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Genomic and fragmentomic landscapes of cell-free DNA for early cancer detection

Nature Reviews Cancer volume 25, pages 341–358 (2025)Cite this article

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Abstract

Genomic analyses of cell-free DNA (cfDNA) in plasma are enabling noninvasive blood-based biomarker approaches to cancer detection and disease monitoring. Current approaches for identification of circulating tumour DNA typically use targeted tumour-specific mutations or methylation analyses. An emerging approach is based on the recognition of altered genome-wide cfDNA fragmentation in patients with cancer. Recent studies have revealed a multitude of characteristics that can affect the compendium of cfDNA fragments across the genome, collectively called the ‘cfDNA fragmentome’. These changes result from genomic, epigenomic, transcriptomic and chromatin states of an individual and affect the size, position, coverage, mutation, structural and methylation characteristics of cfDNA. Identifying and monitoring these changes has the potential to improve early detection of cancer, especially using highly sensitive multi-feature machine learning approaches that would be amenable to broad use in populations at increased risk. This Review highlights the rapidly evolving field of genome-wide analyses of cfDNA characteristics, their comparison to existing cfDNA methods, and recent related innovations at the intersection of large-scale sequencing and artificial intelligence. As the breadth of clinical applications of cfDNA fragmentome methods have enormous public health implications for cancer screening and personalized approaches for clinical management of patients with cancer, we outline the challenges and opportunities ahead.

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Fig. 1: cfDNA features and analysis for early detection of cancer.
Fig. 2: Differences in genome-wide cfDNA characteristics between individuals with and without cancer.

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Acknowledgements

The authors thank the members of their laboratories for the critical review of the manuscript. This work was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, SU2C in-Time Lung Cancer Interception Dream Team Grant, Stand Up to Cancer-Dutch Cancer Society International Translational Cancer Research Dream Team Grant (SU2C-AACR-DT1415), the Gray Foundation, The Honorable Tina Brozman Foundation, the Commonwealth Foundation, the Mark Foundation for Cancer Research, the Cole Foundation, a research grant from Delfi Diagnostics, and US National Institutes of Health grants CA121113, CA006973, CA233259, CA062924 and CA271896. Stand Up To Cancer is a programme of the Entertainment Industry Foundation administered by the American Association for Cancer Research. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Daniel C. Bruhm, Nicholas A. Vulpescu, Zachariah H. Foda, Jillian Phallen, Robert B. Scharpf & Victor E. Velculescu

  2. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Zachariah H. Foda & Victor E. Velculescu

  3. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Robert B. Scharpf

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All authors researched data for the article, contributed substantially to the discussion of the content, wrote the article, and reviewed and/or edited the manuscript before submission.

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Correspondence to Victor E. Velculescu.

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Competing interests

D.C.B., Z.H.F, J.P. and R.B.S. are inventors on patent applications submitted by Johns Hopkins University related to cell-free DNA analyses. J.P. and R.B.S. are founders of Delfi Diagnostics, and R.B.S is a consultant for this organization. V.E.V. is a founder of Delfi Diagnostics, serves on the board of directors, and owns Delfi Diagnostics stock, which is subject to certain restrictions under university policy. Additionally, Johns Hopkins University owns equity in Delfi Diagnostics. V.E.V. divested his equity in Personal Genome Diagnostics (PGDx) to LabCorp in February 2022. V.E.V. is an inventor on patent applications submitted by Johns Hopkins University related to cancer genomic and cell-free DNA analyses that have been licensed to one or more entities, including Delfi Diagnostics, LabCorp, Qiagen, Sysmex, Agios, Genzyme, Esoterix, Ventana and ManaT Bio. Under the terms of these license agreements, the University and inventors are entitled to fees and royalty distributions. V.E.V. is an adviser to Viron Therapeutics and Epitope. These arrangements have been reviewed and approved by the Johns Hopkins University in accordance with its conflict-of-interest policies.

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Glossary

Apoptosis

A form of programmed cell death that can be initiated by either extracellular or intracellular mediators in response to a predefined developmental programme or in response to cellular stress.

Cancer screening

Population-scale testing of asymptomatic individuals for cancer.

Cell-free DNA

(cfDNA). DNA fragments that are not contained within cells, which can be produced through apoptosis, necrosis and active secretion.

cfDNA fragmentome

The genome-wide compendium of cfDNA fragments in the circulation, providing an integrated view of the chromatin, genome, epigenome and transcriptome states of normal and cancer cells of an individual.

Chromatin

A complex of DNA and proteins that can exist as open, ‘active’ chromatin termed euchromatin, or as heterochromatin, which refers to closed ‘inactive’ chromatin.

Circulating tumour DNA

(ctDNA). cfDNA fragments from tumour cells released into the bloodstream.

Classifiers

Algorithms that assign an entity to one or more groups.

Clonal haematopoiesis of indeterminate potential

(CHIP). A genetically distinct population of blood cells caused by somatic mutations in blood cell progenitors.

Diagnostic odyssey

When the process to diagnose a disease is long and difficult, often requiring multiple tests and procedures.

False-negative rate

The probability that an individual with cancer will test negative, which is equivalent to 1-sensitivity.

False-positive rate

The probability that an individual without cancer will test positive, which is equivalent to 1-specificity.

Germline variants

Genetic variants that were already present in the germline leading to its presence in all cells throughout the body.

Li–Fraumeni syndrome

A rare disorder resulting from pathogenic germline variants in the TP53 gene that greatly increases the risk of developing cancer.

Lymphoblastoid cells

Immortalized B lymphocytes generated by infection with Epstein–Barr virus.

Massively parallel sequencing

Often referred to as next-generation sequencing (NGS), this laboratory approach is used to determine the sequence of a large number of DNA fragments simultaneously.

Microsatellites

Short stretches of DNA wherein one to several nucleotides are repeated multiple times.

Necrosis

A form of cell death distinct from apoptosis; necrosis can be induced by irreversible cell injury and is characterized by breakdown in the plasma membrane and release of intracellular contents.

Negative predictive value

(NPV). The probability that an individual with a negative screening test does not have cancer.

Nucleosomes

Segments of DNA wrapped around histone proteins; a mononucleosome refers to a single nucleosome, whereas a di-nucleosome or tri-nucleosome refers to two or three nucleosomes.

Pack-year

A quantification of the smoking history of an individual determined by multiplying the number of packs of cigarettes smoked per day by the number of years of smoking.

Polygenic risk scores

(PRS). Scores derived from multiple genetic variants related to the risk of an outcome.

Polymorphisms

Variations in DNA sequence at specific positions in the genome that contribute to genetic variation and might alter the structure, function or expression of the gene product.

Positive predictive value

(PPV). The probability that an individual with a positive screening test has cancer.

Pre-analytical factors

Factors that occur before sample analysis in the laboratory that may influence test results, such as how samples are collected and stored, which have been shown to influence ctDNA levels.

PTEN hamartoma tumour syndrome

A rare genetic condition caused by germline mutations in the PTEN gene with multiple health implications including an increased risk of developing certain types of cancer.

Repetitive elements

Sequences of DNA that are repeated multiple times in the genome.

Sensitivity

The probability that an individual with cancer will test positive, which can be estimated directly from a case–control study as the proportion of cancers that test positive out of all cancers in the study (also known as the true-positive rate).

Specificity

The probability that an individual without cancer will test negative, which can be estimated directly from a case–control study as the proportion of individuals without cancer that test negative out of all individuals without cancer in the study (also known as the true-negative rate).

Stage-shifting

Detecting cancers at an earlier stage of the disease owing to screening.

Structural variants

Large genomic rearrangements that are typically ≥50 bp.

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Bruhm, D.C., Vulpescu, N.A., Foda, Z.H. et al. Genomic and fragmentomic landscapes of cell-free DNA for early cancer detection. Nat Rev Cancer 25, 341–358 (2025). https://doi.org/10.1038/s41568-025-00795-x

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