The study enrolled 41 children and adolescents—20 males and 21 females—each of whom presented with a vascular malformation, clinically appreciable overgrowth of a body region beyond the vascular lesion itself, and a confirmed pathogenic or likely pathogenic variant in genes of the PI3K/AKT/mTOR pathway or related vascular signaling pathways, with PIK3CA deliberately excluded. The mean age at first clinical assessment was 9.0 years, while the mean age at molecular diagnosis was 12.1 years, a gap that underscores how long these conditions can evade a definitive label. Participants were recruited from the Regina Margherita Children’s Hospital in Turin, the Fondazione Policlinico Universitario Agostino Gemelli and the Bambino Gesù Children’s Hospital in Rome, the Santa Maria della Misericordia Hospital in Udine, and the San Bortolo Hospital in Vicenza, with genetic analysis performed in Bari.

The molecular results reveal a landscape far more diverse than the PIK3CA-centric literature might suggest. Variants in TEK, a gene encoding the TIE2 receptor tyrosine kinase that governs venous endothelial cell survival, were the most common, found in 24.4 percent of patients. GNAQ and GNA11, two closely related G-protein genes recurrently implicated in capillary malformations and Sturge-Weber syndrome, each accounted for 21.9 percent. PTEN variants, which define the PTEN hamartoma tumor syndrome spectrum, were present in 14.6 percent, RASA1 in 12.2 percent, and single patients carried variants in AKT3 and EPHB4. Critically, 65.9 percent of the identified variants were somatic—acquired after fertilization and present only in a mosaic fraction of cells—while 34.1 percent were germline, inherited or present in every cell of the body.

Detecting these variants demanded sequencing strategies far beyond conventional diagnostic testing. The team used next-generation sequencing with a targeted 17-gene panel at a read depth exceeding 2,000 reads per base, a level of coverage that allows detection of mosaic variants present at allele fractions as low as roughly 5 percent or below. Samples were drawn from peripheral blood in 12 patients, buccal swabs in 2, and—most importantly—biopsies of affected tissue in 27. This tissue-first strategy proved decisive: somatic variants identified in lesions were absent from blood DNA in every case, confirming that blood-based testing alone would have missed nearly two-thirds of the molecular diagnoses. Conversely, in several patients whose segmental, apparently sporadic presentations strongly suggested mosaicism, germline variants were ultimately identified, a discordance the authors emphasize as a warning against inferring mutational origin from clinical pattern alone.

The phenotypic data are equally revealing. Soft tissue or muscular overgrowth was documented in 60.9 percent of patients, skeletal anomalies in 46.3 percent, and macrocrania in 19.5 percent, the latter concentrated among children with PTEN variants. Adipose overgrowth appeared in a smaller subset, and internal organ involvement in just three individuals, including one child with a germline TEK variant whose colon harbored extensive vascular malformations and two patients with GNA11 or AKT3 variants who exhibited hemimegalencephaly, a dysplastic overgrowth of one cerebral hemisphere. Perhaps most strikingly, a minority of patients displayed segmental undergrowth rather than overgrowth: in one TEK patient, serpiginous vascular overgrowth coexisted with limb hypoplasia and muscle atrophy, and a GNA11 patient with cutis marmorata telangiectatica congenita showed mild hypoplasia of the affected limb. The authors interpret these cases as evidence that disturbed vascular hemodynamics—venous hypertension, microvascular shunting, chronic hypoperfusion—can impair normal tissue development, meaning the same underlying biology can push growth in opposite directions depending on timing, location, and severity.

Genotype-phenotype correlations, however, proved frustratingly loose. A syndromic diagnosis could be assigned on clinical grounds alone in 63.4 percent of patients, but the same clinical entities mapped onto multiple genes and vice versa. GNAQ and GNA11 variants surfaced in patients labeled with Klippel-Trenaunay syndrome, diffuse capillary malformation with overgrowth, Sturge-Weber syndrome, phakomatosis pigmentokeratotica, and in several cases that fit no defined syndrome at all. TEK variants spanned Klippel-Trenaunay syndrome, blue rubber bleb nevus syndrome, and unclassifiable presentations, while RASA1 variants appeared in Parkes-Weber syndrome and beyond. Even within a single gene, severity varied enormously. The authors argue that this overlap renders phenotype-based classification unreliable and advocate a shift toward molecularly driven frameworks, in which the gene and pathway—rather than the eponym—anchor the diagnosis.

The study also probes what overgrowth actually means. Regional enlargement in these patients may reflect true mesenchymal proliferation, but it can equally represent apparent enlargement driven by venous ectasia, increased regional perfusion, or secondary deformation of neighboring structures. Macrocrania in PTEN-related disease, for instance, likely reflects hamartomatous dysplasia rather than vascular-mediated expansion, and hemimegalencephaly in GNA11 and AKT3 patients represents cortical dysplasia rather than classical somatic overgrowth. These distinctions matter clinically, because they influence how imaging findings are interpreted, how cohorts are compared across studies, and ultimately how therapeutic decisions are made. The authors acknowledge that their inclusive definition—accepting both true and apparent overgrowth—broadens the cohort but also blurs a boundary that current imaging techniques cannot reliably draw.

The clinical burden documented in the cohort was substantial and, notably, not strictly proportional to lesion size. Nearly 44 percent of patients reported functional limitations ranging from fatigue and impaired high-demand physical activity to gait abnormalities, pain episodes, and visual deficits. Four patients experienced significant hemostatic or thrombotic complications, including one GNA11 patient who suffered cerebral ischemia with subsequent epilepsy and hemiparesis, and several TEK patients with recurrent intralesional thrombosis and phlebolithiasis. Psychosocial impact was formally recorded in only one patient, but the authors suspect this dramatically underestimates the true toll of disfiguring lesions, which families often underreport to clinicians. The findings argue for multidisciplinary assessment that encompasses functional and psychological dimensions alongside anatomical characterization, and for structured transition pathways as patients move into adult care.

Treatment data carry perhaps the most consequential message. Surgery was frequently non-curative, with relapse of overgrowth in nearly every treated region. Sirolimus, an mTOR inhibitor often used off-label in vascular anomalies, showed limited or absent benefit and was discontinued in all four patients who received it, in one case because of severe recurrent infections. Yet alpelisib, a selective PI3K inhibitor developed for PIK3CA-driven disease, produced clinical and volumetric improvement in a subset of TEK-variant patients despite the absence of any PIK3CA mutation. This unexpected efficacy supports the concept of convergent downstream pathway activation: distinct upstream genetic lesions—whether in TEK, GNAQ, or PIK3CA—may funnel into shared PI3K/AKT/mTOR signaling, creating a biological rationale for pathway-targeted therapies that extends beyond the classical PROS population. One TEK patient also responded favorably to propranolol, though the authors caution that this single observation remains anecdotal, since propranolol’s established use is confined to infantile hemangiomas.

The study’s limitations are acknowledged candidly: its retrospective design, the selection bias inherent in requiring an identifiable pathogenic variant, and the absence of standardized quality-of-life measures that likely understated disease burden. Even so, the implications are clear. For children with vascular malformations and overgrowth who test negative for PIK3CA, the diagnostic journey should not end; broad gene panels, deep sequencing of affected tissue whenever feasible, and systematic parental testing offer the best route to a molecular diagnosis. And as targeted therapies mature, the gene a child carries—not the name of a syndrome—may determine whether an effective drug exists. This cohort of 41 patients makes a compelling case that the era of molecularly driven classification for vascular overgrowth disorders has arrived, and that the patients it will benefit most are precisely those the old system left unclassified.

Subject of Research: Genetic and clinical characterization of non-PIK3CA vascular malformations with overgrowth in children

Article Title: Clinical and molecular characterization of non-PIK3CA-related vascular malformations with overgrowth in a pediatric cohort

Article References: Reynolds, G., Luca, M., Coppo, P., La Selva, R., Leoni, C., Bellani, I., Ragusa, S., Massuras, S., Perrelli, S., Martino, S., Buonuomo, P. S., Rondot, F., Spinelli, A. M., Morando, C., Piglionica, M., Resta, N., & Mussa, A. (2026). Clinical and molecular characterization of non-PIK3CA-related vascular malformations with overgrowth in a pediatric cohort. World Journal of Pediatrics. https://doi.org/10.1007/s12519-026-01098-3

Image Credits: AI Generated

DOI: 10.1007/s12519-026-01098-3

Keywords: vascular malformations, overgrowth, PIK3CA, TEK, GNAQ, GNA11, PTEN, RASA1, somatic mosaicism, next-generation sequencing, alpelisib, sirolimus

Unlike germline variants, which are inherited in every cell, somatic variants arise post-zygotically and are unevenly distributed across brain regions, cell types and even individual neurons. This patchwork enables focal biological effects that can scale up to network-level dysfunction. Because each variant is private to a lineage or even a single cell, its influence depends critically on when during development it arose. Early embryonic events can generate broad regional clones and severe malformations, whereas variants arising later are confined to smaller populations of cells, producing more restricted lesions.

The developmental logic is now well illustrated in epilepsy. Somatic mutations activating the PI3K-AKT3-mTOR pathway cause hemimegalencephaly and focal cortical dysplasia, while mutations in genes such as SLC35A2 and components of the Ras-MAPK pathway underlie drug-resistant focal epilepsies. Recent cell-type-resolved studies have shown that clonal dynamics and cell-type-specific selective pressures shape mosaic architecture in the human forebrain, with lineage-tracing experiments revealing how neocortical clones distribute across lobes and hemispheres. Developmental timing, in other words, writes an anatomical map into the genome itself.

Ageing adds a second layer. Neurons, which do not divide and must survive for decades, accumulate DNA damage from oxidative stress and the energetic demands of signalling, and studies of single human neurons show mutation burdens rising steadily with age. Contrasting patterns have been documented between ageing neurons and oligodendrocytes, and some analyses point to age-associated hypermutability in a subset of brains. These private variants might cumulatively erode cellular resilience, weakening neurons’ capacity to withstand further stress and lowering the threshold for disease.

Neurodegenerative diseases show distinct increases in neuronal somatic variant burden, and the review highlights convergent mutational signatures implicating oxidative stress and topoisomerase 1, or TOP1, mediated DNA repair as shared mechanisms of genomic instability. Work on single Alzheimer’s disease neurons has documented diverse somatic genomic changes, and related alterations have been reported in chronic traumatic encephalopathy and in a range of tauopathies, suggesting that distinct disorders may leave characteristic genomic fingerprints in the cells they damage.

A separate axis of mosaicism involves microglia, the brain’s resident immune cells. Clonal haematopoiesis of indeterminate potential, or CHIP, describes age-related expansion of blood cell clones carrying mutations in genes such as TET2 and DNMT3A, and evidence now indicates that CHIP-associated clones can populate the brain as microglia. These mutant microglia adopt inflammatory and sometimes proliferative states and have been linked to Alzheimer’s disease and other neurodegenerative conditions, although mouse studies show the effects can be context-dependent, with some TET2-mutant myeloid cells appearing protective. Clonal inflammatory microglia have also been implicated in histiocytosis-associated neurodegeneration, underscoring that mosaicism in glia may be as consequential as mosaicism in neurons.

Perhaps the most provocative proposal in the review is that somatic variants confined to disease-relevant brain regions could act as focal initiating lesions. In diseases such as amyotrophic lateral sclerosis and frontotemporal dementia, recent sequencing studies have identified focal mutations associated with widespread degeneration, and somatic TARDBP variants have been reported as a cause of semantic dementia. The authors suggest that a local genetic insult could trigger pathology, including protein aggregation, that then propagates across anatomically connected brain regions, explaining the characteristic focal onsets and asymmetric spreads seen in Parkinson’s disease and ALS.

Detecting these variants is technically demanding, and the review takes stock of the rapidly evolving toolkit. Bulk sequencing with matched controls, error-corrected duplex sequencing and single-cell whole-genome amplification methods each trade sensitivity for coverage, and machine-learning callers such as DeepMosaic and DeepSomatic are improving detection across platforms. Single-cell approaches now extend to long-read sequencing and to single-cell transcriptomes, enabling de novo variant calling and the resolution of structural variants, retrotransposon activity and repeat expansions, including the somatic CAG repeat expansions that drive Huntington’s disease.

Clinical translation remains early. Mosaicism complicates genetic diagnosis because a variant detectable in blood may be absent from the affected brain tissue, and vice versa, and cerebrospinal fluid liquid biopsy is emerging as one route to sampling brain-specific mosaicism non-invasively. Yet the framework already has therapeutic echoes: mTOR inhibitors such as everolimus and sirolimus, developed for tuberous sclerosis, are being tested against focal cortical dysplasias driven by somatic mTOR mutations, demonstrating that mosaic lesions can be drug targets.

Zhou and Walsh argue that the next phase requires integrating genomic, cellular and physiological analyses in longitudinal human studies to establish causality, identify biomarkers and guide targeted interventions. If somatic mosaicism proves to be a genuine driver of neurodegeneration rather than a by-stander, medicine may need to treat the ageing brain not only as an organ under metabolic and inflammatory attack, but as a shifting genetic mosaic whose private mutations accumulate over a lifetime, quietly reshaping the vulnerability of each neuron and glial cell one DNA lesion at a time.

Subject of Research: Somatic mosaicism in the human brain across development, ageing and neurodegenerative disease

Article Title: Somatic mosaicism in the brain: linking development, ageing and neurodegeneration

Article References: Somatic mosaicism in the brain: linking development, ageing and neurodegeneration. (n.d.). https://doi.org/10.1038/s41582-026-01268-x

Image Credits: AI Generated

DOI: 10.1038/s41582-026-01268-x

Keywords: somatic mosaicism, brain, neurodegeneration, ageing, epilepsy, Alzheimer's disease, clonal hematopoiesis, microglia, DNA damage, single-cell sequencing, neurodevelopment, TOP1

The decision to centre emerging investigators rather than established luminaries is itself a statement about how science should evolve. The authors argue that researchers early in their careers are uniquely positioned to challenge prevailing assumptions, adopt interdisciplinary approaches and redirect priorities that may have calcified over decades. The resulting collection of perspectives spans an unusually wide technical range, from neoadjuvant immunotherapy in colorectal cancer to somatic mosaicism in healthy tissues, from the nervous system’s role in tumour progression to artificial intelligence models that predict cellular responses to genetic perturbation. Together, the six contributions sketch a research agenda that is more integrated, more prevention-focused and more computationally ambitious than anything the field has attempted before.

One thread running through the article is the remarkable maturation of cancer immunotherapy, particularly when treatment is moved earlier in the disease course. Myriam Chalabi, a medical oncologist and physician scientist at the Netherlands Cancer Institute in Amsterdam, has built her research programme around immunotherapy delivered in the neoadjuvant setting, using novel treatment combinations within innovative trial designs. The clinical evidence underpinning this shift is striking: recent work has demonstrated neoadjuvant immunotherapy in mismatch-repair-proficient colon cancers, while separate research has shown that non-operative management of mismatch repair deficient tumours can produce durable responses, in some cases allowing patients with rectal cancer to avoid surgery entirely. These results suggest that the immune system, when engaged before a tumour has been removed, can eliminate disease that conventional staging would consider established, and they raise the prospect of organ-preserving treatment as a realistic goal rather than an aspirational one.

Yet immunotherapy has also exposed the limits of tumour-centric thinking, and several of the authors argue that the next 25 years must focus on the host as much as the tumour. James L. Reading, an associate professor of cancer immunology at UCL who leads the Pre-cancer Immunology Laboratory, studies T cell-driven cancer interception — the idea of detecting and eliminating tumours before they become clinically invasive. His work builds on the discovery that reservoirs of stem-like CD8-positive T cells in tumour-draining lymph nodes sustain ongoing antitumor immune responses, and that conventional type I dendritic cells maintain pools of proliferative, tumour-antigen-specific TCF1-positive CD8-positive T cells in those same nodes. Understanding how these immune reservoirs are established and maintained during pre-invasive disease, he argues, could transform early detection from passive imaging into active, immune-guided interception, catching malignancy at a stage when cure rates approach certainty.

The genomic dimension of this preventive agenda is developed most fully by Tim H. H. Coorens, a group leader at the European Bioinformatics Institute who studies how somatic mutations accumulate in normal cells. Twenty-five years ago, cancer genomes were largely studied in isolation from the tissues that produced them. Today, it is clear that essentially every cell in the body accrues mutations over a lifetime, and that clones of mutant cells — some harmless, some pre-malignant — expand and compete in otherwise healthy tissue. Coorens contributed to the Somatic Mosaicism Across Human Tissues network, an effort to catalogue this variation systematically, and recent analyses have shown that age itself can distinguish selective clonal expansion from simple mutational causation in cancer genomes. Meanwhile, the real-world clinical utility of tumour whole-genome sequencing in solid cancers has now been demonstrated at scale, suggesting that comprehensive genomic profiling is moving from research luxury to standard of care. The conceptual shift is profound: cancer becomes not a foreign invader but one possible endpoint of a lifelong evolutionary process, and the levers for prevention may lie in the dynamics of normal tissue.

Perhaps the most visually striking frontier is cancer neuroscience. Leanne Li, a group leader at the Francis Crick Institute in London, combines cancer genetics with neurotechnologies to decipher the logic of interactions between tumours and the nervous system in mouse models. The field’s roots reach back more than a century to observations of nerves within tumours made using methylene blue vital staining, but modern cancer neuroscience has exploded in the past decade. Recent single-neuron sequencing has revealed how individual neurons are reprogrammed by pancreatic cancer, and comprehensive reviews have mapped the past, present and future of the discipline. Li also leads InteroCANCEption, a multidisciplinary team funded by Cancer Grand Challenges to tackle the broader question of how interoception — the body’s sensing and regulation of its own internal signals, a concept elaborated in modern neuroscience — shapes tumour initiation, growth and response to therapy. If tumours co-opt neural circuitry the way they co-opt blood vessels, then neuromodulatory drugs already approved for other conditions could become unexpected additions to the oncology arsenal.

Resistance to therapy, the stubborn core of cancer mortality, is the focus of Shensi Shen, associate professor at West China Hospital, Sichuan University. His work centres on drug-tolerant persister cells — a subpopulation of cancer cells that survives initial treatment not through genetic mutation but through reversible shifts in cell state. Reviews have traced the journey of persister cell biology from basic questions to clinical opportunities, and single-cell analyses have shown that genetically homogeneous cancer cells can diverge into multiple distinct clonal fates when exposed to the same drug. Shen’s particular interest is in layered translational control: the regulation of how messenger RNA is decoded into protein, which allows cancer cells to deploy hidden protein functions and switch states under therapeutic pressure. Because these transitions are non-genetic, they are also potentially reversible, which makes the persister state an attractive target for combination strategies designed to block the escape routes that tumours use to survive targeted therapy and immunotherapy alike.

Underpinning all of these biological questions is a computational revolution, examined by Ewa Szczurek, associate professor at the University of Warsaw and director of the Institute of AI for Health at Helmholtz Munich. Szczurek develops artificial intelligence models for molecular biology and medicine, and her perspective is notably sober about the current state of the field. While foundation models promise to predict how cells respond to genetic and pharmacological perturbations — an ambition exemplified by recent preprint work on state-based prediction of cellular responses — independent evaluations have shown that deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines in many settings. Her message is that the next 25 years of AI in cancer research will be defined not by model size but by data quality, experimental validation and careful benchmarking. If the field heeds that warning, machine learning could genuinely accelerate target discovery and personalised treatment; if it does not, hype risks outrunning biology.

Woven together, the six perspectives describe a field in mid-revolution. The tumour-as-isolated-entity model is giving way to a systems view in which cancer is embedded in the evolutionary dynamics of normal tissues, the immune landscape of pre-invasive disease, the neural circuitry of the host body and the non-genetic plasticity of individual cells. Clinical paradigms are shifting in parallel: treatment is moving earlier, surgery is sometimes becoming optional, and molecular residual disease monitoring — exemplified by analyses of adjuvant osimertinib in resected EGFR-mutated lung cancer — is becoming a guide for post-operative decisions. The anniversary article also translates premalignant biology into strategies for intercepting non-small-cell lung cancer, illustrating how laboratory insight can be converted directly into prevention trials.

What emerges most clearly is a demand for interdisciplinarity as a structural principle rather than a slogan. The authors themselves embody it: a clinician designing immunotherapy trials, a bioinformatician decoding mutation accumulation, a neuroscientist engineering tools to interrogate tumour-nerve crosstalk, an immunologist chasing T cells before invasion, a molecular biologist tracking protein-level resistance and a computer scientist stress-testing the field’s newest models. Their collective wager is that the major killers of the next quarter-century will not be defeated by any single breakthrough but by the deliberate integration of genomics, immunology, neuroscience, developmental biology and computation — and by the willingness of a new generation to ask questions their predecessors did not think to ask.

Subject of Research: Emerging investigators' perspectives on the future priorities of cancer research over the next 25 years

Article Title: The next 25 years of cancer research: emerging perspectives and priorities

Article References: Chalabi, M., Coorens, T. H. H., Li, L., Reading, J. L., Shen, S., & Szczurek, E. (2026). The next 25 years of cancer research: emerging perspectives and priorities. Nature Reviews Cancer. https://doi.org/10.1038/s41568-026-00975-3

Image Credits: AI Generated

DOI: 10.1038/s41568-026-00975-3

Keywords: cancer research, Nature Reviews Cancer, immunotherapy, neoadjuvant therapy, somatic mosaicism, cancer neuroscience, cancer interception, drug-tolerant persister cells, tumour heterogeneity, whole-genome sequencing, artificial intelligence, early detection

The conceptual foundation dates back to 1976, when Peter Nowell proposed that tumour cell populations evolve through acquired genetic lability, with stepwise selection of variant sublines driving progression. Half a century of bulk sequencing vindicated the model, revealing branched evolution, intratumoural heterogeneity and the selective sweeps that follow treatment. Yet bulk measurements average across millions of cells, obscuring which mutation resides in which cell and, crucially, what that mutation actually does to the cell carrying it. The review’s authors argue that closing this genotype-to-phenotype gap is now the central task of cancer evolutionary biology.

One striking motivation comes from healthy tissue. Landmark studies of normal skin, oesophagus, colon, endometrium, bladder and bronchial epithelium have shown that somatic mutations in canonical cancer driver genes are under pervasive positive selection in tissue that looks entirely normal under the microscope. In sun-exposed skin, roughly a quarter of cells carry cancer-associated mutations, and mutation burdens in some cells rival those of tumours. Clonal haematopoiesis, the age-related expansion of blood cells carrying mutations in genes such as DNMT3A, TET2 and JAK2, likewise demonstrates that genetic mosaicism is a feature of ordinary physiology and ageing, seeding the pre-malignant landscape from which frank cancers emerge.

Mapping this diversity, however, is only the first step. The review emphasises that understanding somatic clonal evolution requires defining the phenotypes that give mutated clones a fitness advantage, whether those phenotypes involve altered differentiation, survival, proliferation or interaction with the microenvironment. This is where genotype-aware single-cell multi-omics enters. Methods such as G&T-seq and its descendants physically split or barcode the genome and transcriptome of an individual cell, while genotyping-of-transcriptomes approaches recover expressed mutations directly from single-cell RNA-sequencing data. Targeted strategies enrich for known mutant loci, and chromatin-focused assays now co-capture mutations alongside single-cell accessibility profiles.

The biological payoffs have been substantial. In clonal haematopoiesis, single-cell multi-omics has shown that the effects of a mutation are often cell-state specific. DNMT3A R882 mutations, for example, were found to perturb early progenitor states through selective hypomethylation, a phenotype invisible to bulk assays. Splicing aberrations in haematopoietic clonal outgrowths display distinct cell-type-specific impacts, and maps linking genotypes to chromatin accessibility profiles reveal how individual mutations reshape regulatory landscapes in a lineage-dependent manner. In myeloproliferative neoplasms, clonally resolved analyses have traced how JAK2 and CALR mutations propagate through differentiation hierarchies, while work in acute myeloid leukaemia has connected RAS-mutant leukaemia stem cells to clinical resistance against the BCL-2 inhibitor venetoclax.

Beyond single time points, the review highlights the power of coupling phylogenetic reconstruction with phenotypic measurement. Endogenous marks such as somatic point mutations, copy-number alterations, mitochondrial DNA mutations, microsatellite shifts and stochastic epimutations each leave heritable traces that allow researchers to infer the ancestral relationships among single cells. Mitochondrial mutations in particular have enabled lineage tracing directly in human samples, and somatic epimutations have recently been used to chart the dynamics of blood ageing. Reconstructed single-cell phylogenies can then be time-calibrated, converting a branching diagram into a chronogram that estimates when a clone originated within a patient’s lifespan.

Such temporal mapping demands careful statistical treatment. The authors describe phylogenetic frameworks that quantify heritability and plasticity of cell states, decoupling genetic inheritance from non-genetic, environmentally driven transitions. Molecular clock models, whether strict or relaxed, permit inference of mutation rates and timing of clonal expansions, and phylodynamic approaches borrowed from pathogen genetics now illuminate how tumour population sizes fluctuate over the course of disease. Applied to colorectal cancer, these tools have revisited the Big Bang model of tumour growth, in which most subclonal diversity is generated in an early expansion rather than through later selective sweeps, and have documented phenotypic plasticity under genetic control during malignant progression.

Spatial context adds a further dimension. Multiclonal invasion patterns in breast tumours, spatially resolved copy-number maps in benign and malignant tissue, and spatial genomics of cancer clones all demonstrate that evolutionary dynamics are constrained by tumour architecture. Mechanical confinement has been shown to govern phenotypic plasticity in melanoma, and harsh microenvironments select for glycolytic phenotypes in early breast cancer. Integrating spatially resolved or lineage-resolved phenotypes with genotype maps is therefore revealing how selection operates not just on mutations but on the cell states and niches in which those mutations find themselves.

Translationally, the authors argue that genotype-to-phenotype mapping can expose therapeutic vulnerabilities for the precision elimination of disease-propagating mutant cells. Because mutant phenotypes are often confined to specific cell states or lineages, vulnerabilities may exist that spare wild-type tissue. Single-cell analyses have identified drug-tolerant persister states, non-genetic determinants of clonal fitness, and epigenetically inherited plasticity that drives drug resistance through one-to-many genotype-to-phenotype relationships. In glioblastoma, recurring cellular states whose abundance is modulated by genetic aberrations suggest combination strategies; in IDH-mutant oligodendroglioma, mutant IDH inhibitors induce lineage differentiation detectable at single-cell resolution. Evolutionary steering, in which treatment is designed to guide tumours toward collateral sensitivities, becomes more tractable when clonal phenotypes can be read directly in patients.

The review closes with a sober assessment of remaining challenges. Whole-genome amplification artefacts, allelic dropout and tissue dissociation biases still limit sensitivity and fidelity, and artifacts in mitochondrial DNA analyses can misinform phylogenetic inference if uncorrected. Computational methods continue to mature, from probabilistic single-cell phylogeny inference that accounts for sequencing error to models that relax the infinite-sites assumption when back mutations and parallel evolution occur. Yet the trajectory is clear: by pairing genotype with phenotype in the same cell and embedding those pairs within time-calibrated phylogenies, researchers can now define, directly in primary human samples, the mechanisms underlying clonal expansion in both healthy and malignant tissues. For a disease that evolves to evade every therapy thrown at it, that may prove the most consequential lens oncology has yet acquired.

Subject of Research: Single-cell multi-omics mapping of genotype and phenotype co-evolution in clonal evolution of healthy and cancerous tissues

Article Title: A single-cell lens into the co-evolution of genotypes and phenotypes in cancer

Article References: Izzo, F., Prieto, T., Potenski, C., & Landau, D. A. (2026). A single-cell lens into the co-evolution of genotypes and phenotypes in cancer. Nature Reviews Cancer. https://doi.org/10.1038/s41568-026-00970-8

Image Credits: AI Generated

DOI: 10.1038/s41568-026-00970-8

Keywords: single-cell multi-omics, clonal evolution, genotype-phenotype mapping, tumour heterogeneity, clonal haematopoiesis, single-cell phylogenetics, lineage tracing, somatic mosaicism, phenotypic plasticity, cancer genomics, epigenetics, therapeutic vulnerabilities