Around a quarter of the estimated 15,000 Australians diagnosed with lung cancer each year have no smoking history.

While tobacco smoking remains the primary cause of lung cancer, environmental triggers – such as exposure to air pollution from sources like traffic and coal burning – are increasingly recognised as risk factors, particularly among people who have not smoked.

Yet lung cancer screening programs continue to be strictly offered to individuals aged between 50–70 who currently smoke or have a history of smoking – leaving many at-risk individuals without access to early detection tools.

Dr Clare Weeden, a corresponding author on the paper, said the new study could lead to more inclusive and effective screening approaches for people in Australia and across the world.

“Figuring out who is at risk of developing cancer is the holy grail of cancer prevention medicine,” said Dr Weeden, who returned to WEHI in 2025.

“This proof-of-concept study offers new ideas that could fill this critical knowledge gap.

“In doing so, these findings bring us closer to a future where early intervention is possible, even before the cancer has a chance to develop.”

All of us accumulate cells with cancer-causing mutations as we age. While cancers rely on these mutations to develop, emerging research shows mutated cells alone are rarely enough to trigger the onset of cancer.

So what exactly determines if mutated cells turn cancerous or not? The cell’s environment.

Building on their previous research showing that air pollution can drive cancer by causing inflammation and waking up dormant cells with mutations, the research team aimed to find a signature of inflammation that can more accurately predict lung cancer – moving beyond risk assessments based purely on age and lifestyle factors.

The team applied machine learning to blood plasma protein data from more than 48,000 UK Biobank participants, using matched cancer registry records to identify those who later developed lung cancer.

Along with age, smoking status and previous history of lung disease, the machine learning algorithm identified 14 key proteins in the blood that could predict a future diagnosis of lung cancer within five years.

The team validated this protein signature in eight datasets from across the world, finding that it was higher in patients who developed lung cancer in all studies, including one cohort of people without smoking histories.

Analysis in patients and animal models suggested that the signature does not come from the tumour itself, but reflects an altered inflammatory lung environment that precedes cancer.

The signature was also increased in people who later developed idiopathic pulmonary fibrosis or chronic obstructive pulmonary disease (COPD), supporting the idea that it may capture a shared, pre-disease state of lung inflammation.

Charlie Swanton, Clinical Research Director and Principal Group Leader at the Crick, Professor in Cancer at UCL and lead investigator for TRACERx, said: “Finding a signal for an inflammatory state in the lungs has given us insight into this window of opportunity, when preventative treatment could work best.

“This work supports a relatively new idea in the field, that some common age-related diseases, causing a high burden of disease in the community, share a common, presymptomatic state of inflammation.

“We think the signature could in the future help to predict and help prevent lung cancer and other lung diseases.”

The lab’s earlier work showed that air pollution exposure triggers immune cells in the lung to release an inflammatory signal called interleukin-1 beta (IL-1β), which can wake up dormant cells carrying cancer-causing mutations.

In this study, they showed that pollution exposure simultaneously increases the signature proteins and boosts the population of ‘KAC cells’, an adaptive cell state that occurs in response to injury but can also become cancerous if mutations are present.

The researchers showed that mutant cells from several different lung cell types all enter the same KAC state on their way to cancer, and that air pollution expanded this pool of KAC cells and increased the 14-protein signature.

Dr Weeden said: “What surprised us was that very different lung cell types all seemed to converge on the same intermediate state before becoming cancerous – suggesting KACs represent a common vulnerability in lung adenocarcinoma.

“If we can identify people in whom this process is active and intervene at that stage, we may be able to prevent cancer before it develops.”

The team also found that components of the signature were increased in the presence of IL-1β linked to air pollution.

Blocking IL-1β in mice exposed to pollution reduced the number of KAC cells and slowed early tumour development, suggesting anti-IL-1β drugs could prevent lung cancer in people whose lungs are showing this inflammatory signal.

Tej Pandya, Clinical PhD Student at UCL, said: “Working hand-in-hand with scientists in the lab to understand the biology in mouse models, we’ve shown that the signature reflects an altered inflammatory lung environment before cancer takes hold.

“It’s a proof of concept that, one day, we could use this signature to offer preventive treatment to people at risk of lung cancer.”

In 2017, Novartis’s CANTOS trial tested the IL-1β blocker canakinumab to prevent cardiovascular disease and reported as an exploratory finding that the drug also reduced lung cancer incidence.

However, the benefit was modest at a population level, limiting its use as a prevention strategy in unselected people.

Re-analysing data from 4651 CANTOS participants, the researchers found that people with a high baseline 14-protein signature were the ones who clearly benefited from canakinumab, with their lung cancer risk almost halved.

By selecting only those with a high signature, the number of people needed to treat to prevent one incidence of lung cancer was 55, comparable to established cardiovascular prevention strategies such as statins.

This work was a collaboration between the Francis Crick Institute, UCL, the CRUK Lung Cancer Centre of Excellence, Novartis, RVC, EPIC, ARIC, TALENT and CKB consortia, QMUL, WEHI and the University of Manchester. Funders include the Francis Crick Institute, UCL, CRUK Lung Cancer Centre of Excellence, the Mark Foundation, the Ruth Strauss Foundation, European Research Council, EMBO, Rosetrees Trust, MRC, Wellcome, UKRI and Barts Charity.

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Header image: This image shows tumours growing in a mouse lung, with the colours indicating different gene deletions. The team used mouse models in the study to show the protein signature reflects an altered inflammatory lung environment before cancer takes hold.