ArticleGenome medicine2026
Preservation and clonal behavior of extrachromosomal DNA in patient-derived xenograft models of childhood cancers.
Article in Genome medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Extrachromosomal DNA as a platform for epigenetic reprogramming in cancer.Molecular cancer · 2026Review
Corrections and comments
- Update of
Authors and funding
13 authors.
Funding
Abstract
backgroundExtrachromosomal DNA (ecDNA) is a structural variant linked to poor prognosis in pediatric cancers. Patient-derived xenograft (PDX) models are crucial tools for cancer research, as they are believed to recapitulate the molecular features and intratumoral heterogeneity in patient tumors. However, ecDNA demonstrates unique evolutionary dynamics under selective pressure, and its behavior during PDX development remains largely uncharacterized. This study investigates the fidelity of PDX models in representing ecDNA from primary tumors. By analyzing ecDNA sequence composition and copy number conservation across pediatric solid cancers, we assess how well PDX models recapitulate the ecDNA landscape observed in human tumors.
methodsAmpliconArchitect was used to analyze whole-genome sequencing (WGS) of 338 PDX models and 127 corresponding primary tumors. ecDNA status, sequence, copy number, and associated genes were compared between PDX models and their matched human tumors. Additionally, multiome RNA and ATAC single-cell sequencing of a PDX tumor enabled comparison of ecDNA intratumoral heterogeneity relative to similar data from the primary tumor.
resultsecDNA in PDX models largely recapitulated oncogene amplifications observed in human tumors, with MYCN being the most frequently amplified. ecDNA status remained unchanged for a majority of the PDX models (105/127, 83%) compared to primary tumors, with 20% of previously ecDNA-negative cases acquiring ecDNA during PDX development. Consequently, ecDNA was more prevalent in the PDX models than in their corresponding human tumors (McNemar's test, p = 0.00086). Detailed examination of ecDNA sequences in tumor-PDX pairs showed substantial conservation (67% with > 90% sequence overlap) but variable breakpoint concordance. Single-cell analysis demonstrated that rare ecDNA-positive cells from the primary tumor preferentially drive PDX tumor development.
conclusionThis study highlights the prevalence, oncogenic content, and conservation of ecDNA in PDX models relative to pediatric patient tumors. We observed that ecDNA frequently recapitulates oncogene amplifications found in human cancers, is generally preserved during PDX establishment, and reflects subtype-specific patterns across tumor types. These findings support the utility of PDX models in studying ecDNA biology in pediatric cancer progression and therapy. Longitudinal sampling during PDX tumor growth and under therapeutic pressure could provide insights into molecular evolution, clonal selection, and ecDNA-driven therapy resistance.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.