TL;DR

In 2025, ecDNA/eccDNA studies started answering the practical "how" questions—how circles persist through division, how they concentrate transcriptional machinery, and why their copy-number variability matters under drug selection in experimental models. This roundup highlights nine papers and turns them into a short study-design checklist (capture → validate → quantify → function).

This roundup summarizes nine high-impact studies and ends with a practical ecDNA/eccDNA study checklist—including hands-on experimental tips to reduce false junctions, control linear DNA carryover, and design validation that reviewers commonly request.

Summary of five key themes from nine 2025 ecDNA/eccDNA studies, with a practical study workflow (capture → validate → quantify → function).

Why ecDNA/eccDNA matters now (and what changed in 2025)

ecDNA/eccDNA has become a central theme in cancer genome regulation because it can uncouple gene dosage from chromosomal inheritance, creating rapid shifts in copy number and regulation at the individual-cell level. What stands out in 2025 is that multiple groups are converging on mechanisms—inheritance, nuclear organization, and heterogeneity—rather than treating ecDNA as "extra copies" alone.

Instead of stopping at "ecDNA amplifies oncogenes," the newest work asks:

• Inheritance mechanics: How can circular DNA persist across divisions if it lacks a centromere?
• Regulatory logic: Why do ecDNA clusters often behave like super-enhancer-like hubs, and what molecular dependencies hold them together?
• Evolution under selection: How does ecDNA create spatial heterogeneity and dosage heterogeneity that can accelerate adaptation under drug selection pressure in experimental models?
• Sequence innovation: Can repeats and transposon-derived sequences become functional enhancers on circular DNA?
• Beyond cancer: What does eccDNA do in stress responses and genome plasticity in plants and other systems?

Taken together, these questions map to three decisions you'll face in practice: what to measure (structure vs regulation vs heterogeneity), how to validate, and how to report results in a way reviewers can audit.

If you're new to circular DNA terminology (microDNA, eccDNA, ecDNA), our short primer eccDNA 101: Biogenesis, Classes, and Why It Matters can help.

2025 "9 Studies" Showcase (high-impact findings + practical implications)

Below, each study is summarized in a consistent "what they asked → what they found → why it matters → what to copy in your design" format.

Table 1. Overview of the nine ecDNA/eccDNA studies highlighted in this 2025 roundup

Study #1 — Retention elements help ecDNA persist across mitosis (Nature, 2025)

ecDNA retention mechanism via chromosome hitchhiking during mitosis. (from paper Fig. 1a)

What they asked: ecDNA lacks centromeres and should segregate randomly—so why does it often persist over many generations in cancer cells?

Core finding (high-level): The authors identify genomic "retention elements" enriched in CpG-rich promoter-like sequences that can physically link ecDNA to mitotic chromosomes, increasing transmission to daughter cells.

Methods used: GRO-seq, WGS, Hi-C–style approaches, FISH, live imaging, and a genome-wide assay introduced as Retain-seq.

Why it matters: This is a concrete answer to a long-standing question: ecDNA persistence can be sequence-encoded and regulation-sensitive, not merely stochastic.

Study design implication: If you're comparing ecDNA across conditions, consider that epigenetic state and promoter-like elements may influence retention. For mechanistic studies, plan to measure both ecDNA abundance and epigenetic context rather than treating ecDNA copy number as a static trait.

ecDNA–chromosome interactions resemble enhancer–promoter regulation model. (from paper Fig. 3k)

Study #2 — ecDNA clusters integrate into nuclear condensates and reshape chromatin contacts (Cancer Cell, 2025)

What they asked: Do ecDNA clusters act only as "mobile enhancers," or do they restructure nuclear organization in cancer-specific ways?

Core finding (high-level): Across multiple cancer models, ecDNA assemblies are reported to associate with nuclear condensate components (e.g., coactivator hubs), showing cancer-specific chromatin connectivity. Perturbing ecDNA-specific regulatory modules or disrupting condensate integrity can reduce coactivator occupancy and dampen oncogenic transcription.

Methods used: ChIP-seq, CUT&Tag, ATAC-seq, RNA-seq, CRISPR epigenetic perturbation, and chromatin interaction assays (e.g., ChIA-drop).

Why it matters: The key point is that ecDNA activity may depend on where circles sit in nuclear space, not only on which enhancers they carry—an important distinction when you interpret bulk chromatin signals.

Study design implication: If your goal is functional dependency mapping, your readouts should include coactivator localization and chromatin connectivity, not just ecDNA copy number.

With retention and hub formation on the table, the next practical question is distribution: how unevenly are circles shared across cells and tumor regions?

Study #3 — Spatial heterogeneity and evolution of ecDNA in glioblastoma (Cancer Discovery, 2025)

What they asked: How does ecDNA vary across tumor regions, and what determines whether ecDNA becomes dominant early or late?

Core finding (high-level): Using patient samples and modeling, the study argues that ecDNA spatial heterogeneity can show oncogene-specific patterns shaped by random segregation plus different selective advantages, with some ecDNA types accumulating early.

Methods used: WGS and FISH with tumor sampling logic.

Why it matters: It reframes ecDNA interpretation as inherently spatiotemporal: a single biopsy or single region can miss the true evolutionary picture.

Study design implication: For solid tumors, consider multi-region sampling (when feasible in research settings) and plan analyses that explicitly test regional ecDNA variability.

Study #4 — ecDNA dosage heterogeneity enables rapid adaptation in MYCN-amplified cancers (Cancer Discovery, 2025)

What they asked: How does ecDNA-driven copy number variation translate into phenotypic diversity under drug selection pressure in experimental models?

Core finding (high-level): The study links ecDNA copy number heterogeneity to cell-fate decisions and adaptive responses under selection, using individual-cell measurements and modeling.

Methods used: Individual-cell transcriptomics, FISH, immunofluorescence, and theoretical modeling tied to copy-number–dependent fitness.

Why it matters: What makes this compelling is the distribution: ecDNA can produce wide cell-to-cell copy-number spread without waiting for new chromosomal rearrangements—exactly the kind of variability bulk averages smooth out.

Study design implication: If your hypothesis involves adaptation under selection, include individual-cell readouts (or at minimum distribution-aware metrics) rather than relying solely on bulk averages.

Study #5 — Transposable elements can become enhancers on ecDNA (Nature Cell Biology, 2025)

What they asked: Transposon reactivation is common in cancer—but can transposon-derived sequences contribute directly to ecDNA regulatory activity?

Core finding (high-level): The authors map 3D structure and identify repeat-rich regions frequently incorporated into ecDNA; a highlighted transposon fragment shows enhancer-like activity specifically in the ecDNA context and contributes to cancer cell fitness.

Methods used: Hi-C–like 3D mapping, ATAC-seq, CRISPR-based functional tests, and targeted capture approaches.

Why it matters: This expands the "regulatory parts list" for ecDNA: repeats are not merely passengers—they can be repurposed as functional enhancers.

Study design implication: When annotating ecDNA, don't automatically downplay repeats. Consider explicit analyses for transposable element enhancer on ecDNA and include functional validation when candidate elements are repeat-derived.

A second theme in 2025 is that "repeat-rich" no longer automatically means "non-functional"—especially on circular DNA.

EIE 14 is important for cell proliferation and has enhancer signatures. (from paper Fig. 4)

Study #6 — eccDNA dynamics under nutrient stress in rice (Nature Communications, 2025)

What they asked: eccDNA is widespread in eukaryotes, but how does it respond to environmental signals in crops, particularly nutrient stress?

Core finding (high-level): The study reports eccDNA classes overlapping genes, transposable elements, and full-length repeat units, and observes condition-responsive changes under nitrogen/phosphorus stress. It also discusses multi-fragment eccDNA and a potential recombination mechanism.

Methods used: eccDNA sequencing, RNA-seq, ATAC-seq.

Why it matters: It reinforces that eccDNA is not "only cancer biology." In plants, eccDNA can be part of stress-responsive genome plasticity—a valuable direction for agricultural genomics.

Study design implication: In non-cancer systems, build designs that connect eccDNA landscapes to stress conditions and pair eccDNA profiling with transcriptome and chromatin accessibility.

Global eccDNA dynamics under optimal growth and nutritional stress conditions in rice shoot tissue. (from paper Fig. 8)

For multi-species eccDNA context (humans, plants, and model organisms) and design tips, see our cross-species overview: eccDNA Across Species

Study #7 — Enhancer-like eccDNA drives a transcriptional network linked to drug resistance (Advanced Science, 2025)

What they asked: Non-coding eccDNA is common but often ignored—can enhancer-like eccDNA actively drive resistance-associated transcriptional programs?

Core finding (high-level): The paper describes an eccDNA element with enhancer activity that integrates into a transcription-factor–driven network and associates with resistance phenotypes, supported by multi-omics evidence.

Methods used: FISH, ChIP-seq/CUT&Tag, CRISPR perturbations, and integrated individual-cell and bulk multi-omics analyses.

Why it matters: It pushes the field toward "regulatory eccDNA" as a first-class object, not just ecDNA carrying coding oncogenes.

Study design implication: If you suspect regulatory eccDNA, plan enhancer activity evidence (chromatin marks, TF binding, accessibility) plus functional perturbation, not only detection.

Schematic representation for the role of eccANKRD28 in VRd-resistant MM cells. (from paper Fig. 9)

Study #8 — Plasma eccDNA research suggests disease-association signals in a myocardial infarction study context (Research, 2025)

What they asked: Can circulating eccDNA be characterized and investigated as a research biomarker candidate associated with disease phenotypes?

Core finding (high-level): The study reports a named eccDNA candidate detected from plasma eccDNA sequencing, validates circularity/sequence, and explores potential mechanistic links to regulated cell death pathways in model systems.

Methods used: eccDNA sequencing, Sanger validation, qPCR, and mechanistic assays in experimental models.

Why it matters: It highlights how circular DNA profiling is expanding into circulating nucleic acid research.

Study design implication: For plasma eccDNA research, prioritize artifact control (low input, PCR duplicates, linear DNA carryover) and include orthogonal validation (junction PCR + Sanger + qPCR).

RUO note: This type of work should be described as "research suggests associations" and typically requires independent validation in additional cohorts before any broader interpretation.

Study #9 — ecDNA amplification of a chromosome 1q21-derived oncogene in HCC (Cancer Letters, 2025)

What they asked: What does the ecDNA landscape look like in tumor vs adjacent tissue (research samples), and which amplified genes appear functionally important?

Core finding (high-level): The study reports ecDNA presence in a subset of tumors, validates extrachromosomal localization and circularity with orthogonal methods, and links amplification to malignant phenotypes in experimental systems.

Methods used: Circle-seq–style profiling, RNA-seq, outward/inward PCR, Sanger sequencing, FISH, and functional assays.

Why it matters: This is a good example of an end-to-end "discovery → validation → functional follow-up" path that reviewers tend to trust.

Study design implication: If publication is your goal, plan a validation stack from day one: detection alone is rarely enough.

What these 9 studies collectively say (5 themes you can use immediately)

1) ecDNA retention is partly sequence-encoded

Key idea: Persistence is not just random segregation—sequence features and chromatin state may contribute.

Use it: When comparing conditions, measure both ecDNA abundance and regulatory context (e.g., promoter-like content, methylation or accessibility proxies).

2) ecDNA transcription often depends on nuclear organization

Key idea: ecDNA clusters can behave like structured transcriptional hubs associated with coactivator-rich condensates.

Use it: Add at least one assay that informs on chromatin state or coactivator association when "expression impact" is your endpoint.

3) Evolution is distribution-aware, not mean-aware

Key idea: Spatial and dosage heterogeneity matter—bulk averages can hide the biology.

Use it: For heterogeneity questions, incorporate individual-cell or region-aware sampling strategies where possible.

4) Repeat-derived sequences can be functional parts on ecDNA

Key idea: Transposable elements and repeats can become enhancer-like modules in the ecDNA context.

Use it: Don't filter repeats too early in annotation. Instead, evaluate transposable element enhancer on ecDNA candidates with accessible chromatin and TF motif evidence.

5) eccDNA biology is not cancer-exclusive

Key idea: Stress and genome plasticity contexts (e.g., plant nutrient stress) are becoming mainstream eccDNA directions.

Use it: Pair eccDNA profiling with RNA-seq/ATAC-seq to connect eccDNA to biological response pathways.

How to study ecDNA/eccDNA in 2025: a practical checklist

This section is intentionally hands-on and reviewer-oriented, built around what commonly causes ecDNA/eccDNA projects to stall: false junctions, linear DNA contamination, and insufficient orthogonal validation.

Step 1: Define the biological question in measurable outputs

Instead of "map ecDNA," choose an endpoint:

• Architecture question: breakpoint/junction reconstruction, amplicon structure
• Regulatory question: enhancer activity, coactivator association, chromatin accessibility
• Evolution question: heterogeneity across cells/regions, changes under selection
• Stress response question: eccDNA shifts under environmental perturbation

This prevents scope creep and makes assay selection obvious.

For a deeper dive into sample types, controls, biological replicates, and read depth planning, see our study design guide: Designing an eccDNA sequencing study: sample types, controls, and read depth

Step 2: Enrichment strategy—optimize for your sample type, not for what's popular

A common practical mistake is treating enrichment like a one-size-fits-all step. In practice:

• Low-input samples (e.g., plasma): your main enemy is PCR duplication and background linear DNA. If library complexity is low, adding depth usually just buys you more duplicates—check complexity early before scaling sequencing.
• Solid tissue/cell lines: your enemy is fragmentation bias and incomplete linear DNA removal, which can inflate false circular calls.

Step 3: Build a validation stack that reviewers trust

For circular DNA claims, the strongest pattern is orthogonal confirmation:

1. Outward-facing junction PCR (primer design spanning the circle junction)
2. Sanger sequencing of the junction amplicon (sequence-level traceability)
3. qPCR for relative abundance across conditions or sample groups (with appropriate normalization)

Practical tip: design two independent junction primer pairs when feasible. If only one primer pair works, reviewers may suspect off-target amplification.

Step 4: Control linear DNA carryover (and document it)

Linear DNA contamination can create misleading signals. Practical controls that labs commonly use in circular DNA sequencing projects include:

• An explicit linear DNA digestion step (enzyme-based) with documentation of conditions
• A no-enzyme or "mock digest" control to estimate how much linear DNA remains
• Post-enrichment QC (e.g., qPCR targets known to be linear) to quantify carryover

Even if you don't publish every QC panel, having them available reduces rework later.

Step 5: Reduce false junctions and mapping artifacts

False junctions can arise from chimeric ligation, PCR artifacts, or repetitive regions.

Experience-based suggestions (general best practices):

• Use molecular barcodes when input is low or PCR cycles are high.
• Be most skeptical around repeat-adjacent junctions—this is where many false positives concentrate, and where an extra validation step saves the most time.
• For any "headline" circle, verify with Sanger—it's still one of the cleanest ways to show traceable evidence.

Step 6: Report results in a way that is easy to audit

When publishing or sharing internally, include:

• Clear definitions (ecDNA vs eccDNA; circle vs amplicon)
• Junction evidence summary (read support, orientation, uniqueness)
• Validation results (PCR gel + Sanger trace availability, qPCR design notes)

This improves credibility without exaggerated claims.

How CD Genomics can support ecDNA/eccDNA research

If you want to translate the above lessons into a practical project plan, CD Genomics supports research-use-only ecDNA/eccDNA workflows designed around three pillars: discovery, validation, and interpretation.

Service components commonly requested for circular DNA studies

• ecDNA/eccDNA profiling by circular DNA enrichment + sequencing (often described as Circle-seq–style workflows in the literature)
• Junction validation: outward PCR design support and optional Sanger confirmation for high-confidence circles
• qPCR quantification for relative abundance comparisons (e.g., condition A vs B; tumor vs matched non-tumor research samples)
• Bioinformatics reporting focused on actionable outputs: junction lists, annotations, candidate prioritization, and publication-ready (original) figures

What you receive (typical deliverables for RUO projects)

• Raw sequencing data (FASTQ) and processing summaries
• Circular DNA candidate tables (junction coordinates, supporting evidence, annotations)
• Prioritized candidate list with rationale (gene content, regulatory features, repeat context)
• Optional validation package results (PCR/Sanger traces, qPCR primer details)

Conclusion: what to do next after this 2025 roundup

The 2025 ecDNA/eccDNA literature strengthens a core message: circular DNA is not only a structural oddity—it can be retained, organized, and evolved in ways that reshape gene regulation and phenotype. Across cancers, the field is converging on models that combine inheritance mechanics, nuclear organization, and heterogeneity-aware evolution. Beyond cancer, eccDNA continues to emerge as a contributor to stress responses and genome plasticity.

If you're planning a circular DNA sequencing study in 2025–2026, an efficient path is usually:

1) profile → 2) validate junctions → 3) quantify → 4) test function,

while documenting artifact controls so your claims remain audit-ready.

If you upgrade one thing in your next project, make it an explicit validation plan tied to the biological question—most rework happens when validation is treated as an afterthought.

FAQ

• What is the difference between ecDNA and eccDNA?

  • In most research usage, ecDNA often refers to large extrachromosomal DNA elements frequently associated with oncogene amplification in cancer, while eccDNA is a broader term for extrachromosomal circular DNA found across many eukaryotes (including smaller circles and non-cancer contexts). Terminology can vary by field, so it's helpful to define your usage explicitly in the Methods.

• What is the best method for circular DNA enrichment before sequencing?

  • There isn't one universal "best." The best enrichment strategy depends on sample type (cells/tissue vs plasma), input amount, and your endpoint (architecture vs abundance vs regulatory profiling). In practice, controlling linear DNA carryover and documenting QC often matters as much as the enrichment chemistry itself.

• How do I validate that a candidate circle is real (not a mapping artifact)?

  • A reviewer-friendly approach is a validation stack: outward-facing junction PCR, Sanger sequencing across the junction, and (if comparing conditions) qPCR to quantify relative abundance. For high-impact claims, using two independent primer sets can further increase confidence.

• Can repeats and transposable elements be important on ecDNA, or should I filter them out?

  • Recent work suggests repeat-derived sequences can contribute functional enhancer activity in ecDNA contexts. Rather than filtering repeats early, consider flagging them and evaluating evidence (accessibility, TF motifs, functional perturbation) before discarding them.

• What are the most common experimental pitfalls in eccDNA sequencing from plasma?

  • Common pitfalls include low library complexity (PCR duplicates), linear DNA background, and over-interpreting junctions supported by few reads. Molecular barcodes, careful QC, orthogonal validation, and conservative calling thresholds help reduce false positives.