢的药物的精确评估至关重要。该平台还将允许完整肿瘤活检的大面积绘图,并提供关于指示癌症侵袭性的代谢生物标志物(例如胆固醇酯)的信息。
英文摘要
DESCRIPTION (provided by applicant): While altered cell metabolism is an emerging hallmark of cancer, there is a crucial need of new tools for quantitation of metabolites. Though NMR spectroscopy, mass spectrometry, and Raman spectroscopy are widely used for molecular detection in tissue extracts or intact tissues, these tools do not tell the spatial locations of the analytes inside the cell. We address this unmet need via development of multiplex stimulated Raman scattering (SRS) microscopy to enable quantitative vibrational imaging of metabolites in live tumor cells and intact biopsies. The recently developed SRS microscopy allows high-speed, high-sensitivity imaging of single Raman bands in live cells. However, the single-frequency SRS imaging technique has limited capability because it cannot resolve molecular species that often have overlapped Raman bands. We propose to overcome this technical barrier via parallel detection of spectrally dispersed SRS signals enabled by a homebuilt tuned amplifier array. In a pilot study, we demonstrated multiplex SRS imaging of live pancreatic cancer cells with a pixel dwell time of 40 μs. In Aim 1, we will develop multiplex stimulated Raman loss (SRL) microscopy and multivariate analysis algorithm to enable quantitative vibrational imaging of lipid metabolites in live cells. In Aim 2, we will develop epi-detected multiplex SRL microscopy to enable high-speed, large-area spectroscopic imaging of tumor biopsies. By accomplishment of the two aims, we will generate a high- sensitivity, high-speed, spectral imaging platform for molecular analysis of live cells with sub-micron spatial resolution. This platform will permit label-free visualization of metabolic conversion in live cancr cells, which is not possible with proteomics tools. Such capability is critical for mechanistic understanding of cancer metabolism and precise evaluation of drugs targeting cancer metabolism. This platform will also permit large- area mapping of intact tumor biopsies and offer information about metabolic biomarkers (e.g. cholesteryl ester) that are indicative of cancer aggressiveness.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.cmet.2014.01.019
发表时间: 2014-03-04
期刊: Cell metabolism
影响因子: 29
作者: [Yue S, Li J, Lee SY, Lee HJ, Shao T, Song B, Cheng L, Masterson TA, Liu X, Ratliff TL, Cheng JX]
通讯作者: Cheng JX
DOI: 10.1021/acs.jpcc.5b06980
发表时间: 2015-08-20
期刊: The journal of physical chemistry. C, Nanomaterials and interfaces
影响因子: --
作者: [Liao CS, Choi JH, Zhang D, Chan SH, Cheng JX]
通讯作者: Cheng JX
DOI: 10.1016/j.cbpa.2016.05.016
发表时间: 2016-08
期刊: Current opinion in chemical biology
影响因子: 7.8
作者: [Yue S, Cheng JX]
通讯作者: Cheng JX
2023 Chemical Imaging Gordon Research Conferences
  • 批准号:
    10605394
  • 项目类别:
  • 资助金额:
    $0.99万
  • 财政年份:
    2023
  • 负责人:
    Ji-Xin Cheng
  • 依托单位:
Sub-millimeter precision wireless neuromodulation using a microwave split ring resonator
High-content High-speed Chemical Imaging of Metabolic Reprogramming by Integration of Advanced Instrumentation and Data Science
High-content High-speed Chemical Imaging of Metabolic Reprogramming by Integration of Advanced Instrumentation and Data Science
海外基金