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PubMed2025

Defective but tumorigenic: the evolutionary and functional roles of mutated oncoviruses.

Human oncogenic viruses contribute significantly to the global health burden and include seven types: Epstein-Barr virus, hepatitis B virus, human T-cell leukemia virus type 1, human papillomavirus, hepatitis C virus, Kaposi's sarcoma-associated herpesvirus, and Merkel cell polyomavirus. While the roles of latent or integrated viral genomes in cancer have been documented, emerging evidence highlights the contribution of defective viruses-those carrying intragenic deletions or loss-of-function mutations-in promoting viral oncogenesis. These altered genomes often lack genes essential for lytic replication or immune recognition, which enhances their persistence and immune evasion. In virus-associated diseases, specific patterns of gene retention and deletion suggest that host-driven selective pressures drive the emergence of these altered genomes. This review examines the generation, prevalence, and functional impact of these viruses, reframing them as active participants in disease development and progression. Recognizing their role offers new insights into viral tumor evolution and creates opportunities for applications in viral diagnostics and targeted intervention strategies.

Humans↗

PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗

PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗

PubMed2026

RAS Pathway Activation and Microenvironmental Adaptation as Hallmarks of Myeloid Sarcoma.

UNLABELLED: Myeloid sarcoma, an aggressive extramedullary subtype of acute myeloid leukemia (AML), occurs in approximately 20% of patients and remains strikingly understudied in large-scale genomic and multiomic investigations. The key drivers of its tumor evolution are largely unknown; timely detection in asymptomatic patients poses a clinical challenge, and effective treatment options are limited, as patients are often excluded from clinical trials, rendering it a largely neglected disease entity. In this study, we demonstrate that myeloid sarcoma evolves from medullary AML but exhibits distinct site-specific clonal evolution. This is supported by unique transcriptional signatures of myeloid sarcoma, reflecting adaptation to the extramedullary microenvironment. We establish a proof of concept that circulating tumor DNA (ctDNA) sequencing captures the molecular composition of myeloid sarcoma, offering a potential noninvasive approach for molecular profiling of extramedullary AML. Our findings highlight marked differences between medullary AML and myeloid sarcoma, including universal molecular evolution and RAS pathway activation as disease hallmarks. SIGNIFICANCE: We provide a comprehensive multiomic characterization of myeloid sarcoma, identifying key molecular pathways that contribute to its development, and suggest ctDNA as a noninvasive method of detection. We identify RAS pathway activation and transcriptional adaptation to the solid tissue microenvironment as cardinal features of myeloid sarcoma, suggesting novel therapeutic avenues.

Sarcoma, Myeloid↗

PubMed1977

Effect of cyclophosphamide on syngeneic transplantation of adenovirus 12-transformed tumor cells in C3H/he mice.

We tested the cyclophosphamide effects against the growth of adenovirus-transformed cells and the subsequent tumor development in the syngeneic host. Cyclophosphamide did not show any effect on the tumor evolution when injected 24 and 6 hours before cell implantation. Cyclophosphamide injected 24 or 39 hours after cell implantation prevented or retarded the tumor growth. In mice bearing palpable tumors, it induced their complete regression in 85,7% of the animals, but did not effect the development of the homograft immunity.

Adenoviridae↗

PubMed2026

Mutational signature stratification of recurrent gliomas reveals distinct patterns of genomic traits.

BACKGROUND: Although temozolomide (TMZ) is widely used for glioma treatment, its therapeutic benefit is limited by acquired resistance and recurrence, facilitated by intratumor heterogeneity. Mutational signatures (MSs) inform tumor evolution and reveal alterations associated with treatment response. METHODS: We performed molecular analyses of 96 glioma recurrences with sufficient private single-nucleotide variants relative to their matched primary tumors, stratified by their dominant MS. RESULTS: Four groups were identified: MS11/TMZ-related (n = 38), MS1/5/aging-related (n = 32), MS6/15/21/26/microsatellite instability (MSI)-related (n = 13), and other MS-related recurrences (n = 13). MS11/TMZ-related recurrences showed higher acquired mutational counts than the other groups (1338 vs 59 (MS1/5/aging) vs 57 (MS6/15/21/26/MSI) vs 57 (other MSs); P < .01). Mutations in SYNE2, SZT2, and FBN3 were restricted to recurrences with dominant or second-dominant MS11/TMZ-related signature (n = 41), and 85% (35/41) harbored mutations in these genes. In MS11/TMZ-related recurrences with RNA sequencing data (n = 17), mRNA co-expression analyses identified SYNE2-ATAD5 and SZT2-MAPKBP1 associations. Among MS11/TMZ-related recurrences, MS23 was frequent (44%, 18/41) and associated with higher acquired mutational counts (2089 vs 1188; P = .018) and more IDH-wildtype tumors (67% vs 30%; P = .037). MAPKBP1 mutations were enriched in MS23-positive recurrences (56% (10/18) vs 0% (0/23); P < .001). MS1/5/aging-related recurrences showed more frequent acquired chromosome 16q losses (22% vs 8% (TMZ) vs 0% (MSI) vs 0% (other); P < .05), which were associated with an increased fraction of genome altered relative to 16q-diploid cases (15% vs 7%; P = .01). CONCLUSIONS: These findings show that MS-based stratification of recurrences refines molecular characterization after therapy and nominates candidate biomarkers and pathways for functional studies of treatment-associated glioma evolution.

mutational signatures↗

PubMedDate not supplied

Xeroradiographic evaluation of murine osteosarcoma.

Xeroradiography, a method of X-ray imaging based upon selenium photoconductivity, was used for the study of experimental osteosarcoma induced by MSV-M virus in rats. Due to the peculiar features of xeroradiographic image (enhancement of details and lowering of the overall contrast) good pictures of osseous structures together with soft tissues were obtained even in very young animals. Serially perfomred xeroradiographies gave a permanent representation of tumor evolution with time. Advantages and drawbacks of this method are discussed, particularly with respect to radiation dosage. Xeroradiography is proposed for the study of the response to antiblastic chemotherapy of experimental bone tumors.

Animals↗

PubMed2025

MIF as an oncogenic driver of low-heterogeneity melanomas.

Identifying targets involved in tumor evolution and immune escape is an active area of research in oncology. Macrophage migration inhibitory factor (MIF) is an upstream immunoregulatory cytokine that promotes transformed cell proliferation and survival, and generates a tumor-permissive immune landscape of immunosuppressive myeloid and T cells. Shvefel and colleagues have identified a key role for MIF in tumor progression in melanoma clones with low tumor heterogeneity. These findings provide important insights into the potential therapeutic utility of MIF antagonists and support ongoing research to utilize MIF pathway inhibitors for improved therapeutic outcomes.

Animals↗

PubMed2026

Personalized medicine strategy for MPNSTs: using precision oncology on PDOX models to inform tumor boards.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. METHODS: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. RESULTS: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiring additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDX model, whose patient has been receiving this therapy for eight months with sustained remission. CONCLUSIONS: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

Precision Medicine↗

PubMed2026

Exploiting DNA damage tolerance for precision oncology.

Unresolved DNA lesions trigger replication stress, forcing cancer cells to hijack DNA damage tolerance (DDT) networks, specifically translesion synthesis (TLS) and template switching, to sustain replication. While DDT prevents lethal fork collapse, error-prone TLS drives mutagenesis, tumor evolution, chemoresistance and radioresistance. Proliferating cell nuclear antigen post-translational modifications dynamically govern pathway selection. Cancer cells exploit this plasticity, creating actionable vulnerabilities such as postreplicative single-stranded DNA gaps. Emerging inhibitors targeting TLS polymerases, upstream regulators such as ubiquitin-specific peptidase 1 (USP1), and critical protein-protein interactions offer unprecedented opportunities for precision oncology. By integrating DDT inhibition with biomarkers such as homologous recombination deficiency and tumor mutational burden, we can drive synthetic lethality, sensitize tumors to genotoxic agents, suppress treatment-induced mutagenesis, and potentially enhance responses to immunotherapy.

DDT↗

PubMed2025

Defining the genome-wide mutagenic impact of APOBEC3 enzymes.

Somatic mutations drive cancer initiation and tumor evolution. Therefore, the etiology of mutagenesis in cancer is important to preventative and treatment strategies. Somatic mutagenesis in cancer is a multifactorial process and includes both endogenous and exogenous sources of mutations. One recently recognized source of mutagenesis in cancer is the innate immune APOBEC3 family of enzymes, which catalyze cytosine deamination to restrict viral infection but can aberrantly act on the cellular genome, resulting in mutations. Single base substitution (SBS) signatures, or mutational patterns, identified in cancer genomes have demonstrated widespread mutagenesis caused by APOBEC3 enzymes throughout human tumors. To comprehensively define the consequences of APOBEC3 mutagenesis, we developed an experimental pipeline for prospective analysis of genome-wide mutations caused by APOBEC3 activity. This pipeline can be adapted to analyze additional sources of mutagenesis across a spectrum of cells.

Humans↗

PubMed2025

CINner: Modeling and simulation of chromosomal instability in cancer at single-cell resolution.

Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types from the Pan-Cancer Analysis of Whole Genomes (PCAWG, [Formula: see text]). We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Analysis of inference results using CINner across cancer types in The Cancer Genome Atlas ([Formula: see text]) further reveals that the inferred selection parameters reflect the bias between tumor suppressor genes and oncogenes on specific genomic regions. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) in PCAWG uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions (chronic lymphocytic leukemia in PCAWG, [Formula: see text]). Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.

Chromosomal Instability↗

PubMed2026

MET Exon 14 Skipping Mutation in NSCLC: From Genomic Discovery to Biomarker-Guided Therapeutic Innovation.

INTRODUCTION: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the MET exon 14 skipping mutation is a key oncogenic driver, which promotes tumor progression and provides a new direction for precision therapy. METHODS: A systematic search of English-language literature and clinical trial data related to the MET exon 14 skipping mutation from 2020-2025 was performed to summarize the role of the mutation and therapeutic advances. RESULTS: DNA-based next-generation sequencing (NGS), RNA-based NGS, and RT-qPCR were employed as the main detection methods. Preclinical models confirmed that mutations promote tumor progression by activating the RAS/MAPK pathway. Clinical trials have reported objective remission rates (ORR) of 46-68% for first-line treatment with MET inhibitors in NSCLC patients harboring MET exon 14 skipping mutations. DISCUSSION: MET exon 14 skipping mutation as a therapeutic target for NSCLC has made significant progress, and MET inhibitors are more advantageous than chemotherapy and immunotherapy, and have been recommended by national and international guidelines as a first-line treatment option. Additionally, NGS technology has the potential to dynamically monitor tumor evolution and drugresistant mutations, thereby helping to realize precision medicine. CONCLUSION: The MET exon 14 skipping mutation is an important target for the precision treatment of NSCLC, and MET-TKIs have remarkable efficacy but a prominent problem with drug resistance. The construction of a precision medicine system encompassing diagnosis, treatment, and drug resistance management through multi-omics research, technological innovation, and international collaboration is a key direction for improving prognosis.

Humans↗

PubMed1977

[Evolution of hepatocyte population in the process of chemical carcinogenesis].

By means of two different markers of differentiation, using immunofluorescene method, the authors have characterized changes in the population of hepatic cells 1-8 weeks following the start of 3'-methyl-4-dimethyl-aminoazobenzene or 2-acetyl-aminofluorene action. Alpha-fetoprotein served as a marker of embryonic hepatocyte differentiation; while ligandin-as a marker of high-differentiated mature hepatocytes. The toxic effect of the carcinogens on hepatic stem cells was accompanied with a decrease of ligandin content in centrilobular hepatocytes. Among newly proliferating elements "oval" cells, cells of bile tract epithelium and most of basophilic hepatocyte-like cells fail to contain either alpha-fetoprotein or ligandin. Small groups of basophilic hepatocyte-like cells would contein alpha-fetoprotein. In cells of high cylinder-shaped epithelium of intestinal type ligandin was found, but alpha-fetoprotein was not found. The latter was absent in oxyphilous hepatocytes of hyperplastic nodules. In terms of ligandin content three types of morphologically identical nodules were differentiated; a) ones not containing this protein, b) ones containing it in amounts common to normal mature hepatocyte, and c) hyperdifferentiated nodules containing abnormally high concentrations of ligandin. Within one nodule cell all cells were identical in ligandin content. Thus, it is shown that at early stages of chemical carcinogenesis there occure in the liver multiple foci of differentiation of various kind. These intensive processes are assumed to be essential for tumor evolution in the tissue.

2-Acetylaminofluorene↗

PubMed2026

Non-coding RNAs as regulators of chromosomal instability in breast cancer.

Breast cancer is a highly heterogeneous disease characterized by extensive genomic and chromosomal instability (CIN), a hallmark that drives tumor evolution, intratumoral heterogeneity, therapeutic resistance, and poor clinical outcomes. Increasing evidence indicates that non-coding RNAs (ncRNAs) are important regulators of genome maintenance and chromosome stability. However, their specific contributions to CIN and the strength of the available evidence remain incompletely understood. This review examines the role of the major ncRNA classes, including circular RNAs, microRNAs, PIWI-interacting RNAs, small nucleolar RNAs, and long non-coding RNAs, in the regulation of CIN-related processes in breast cancer. We discuss the molecular mechanisms by which these ncRNAs regulate key pathways involved in CIN, while critically evaluating the strength of the experimental evidence supporting their functional roles. We also examine their associations with distinct breast cancer molecular subtypes and assess their potential as biomarkers and therapeutic targets, highlighting current limitations and knowledge gaps that hinder clinical translation. Collectively, the available evidence supports an emerging role for ncRNAs as regulators of CIN while underscoring the need for further mechanistic and subtype-specific studies to validate their clinical utility.

DNA repair↗

PubMed2026

A stratified urine-based molecular diagnostic and prognostic model for non-muscle-invasive bladder cancer management.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate requiring lifelong cystoscopic surveillance. Existing urine-based molecular assays mainly rely on mutations or methylation, which fail to capture large-scale genomic instability. Copy number variation (CNV) profiling offers complementary information on tumor evolution and aggressiveness, but its application in urinary diagnosis remains limited. We aimed to integrate CNV and DNA methylation signals from urinary DNA to establish a noninvasive and biologically informed stratified diagnostic model for NMIBC recurrence surveillance and risk stratification. METHODS: Urine samples were prospectively collected from 91 patients (75 evaluable) between June 2021 and August 2023. Shallow whole-genome sequencing (sWGS) was used to detect CNVs at chromosomal arm and focal gene levels, while ONECUT2 promoter methylation was quantified by qPCR. Diagnostic and prognostic performance was evaluated by ROC analysis, Kaplan-Meier survival, and stratified recurrence assessment. RESULTS: We evaluated a stratified diagnostic model combining CNV and ONECUT2 methylation testing in a cohort of 79 patients. CNV analysis alone showed high specificity (0.923) for NMIBC diagnosis. A combined model, using CNV as an initial screen followed by ONECUT2 methylation testing in CNV-positive cases, achieved a sensitivity of 0.783, specificity of 0.981, and a negative predictive value (NPV) of 0.911. This approach reduced the number of required ONECUT2 tests by 35% and identified a high proportion of true-negative patients (98.1%), which may help reduce unnecessary cystoscopy procedures. The model also demonstrated significant prognostic value, with the molecularly defined high-risk group showing significantly shorter recurrence-free survival (RFS) than the low-risk group (median RFS: 4.33 months vs. not reached; p < 0.001). Additional, in patients with initially negative cystoscopy after urine sample collection, the model demonstrated a predictive accuracy of 0.922 for recurrence, with molecular positivity observed a median of 9.6 months prior to clinical diagnosis. CONCLUSIONS: Integrating CNV and DNA methylation profiling from urinary DNA provides a powerful and noninvasive molecular framework for NMIBC surveillance. By combining early epigenetic changes with genomic instability signals, this approach enhances recurrence risk assessment and enables earlier detection compared with conventional cystoscopy. It offers a practical route toward personalized and adaptive post-treatment monitoring of NMIBC. TRIAL REGISTRATION: NCT04994197.

Humans↗

PubMed2025

Cloning and validating systems for high throughput molecular recording.

Molecular recording technologies record and store information about cellular history. Lineage tracing is one form of molecular recording and produces information describing cellular trajectories during mammalian development, differentiation and maintenance of adult stem cell niches, and tumor evolution. Our molecular recorder technology utilizes CRISPR-Cas9 barcode editing to generate mutations in genomically integrated, engineered DNA cassettes, which are read out by single-cell RNA sequencing and used to produce high-resolution lineage trees. Here, we describe optimized cloning and validation procedures to construct the molecular recorder lineage tracing system. We include information on considerations of technology design, cloning procedures, the generation of lineage tracing cell lines, and time course experiments to assess their performance.

Cloning, Molecular↗

PubMed2026

Mirror worlds: The shared regulatory architecture of cell fate in development and cancer.

Lineage plasticity has emerged as a central mechanism through which cancer cells adapt to therapeutic pressure, evade immune surveillance, and acquire aggressive phenotypes. Although recognized across tumor types, the regulatory principles governing how cancer cells reprogram cellular identity remain incompletely understood. In this review, we propose that lineage plasticity in cancer reflects the redeployment of regulatory frameworks established during normal development. Rather than representing a stochastic byproduct of genomic instability, cancer plasticity frequently unfolds within gene regulatory architectures that also govern cell fate specification, lineage commitment, and controlled state transitions during embryogenesis and tissue homeostasis. Developmental transcription factors, including members of the SOX family, FOXA1, ASCL1, NKX2-1, and epithelial-mesenchymal transition regulators, function as lineage gatekeepers during development but are repurposed in cancer to destabilize lineage commitment and enable phenotypic switching. Similarly, epigenetic regulators that guide developmental trajectories, including chromatin remodeling complexes, Polycomb group proteins, and DNA methylation machinery, are frequently dysregulated or redistributed in tumors, altering the repression of lineage-stabilizing and alternative lineage programs and thereby weakening epigenetic barriers to lineage transitions. Together, these observations support a model in which development and cancer operate as mirror regulatory systems: one establishing and stabilizing cellular identity, the other exploiting the same regulatory architecture to permit adaptive reprogramming under selective pressure. We further discuss how emerging single-cell and spatial multi-omics technologies, integrated with artificial intelligence-based modeling, enable mapping of cell state landscapes and transitional trajectories, transforming lineage plasticity from a descriptive phenomenon into a measurable and predictable property of tumor evolution.

Humans↗