2022 World Conference on Lung Cancer (ePosters)-EP01.01-003. DELFI-L101: Development of a Blood Based Assay That Evaluates Cell-Free DNA Fragmentation Patterns to Detect Lung Cancer

EP01.01-003. DELFI-L101: Development of a Blood Based Assay That Evaluates Cell-Free DNA Fragmentation Patterns to Detect Lung Cancer

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Researchers have developed a blood-based assay called DELFI-L101 that evaluates cell-free DNA (cfDNA) fragmentation patterns to detect lung cancer. Lung cancer screening programs have faced challenges in global implementation, including low uptake and concerns over false-positives and radiation exposure. The DELFI technology uses supervised machine learning to distinguish cancer from non-cancer by analyzing fragmentation patterns of cfDNA. This assay could address some of the barriers to lung cancer screening and improve early detection.<br /><br />The DELFI-L101 study is a prospective, case-control, observational study designed to train and test classifiers for lung cancer detection using the DELFI assay and other biomarkers and clinical features. Eligibility criteria for participants include being 50 years of age or older with a current or previous smoking history of at least 20 pack-years. Participants are divided into three groups: Group A (Lung Cancer), Group B (Non-Cancer), and Group C (Non-Lung Cancer). Group A consists of individuals with confirmed, untreated lung cancer, while Group B represents the general screening-eligible population without suspected or confirmed lung cancer. Group C includes individuals with non-lung cancers originating from various organs.<br /><br />The primary objective of the study is to train and test classifiers for lung cancer detection using the DELFI assay and other biomarkers and clinical features. Secondary objectives include evaluating the performance of classifiers in specific clinical subgroups and developing classifiers for multi-cancer detection. The primary endpoint is the accuracy of lung cancer detection measured by sensitivity, specificity, and the area under the receiver operating characteristic curve.<br /><br />The DELFI-L101 study is currently enrolling participants at 50 academic and community sites across the United States. The development of a noninvasive, accurate, low-cost DELFI test has the potential to improve lung cancer screening by identifying individuals who are more likely to have lung cancer and benefit from screening. This could reduce potential harms associated with screening and make it more accessible to a broader population.

Asset Subtitle

Peter Bach, United States

Meta Tag

Speaker Peter Bach, United States

Topic Early Detection and Screening - Biomarkers

Keywords

blood-based assay

DELFI-L101

cfDNA fragmentation patterns

lung cancer

supervised machine learning

barriers to lung cancer screening

early detection

biomarkers

sensitivity

specificity