Evidence map›Paper›PMID 42681298›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Computational Spatial Modeling of Extrachromosomal DNA to Decipher Cancer Evolution.

Magnus Haughey, Imran Noorani

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Magnus HaugheyEvolutionary Dynamics Group, Centre for Cancer Evolution, Barts Cancer Institute, Queen Mary University of London, London, UK. m.j.haughey@qmul.ac.uk.
Imran NooraniInstitute of Neurology, University College London, London, UK. imran.noorani@cantab.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging techniques such as DNA fluorescent in situ hybridization (FISH) and nascent RNAscope enable detection and quantification of extrachromosomal DNA (ecDNA) in tumor cells. Here, we describe a workflow of ecDNA detection and spatial characterization using DNA FISH, and integration of these data with a spatial evolutionary model to estimate past evolution in individual patients' tumors, such as brain cancers. This analysis leverages the spatial patterns of ecDNA measured across multiple spatial regions of a solid tumor to predict the competitive advantage conferred by oncogenic ecDNA to their host tumor cell, and the number of these ecDNAs present around the time of the beginning of clonal expansion of the tumor, informing us on the origins of cancer.

Indexed as

Extrachromosomal DNANeoplasmsComputer SimulationHumansIn Situ Hybridization, FluorescenceExtrachromosomal DNAEvolutionary modelingExtrachromosomal DNAFluorescent in situ hybridizationMulti-region sampling

Identifiers

PMID42681298

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.