Understanding lung cancer related risk factors and their Impact

肺癌(LC)是世界上最大的癌症杀手，确诊后五年存活率在5%到25%之间。尽管吸烟长期以来一直被认为是LC的主要危险因素，但许多病例(包括。不吸烟的LC患者)不能用这个原因来解释。在这个意义上，Lucia的目标是建立一个新的工具箱，用于发现和了解有助于LC发展的新风险因素。该工具箱包括三个方面的分析：(I)个人风险因素，包括个人接触化学污染物以及行为和生活方式因素；(Ii)外部风险因素，如城市、建筑和交通环境、社会方面和气候；以及(Iii)对个人和外部风险因素的生物反应，包括遗传、表观遗传、新陈代谢和老龄化的变化。用于分析个人和外部风险因素的工具箱的关键组件包括回顾和预期队列数据库、人工智能模型、可穿戴设备、新型非侵入性传感器和多组学。这些工具将一起用于确定与LC形成相关的广泛的环境、生物、人口、社区和个人层面风险因素的影响。与这套工具确定的危险因素相关的分子变化将通过细胞和分子生物学方法以及体内分析进行验证。确定的个人和外部风险因素的影响以及相关的生物反应将在三个临床使用案例中得到验证：一般人群风险评估和筛查、高风险人群的精确筛查以及数字诊断。在Lucia内部产生的证据将被转化为政策制定建议，目的是在LC的筛查计划中实施这些建议。这项行动是癌症使命关于“了解”和“包括筛查在内的预防”两个项目集群的一部分。

Lung Cancer (LC) is the biggest cancer killer worldwide, with five-year survival following diagnosis varying between 5% to 25%. Though tobacco smoking has long been recognized as the major risk factor for LC, many cases (incl. LC patients that are non-smokers) cannot be explained by this reason. In this sense, LUCIA aims to establish a novel toolbox for discovering and understanding new risk factors that contribute to LC development. The toolbox encompasses the analysis of three aspects: (i) personal risk factors, which include a person’s exposure to chemical pollutants and behavioural and lifestyle factors; (ii) external risk factors, such as urban, built and transport environments, social aspects, and climate; and (iii) biological responses to the personal and external risk factors, including changes in genetics, epigenetics, metabolism, and aging. Key components of the toolbox for analysing personal and external risk factors include retrospective and prospective cohort databases, AI models, wearable devices, novel non-invasive sensors, and multi-omics. Together, these tools will be used to identify the effects of a wide range of environmental, biological, demographic, community and individual level risk factors associated with the formation of LC. Molecular changes associated with the risk factors identified by this set of tools will then be validated by cell and molecular biology methods and through in vivo analysis. The impact of the identified personal and external risk factors and the associated biological responses will be then validated in three clinical use cases: general population risk assessment and screening, precision screening of high-risk populations, and digital diagnostics. The resulting evidence within LUCIA will be translated into policymaking recommendations, with the aim to implement them in a screening program for LC. This action is part of two Cancer Mission clusters of projects on ‘Understanding' and ‘Prevention including Screening’.