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Using human genetics to identify novel biomarkers for enhanced prediction and early detection of cancer

利用人类遗传学来识别新的生物标志物，以增强癌症的预测和早期检测

基本信息

批准号：
2897051
负责人：
金额：
--
依托单位：
University of Bristol
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-2897051
关键词：
Using human genetics identify novel

项目摘要

Cancer is the 2nd leading cause of death globally. Despite important advances in treatment in recent decades, the prognosis for many cancers remains poor because individuals typically present with advanced disease at which point curative treatment is no longer an option. The NHS Long Term Plan aims to increase the percentage of cancers caught at an early stage, thus potentially curable, from 50-75% by 2028. Improvements in early detection and prediction of cancer is an important vehicle to achieve that goal. Proteomic Reverse Mendelian randomization (RMR) is a novel human genetics approach that uses germline genetic variants to identify circulating proteins associated with a genetic tendency to develop disease. The approach can be used to identify circulating proteins implicated in disease aetiology as well as non-causal "bystander" proteins that may nonetheless be informative biomarkers for disease prediction and detection. In this project, the student will use a Proteomic RMR framework to identify proteins associated with a genetic predisposition to develop cancer. These findings will be validated using direct protein measures and cancer data in UK Biobank (UKB). The potential clinical application of the identified proteins will be assessed by integrating circulating protein data into current clinical cancer risk prediction models, using linked medical records in UKB.

癌症是全球第二大死亡原因。尽管近几十年来在治疗方面取得了重要进展，但许多癌症的预后仍然很差，因为个体通常患有晚期疾病，此时治愈性治疗不再是一种选择。NHS长期计划的目标是到2028年将早期发现的癌症比例从50%提高到75%，从而可能治愈。改善癌症的早期检测和预测是实现这一目标的重要手段。蛋白质组反向孟德尔随机化（RMR）是一种新的人类遗传学方法，它使用种系遗传变异来识别与疾病发生遗传倾向相关的循环蛋白质。该方法可用于鉴定与疾病病因学有关的循环蛋白质以及非因果性“旁观者”蛋白质，尽管如此，这些蛋白质仍可能是用于疾病预测和检测的信息性生物标志物。在这个项目中，学生将使用蛋白质组学RMR框架来识别与癌症遗传易感性相关的蛋白质。这些发现将使用英国生物银行（UKB）中的直接蛋白质测量和癌症数据进行验证。将通过将循环蛋白质数据整合到当前的临床癌症风险预测模型中，使用UKB中的链接医疗记录来评估所识别蛋白质的潜在临床应用。