Evidence map›Paper›PMID 42706270›Full record

ArticleNature communications2026

scAmp enables focal gene amplification analysis from single-cell data.

Matthew G Jones, Natasha E Weiser, King L Hung, Xiaowei Yan, Sangya Agarwal, Jens Luebeck, Aditi Gnanasekar, Shu Zhang, Ivy Tsz-Lo Wong, Jun Tang and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 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

20 authors.

Matthew G Jones *Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-0363-4493
Natasha E Weiser *Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9971-2961
King L HungCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-3662-4662
Xiaowei YanCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-4846-8812
Sangya AgarwalCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
Jens LuebeckDepartment of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0003-4391-979X
Aditi GnanasekarDepartment of Pathology, Stanford University, Stanford, CA, USA.
Shu ZhangCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
Ivy Tsz-Lo WongDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-9761-3422
Jun TangDepartment of Pathology, Stanford University, Stanford, CA, USA.
Brooke E HowittDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-0309-6680
Ellis J CurtisDepartment of Pathology, Stanford University, Stanford, CA, USA.
Kevin YuKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0009-0002-1164-1252
John C RoseCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1810-4337
Katerina KraftCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
Valeh Valiollah Pour AmiriDepartment of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.
Leena SatpathyCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
Vineet BafnaDepartment of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-5810-6241
Paul S MischelDepartment of Pathology, Stanford University, Stanford, CA, USA. pmischel@stanford.edu.ORCID http://orcid.org/0000-0002-4560-2211
Howard Y ChangCenter for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA. howchang@stanford.edu.ORCID http://orcid.org/0000-0002-9459-4393

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oncogene amplification on extrachromosomal DNA is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While bulk whole genome sequencing studies have revealed the landscape of genes amplified on extrachromosomal DNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of extrachromosomal DNA on tumors. To address this, we introduce scAmp: a probabilistic algorithm for detecting and analyzing extrachromosomal DNA from single-cell datasets. Using well-characterized cell lines, we demonstrate that scAmp has improved specificity over bulk genome sequencing in predicting extrachromosomal DNA status and can resolve the status of chromosomal amplifications that were historically extrachromosomal. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell assay for transposase-accessible chromatin by sequencing, where we characterize the subclonal evolution of subclones with extrachromosomal DNA and identify the effect of these amplifications on the chromatin accessibility landscape of cancer cells. Finally, we provide proof-of-concept analyses that scAmp aids in the detection of extrachromosomal DNA from clinical histopathology assays. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how extrachromosomal DNAs affect cancer cells and the tumors in which they reside.

Indexed as

AlgorithmsGene AmplificationNeoplasmsSingle-Cell AnalysisCell Line, TumorChromatinExtrachromosomal DNAHumansChromatinExtrachromosomal DNA

Identifiers

PMID42706270
PMCPMC13550473

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.