Evidence map›Paper›PMID 42079039›Full record

ArticlebioRxiv : the preprint server for biology2026

Topographical archetypes of somatic mutagenesis in cancer.

Allen W Lynch, Sangmi Sandra Lee, Jan P Hummel, Benedikt Geiger, Michael S Lawrence, Hu Jin, Doga C Gulhan, Peter J Park

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

8 authors.

Allen W LynchDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-0796-3232
Sangmi Sandra LeeDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Jan P HummelDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Benedikt GeigerDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-1854-3428
Michael S LawrenceKrantz Family Center for Cancer Research, Mass General Brigham, Boston, MA, USA.
Hu JinDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Doga C GulhanKrantz Family Center for Cancer Research, Mass General Brigham, Boston, MA, USA.ORCID 0000-0001-5419-0549
Peter J ParkDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-9378-960X

Funding

Development and Application of Computational Methods for Single Cell DNA Sequencing DataR01HG012573 · NHGRI · HARVARD MEDICAL SCHOOL · PI PARK, PETER J · 2022 to 2025
$2.7M
Mutational signature analysis: methods and applications to the clinicR01CA269805 · NCI · HARVARD MEDICAL SCHOOL · PI Peter J Park · 2022 to 2026
$2.2M
NCI NIH HHS R01 CA269805NHGRI NIH HHS R01 HG012573
6 · The paper itself

Abstract

The genome of every cancer cell carries a record of the mutational processes that have acted throughout its history. Mutational signature analysis, which infers the activity of mutagenic processes from their characteristic base-change patterns, has become an indispensable tool for interpreting somatic mutations. However, this framework captures only which types of mutations a process generates and not where in the genome they occur - a distribution influenced by replication timing, chromatin organization, transcription, DNA secondary structure, and other genomic features. Here, we present a generative probabilistic framework (MuTopia) that jointly infers mutational spectra and their genome-wide topography as nonlinear functions of genomic and epigenomic state. Applied to whole-genome sequencing data from 15 tumor types, MuTopia reveals that mutational processes fall into eight conserved topographic archetypes, or topotypes, shaped primarily by replication timing and chromatin state. Diverse mutational processes converge upon this limited repertoire, indicating that the genomic distribution of mutagenesis is constrained less by the source of damage than by how that damage is processed. Individual mutational processes exhibit state-dependent variation in their genomic distributions: the same signature can adopt distinct topotypes depending on repair proficiency and replication stress. For instance, SBS8 shifts from a canonical late-replicating profile in homologous recombination-proficient tumors to an early-replicating, stress-associated topotype in HR-deficient tumors, and replication stress similarly reshapes the genomic distribution of APOBEC editing. Topotypes, therefore, provide a classification of mutagenesis distinct from spectral signatures, capturing aspects of tumor biology that spectra alone cannot resolve.

Identifiers

PMID42079039
PMCPMC13131822

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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.