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Detection and characterization of lung cancer using cell-free DNA fragmentomes

Lung cancer remains the leading cause of cancer death world-wide, largely due to its late diagnosis. Non-invasive approaches for assessment of cell-free DNA (cfDNA) provide an opportunity for detection and intervention that may have broader accessibility than current imaging approaches. Using a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation, we examined a prospective study of 365 individuals at risk for lung cancer (Lung Cancer Diagnostic Study, LUCAS), including 129 individuals ultimately diagnosed with lung cancer and 236 individuals determined to not have lung cancer. We externally validated the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 predominantly early stage lung cancer patients. Combining fragmentation features with clinical risk factors and CEA levels followed by CT imaging detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites could be used to distinguish individuals with small cell lung cancer (SCLC) from those with non-small cell lung cancer (NSCLC) with high accuracy (AUC=0.98). Among individuals with lung cancer, a higher cfDNA fragmentation score was associated with tumor size and invasion, and represented an independent prognostic indicator of survival. These studies provide a facile approach for non-invasive detection of lung cancer and clinical management of this disease.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001007796 Illumina HiSeq 2500 872
Publications Citations
Detection and characterization of lung cancer using cell-free DNA fragmentomes.
Nat Commun 12: 2021 5060
134
A novel approach for the non-invasive diagnosis of pulmonary nodules using low-depth whole-genome sequencing of cell-free DNA.
Transl Lung Cancer Res 11: 2022 2094-2110
1
Detecting Liver Cancer Using Cell-Free DNA Fragmentomes.
Cancer Discov 13: 2023 616-631
36
A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA.
Nat Commun 13: 2022 7475
24
Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer.
Nat Genet 55: 2023 1301-1310
10
Genome-wide repeat landscapes in cancer and cell-free DNA.
Sci Transl Med 16: 2024 eadj9283
3
Systematically Evaluating Cell-Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns.
Adv Sci (Weinh) 11: 2024 e2308243
2
DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation.
Nat Commun 15: 2024 6690
0
Cancer treatment monitoring using cell-free DNA fragmentomes.
Nat Commun 15: 2024 8801
0