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Principal Investigator
Name
Robert Philibert
Degrees
MD PhD
Institution
Behavioral Diagnostics
Position Title
Professor
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
2022-0014
Initial CDAS Request Approval
Aug 1, 2022
Title
A Phase II extension of the use of cg05575921 Methylation to predict risk for lung cancer
Summary
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, in R43CA257372, 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. Since the current guideline now call for examining all of those with >20 PY of exposure, we need to assess additional samples to extend our method to those with lower PY consumption levels.
In this Phase II NIH SBIR extension, we hypothesize by adding additional methylation information from samples with greater ranges of exposure who received X-ray screening only, then adjusting the regression formula to account for the differing sensitivity and specificity of the X-ray method could address the exposure window shortcoming. To accomplish this, we propose to determine cg05575921 methylation from 4800 subjects in x-ray only arm of the NLST, who have lifetime exposure > 30 PY, and 4800 subjects from the PLCO collection, who have lifetime exposure > 20 PY. We will then analyze these new data with our prior studies of the NLST LDCT to 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.
Aims

Aim 1. Determine cg05575921 methylation in DNA from blood from 4800 subjects with >20 PY of smoking from the Prostate, Lung, Colon and Ovarian (PLCO) Cancer trial and 4800 subjects from the X-ray arm of the NLST study.
Aim 2. Analyze the new data together with the previously derived data, and develop a formula for predicting likelihood of developing Lung CA in those with >20 PY of smoking.
Hypothesis. The addition of the data from Aim 1 will extend the range of prediction for PY.

Collaborators

Robert Philibert (Behavioral Diagnostics)
Jeffrey D Long (University of Iowa)