Clonal hematopoiesis (CH) results from the acquisition and expansion of somatic mutations in hematopoietic stem and progenitor cells and is associated with age-related clinical sequelae, including an increased risk for cardiovascular disease, myeloid neoplasms and complications related to cancer therapy. Chemotherapy and radiation can accelerate CH expansion and further elevate the risk of adverse events, including cardiotoxicity and therapy-related myeloid neoplasms. Although CH is increasingly recognized as a clinically relevant precursor state and predictive biomarker, the long-term dynamics of CH expansion in humans remain poorly understood. Longitudinal data are often collected but not integrated with mathematical prediction. Mathematical modeling is essential for characterizing CH evolution, estimating clone fitness, inferring stem cell pool dynamics and enabling patient-level predictions. This study summarizes the current evidence on CH dynamics in humans, compares mathematical models used to predict CH progression, assesses the validity of model assumptions and discusses the implications for clinical management of individuals with these precursor conditions.

Abstract Somatic mutations may drive adaptation and aging across diverse life forms, yet their role remains poorly understood in many early-branching animals. Here, we compare somatic mutation accumulation in the robust coral Orbicella faveolata with previous findings in the complex coral Acropora palmata . Whole-genome sequencing revealed high fixation of somatic genetic variants in O. faveolata , particularly in older, interior regions of colonies—contrasting with A. palmata . These patterns suggest distinct cell population dynamics between clades, indicating a segregated, mammal-like germline in O. faveolata , whereas such a germline remains undetected in A. palmata . This underscores the diversity of somatic evolutionary mechanisms across scleractinian corals.

Clonal hematopoiesis (CH)-the expansion of genetic variants in blood-is a prime example of somatic evolution. Although it often precedes malignant transformation, many aspects of this process remain unknown. We show that a model of polyclonal competition, in which selectively advantaged clones continually occur and compete, explains observed CH dynamics throughout human life. We quantify the fitness distribution and occurrence rate of clonal expansions using either variant trajectories or hematopoietic stem cell (HSC) genetic heterogeneity. Inferences on both data converge. Approximately 3 fit clones enter the HSC pool per year, yet rarely more than 5 achieve >1.5% frequency throughout life. The fittest clones emerge predominantly later in life in accordance with a multistep evolutionary process. DNMT3A variants were enriched for single-hit clones, whereas TET2, ASXL1, JAK2, SF3B1, and SRSF2 showed enrichment for multihit evolution. These findings suggest that precursors of hematologic malignancies are identifiable prior to transformation and may facilitate early intervention strategies. SIGNIFICANCE:We study the evolution of CH through longitudinal variant trajectories and HSC genetic heterogeneity. Clonal interference and a multistep evolutionary process become evident. Clones further advanced on the path to malignant transformation are identifiable, and propensities for multiple hits differ among most commonly mutated CH variants.

Extrachromosomal DNA (ecDNA) is common in human cancers and is associated with poor clinical outcomes, yet how ecDNA-driven genetic heterogeneity is translated into functional heterogeneity remains unclear. Using single-cell multiomics sequencing and multiplexed IF-FISH, we show that asymmetric inheritance of ecDNA generates copy number heterogeneity that propagates to gene expression programs, including oncogenic signaling and cellular stress responses. Transgenerational live-cell lineage tracking directly shows that ecDNA heterogeneity arises within only a few cell divisions and modulates daughter cell division timing in a copy number-dependent manner, a property not observed for evenly inherited chromosomal amplicons. We identify an optimal middle ecDNA copy number range that maximizes proliferative fitness at baseline, while drug selection pressure induced by low-dose CHK1 inhibition selects for cells with a new optimal range at low ecDNA copy numbers. These low ecDNA copy number cells pre-exist in the population and can be generated de novo, driving copy number shifts promoting drug resistance. In vivo experiments further demonstrate that shifts toward ecDNA copy numbers that are optimal under the tumour microenvironment enhance tumourigenicity. Together, these findings establish ecDNA copy number plasticity as a central driver of tumour evolution.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is projected to become the second leading cause of cancer-related death within the next decade. Population-scale genomic analyses of PDAC tumors have revealed extensive chromosomal instability (CIN), indicating high levels of genomic diversification that may influence therapy response. However, the mechanisms driving CIN during PDAC progression and its role in treatment response remain poorly understood. We hypothesize that specific patterns of genomic rearrangements emerging during PDAC evolution can inform two key aspects of tumor biology: (i) the underlying processes driving CIN, which may be therapeutically targetable, and (ii) subclonal CIN signatures that predispose tumors to develop chemoresistance. To investigate the dynamics of CIN and chemoresistance, we employed an in-house single-cell clonal outgrowth assay integrated with single-cell whole-genome sequencing (sc-WGS) and mathematical modelling of clonal growth. Experiments were performed in PDX-derived primary cultures and patient-derived 3D organoids. We tracked clonal outgrowth under both untreated conditions and following exposure to chemotherapeutic agents relevant to PDAC treatment. Comparative analyses of single-cell copy number profiles between parental populations and drug-exposed clones allow us to identify any de novo genomic alterations acquired during treatment, as well as pre-existing events enriched by drug selection. We observed ongoing CIN in PDAC cells, leading to continuous generation of new CNAs and enhanced cell-to-cell genomic diversity. Our data demonstrate pronounced heterogeneity in copy number states and growth dynamics among individual clones from the same cell line. This intrinsic heterogeneity provides a reservoir for evolutionary selection and may promote the emergence of drug-resistant phenotypes. We were able to analyse which clones carried pre-existing alterations and/or which generated new ones under the pressure of chemotherapy, allowing us to understand the diversity of responses and general principles of CNA changes in response to therapy. These findings underscore the innate adaptability of PDAC cells under therapeutic pressure. Our study highlights the dynamic nature of CIN in PDAC and its critical role in promoting chemoresistance. The identification of specific genomic alterations enriched in resistant subclones could offer potential biomarkers predictive of therapy response. This approach provides new insights into the interplay between CIN, cell-to-cell heterogeneity, and therapeutic adaptation, with potential future implications for guiding personalized treatment strategies in PDAC. Audrey Lumeau, Molly Anne. Guscott, Nathaniel Mon Pere, Isabel Nichols, Benjamin Werner, Nelson Dusetti, Sarah E. McClelland. Tracking genome evolution and chemoresistance in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B129.

Somatic genetic variation (SOGV), accumulating during an organism’s lifetime, was traditionally viewed as detrimental rather than adaptive due to links with cancer and senescence. However, in modular organisms like corals, deleterious mutations can be purged at the cellular or polyp level, while adaptive mutations may rise in frequency as polyps create genetically distinct modules. Quantifying the somatic genetic landscape in corals is necessary to understand the role these mutations may have in coral and clonal animal development and evolution. Here, we catalog somatic genetic variation in eight Acropora palmata colonies from Curaçao. Whole genomes were sequenced (70-100x depth), documenting mutation variant allele frequency shifts as genets aged. Large numbers of SOGVs were observed in six- to ten-year-old colonies, and inferred mutation rates were used to age a genet of uncertain age to almost a century old. Although mutations were not fixed at the polyp or branch levels, i.e. they always displayed frequencies <0.5 as expected at mutating homozygous sites, their allele frequencies followed a power-law distribution, similar to aging human tissues. No signs of positive selection were found; instead SOGVs in the colony of uncertain age were under purifying selection. In one colony, mutations in 28 samples from along a branch were analyzed using a SNP microarray. Contrary to expectations, genetic and physical distances were unrelated. This observation together with the observed lack of fixation may be explained by a large stem cell population, the de-differentiation or dormancy of stem cells, the contribution of strong purifying selection, or a combination of the previously mentioned. Our findings provide a neutral framework against which to test for module-level selection of genetic variation in corals, explore the relationship between physical and genetic distance within a colony, and apply a somatic genetic clock to colonies of Acropora palmata. This work provides necessary fundamental insights into the landscape of somatic mutations in reef-building coral, highlighting the importance of studying these mutations as they may contribute to genetic diversity and adaptability in colonial animals. ### Competing Interest Statement The authors have declared no competing interest.

Supplementary Figure S4 provides computational and experimental models of ecDNA-dependent treatment responses in neuroblastoma

Supplementary Figure S2 shows simulation results of clonogenic assays under copy number-dependent and -independent cell fitness

Supplementary Table S1 contains FISH proteomics datasets

Simulating multi-ecDNA dynamics in vivo.A, DNA FISH and nascent RNAscope images from the tumor of patient A5, showing the coexistence of both EGFR-ecDNA and PDGFRA-ecDNA. B, Circular structures of three distinct oncogenic ecDNAs detected in the tumor of patient A5. C, GBMs in the GB-UK and PCAWG cohorts containing more than one oncogenic species and their respective copy numbers. D, In a multiple-ecDNA application of SPECIES, the clone-initiating cell begins with k1 and k2 copies of ecDNA 1 and ecDNA 2, respectively. E, Representation of the impacts of ecDNA cosegregation and coselection on the number of inherited ecDNA copies during cell division. Cosegregation drives correlated inheritance of both ecDNA types, whereas coselection favors tumor cells carrying at least one copy of each type. F, Application of SPECIES to simulate two separate ecDNA species. Simulated tumors were initialized with a single cell, carrying k1 and k2 copies of each ecDNA species. Representative model images show examples of low and high cosegregation and coselection. G and H, Parameter inference summary for the tumor of patient A5, for which we measured both the EGFR-ecDNA and PDGFRA-ecDNA copy-number distributions using DNA FISH, using multiple-ecDNA SPECIES. Parameters sp and sm represent selection coefficients for tumor cells with 1 (pure) or 2 (mixed) ecDNA species, respectively. I, Comparison of inferred k and k1 values for all patient tumors confirmed by WGS to harbor two or more ecDNA species. J, The presence of ecDNA amplifications may be used to aid stratification, given that oncogenes on ecDNA have an inherent resistance mechanism through the ability of ecDNA to dynamically adjust copy number in response to targeted agents. Earlier monitoring and intervention are recommended for those patient tumors with ecDNA that will receive targeted therapies.

Supplementary Figure S1 characterises the MYCN amplification status, copy number heterogeneity and growth behaviour in neuroblastoma samples

Cancers are complex, diverse, and elusive, with extrachromosomal DNA (ecDNA) recently emerging as a crucial player in driving the evolution of about 20% of all tumors. In this review we discuss open questions concerning the evolutionary role of ecDNA in tumor development, including tumorigenesis and metastatic seeding, the mutational landscape on ecDNA, the dynamic ecDNA genotype-phenotype map, the structural evolution of ecDNA, and how knowledge of tissue-specific ecDNA evolutionary paths can be leveraged to deliver more effective clinical treatment. Looking forward, evolutionary theoretical modeling will be instrumental in advancing new research in the field, and we explore how modeling has contributed to our understanding of the evolutionary principles governing ecDNA dynamics. Ultimately, these challenges must be tackled to improve clinical stratification and create tumor- and patient-specific ecDNA-based therapies.

Oncogenes amplified on extrachromosomal DNA (ecDNA) contribute to treatment resistance and poor survival across cancers. Currently, the spatiotemporal evolution of ecDNA remains poorly understood. In this study, we integrate computational modeling with samples from 94 treatment-naive human glioblastomas (GBM) to investigate the spatiotemporal evolution of ecDNA. We observe oncogene-specific patterns of ecDNA spatial heterogeneity, emerging from random ecDNA segregation and differing fitness advantages. Unlike PDGFRA-ecDNAs, EGFR-ecDNAs often accumulate prior to clonal expansions, conferring strong fitness advantages and reaching high abundances. In corroboration, we observe pretumor ecDNA accumulation in vivo in genetically engineered mouse neural stem cells. Variant and wild-type EGFR-ecDNAs often coexist in GBM. Those variant EGFR-ecDNAs, most commonly EGFRvIII-ecDNA, always derive from preexisting wild-type EGFR-ecDNAs, occur early, and reach high abundance. Our results suggest that the ecDNA oncogenic makeup determines unique evolutionary trajectories. New concepts such as ecDNA clonality and heteroplasmy require a refined evolutionary interpretation of genomic data in a large subset of GBMs. SIGNIFICANCE:We study spatial patterns of ecDNA-amplified oncogenes and their evolutionary properties in human GBM, revealing an ecDNA landscape and ecDNA oncogene-specific evolutionary histories. ecDNA accumulation can precede clonal expansion, facilitating the emergence of EGFR oncogenic variants, reframing our interpretation of genomic data in a large subset of GBMs. See related commentary by Korsah et al., p. 1979.

Supplementary Figure S8 illustrates how one-two punch, senolytic therapies can be used to target tumor cells with low MYCN copy numbers

Extrachromosomal DNA (ecDNA) has emerged as a key driver of oncogene amplification and a major contributor to rapid intra-tumour heterogeneity, thereby promoting tumour progression and therapeutic resistance. This heterogeneity arises from pronounced cell-to-cell variability in ecDNA copy number, enabling complex ecDNA amplicon compositions within individual tumour cells. Approximately one-third of ecDNA-positive tumours harbour multiple co-selected ecDNA species. However, the mechanisms governing the heterogeneity and persistence of ecDNA variants - beyond the presence of distinct ecDNA species - remain less well understood. In particular, little is known about the maintenance of genetic or phenotypic diversity within a single ecDNA species. Here, we develop computational models to investigate the dynamics that enable the stable maintenance of tumour cells carrying multiple ecDNA variants ("mixed cells"). We explore how variant switching contributes to the persistence of ecDNA diversity under varying fitness regimes. Our results demonstrate that both a positive fitness of ecDNA+ cells and variant switching are required to maintain mixed cell subpopulations, whereas direct co-selection of mixed cells is not necessary. Notably, the fraction of mixed cells peaks at intermediate switching rates across fitness landscapes, a pattern reflected in subpopulation structures, transition probabilities between pure and mixed ecDNA states, and single-cell Shannon diversity indices.

Supplementary Methods, providing details about methodology used throughout the study.

Extrachromosomal DNA (ecDNA) is a common source of oncogene amplification across many types of cancer. The non-Mendelian inheritance of ecDNA contributes to heterogeneous tumour genomes that rapidly evolve to resist treatment. Here, using single-cell and live-cell imaging, single-micronucleus sequencing, and computational modelling, we demonstrate that elevated levels of ecDNA predisposes cells to micronucleation. Damage on ecDNA, commonly arising from replication stress, detaches ecDNA from the chromosomes upon which they hitchhike during cell division, thereby causing micronucleus formation in daughter cells. Clusters of oncogene-containing, CIP2A-TOPBP1-associated ecDNA molecules form, and asymmetrically segregate into daughter cell micronuclei during cell division. ecDNA chromatin remains highly active during mitosis, but upon micronucleation, it undergoes suppressive chromatin remodeling, largely ceasing oncogene transcription. These studies provide insight into the fate of damaged ecDNA during cell division.

Supplementary Table S4 contains information about the MYCN status of neuroblastoma patient samples used in Figure 1 and Supplementary Figure 1

Extrachromosomal DNA (ecDNA) amplification enhances intercellular oncogene dosage variability and accelerates tumor evolution by violating foundational principles of genetic inheritance through its asymmetric mitotic segregation. Spotlighting high-risk neuroblastoma, we demonstrate how ecDNA amplification undermines the clinical efficacy of current therapies in cancers with extrachromosomal MYCN amplification. Integrating theoretical models of oncogene copy number-dependent fitness with single-cell ecDNA quantification and phenotype analyses, we reveal that ecDNA copy-number heterogeneity drives phenotypic diversity and determines treatment sensitivity through mechanisms unattainable by chromosomal oncogene amplification. We demonstrate that ecDNA copy number directly influences cell fate decisions in cancer cell lines, patient-derived xenografts, and primary neuroblastomas, illustrating how extrachromosomal oncogene dosage-driven phenotypic diversity offers a strong evolutionary advantage under therapeutic pressure. Furthermore, we identify senescent cells with reduced ecDNA copy numbers as a source of treatment resistance in neuroblastomas and outline a strategy for their targeted elimination to improve the treatment of MYCN-amplified cancers. SIGNIFICANCE:ecDNA-driven tumor genome evolution provides a major challenge to curative cancer therapies. We demonstrate that ecDNA copy-number dynamics drives treatment resistance by promoting oncogene dosage-dependent phenotypic heterogeneity in MYCN-amplified cancers. Exploiting phenotype-specific vulnerabilities of ecDNA cells, therefore, presents a powerful strategy to overcome treatment resistance. See related commentary by Korsah, p. 1979.

ecDNA accumulation in genetically engineered in vivo and ex vivo murine models. A, Neural stem cells were propagated within the SVZ of genetically engineered mice for 4 months. B,Myc-ecDNAs were induced in adult murine neural stem cells, which were then cultured ex vivo for 5 weeks. C, DNA FISH analysis of neural stem cells within the SVZ of genetically engineered mice (i) without Myc-ecDNA (Myc+/+; P53fl/fl; Nestin-Cre, n = 2) and (ii) with Myc-ecDNA (Mycec/+; p53fl/fl; Nestin-Cre, n = 2), both on a background of homozygous Trp53 loss. D, ecDNA copy-number dynamics in murine adult neural stem cells (data from ref. 33) with corresponding simulated dynamics, assuming either neutral or positively selected ecDNA. (A and B, created using BioRender assets. https://BioRender.com/a1hpt9n.)