![]() ![]() However, this would require efficient detection of somatic changes in cfDNA, including those related to mutational signatures 24, and the ability to effectively distinguish these from non-tumor-derived alterations. In principle, if mutations could be identified in cfDNA without knowledge of alterations in the tumor, then they could be useful for early cancer detection. Tumor genomes contain thousands of somatic changes 20, 21, and knowledge of such alterations from tumor tissue has guided ctDNA analyses during therapy 22, 23. Here, we considered whether identifying somatic mutations genome-wide could enable the detection of an increased number of circulating tumor DNA (ctDNA) alterations and increase the detection of early stage disease. ![]() Recent analyses have shown that genome-wide fragmentation and methylation analyses could be used for non-invasive early cancer detection 13, 14, 18, 19. Additionally, cfDNA sequence alterations may arise from white blood cells, confounding cancer detection 8, 16, 17. Owing to the low number of tumor genome equivalents in cfDNA, such approaches have limited efficacy for detecting cancer, especially at early stages 13, 14, 15. However, these methods typically rely on deep sequencing and have been restricted to examining specific genes comprising a small subset of the genome 10, 11, 12. Extensive efforts have been made to detect low-frequency mutations in cfDNA. Sequence alterations are abundant in cancer genomes but the proportion of fragments in cell-free DNA (cfDNA) that harbor tumor-specific (somatic) mutations is often low 8, 9, making it difficult to detect bona fide variants amidst background noise from sequence changes introduced in library construction and sequencing. Liquid biopsies may overcome these challenges and provide an attractive approach for the non-invasive detection of lung cancer and other malignancies. For other cancers, although early detection could improve patient outcomes, no effective screening modalities are available 7. Although screening with LDCT has been shown to reduce mortality 4, 5, adherence to this test is low (<6%) among high-risk individuals 6, in part owing to the potential harm caused by its low specificity, radiation exposure and unnecessary diagnostic procedures as a result of overdiagnosis. For example, screening for lung cancer using low-dose computed tomography (LDCT) is recommended in the United States for adults aged 50–80 years who have smoked at least 20 pack years and currently smoke or have quit smoking within the last 15 years 3. Early detection of cancer has demonstrated clinical benefits in multiple cancer types, but the implementation of screening approaches remains challenging 2. ![]() Most human mortality associated with cancer is a consequence of diagnosis at late stages, when therapies are less effective 1. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. ![]()
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