Understanding lung cancer related risk factors and their Impact

肺癌（LC）是世界上最大的癌症杀手，诊断后的五年生存率在5%至25%之间。虽然长期以来吸烟一直被认为是LC的主要危险因素，但许多病例（包括非吸烟的LC患者）不能用这个原因来解释。从这个意义上说，LUCIA旨在建立一个新的工具箱，用于发现和理解有助于LC发展的新风险因素。该工具箱包括对以下三个方面的分析：（一）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;（二）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（三）对个人和外部风险因素的生物反应，包括遗传学、表观遗传学、新陈代谢和衰老方面的变化。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性和前瞻性队列数据库、人工智能模型、可穿戴设备、新型非侵入性传感器和多组学。总之，这些工具将用于确定与LC形成相关的环境，生物，人口，社区和个人水平风险因素的影响。然后，将通过细胞和分子生物学方法以及体内分析来验证与这套工具所识别的风险因素相关的分子变化。然后将在三个临床用例中验证已确定的个人和外部风险因素的影响以及相关的生物反应：一般人群风险评估和筛查，高风险人群的精确筛查和数字诊断。在LUCIA中产生的证据将被转化为政策制定建议，目的是在LC筛查计划中实施这些建议。这一行动是“了解”和“包括筛查在内的预防”两个癌症使命项目组的一部分。

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’.