Scientists have identified a blood-based protein signature that could help predict lung cancer up to five years before diagnosis, offering a potential shift from traditional risk models based mainly on age and smoking history.
The research, published in Cell, shows that environmental factors such as air pollution may play a key role in triggering cancer development in genetically mutated cells.
Exposure to pollution from vehicle emissions, coal burning, and cigarette smoke is believed to create an inflammatory environment that can “activate” dormant mutated cells and push them toward cancer.
The study, led by researchers supported by the National Institute for Health and Care Research and the UCLH Biomedical Research Centre, analyzed blood plasma data from more than 48,000 participants in the UK Biobank.
Using machine learning, the team identified 14 key proteins in the blood that were strongly associated with future lung cancer diagnosis within five years.
The model also incorporated age, smoking status, and prior lung disease history to improve predictive accuracy.
Researchers validated the protein signature across eight international datasets and found it consistently elevated in individuals who later developed lung cancer, including non-smokers exposed to environmental risks.
Scientists found that the protein signature reflects an altered inflammatory state in the lungs rather than the presence of a tumor itself.
This inflammatory environment was also linked to conditions such as chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis, suggesting a shared pre-disease mechanism.
The study builds on earlier findings that air pollution can trigger immune responses, particularly involving the inflammatory molecule interleukin-1 beta (IL-1β), which may “wake up” mutated dormant cells in lung tissue.
In mouse models, blocking IL-1β reduced the number of pre-cancerous cells and slowed early tumor development, raising the possibility that targeted anti-inflammatory treatments could help prevent lung cancer in high-risk individuals.
Researchers also re-analyzed data from the CANTOS clinical trial, which tested the IL-1β inhibitor canakinumab. They found that participants with high levels of the 14-protein signature had their lung cancer risk reduced by nearly 50% when treated with the drug.
The findings suggest that only a selected high-risk group may benefit significantly from preventive treatment, improving efficiency compared to treating broad populations.
Scientists say the approach could pave the way for precision prevention strategies, similar to how cholesterol testing guides statin use in cardiovascular disease.
Researchers involved in the study said the findings demonstrate that lung cancer may be preceded by a detectable inflammatory state that can be identified through blood testing, potentially enabling earlier intervention.
Cancer experts described the discovery as a step toward identifying cancer risk earlier and reducing the burden of late-stage diagnosis, which remains a major challenge in lung cancer care.
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