Introduction Bladder cancer (BLCA), particularly the muscle-invasive (MIBC) subtype, represents one of the most challenging malignancies of the urinary tract and poses substantial difficulties in clinical management. Although therapeutic advances such as neoadjuvant chemotherapy and immune checkpoint inhibitors have improved patient outcomes, pronounced intratumoral heterogeneity (ITH) results in considerable inter-individual variability in treatment response, contributing to treatment failure and disease recurrence.1 Consequently, a deeper understanding of tumor evolution and precise tumor classification is critical for identifying effective therapeutic targets and diagnostic or prognostic biomarkers. This commentary proposes a novel integrative model of BLCA progression that synthesizes the most recent findings from our group. By addressing existing knowledge gaps, we present a more comprehensive framework of the biochemical and mechanistic processes underlying BLCA evolution, linking epigenetic plasticity as a genesis, metabolic reprogramming as a mechanophenotype initiator, and DNA methylation (DNAm) signatures as clinical biomarkers to be translated to beneficially inform clinical practice. This model challenges the previous mutation-centered paradigm as outdated and outlines a dynamic framework of cellular evolution, positing that the effective diagnosis and treatment of BLCA reside within this adaptive evolutionary perspective. 2. Evolutionary origins of BLCA in epigenetic plasticity Previous molecular classifications and MIBC research have been based on bulk sequencing, which conceptualizes carcinogenesis and tumor evolution as static and irreversible genetic events (exemplified by recurrent mutations in TP53, ARID1A, and KDM6A).2 However, this model does not sufficiently explain the spatiotemporal dynamics of ITH and the nongenetic origins of the disease. Accumulating evidence suggests that epigenetic plasticity-mediated functional heterogeneity enables tumors to rapidly adapt to selective pressures, thereby circumventing the temporal constraints inherent to genetic evolution.3 Single-cell technologies represent a means of overcoming this complexity. Collectively, these advances have driven a paradigm shift from a static mutation-focused framework to a dynamic model of cell evolution, guiding new approaches for the accurate diagnosis and treatment of tumors. Building on our recent work with EpiTrace,4 a technology that utilizes the chromatin accessibility landscape to infer the mitotic age and developmental history of a cell, we gained unprecedented insight into MIBC evolution. Our application of this technology demonstrated that MIBC can originate from urothelial basal cells following critical epigenetic alterations,5 leading to the emergence of an adaptive, stem cell-like state, which we described as a TM4SF1-positive cancer subpopulation (TPCS). The diversification of the TPCS without new genetic mutations is driven by high epigenetic plasticity, regulated through dynamic chromatin accessibility, which enables the generation of heterogeneous descendant clonal lineages that populate the tumor.6 3. Epigenetic-metabolic reciprocity Cellular plasticity requires a shift in the cellular energetics. Although epigenetic alterations provide the “software” for malignant transformation, metabolic reprogramming supplies the “fuel,” establishing a clear and interactive relationship between the 2 processes. Metabolic reprogramming provides materials and energy for rapid tumor proliferation, and its intermediate metabolites directly modify epigenetic regulators and oncogenic proteins, creating a feedback loop that sustains the malignant state. In a study on the evolution of BLCA, we identified Myc as the major driver pathway,7,8 which regulates proliferation, metastasis, and chemoresistance via the regulation of lipid metabolism genes, including adenosine triphosphate citrate lyase,9 a rate-limiting lipid molecule-producing enzyme. Moreover, TM4SF1 serves as the marker of TPCS and is activated by the PPARγ pathway, closely connected to lipid and cholesterol biosynthesis.10 This signaling cascade regulates lipid metabolism by increasing the levels of metabolites, including geranylgeranyl pyrophosphate and palmitic acid. These metabolites serve as donors for protein lipidation, thereby modulating the activity and stability of epigenetically-modifying enzymes and other key proteins.11 Based on these observations, we hypothesized a self-perpetuating cycle: the plastic epigenetic state of the TPCS induces lipid metabolism remodeling, which in turn generates metabolic products that reinforce the malignant epigenetic program and maintain stem cell-like properties. This feedback loop between epigenetic plasticity and metabolic reprogramming drives ITH and tumor evolution. 4. New approach for clinical diagnostics This fundamental biology leaves tangible epigenetic imprints and aberrant DNAm patterns that can be detected in patient samples. These molecular fingerprints serve as a roadmap for clonal evolution, linking the basic science of disease origin to clinical applications in lineage tracking and prognostication. Consequently, the development of noninvasive biomarkers represents a critical objective. Urinary biomarkers are particularly promising, as noninvasive serial sampling is ideal for large-scale screening and longitudinal disease surveillance. Our example is the development of a noninvasive diagnosis and surveillance system for BLCA, representing a bench-to-bedside translational approach.12 The system is used to assess cell-free DNA methylation signatures in urine to perform a variety of clinical tasks and includes 2 different scoring models: the Urine Cancer Score, which identifies cancer, and the Basal/Luminal Cancer Score, which subtypes cancer. The assay has very high sensitivity and specificity for the noninvasive early diagnosis of BLCA, especially for high-grade tumors. Importantly, this framework integrates mechanistic findings with the urine-based testing results. The epigenetic and metabolic alterations driving the TPCS also generate stable and detectable patterns of DNAm, which are released into the urine as cell-free DNA. With the determination of these epigenetic signatures, an early diagnostic and molecular classification system could stratify patients at risk of recurrence and metastasis more effectively than conventional pathological assessment, while providing a robust system to monitor postoperative data (Figure 1).Figure 1.: Workflow for epigenetic-based early diagnosis and molecular classification of bladder cancer. This process begins with the analysis of differentially methylated regions in cell-free DNA (cfDNA) from urine or tissue samples. The epigenetic information undergoes bioinformatics processing, enabling 2 concurrent clinical applications. The first component is early diagnosis, in which the UCAS algorithm classifies samples as positive or negative for bladder cancer. The second component is risk stratification, in which the BLCAS model categorizes patients into low- or high-risk groups and distinguishes tumors by molecular subtypes: the luminal type, often associated with NMIBC, and the basal type, predominantly associated with MIBC. This workflow links the molecular origins of bladder cancer to clinically actionable diagnostic strategies. BLCAS, Basal/Luminal Cancer Score; MIBC, muscle-invasive bladder cancer; NMIBC, nonmuscle-invasive bladder cancer; UCAS, Urine Cancer Score.5. Conclusion This observation is a synthesis of our current research and proposes a composite hypothesis for the formation, progression, and translation of biomarkers in BLCA. Here, we present a vicious cycle of self-perpetuation of epigenetic plasticity and metabolic reprogramming. This approach enabled us to identify the pathogenesis of the disease (TPCS), the mechanism of its maintenance (the metabolic-epigenetic feedback loop), and its evolution using a different epigenetic signature (diagnosis of the disease via DNAm). Integrated insights are poised to usher in a new era of precision oncology for BLCA, enabling interventions that can effectively disrupt this self-perpetuating cycle. Through a combination of genetic lineage tracking, metabolic profiling, and delicate epigenetic diagnostics, the future of patient-specific therapies will focus on destabilizing the cancer stem cell reservoir, overcoming resistance, and preventing relapse. Acknowledgements The excellent technical assistance of Yayun Fang and Danni Shan at Zhongnan Hospital of Wuhan University is gratefully acknowledged. We thank Dr. Yuruo Chen for exceptional assistance in editing the diagram. Financial support and sponsorship Not applicable. Conflict of interest statement The authors declare that they have no conflict of interest with regard to the content of this report. Author contributions YX and GW conceived and designed the study. ZX, LJ, WX, FC, and GW contributed to the methodology. FC, LJ, and YX performed computations and formal analysis. ZX, SL, WX, HP, MY, KQ, and LJ performed the experiments. WX, HP, and KQ contributed to the collection of study resources. YX and GW wrote the manuscript. ZX, SL, and LJ critically reviewed the manuscript. All the authors have read and approved the final manuscript. Data availability statement Not applicable. Ethical approval Not applicable.
Xu et al. (Wed,) studied this question.
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