Methylated Biomarkers of Smoking as a Selection Tool in Participants for Lung Cancer Screening

The MET-SELS study represents a sophisticated paradigm shift in oncology and preventive medicine, aiming to solve one of the most persistent challenges in lung cancer screening (LCS): the accurate identification of the high-risk population. Currently, global screening protocols-which rely on low-dose CT (LDCT) scans-target individuals based on "categorical smoking criteria," typically defined by age and a history of at least 30 pack-years. However, as the MET-SELS researchers argue, these criteria are fundamentally flawed. They are largely arbitrary, susceptible to significant recall and volunteer bias, and fail to capture the biological reality of smoking behavior, such as inhalation depth, nicotine retention, or the compounding effects of second-hand smoke. Because current methods only capture approximately 50% of incidental lung cancers, there is a critical need for a "bias-proof" and biologically grounded selection tool.

To address this, the study, led by Principal Investigator Professor Dr. Annemiek Snoeckx and a multidisciplinary team including Professors Ken Op de Beeck, Guy Van Camp, and Jan van Meerbeeck, turns to the cutting-edge field of epigenetics. The central hypothesis is that tobacco smoke leaves a permanent and quantifiable "molecular scar" on the human genome through DNA methylation. While traditional biomarkers like carbon monoxide in exhaled breath or cotinine in serum only reflect short-term nicotine exposure-and can be easily masked by temporary abstinence or nicotine replacement therapy-DNA methylation patterns in specific genes are remarkably robust. Specifically, the study focuses on a panel of genes including AHRR, F2RL3, and ALPPL2. Research has shown that people who smoke or used to smoke exhibit significantly lower methylation levels at the AHRR site (cg05575921) compared to people who never smoked. Crucially, while some of these epigenetic markers begin to reverse upon quitting, others remain stable for more than 30 years after cessation, providing a reliable "biological ledger" of a person's lifetime tobacco exposure and their true risk profile.

The methodology of the MET-SELS study is designed for high statistical power and clinical relevance. It utilizes two distinct cohorts: Cohort 1 consists of 850-900 participants from the ZORALCS screening implementation study at UZA, and Cohort 2 includes 150 volunteers aged 50 and older, covering a spectrum of smoking histories. Participants provide a simple 2 ml saliva sample, which is far less invasive and more cost-effective for mass screening than blood-based liquid biopsies. These samples undergo rigorous genomic and methylomic analysis at the Centre for Medical Genetics, employing techniques such as whole-genome sequencing (WGS) and quantitative methylation-specific PCR (qMSP). These biological results are then cross-referenced against two types of behavioral data: self-reported questionnaires and intensive, structured interviews led by specialized healthcare providers. By using ROC analysis and linear regression, the study aims to validate how accurately these salivary biomarkers can predict smoking status, pack-years, and duration of abstinence compared to traditional reporting.

The long-term vision of MET-SELS is nothing short of a total transformation of public health policy. The researchers aim to validate a "saliva-first" triage model for lung cancer, analogous to the FIT (Fecal Immunochemical Test) used in colorectal cancer screening. In this envisioned future, a saliva collection kit would be mailed to the target-age population; only those whose epigenetic signature reveals a high-risk profile would be invited for a clinical LDCT scan. This approach would not only improve the yield of early-stage lung cancer detection but also significantly enhance the cost-effectiveness of screening programs by excluding low-risk individuals who are currently selected based on inaccurate self-reporting. By replacing subjective anecdotes with objective genomic data, the MET-SELS study paves the way for a more precise, equitable, and effective era of cancer prevention.