Imaging metabolic heterogeneity in Glioblastoma

胶质母细胞瘤的代谢异质性成像

• 批准号: 2899532
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2899532
• 关键词: Imaging; metabolic; heterogeneity; Glioblastoma

GBM is a fast-growing and invasive type of brain tumour with a poor prognosis, with an average survival time of only 12-18 months. Through this project we aim to understand more about the mechanisms of tumour progression that can provide new insights into early diagnosis and treatment strategies.Using a preclinical model of GBM as well as human tissues resected during surgery, we will explore the heterogeneity of metabolic processes across thin sections of these tumours. In collaboration with Waters UK, we will use DESI-Mass Spectrometry Imaging to image metabolites in tissue sections at high spatial resolution. The rich datasets generated by this approach will be mined to further our understanding of tumour metabolism and provide insights into potential new treatments. We will work with the wider mass spectrometry imaging community, particularly Professor Nick Lockyer's group, equipped with both MALDI and SIMS imaging mass spectrometers. The project will involve collaboration with Dr Kevin Couper's group, who will map the same tissues using Imaging Mass Cytometry allowing identification of cell types and their distribution within the tumours and surrounding tissues. We will also collaborate with Prof. David Wedge's bioinformatics group who will support computational aspects of the work. The research will focus mainly on the use of DESI-IMS for metabolic imaging and the comparison of DESI imaging data with other modalities IMC, microscopy etc. It will therefore involve co-registration and data merging from images across modalities. Using automated slide changing technology, multiple images can be acquired, allowing the construction of 3D images, where serial tissue sections are available.The student will be based at the Wolfson Molecular Imaging Centre, on the site of the Christie Hospital, where we have a Waters XEVO DESI instrument capable of more than 10 micron spatial resolution and associated tissue processing capabilities. The student will perform placement work at Waters' laboratories in Wilmslow, where they will have access to further state of the art mass spectrometry instrumentation and technical support.The project will be cross-disciplinary, developing skills and knowledge in the interpretation of mass spectra, image analysis, and an understanding the associated cancer biology. Candidates should have a background in the physical or biological sciences, with an interest in developing their expertise across these sub-disciplines.

GBM是一种生长快速、侵袭性强的脑肿瘤，预后较差，平均生存期仅为12-18个月。通过这个项目，我们旨在更多地了解肿瘤进展的机制，从而为早期诊断和治疗策略提供新的见解。使用 GBM 的临床前模型以及手术期间切除的人体组织，我们将探索这些肿瘤薄片代谢过程的异质性。我们将与英国沃特世合作，使用 DESI 质谱成像以高空间分辨率对组织切片中的代谢物进行成像。通过挖掘这种方法生成的丰富数据集，我们将进一步了解肿瘤代谢，并为潜在的新疗法提供见解。我们将与更广泛的质谱成像界合作，特别是配备 MALDI 和 SIMS 成像质谱仪的 Nick Lockyer 教授的团队。该项目将涉及与 Kevin Couper 博士的团队合作，他们将使用成像质谱流式细胞术绘制相同的组织图，从而识别细胞类型及其在肿瘤和周围组织内的分布。我们还将与 David Wedge 教授的生物信息学小组合作，他们将为这项工作的计算方面提供支持。该研究将主要集中于使用 DESI-IMS 进行代谢成像，以及将 DESI 成像数据与其他模态 IMC、显微镜等进行比较。因此，它将涉及跨模态图像的共同配准和数据合并。使用自动载玻片更换技术，可以采集多个图像，从而构建 3D 图像，其中可以提供连续的组织切片。学生将在位于 Christie 医院的 Wolfson 分子成像中心工作，我们在那里拥有一台 Waters XEVO DESI 仪器，能够超过 10 微米的空间分辨率和相关的组织处理能力。学生将在沃特世位于威姆斯洛的实验室进行实习工作，在那里他们将获得更先进的质谱仪器和技术支持。该项目将是跨学科的，培养质谱解释、图像分析和理解相关癌症生物学方面的技能和知识。候选人应具有物理或生物科学背景，并有兴趣发展这些子学科的专业知识。