Evidence map›Paper›PMID 41256703›Full record

ArticlebioRxiv : the preprint server for biology2025

Segregating DNA lesions point to high selective advantage of tumor initiating cells.

Vladimir Seplyarskiy, Maha Shady, Maria A Andrianova, Michael Spencer Chapman, Eliezer M Van Allen, Shamil R Sunyaev

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

6 authors.

Vladimir SeplyarskiyDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Maha ShadyDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Maria A AndrianovaInstitute for Research in Biomedicine, The Barcelona Institute of Science and Technology, Barcelona, Spain.
Michael Spencer ChapmanBarts Cancer Institute, Queen Mary University of London, London, UK.
Eliezer M Van AllenBroad Institute of Harvard and MIT, Cambridge, MA, USA.ORCID 0000-0002-0201-4444
Shamil R SunyaevDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Funding

The origin, the function and the phenotypic impact of human allelesR35GM127131 · NIGMS · HARVARD MEDICAL SCHOOL · PI SHAMIL SUNYAEV · 2018 to 2026
$8.1M
Predicting the impact of genetic variants, genes and pathways on human DiseaseU01HG012009 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ALKES L PRICE, Soumya Raychaudhuri · 2021 to 2026
$4.2M
NHGRI NIH HHS U01 HG012009NIGMS NIH HHS R35 GM127131
6 · The paper itself

Abstract

The complications with identifying cells at the origin of cancer and tracking their early divisions impede studies of cancer initiation. Recently, it was shown that some DNA lesions generated by a pulse of damage-inducing mutagen persist over multiple rounds of replication. Segregation of DNA lesions in the early genealogy of an expanding clone leaves a statistically interpretable footprint of cancer initiating events. Specifically, it allows for estimating the number of cell divisions between the initiating DNA lesion and the most recent common ancestor of the tumor. Here, we analyze footprints of segregating lesions from a previously published experimental mouse system, as well as post-chemotherapy human metastatic tumors and the blood of chemotherapy treated patients. In all contexts, clones tend to start early, usually within the span of 4 cell generations from mutagen exposure. Using a branching process model, we show that fitness advantage of early cancer drivers exceeds 30%, with each early division leading to at least 1.3 self-renewing cells. We highlight an example of a blood-derived single cell phylogeny with major subclones separated by just two cell divisions. Broadly, our approach allows inference of tumor initiation and growth parameters based on events preceding the most recent common ancestor of the initiating clone as opposed to characteristics of fully grown tumors.

Identifiers

PMID41256703
PMCPMC12621763

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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.