At the request of the French National Cancer Institute, IHU RespirERA is developing the information system (IS) that will support the national roll-out of lung cancer screening from 2025.
This IS is the foundation of clinical, imaging and biological databases, facilitating the set-up of clinical trials dedicated to (i) “go-to” strategies to reach at-risk populations, (ii) exposome analysis to assess environmental and lifestyle factors influencing lung cancer risk, and (iii) the application of artificial intelligence to imaging and biomarker identification for enhanced diagnostic accuracy.
Lung cancer is the leading cause of cancer-related death worldwide. Screening through chest CT scans (secondary prevention) can reduce lung cancer mortality by 21%.
The French National Cancer Institute (INCa) has entrusted IHU RespirERA with developing the information system that will manage the national rollout of lung cancer screening in France starting in 2025.
Reaching At-Risk Populations
Limited access to healthcare and social vulnerability are key risk factors for missing out on screening programs. These challenges particularly affect individuals with high tobacco exposure, who are therefore at an increased risk of developing lung cancer.
To address this, IHU RespirERA is conducting research on "outreach" strategies to ensure equitable access to screening while minimising ethical and societal barriers. Screening campaigns targeting at-risk populations (report by France 3 PACA) will also include chronic obstructive pulmonary disease (COPD) screening, as this smoking-related disease often coexists with lung cancer. Additionally, these initiatives will integrate smoking cessation programs, bridging the gap between prevention and early detection.
Predicting Lung Cancer Through Exposome Analysis and Artificial Intelligence
Lung cancer is closely linked to environmental and occupational exposures. That’s why IHU RespirERA is studying the exposome of screened individuals, analysing carcinogens found in hair and urine, as well as biological cancer signatures in the blood.
Artificial intelligence (AI) plays a key role in lung cancer screening by enhancing thoracic imaging at three levels:
1. Nodule detection assistance
2. Assessment of malignancy probability for detected nodules
3. Prediction of lung cancer onset
Blood-based biomarkers (such as miRNA, circulating tumor DNA, and protein panels) are considered potential screening tools. However, their sensitivity and specificity are limited when used alone. Combining multi-biomarker panels with AI-driven CT scan analysis in predictive models could be a game-changer.
Early-Stage Lesion Characterisation and Treatment
Fifteen percent of individuals undergoing lung cancer screening are found to have an indeterminate pulmonary nodule (IPN) on their scan. However, less than 15% of these nodules are early-stage cancers.
When an IPN is detected, two main approaches are considered:
1. Radiological monitoring – If the nodule remains stable over time, it is likely benign.
2. Diagnostic assessment – This can be challenging, as these nodules are small and deep within the lung.
A third approach, currently being evaluated in specialised centers, involves preventive treatment—also known as cancer interception. At IHU RespirERA, we aim to combine diagnostic and preventive strategies using robot-assisted endoscopy. This technique enables histopathological, immunological, and molecular characterisation of hard-to-reach lesions, improving early diagnosis and treatment.
