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bioRxiv · 10.64898/2026.01.20.700537

SigDyn: single-cell mutational signature dynamics

Abstract

MotivationCancer is driven by mutations that confer tumor cells proliferation advantages but also vulnerabilities with therapeutic potential. Underlying tumor progression are mutational processes that imprint signatures of co-occurring mutation types in tumor cell genomes. The discovery of signatures and their etiologies offers insight into disease mechanisms and treatment opportunities, however acquisition of mutations by tumor cells over time leads to intratumor heterogeneity that may challenge treatment efficacy. Understanding which mutational processes contribute to the evolution of each tumor can reveal therapeutic strategies, but it requires single-cell mutational signature analysis, which remains unexplored. ResultsWe present SigDyn, a framework enabling analysis of tumor mutational signature dynamics at single-cell resolution. To do this, SigDyn combines variant detection, tumor phylogeny inference, and signature identification. We applied SigDyn to scRNA-seq of invasive ductal carcinoma (IDC) and laryngeal squamous cell carcinoma (LSCC). Inferred phylogenies recapitulated tumor markers and progression from normal tissue to tumor metastasis. Tumor-specific processes beyond aging, like cellular disruptions or patient treatments, were only exposed at single-cell level reinforcing the importance of granularity. For IDC, prominence of signature SBS26 with tumor evolution pointed to mismatch repair (MMR) deficiency, supported by downregulation of MMR genes. For LSCC, metastasis enrichment with SBS32-active cells and immune markers suggested influence of immunosuppressant treatment azathioprine, linked to increased risk of SCCs. The dynamics uncovered by SigDyn confirm its potential as a tool to investigate mechanisms of tumor evolution and heterogeneity. Availabilitygithub.com/joanagoncalveslab/sigdyn. Contactjoana.goncalves@tudelft.nl. Supplementary Information: included.

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BibTeXRIS

Costa, S. B., Goncalves, J. P.. 2026-01-22. SigDyn: single-cell mutational signature dynamics. https://doi.org/10.64898/2026.01.20.700537

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