Researchers at the Francis Crick Institute and University College London have identified a 14-protein signature in the blood that can predict lung cancer risk more than five years before diagnosis.
Published in Cell, the research 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 5 years. The team validated this protein signature in eight datasets from across the world, finding that it was higher in patients who, in the future, developed lung cancer in all studies, including one cohort of non-smokers.
Analysis of the signature in patients and animal models suggested that the signature does not come from the tumor itself but reflects an altered inflammatory lung environment that precedes cancer.
The lab’s previous 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 show 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.
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 tumor development.
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. Re-analyzing data from 4,651 CANTOS participants, this 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.
Data from Francis Crick Institute