bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–12–28
seventeen papers selected by
Xiao Qin, University of Oxford



  1. bioRxiv. 2025 Dec 10. pii: 2025.12.06.692715. [Epub ahead of print]
      Tissues are shaped by extracellular signaling fields which convey information between cells. The cellular composition of tissues, and the extracellular signaling within the tissue, are innately spatially structured. Modern spatialomics data provide unprecedented measurement of ligand and receptor expressivity in situ from tissue sections. Here, we show that by adapting generalizable geospatial statistical models to spatialomics data, we are able to reveal statistically-detailed portraits of morphogenic field interactions within tissues and thereby approach a richer set of biologic questions than is typically pursued. The general methods piloted here can readily be applied to spatialomics data from diverse platforms with no need to alter data collection techniques. Our results demonstrate that the application of spatial statistical modeling to spatialomics data opens many avenues for future experimentation that will be valuable to fundamental biology and to regenerative medicine.
    Highlights: Tissue biology & regenerative medicine requires analysis of tissue morphogen fields and morphogenic interactionsSpatial statistics can be used to model continuous morphogenic interaction fields in tissues from discrete spatialomics data.
    DOI:  https://doi.org/10.64898/2025.12.06.692715
  2. Aging Dis. 2025 Dec 21.
      Aging is accompanied by a marked increase in cancer incidence and mortality, yet most studies still consider cellular senescence, the tumor microenvironment, and the microbiome as largely separate axes. Here, we propose an integrative triad framework in aging-related cancers in which cellular senescence, tumor microenvironment (conceptualized here as part of a broader tumor microecology), and the microbiome dynamically interact to shape tumor initiation, evolution, and treatment response. We summarize how senescent cells, via context-dependent senescence-associated secretory phenotypes (SASPs), remodel stromal, immune, and metabolic niches in aging hosts and how gut and intratumoral microbiota both induce and are reshaped by senescence. Focusing on colorectal cancer (CRC), hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC), together with pan-cancer transcriptomic and microbiome analyses. We highlight disease and subtype-specific patterns in which senescence signatures, immune contexture, and microbial features co-stratify prognosis and therapeutic outcomes, and integrate pan-cancer transcriptomic and microbiome analyses to illustrate shared and divergent triad configurations across tumor types. Finally, we discuss the therapeutic implications of this triad, including timing-dependent use of senolytics and senomorphics, diet and microbiome-targeted interventions, fecal microbiota transplantation (FMT), and the ecological risks of antibiotics, particularly in multimorbid older patients. We argue that triad-informed biomarkers and trial designs integrating senescence, microenvironment, and microbiome readouts will be important for mechanism-based, age-adapted cancer prevention and therapy in older adults, especially those with CRC, HCC, and PDAC.
    DOI:  https://doi.org/10.14336/AD.2025.1495
  3. Nat Genet. 2025 Dec 23.
      Systematically designing regulatory elements for precise gene expression control remains a central challenge in genomics and synthetic biology. Here we introduce DNA-Diffusion, a generative artificial intelligence framework that uses machine learning trained on DNA accessibility data from diverse cell lines to design compact regulatory elements with cell-type-specific activity. We show that DNA-Diffusion generates 200-base-pair synthetic elements that recapitulate endogenous transcription factor binding grammar while exhibiting enhanced cell-type specificity. We validated these elements using a 5,850-element STARR-seq library across three cell lines. Moreover, we demonstrated successful endogenous gene modulation using EXTRA-seq, reactivating AXIN2, a leukemia-protective gene, in its native genomic context. Our approach outperforms existing computational methods in balancing functional activity with cell-type specificity while maintaining sequence diversity. This work establishes DNA-Diffusion as a powerful tool for engineering compact, highly specific regulatory elements crucial for advancing gene therapies and understanding gene regulation.
    DOI:  https://doi.org/10.1038/s41588-025-02441-6
  4. Mechanobiol Med. 2026 Mar;4(1): 100165
      Cancer cell memory, the ability to retain responses to prior environmental stimuli, has emerged as a key driver of tumor progression, therapeutic resistance, and immune evasion. Mechanical cues within the tumor microenvironment (TME), including matrix stiffness, viscoelasticity, and compressive stress, are increasingly recognized as critical regulators of such memory. These biophysical inputs not only influence immediate cellular behavior but also induce long-lasting transcriptional, epigenetic, and phenotypic changes that sustain cancer cell aggressive traits. In this review, we specifically highlight mechanobiology in shaping cancer cell memory. We summarize how extracellular matrix (ECM) composition and remodeling encodes mechanical inputs into stable gene expression programs that promote tumor progression, and highlight how mechano-regulated plasticity, membrane tension, chromatin remodeling, and epigenetic changes govern self-renewal, differentiation, and drug and immune resistance, underscoring how physical suppression contributes to chemo-, radio-, and targeted therapies failure. We further discuss emerging mechano-targeted strategies, including ECM-degrading agents, sonogenetic engineered cells, and stiffness-responsive nanoparticles, that seek to rewire cancer cell memory and improve treatment outcomes.
    DOI:  https://doi.org/10.1016/j.mbm.2025.100165
  5. Cancer Cell. 2025 Dec 24. pii: S1535-6108(25)00535-5. [Epub ahead of print]
      The epitranscriptome, comprising over 170 distinct RNA modifications, represents a dynamic and multifaceted layer of gene regulation. These chemical marks such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), and pseudouridine (Ψ) modulate RNA processing, localization, stability, and translation, shaping cell identity and stress responses. In cancer, RNA modifications integrate with oncogenic signaling networks to influence cancer cell proliferation, metabolism, immune evasion, stemness, and therapeutic resistance. Recent advances in detection technologies, functional perturbation tools, and spatial profiling have accelerated our understanding of the epitranscriptome's roles and the underlying mechanisms in malignancies. In this review, we provide a mechanistic framework connecting RNA modifications and regulators to the hallmarks of cancer. We highlight emerging insights into the interface between epitranscriptomic regulators and canonical cancer pathways and evaluate their potential as biomarkers and therapeutic targets. Together, these findings underscore RNA modification as a pivotal regulatory axis in cancer biology and a promising frontier for translational intervention.
    Keywords:  ▪▪▪
    DOI:  https://doi.org/10.1016/j.ccell.2025.12.001
  6. Trends Immunol. 2025 Dec 20. pii: S1471-4906(25)00308-4. [Epub ahead of print]
      The advancement of immunotherapy faces significant challenges, including extending its benefits to a growing number of patients and enhancing its efficacy across different tumor types. In this context, γδ T cells emerge as particularly promising candidates owing to their distinctive biological features such as MHC-independent activation, potent cytotoxicity, and capacity to bridge innate and adaptive immunity. Recently, advanced single-cell techniques have allowed detailed γδ T cell characterization in the tumor microenvironment (TME) and have emphasized their heterogeneity, mechanisms of activation, and response to immune checkpoint blockade (ICB). This review provides a comprehensive summary of recent advances in understanding γδ T cells in colorectal cancer (CRC), with a particular emphasis on their prognostic and therapeutic relevance in both primary tumors and metastatic disease.
    Keywords:  colorectal cancer; immunotherapy; liver metastases; single-cell RNA sequencing; tumor microenvironment; γδ T cells
    DOI:  https://doi.org/10.1016/j.it.2025.11.009
  7. Cytokine Growth Factor Rev. 2025 Dec 15. pii: S1359-6101(25)00166-2. [Epub ahead of print]87 102-112
      Cancer stem cells (CSCs) represent a small but critical subset of tumor cells characterized by their inherent self-renewal ability, differentiation potential, and resistance to cancer therapies. Their capacity to reversibly transition between a stem-like and differentiated state, together with their ability to enter into quiescence, are key determinants of their contribution to tumor initiation, tumor progression, metastasis, and cancer recurrence. Among the various factors in the tumor microenvironment, increasing evidence suggests that interferons (IFNs) are key extrinsic modulators of CSC fate. Although type I (IFN-α/β) and type II (IFN-γ) IFNs have long been recognized for their antitumor properties, recent studies indicate that IFN-signaling may also facilitate CSC induction and maintenance. In this review, we summarize and critically assess our current understanding of the complex roles of IFNs in governing CSC survival, plasticity, and immunogenicity. We discuss how IFN-signaling thresholds, signaling duration, and intrinsic CSC regulatory networks determine whether IFNs suppress CSCs or instead reinforce stemness. By bridging mechanistic insights with therapeutic potential and clinical outcomes, we highlight emerging opportunities to exploit IFN pathways for improved biomarkers and therapeutic strategies to overcome CSC-driven resistance.
    Keywords:  Biomarkers; Cancer stem cells; Cancer therapy; IFN signaling; Immune checkpoint therapy; Tumor resistance
    DOI:  https://doi.org/10.1016/j.cytogfr.2025.12.008
  8. STAR Protoc. 2025 Dec 24. pii: S2666-1667(25)00698-7. [Epub ahead of print]7(1): 104292
      Mesenchymal stem/stromal cells (MSCs) are known for their regenerative properties. This protocol describes a co-culture system for investigating molecular interactions between MSCs and intestinal epithelial organoids following injury. We outline steps for assessing the immediate effects of MSCs on organoid growth and survival, as well as a model for evaluating longer term responses. The workflow is adaptable and can be readily modified to examine MSC interactions with additional cell types or in different injury contexts. For complete information on the use and execution of this protocol, please refer to Yetkin-Arik et al.
    Keywords:  Cell biology; Cell-based assays; Molecular biology; Organoids; Signal transduction; Single cell; Stem cells
    DOI:  https://doi.org/10.1016/j.xpro.2025.104292
  9. bioRxiv. 2025 Dec 19. pii: 2025.12.17.694935. [Epub ahead of print]
      best4 +/CFTR-high expressing cells are a recently described intestinal epithelial cell type potentially altered in inflammatory bowel disease and colorectal cancer. However, their developmental origin, developmental regulation, and functions remain undefined. This study identifies their conserved transcriptional program and uses zebrafish to dissect their developmental regulation in vivo . Lineage tracing identified that best4 + cells arise from atoh1b + secretory progenitors. We identify that Notch signaling, mediated by dll4, specifies best4 + cells at the expense of enterochromaffin cells. Downstream of Notch, meis1b confers best4 + cell identity. best4 + cells then exhibit regionalized gene expression, regulated by pbx3a . Additionally, this study demonstrates a system where best4 + cells can be manipulated, observed, and removed in an organismal context. Live imaging and electron microscopy of best4 + cells identified dynamic cellular projections, suggesting a sensory or communicative function. Removal of best4 + cells in vivo eliminated previously proposed functions: they are not required to restore intestinal pH following acidic challenge and do not absorb nutrients. However, we identify region-specific intracellular pH differences that suggest potential functional heterogeneity. Altogether, this study presents a comprehensive description of best4 + cell development from birth to spatial regulation that will be instrumental to understand how best4 + cells change in disease or might be therapeutically manipulated and presents the tools to dissect their function in vivo .
    DOI:  https://doi.org/10.64898/2025.12.17.694935
  10. Mol Cell Proteomics. 2025 Dec 19. pii: S1535-9476(25)00592-4. [Epub ahead of print] 101493
      Cell-cell communications are widely explored to understand tissue homeostasis and diseases. Numerous computational tools have been developed to infer cellular interactions from transcriptomic or proteomic expression data. However, proteins often carry post-translational modifications (PTMs) that can induce conformational switches and alter their functional properties. A key challenge remains to incorporate PTM data in the inference and analysis of cellular interactions. Here, we propose an extension of our previously published tool BulkSignalR to integrate PTM information in ligand-receptor interactions and downstream pathways predictions. This new functionality is compatible with bulk and single-cell data, and it supports all types of PTMs. Based on two illustrative datasets, we show that this new feature provides deeper insights into biological pathway regulation, and that PTM integration helps reducing false positive results occasionally produced by standard approaches.
    DOI:  https://doi.org/10.1016/j.mcpro.2025.101493
  11. MedComm (2020). 2025 Dec;6(12): e70531
      Organoids are three-dimensional structures that closely resemble the architecture and functions of human organs, offering key advantages over traditional models by better replicating tissue complexity and cellular interactions. These systems have become invaluable tools for disease modeling, drug screening, and regenerative medicine applications. Despite this progress, their lack of immune components limits their usefulness in diseases where immune cells are central drivers of pathology and therapy. The absence of an immune system within organoids limits their physiological relevance, particularly for cancer, inflammation, and autoimmunity research. Immune cell-containing organoids provide a comprehensive platform for immunotherapy, host-pathogen interactions, regeneration, and immune disorders. This review first highlights the transformative potential of immune cell-containing organoids across cancer, infection, inflammation, autoimmunity, regeneration, and the modeling of primary lymphoid organs. It then examines current strategies for integrating immune cells into organoids, the variety of immune cell sources employed, and the challenges in maintaining immune cell function. Finally, the role of bioengineering, biobanking, and artificial intelligence in overcoming existing limitations and enhancing immune system modeling is discussed. Overall, this study positions immune cell-containing organoids as powerful platforms for translational research and precision medicine.
    Keywords:  cancer; immune cell; inflammation; organoid; pluripotent stem cell; regenerative medicine
    DOI:  https://doi.org/10.1002/mco2.70531
  12. Clin Transl Oncol. 2025 Dec 22.
       BACKGROUND: Colorectal cancer (CRC) exhibits substantial heterogeneity within the tumor microenvironment (TME), which complicates both diagnosis and treatment.
    OBJECTIVE: This study aimed to explore the cellular composition of CRC through single-cell RNA sequencing (scRNA-seq) and integrate this data with bulk RNA-seq to identify prognostic markers and characterize tumor heterogeneity.
    METHODS: scRNA-seq data from 17 CRC samples were analyzed to identify distinct cell clusters and infer cellular trajectories using computational approaches. Bulk RNA-seq data from 566 CRC samples were subsequently employed to genotype patients based on marker genes identified from the single-cell analysis. Survival and clinical correlation analyses were conducted to assess the prognostic relevance of the identified molecular subtypes.
    RESULTS: Single-cell analysis identified 14 distinct cell clusters, including epithelial, immune, and stromal cells, highlighting the TME's complexity. Trajectory inference revealed three major cellular states, with epithelial cells predominantly representing an early-stage phenotype. Genotyping of patients using bulk RNA-seq data delineated three prognostic clusters, with cluster 2 showing significantly poorer survival and an association with advanced tumor stages.
    CONCLUSION: This study offers a detailed characterization of CRC heterogeneity, identifying key cellular subpopulations and prognostic molecular subtypes. The integration of single-cell and bulk transcriptomic data provides valuable insights into CRC biology and potential prognostic markers. Further functional validation is required to fully understand the clinical implications of these findings.
    Keywords:  Colorectal cancer; Single-cell RNA sequencing; Tumor heterogeneity
    DOI:  https://doi.org/10.1007/s12094-025-04153-z
  13. Nat Cell Biol. 2025 Dec 24.
      Gene activation and coregulation have been attributed to different mechanisms, such as enhancer-promoter interactions via chromatin looping or the accumulation of transcription factors into hubs or condensates. However, genome-wide studies exploring mechanistic differences in endogenous gene regulation in primary human cells are scarce. Here we dissect the proinflammatory gene expression programme induced by tumor necrosis factor (TNF) in human endothelial cells using sequencing- and imaging-based methods. Our findings, enabled by the co-accessibility analysis of deep-coverage single-cell chromatin accessibility data with our RWireX software, identified two distinct regulatory chromatin modules: autonomous links of co-accessibility (ACs) between separated sites and domains of contiguous co-accessibility (DCs) with increased local transcription factor binding. The TNF-dependent induction timing and strength as well as changes in transcriptional bursting kinetics differed for genes in the AC and DC modules, pointing to functionally distinct regulatory mechanisms. These findings provide a framework for understanding how cells achieve rapid and precise control of gene expression.
    DOI:  https://doi.org/10.1038/s41556-025-01819-2
  14. Biomimetics (Basel). 2025 Dec 17. pii: 845. [Epub ahead of print]10(12):
      Organoids are self-organizing three-dimensional (3D) cellular structures derived from stem cells. They can mimic the anatomical and functional properties of real organs. They have transformed in vitro disease modeling by closely replicating the structural and functional characteristics of human tissues. The complexity and variability of organoid-derived data pose significant challenges for analysis and clinical translation. Artificial Intelligence (AI) has emerged as a crucial enabler, offering scalable and high-throughput tools for interpreting imaging data, integrating multi-omics profiles, and guiding experimental workflows. This review aims to discuss how AI is reshaping organoid-based research by enhancing morphological image analysis, enabling dynamic modeling of organoid development, and facilitating the integration of genomics, transcriptomics, and proteomics for disease classification. Moreover, AI is increasingly used to support drug screening and personalize therapeutic strategies by analyzing patient-derived organoids. The integration of AI with organoid-on-chip systems further allows for real-time feedback and physiologically relevant modeling. Drawing on peer-reviewed literature from the past decade, Furthermore, CNNs have been used to analyze colonoscopy and histopathological images in colorectal cancer with over 95% diagnostic accuracy. We examine key tools, innovations, and case studies that illustrate this evolving interface. As this interdisciplinary field matures, the future of AI-integrated organoid platforms depends on establishing open data standards, advancing algorithms, and addressing ethical and regulatory considerations to unlock their clinical and translational potential.
    Keywords:  3D; artificial intelligence; disease modeling; organoid; stem cell
    DOI:  https://doi.org/10.3390/biomimetics10120845
  15. bioRxiv. 2025 Dec 19. pii: 2025.12.17.694784. [Epub ahead of print]
      Cancer cell adaptation to their physical tumor microenvironment is a key driver of malignancy. Recent experimental evolution experiments show that the soft extracellular matrix (ECM) can impose a selection pressure on genetically variable tumor populations. Over months of sustained culture, the selection pressure leads to enrichment of specific genetic variants with high fitness, but the mechanisms underlying the high fitness of these soft-selected clones are not fully understood. Here, we used a combination of RNA-seq, ATAC-seq, and RRBS-seq to compare soft-selected populations with non-selected ancestral populations cultured on soft ECM. We demonstrate that ancestral populations grown on soft ECM for short durations are characterized by a stressed cell state with low fitness marked by cell cycle arrest and distinct metabolic shifts, whereas sustained culture selects for a robust proliferative phenotype. Mechanistically, selected cells exhibit a silenced ancestral stress response through epigenetic modifications, characterized by reduced chromatin accessibility and de novo DNA methylation, including CDH1 promoter hypermethylation. This repressive landscape supports a high-fitness state defined by elevated MYBL2 and FAK levels. An in-silico mechanism-based model shows that these molecular differences, together with high YAP1 nuclear localization in soft-selected cells, are salient features of genetic clones capable of FAK upregulation. These findings uncover a coordinated genetic and epigenetic mechanism driving cancer cell evolution in mechanically soft microenvironments.
    DOI:  https://doi.org/10.64898/2025.12.17.694784