Researchers in London have identified a 14-protein signature in blood that can predict lung cancer risk up to five years before symptoms appear—a breakthrough that could finally extend screening beyond the narrow group of current candidates. Published in Cell, the discovery offers hope to never-smokers and people exposed to high levels of air pollution, populations largely left out of conventional lung cancer screening programs that focus almost exclusively on older former smokers.
The work builds on a crucial insight: cancer develops when mutations alone aren't enough—they need an environmental trigger, often air pollution from combustion engines, coal burning, or cigarette smoke. The research team, supported by the National Institute for Health and Care Research UCLH Biomedical Research Centre, applied machine learning to blood plasma protein data from more than 48,000 UK Biobank participants, matched against cancer registry records. The algorithm identified 14 key proteins that, alongside age, smoking status, and lung disease history, could predict future lung cancer diagnosis within five years.
What makes this signature truly powerful is that it reflects an altered inflammatory state in the lungs—a pre-disease environment that precedes cancer rather than something generated by the tumor itself. The researchers validated the finding across eight datasets worldwide, including a cohort of non-smokers, proving the signature's consistency across different populations. Notably, this same inflammatory signature appeared elevated in people who later developed other lung conditions like idiopathic pulmonary fibrosis or chronic obstructive pulmonary disease, suggesting it captures a shared vulnerability to lung injury.
The mechanism underlying the signature traces back to air pollution exposure triggering immune cells in the lung to release interleukin-1 beta, a powerful inflammatory signal that can activate dormant cells carrying cancer mutations. The research team showed that this pollution exposure simultaneously boosts "KAC cells"—an adaptive state that occurs in response to injury but can turn cancerous if mutations are present. Air pollution expanded this dangerous pool and increased the 14-protein signature, creating a detectable window of vulnerability.
Here's where the research pivots toward prevention: blocking IL-1β in mice exposed to pollution reduced KAC cells and slowed early tumor development. This finding resonates with existing drug research. When Novartis's 2017 CANTOS trial tested the IL-1β blocker canakinumab to prevent heart disease, it reported an exploratory finding that the drug also reduced lung cancer incidence—though modestly in the general population. Reanalyzing data from the trial's 4,651 participants, researchers discovered something crucial: people with a high baseline 14-protein signature showed dramatic benefit, with their lung cancer risk nearly halved. By selecting only those with the high signature, the number needed to treat to prevent one lung cancer case was 55—comparable to established cardiovascular prevention strategies like statins.
This precision approach transforms the possibility of prevention from impractical to viable. Rather than giving anti-IL-1β drugs to millions, doctors could identify high-risk individuals using the blood test and offer them targeted treatment. The signature opens a new chapter in lung cancer prevention, one where a simple blood draw could identify people at highest risk years before cancer develops, allowing interventions before disease takes hold.