A New Path to Preventing Cancer - by Eric Topol
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News and Analyses<br>A New Path to Preventing Cancer<br>A Landmark Study Showing the Way Forward<br>Eric Topol<br>Jun 13, 2026
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In the journal Cell, a team of >80 researchers from 4 continents reported on the discovery of a 14-protein blood test which paved the way for predicting and preventing lung cancer more than 5 years before it would be diagnosed. Current efforts in cancer are largely directed to therapy and early detection, with only a very limited foray to prevention. In a recent Ground Truths, I reviewed the emerging potential for preventive cancer vaccines in people with a known pathogenic mutation (such as Lynch syndrome or BRCA). In contrast, this extraordinary new report used machine learning of high-throughput proteomics, with validation of the 14-protein signature in 8 different cohorts, and in a study of people with lung cancer who never smoked. Beyond that, there was extensive work to understand the role of air pollution (via particulate matter, PM), wild-type and mutant mice, lung organoids, single-cell biology, and adjacent healthy tissue to the tumor microenvironment. The study was covered on the front page of the NY Times (←gift link) in an easy to understand way, although it glossed over its unique features, many important details, and the implications. The infographic below that I made with the help of NotebookLM is also reductionist but conveys the main thrust of the work.<br>In this post, I’ll take you through the findings and the ramifications that it has for preventing cancer in the future. It’s a massive amount of work, so I will not get into the abundant technical details, but instead hit the high points.
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Let’s first go back to the CANTOS trial that set this up.<br>Background on an Old Randomized Trial
Back in 2017, there was publication of CANTOS, a large randomized clinical trial that assessed an anti-inflammatory medication (canakinumab, an interleukin-1β antibody) in more than 10,000 participants with prior heart attack for reduction of subsequent cardiovascular events. While the results were not compelling for this cardiovascular indication (small benefit and a risk of fatal infections), there was an unexpected outcome of reduction of lung cancer and fatal lung cancer during 5 year follow-up, both with a dose-response (Figure below for lung cancer incidence). At the highest dose of the drug, there was nearly an 80% reduction of fatal lung cancer. But the number needed to treat (NNT) with the antibody to prevent 1 person’s lung cancer was >1,000, which reflects there wasn’t a way to know who would benefit from the drug. Wouldn’t it be great if we could understand this better and identify whose lung cancer could be prevented with the interleukin-1β antibody?
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The New Study
Probing the UK Biobank
The first step was to do high-throughput plasma proteomics in over 48,000 UK Biobank participants (schematic below). This cohort had nothing to do with the CANTOS trial.
This involved assessing nearly 3,000 different proteins from the blood (O-link, ThermoFisher) and using machine learning of the data along with age, history of smoking and lung disease, to find the proteins that predicted lung cancer. There were 14 proteins that fulfilled this objective. They had 4 major categories of function indicative of deep lung cell stress: inflammation, lung surfactant production, epithelial cell secretion, and matrix remodeling (more on the latter 2 categories later). The proteins were present on average 5.6 years before UK Biobank participants who developed lung cancer. These 14-proteins (Figure below with risk of lung cancer) were assessed in 8 different cohorts with either the same (O-link) high-throughput proteomic platform or with Somalogic. The proteins were also confirmed in a Taiwanese cohort (comprised of 81% women, 62% adenocarcinomas) of whom 93% never smoked. Prediction of lung cancer incorporating the 14-proteins outperformed 2 prior lung cancer models based on demographics and smoking history (known as LCRAT and LLVP3). The 14-protein signature was also found in some people with idiopathic pulmonary fibrosis and in chronic obstructive pulmonary disease.
Replication of the 14-protein signature in 8 different cohorts (known by their acronyms like ARIC, EPIC, CKB, etc.)
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Probing the Biology
There were important results of the TRACERx clinical study (Tracking Cancer Evolution through therapy [Rx]) that had to be folded in to help identify the source of the 14-proteins. That study tracked lung cancer evolution and post-surgical results. There was no correlation of the 14-proteins with more advanced lung cancer (compared with early cancers) and no reduction of the protein signature after resection of the lung tumor. So, surprisingly the 14-proteins were not coming...