Improving risk stratification for lung cancer screening using peripheral blood leukocyte DNA methylation: an investigation in the National Lung Screening Trial (NLST)
- Institution
- TUFTS UNIVERSITY BOSTON, MA
- Principal investigator
- Dominique S. Michaud
- Funding
- $676K
- Duration
- 2024–2028
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Abstract
Project Summary Lung cancer is the leading cause of cancer death in the US, accounting for approximately 22% of all cancer deaths. Annual screening with low-dose computed tomography (LDCT) is recommended in adults aged 50-80 years who have a history of pack-years to 20 and are current smokers or quit in the past 15 years, but screening with LDCT remains controversial due to the very high false-positive rates, increased radiation exposures, and costs. Moreover, many adults are diagnosed with lung cancer who are not eligible for screening. In the 2021 USPSTF recommendation statement, the task force identified “Future Research Needs,” which includes conducting more research on biomarkers, noting that: “Biomarkers could potentially be used to identify high-risk candidates for screening with LDCT”. For this project, we propose to measure DNA methylation levels in blood leukocytes obtained from samples that were collected prior to screening (and at multiple time points) in participants of the National Lung Screening Trial (NLST). Our first objective is to develop a pre-screening tool that would classify high-risk participants into additional risk categories to reduce number of scans needed. Our second objective is to examine whether differences in DNA methylation markers can distinguish participants with positive screening results who developed lung cancer from those with false positives (i.e., did not develop cancer). Our third objective is to examine whether differences in DNA methylation markers can discriminate participants who had a negative scan and were diagnosed with lung cancer during follow-up and through the end of 2014 from those with a negative scan who did not develop lung cancer. Using the NLST archived samples will allow us to efficiently evaluate whether DNA methylation markers can improve models for risk stratification, thus reduce unnecessary scans needed to be performed, as well as potentially assist in identifying true positive and false negative LDCT scans. .
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