A blood signature for lung cancer risk: 14 proteins identified that may help people who could benefit from cancer prevention drugs

As we age, our cells accumulatecancer causing mutations. However, mutations alone are typically not enough to start a tumour. Additional factors includingenvironmental exposuresuch asair pollution from combustion engines, coal burning and cigarette smoke, may be needed to tip mutant cells into cancer. Currently, lung cancer screening programmes are offered only to people over a certain age who have previously smoked, missing never-smokers and individuals exposed to high levels of pollutants who may also be at risk of the disease.

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 predict lung cancer more accurately, moving beyond the risk based purely on age and lifestyle factors.

The study, published today in Cell, analysed 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 the result 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 non-smokers.

Further analysis of the signature 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. Elevated levels of the signature were also observed 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.

From inflammation to prevention

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 the current study, they show that air 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.

@Cancer Evolution and Genome Instability Laboratory

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.

A precision approach to cancer prevention

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.

In the present study, researchers re-analysed data from 4,651 CANTOS participants andfound 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.

Tej Pandya, Clinical PhD Student at UCL and visiting scientist at the Francis Crick Institute, said: 'We used machine learning on plasma data from over 48,000 people to identify the 14-protein signature, and it has been incredible to validate it across eight datasets with more than 80 collaborators on five continents. 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.'

Charlie Swanton, Clinical Research Director and Principal Group Leader at the Crick, Professor in Cancer at UCL, lead investigator for TRACERx and ERC grantee, said: 'Drugs like statins have transformed the prevention of cardiovascular disease, used to treat individuals with a high 'low density lipoprotein' (LDL). But we don't yet have an LDL-like marker of risk or a statin for lung cancer. In the clinic, I see first-hand the impact of diagnosing lung cancer at a late stage, so being able to identify people at risk and intervene before the disease develops is critical.

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.'

Hayley Brown, Research Information Manager at Cancer Research UK said: 'By revealing the earliest warning signs of cancer, this research brings us closer to intervening sooner and potentially stopping the disease before it starts.

In doing so, it could help spare people and their loved ones from the impact of a cancer diagnosis, treatment, and everything that follows, allowing them instead to focus on the moments that matter most.'

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.