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Understanding the role of non-coding RNAs in intercellular communication and how its potential for the detection and inhibition of pre-metastatic canc

了解非编码 RNA 在细胞间通讯中的作用及其检测和抑制转移前癌症的潜力

基本信息

批准号：
2885885
负责人：
金额：
--
依托单位：
University of Nottingham
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-2885885
关键词：
Understanding role non coding RNAs

项目摘要

The PhD builds upon the successful work of the group in identifying the mechanisms by which extracellular vesicles influence the metastasis of cancer to bone. Once thought to be little more than a way for cells to offload waste, extracellular vesicles (EVs) are now recognised to be a deliberate way for a cell to secrete cargos of RNA, DNA and proteins to reshape tissues and act as signal carriers. These somewhat overlooked organelles may hold the key tounderstanding how tissues and systems in our bodies communicate, particularly within complex diseases (e.g., cancer and dysfunctional immune cells).The project will explore the non-coding RNA elements of these EVs to determine the potential regulatory mechanisms they control. The project will be a mixture of data analysis to build experimental hypothesises of the types of signalling and regulatory mechanisms that are altered by these groups of non-coding RNAs, combined with molecular biology to validate these hypotheses within in vitro models of prostate cancer.The project will require the development of molecular biology techniques alongside the ability to analyse large datasets and create experimental hypothesise based on existing data sources. These skills provide an excellent multidisciplinary basis and fit within the BBSRCs remit of approaches.

该博士学位建立在该小组在确定细胞外囊泡影响癌症骨转移的机制方面的成功工作的基础上。细胞外囊泡 (EV) 曾经被认为只不过是细胞卸载废物的一种方式，现在被认为是细胞分泌 RNA、DNA 和蛋白质以重塑组织并充当信号载体的一种有意方式。这些有些被忽视的细胞器可能是理解我们体内的组织和系统如何沟通的关键，特别是在复杂疾病（例如癌症和功能失调的免疫细胞）中。该项目将探索这些 EV 的非编码 RNA 元件，以确定它们控制的潜在调节机制。该项目将结合数据分析来建立由这些非编码RNA组改变的信号传导和调节机制类型的实验假设，并结合分子生物学在前列腺癌的体外模型中验证这些假设。该项目将需要发展分子生物学技术以及分析大型数据集和基于现有数据源创建实验假设的能力。这些技能提供了出色的多学科基础，并且符合 BBSRC 的方法范围。