# An Improved Epigenetic Algorithm for Guiding Low Dose CT Lung Cancer Screening > **NIH NIH R44** · BD HOLDING, INC. · 2024 · $985,125 ## Abstract SPECIFIC AIMS Approximately 90% of lung cancer results from smoking. Low Dose Computerized Tomography (LDCT) of smokers can detect lung cancer earlier allowing more effective treatment. But determining which smokers should get LDCT screening is controversial and potentially harmful. Recently, the U.S Preventive Services Task Force (USPSTF) updated their opinion on screening to recommend annual LDCT screening for current or recent smokers between the ages of 50 and 80 who have smoked 20 pack years (PY) or more. In addition, they specifically called for the development of biomarker-based methods to predict who will benefit from screening. Precision Epigenetics may answer this call. In 2012, we showed that DNA methylation at cg05575921, a site in the aryl hydrocarbon receptor repressor (AHRR) gene, predicts smoking status. Since then, over 100 studies have replicated those findings. In 2018, we developed Smoke Signature©, a precise, reference free methylation sensitive digital PCR (MSdPCR) assay for this locus. In peer-reviewed publications, we have shown that the Receiver Operator Characteristic (ROC) area under the curve (AUC) for this assay is 0.984 for daily smokers, the amount of demethylation accurately predicts daily consumption and that the re-methylation response to smoking cessation can be used to monitor success of cessation therapy. Intriguingly, in 2017, Bojesen and colleagues showed that cg05575921 methylation also predicts those smokers likely to benefit from LDCT screening. Recently, we have now confirmed and extended these findings using a subset of DNA specimens from the National Lung Screening Trial (NLST). In particular for those NLST subjects who reported quitting smoking, our method significantly predicts lung cancer risk better than PY alone in a racial and gender-free manner. However, our method is based only the data from 3200 NLST subjects, all of whom smoked 30 PY or more. In this Phase II project, we propose to finish our assessments of the 4800 NLST subjects, all of whom have > 30 PY of consumption and LDCT data, then use DNA from 4800 subjects in x-ray only arm of the NLST and 4800 subjects from the PLCO collection to extend the range of our test down to 20 PY of cigarette consumption. We will then analyze the resulting data and develop a race and SES bias free Cox regression formula to predict risk for those between the ages of 50-80 years and >20 PY of smoking. The resulting laboratory developed test (LDT) will run on the 510K approved Bio-Rad QX-200 platform with reagents from companies that can comply with FDA standards. When implemented, the test will decrease healthcare costs and morbidity and mortality from unnecessary procedures. Eventually, we believe that this test will be essential for both prescreening counselling and treatment monitoring of all smokers. ## Key facts - **NIH application ID:** 10890199 - **Project number:** 5R44CA285136-02 - **Recipient organization:** BD HOLDING, INC. - **Principal Investigator:** Kelsey Dawes - **Activity code:** R44 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $985,125 - **Award type:** 5 - **Project period:** 2023-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10890199 ## Citation > US National Institutes of Health, RePORTER application 10890199, An Improved Epigenetic Algorithm for Guiding Low Dose CT Lung Cancer Screening (5R44CA285136-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10890199. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*