Researchers test for cancer-associated extrachromosomal DNA (ecDNA) mainly with metaphase DNA fluorescence in situ hybridization (FISH) and sequencing-based reconstruction. FISH shows where a targeted DNA sequence sits in dividing cells; sequencing workflows infer and classify amplified DNA structures from genomic data. A high copy number alone does not prove that DNA is extrachromosomal.
What an ecDNA test needs to establish
ecDNA is amplified DNA that exists outside chromosomes, often as circular structures carrying oncogenes. A study may aim to detect that location, reconstruct the structure and sequence, or examine its chromatin and variation. Those are related but different questions, and one method may not answer all of them.
Copy-number amplification is a clue, not proof of ecDNA: amplified DNA can also occur in chromosome-associated structures. Researchers therefore look for evidence about the DNA’s physical location or its reconstructed architecture. When reading a study, check whether its conclusion comes from direct cellular imaging, computational classification of sequencing data, or both.
How the main methods work
Metaphase DNA FISH: visualizing DNA relative to chromosomes
For metaphase FISH, researchers use a probe that binds a known amplified sequence and examine chromosome spreads from actively dividing cells. The assay shows the target’s location in relation to chromosomes, providing cytogenetic evidence rather than an inference from sequence patterns alone. Natasha E. Weiser and colleagues’ 2025 Cancer Discovery guide describes metaphase DNA FISH as the gold-standard method for ecDNA detection and says it offers single-molecule resolution.
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The method has practical constraints: cells must be actively cycling, so fixed tissue is not suitable for this assay, and researchers need to know the amplified region in advance to choose a probe. Image-analysis tools such as EcSeg can assist with FISH-image analysis, but do not remove those sample and target-selection requirements.
Short-read whole-genome sequencing: finding and classifying candidate structures
Whole-genome sequencing (WGS) can survey amplified regions without first knowing the target and without culturing cells. One workflow described in the 2025 guide uses CNVKit to identify amplified seed regions, AmpliconArchitect to reconstruct focal amplification structures, and AmpliconClassifier to classify the results as ecDNA, breakage–fusion–bridge (BFB), linear, or complex.
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These classifications are computational conclusions based on sequencing data and the pipeline’s assumptions; they are not direct images of DNA outside chromosomes. WGS can support broad discovery and structural hypotheses, but the evidence summarized here does not establish universal sensitivity or specificity across tumor types and sample preparations.
Long-read sequencing and chromatin-accessibility assays
Long-read WGS tools noted in the 2025 guide include CoRAL (Complete Reconstruction of Amplifications with Long reads) and Decoil (Deconvolve Extrachromosomal Circular DNA Isoforms from Long-read data). These tools address reconstruction of amplified structures and circular DNA isoforms. The guide also notes ATAC-seq as a way researchers have characterized accessible chromatin associated with ecDNA; accessibility information is not, by itself, the same as directly locating DNA outside chromosomes.
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The sources cited here do not provide a universal head-to-head performance ranking of long-read methods, ATAC-seq, short-read WGS, and metaphase FISH. Which method is useful depends on whether the question concerns localization, sequence structure, or chromatin activity.
Enrichment methods: studying circular DNA in greater depth
For deeper analysis of ecDNA sequence heterogeneity, the 2025 guide identifies exonuclease digestion followed by rolling-circle amplification, as well as CRISPR-CATCH, as enrichment approaches. Enrichment adds laboratory processing to obtain material for further characterization.
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Circle-seq is an isolation-and-sequencing method used to profile circular DNA. A 2024 colorectal cancer study reported greater sensitivity for eccDNA with Circle-seq than with WGS or ATAC-seq in that study. That result concerns the study’s eccDNA profiling context; it does not establish that Circle-seq is more sensitive for every question about large cancer-associated ecDNA. The broader term eccDNA includes extrachromosomal circular DNA more generally, so findings about eccDNA should not automatically be treated as findings about cancer ecDNA.
How the methods differ
| Method | What it contributes | Sample or target considerations | Important qualification |
|---|---|---|---|
| Metaphase DNA FISH | Direct cytogenetic localization of a targeted sequence relative to chromosomes | Requires actively dividing cells and prior knowledge of the amplified region to select a probe | Does not provide an unbiased search across unknown targets; described as gold standard by Weiser et al. (2025) |
| Short-read WGS with reconstruction software | Genome-wide survey of amplified regions and computational reconstruction/classification of candidate structures | Can begin without cell culture or a known target; depends on sequencing data and pipeline | Classification is computational; universal sensitivity and specificity are not established in the cited evidence |
| Long-read WGS tools | Structural reconstruction, including analysis of circular DNA isoforms | Uses long-read sequencing data; CoRAL and Decoil are tools noted in the 2025 guide | Universal comparative performance versus other methods is not established in the cited evidence |
| ATAC-seq | Characterizes accessible chromatin associated with ecDNA | Provides chromatin-accessibility information | Accessibility characterization is not equivalent to direct cytogenetic localization |
| Enrichment and Circle-seq | Supports deeper characterization of circular DNA and sequence heterogeneity | May require additional enrichment or isolation steps | The 2024 colorectal cancer Circle-seq finding is specific to that study’s eccDNA profiling context |
What prevalence figures can—and cannot—tell you
Weiser et al.’s 2025 guide reports that a Genomics England consortium study found ecDNA in 17.1% of 15,832 tumor samples from 14,778 patients. In the analyzed data, the reported proportions were 54.9% for liposarcomas, 49.1% for glioblastomas, and 0% for oligodendrogliomas. These are figures for that cohort, not universal prevalence estimates for every population, tumor sample, or detection workflow.
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The same guide describes ecDNA elements as typically larger than 100 kb, based on cited studies. This is a generalization, not a size threshold that identifies every ecDNA molecule.
Are these clinical diagnostic tests?
The methods described here are research approaches. The sources summarized here do not establish a standardized clinical diagnostic test for individual patients or a universal protocol with validated performance across cancers. A research finding that a tumor carries ecDNA should therefore be understood in the context of the assay and analysis used, rather than as a standalone clinical result.
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