Evidence map›Paper›PMID 40500302›Full record

ArticleScientific reports2025

Monitoring the rate and variability of somatic genomic alterations using long-read sequencing.

Xingyao Chen, Hagai Ligumsky, Charlie Ambrose, Denisse Sibrian, Brian Tran, Daoud Arif, Olga Castellanos, Darren Kessner, Hanyi Luo, Mukta Ubale and 7 more

Abstract read
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In one paragraph

Article in Scientific reports, 2025. 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

17 authors.

Xingyao ChenEllison Medical Institute, Los Angeles, CA, USA.
Hagai LigumskyEllison Medical Institute, Los Angeles, CA, USA.
Charlie AmbroseEllison Medical Institute, Los Angeles, CA, USA.
Denisse SibrianEllison Medical Institute, Los Angeles, CA, USA.
Brian TranEllison Medical Institute, Los Angeles, CA, USA.
Daoud ArifEllison Medical Institute, Los Angeles, CA, USA.
Olga CastellanosEllison Medical Institute, Los Angeles, CA, USA.
Darren KessnerEllison Medical Institute, Los Angeles, CA, USA.
Hanyi LuoEllison Medical Institute, Los Angeles, CA, USA.
Mukta UbaleEllison Medical Institute, Los Angeles, CA, USA.
Abigail ColemanEllison Medical Institute, Los Angeles, CA, USA.
Vaidhyanathan MahaganapathyEllison Medical Institute, Los Angeles, CA, USA.
Thomas J JönssonEllison Medical Institute, Los Angeles, CA, USA.
Reva K BashoEllison Medical Institute, Los Angeles, CA, USA.
Jerry S H LeeEllison Medical Institute, Los Angeles, CA, USA.
Naim MatasciEllison Medical Institute, Los Angeles, CA, USA. nmatasci@emila.org.
David B AgusEllison Medical Institute, Los Angeles, CA, USA. agus@emila.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer initiation occurs when a cell acquires and accumulates mutations in genes involved in the regulation of cell processes: each cell division throughout a person's life introduces novel mutations in the cells' DNA and under normal circumstances, the body is primed to prevent those from leading to cancer. Occasionally, a subset of those mutations escapes those safeguards and might eventually result in the emergence of the disease. To understand the dynamics of accumulation of somatic mutations, we have performed longitudinal whole genome sequencing of DNA obtained from whole blood from healthy individuals and cancer patients using Oxford Nanopore Technologies' Long Read Sequencing. Here we show that the number of somatic single nucleotide variants detected increases with their age and that for specific mutational processes, changes can be detected within months. We computed aggregated metrics for unique participants at each timepoint across types of variants (based on single based substitution molecular signatures) and identified patterns of change both over an individual's lifespan (age) and over the sampling period (months). This study showcases the suitability of long read sequencing of blood DNA for detecting coarse-grained differences over time and enable future development of "state of the system" personalized prevention programs.

Indexed as

MutationNeoplasmsAdultAgedFemaleGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedPolymorphism, Single NucleotideSequence Analysis, DNAWhole Genome Sequencing

Identifiers

PMID40500302
PMCPMC12159167

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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.