bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–04–20
eighteen papers selected by
Xiao Qin, University of Oxford
  1. scMultiSim: simulation of single-cell multi-omics and spatial data guided by gene regulatory networks and cell-cell interactions.
  2. Towards multimodal foundation models in molecular cell biology.
  3. Fate and state transitions during human blood vessel organoid development.
  4. Unified molecular approach for spatial epigenome, transcriptome, and cell lineages.
  5. Rewriting regulatory DNA to dissect and reprogram gene expression.
  6. Bridging the gap: The future of cancer research and clinical oncology in Cancer Cell.
  7. New horizons at the interface of artificial intelligence and translational cancer research.
  8. Emerging roles of transcriptional condensates as temporal signal integrators.
  9. A multi-step completion process model of cell plasticity.
  10. Low overlap of transcription factor DNA binding and regulatory targets.
  11. Combining spatial transcriptomics and ECM imaging in 3D for mapping cellular interactions in the tumor microenvironment.
  12. CRISPR-StAR to transform in vivo functional genomic screening.
  13. Generation of human adult hepatocyte organoids with metabolic functions.
  14. Limitations and optimizations of cellular lineages tracking.
  15. Impact of enzymatic isolation on the propagation efficiency of patient-derived colorectal cancer organoids.
  16. From Organoids to Assembloids: Experimental Approaches to Study Human Neuropsychiatric Disorders.
  17. Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network.
  18. Turn cold tumors hot by reprogramming the tumor microenvironment.
  1. Nat Methods. 2025 Apr 17.
    scMultiSim: simulation of single-cell multi-omics and spatial data guided by gene regulatory networks and cell-cell interactions.
    Hechen Li, Ziqi Zhang, Michael Squires, Xi Chen, Xiuwei Zhang.
      Simulated single-cell data are essential for designing and evaluating computational methods in the absence of experimental ground truth. Here we present scMultiSim, a comprehensive simulator that generates multimodal single-cell data encompassing gene expression, chromatin accessibility, RNA velocity and spatial cell locations while accounting for the relationships between modalities. Unlike existing tools that focus on limited biological factors, scMultiSim simultaneously models cell identity, gene regulatory networks, cell-cell interactions and chromatin accessibility while incorporating technical noise. Moreover, it allows users to adjust each factor's effect easily. Here we show that scMultiSim generates data with expected biological effects, and demonstrate its applications by benchmarking a wide range of computational tasks, including multimodal and multi-batch data integration, RNA velocity estimation, gene regulatory network inference and cell-cell interaction inference using spatially resolved gene expression data. Compared to existing simulators, scMultiSim can benchmark a much broader range of existing computational problems and even new potential tasks.
    DOI:  https://doi.org/10.1038/s41592-025-02651-0
  2. Nature. 2025 Apr;640(8059): 623-633
    Towards multimodal foundation models in molecular cell biology.
    Haotian Cui, Alejandro Tejada-Lapuerta, Maria Brbić, Julio Saez-Rodriguez, Simona Cristea, Hani Goodarzi, Mohammad Lotfollahi, Fabian J Theis, Bo Wang.
      The rapid advent of high-throughput omics technologies has created an exponential growth in biological data, often outpacing our ability to derive molecular insights. Large-language models have shown a way out of this data deluge in natural language processing by integrating massive datasets into a joint model with manifold downstream use cases. Here we envision developing multimodal foundation models, pretrained on diverse omics datasets, including genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial profiling. These models are expected to exhibit unprecedented potential for characterizing the molecular states of cells across a broad continuum, thereby facilitating the creation of holistic maps of cells, genes and tissues. Context-specific transfer learning of the foundation models can empower diverse applications from novel cell-type recognition, biomarker discovery and gene regulation inference, to in silico perturbations. This new paradigm could launch an era of artificial intelligence-empowered analyses, one that promises to unravel the intricate complexities of molecular cell biology, to support experimental design and, more broadly, to profoundly extend our understanding of life sciences.
    DOI:  https://doi.org/10.1038/s41586-025-08710-y
  3. Cell. 2025 Apr 16. pii: S0092-8674(25)00387-3. [Epub ahead of print]
    Fate and state transitions during human blood vessel organoid development.
    Marina T Nikolova, Zhisong He, Makiko Seimiya, Gustav Jonsson, Wuji Cao, Ryo Okuda, Reiner A Wimmer, Ryoko Okamoto, Josef M Penninger, J Gray Camp, Barbara Treutlein.
      Human blood vessel organoids (hBVOs) have emerged as a system to model human vascular development and disease. Here, we use single-cell multi-omics together with genetic and signaling pathway perturbations to reconstruct hBVO development. Mesodermal progenitors bifurcate into endothelial and mural fates in vitro, and xenografted BVOs acquire definitive arteriovenous endothelial cell specification. We infer a gene regulatory network and use single-cell genetic perturbations to identify transcription factors (TFs) and receptors involved in cell fate specification, including a role for MECOM in endothelial and mural specification. We assess the potential of BVOs to generate organotypic states, identify TFs lacking expression in hBVOs, and find that induced LEF1 overexpression increases brain vasculature specificity. Finally, we map vascular disease-associated genes to hBVO cell states and analyze an hBVO model of diabetes. Altogether, we provide a comprehensive cell state atlas of hBVO development and illuminate the power and limitation of hBVOs for translational research.
    Keywords:  arteriovenous specification; human blood vessel organoid; human development; organoid cell atlas; single-cell genomics; single-cell perturbation screen
    DOI:  https://doi.org/10.1016/j.cell.2025.03.037
  4. Proc Natl Acad Sci U S A. 2025 Apr 22. 122(16): e2424070122
    Unified molecular approach for spatial epigenome, transcriptome, and cell lineages.
    Yung-Hsin Huang, Julia A Belk, Ruochi Zhang, Natasha E Weiser, Zachary Chiang, Matthew G Jones, Paul S Mischel, Jason D Buenrostro, Howard Y Chang.
      Spatial epigenomics and multiomics can provide fine-grained insights into cellular states but their widespread adoption is limited by the requirement for bespoke slides and capture chemistries for each data modality. Here, we present SPatial assay for Accessible chromatin, Cell lineages, and gene Expression with sequencing (SPACE-seq), a method that utilizes polyadenine-tailed epigenomic libraries to enable facile spatial multiomics using standard whole transcriptome reagents. Applying SPACE-seq to a human glioblastoma specimen, we reveal the state of the tumor microenvironment, extrachromosomal DNA copy numbers, and identify putative mitochondrial DNA variants.
    Keywords:  cell lineages; chromatin accessibility; spatial genomics; spatial multiomics
    DOI:  https://doi.org/10.1073/pnas.2424070122
  5. Cell. 2025 Apr 14. pii: S0092-8674(25)00352-6. [Epub ahead of print]
    Rewriting regulatory DNA to dissect and reprogram gene expression.
    Gabriella E Martyn, Michael T Montgomery, Hank Jones, Katherine Guo, Benjamin R Doughty, Johannes Linder, Deepa Bisht, Fan Xia, Xiangmeng S Cai, Ziwei Chen, Kelly Cochran, Kathryn A Lawrence, Glen Munson, Anusri Pampari, Charles P Fulco, Nidhi Sahni, David R Kelley, Eric S Lander, Anshul Kundaje, Jesse M Engreitz.
      Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context.
    Keywords:  CRISPR; RNA FlowFISH; enhancers; gene regulation; high-throughput screening; non-coding variants; predictive models; prime editing; sequence design; transcription factors
    DOI:  https://doi.org/10.1016/j.cell.2025.03.034
  6. Cancer Cell. 2025 Apr 14. pii: S1535-6108(25)00125-4. [Epub ahead of print]43(4): 575-576
    Bridging the gap: The future of cancer research and clinical oncology in Cancer Cell.
    Steve Mao.
      
    DOI:  https://doi.org/10.1016/j.ccell.2025.03.024
  7. Cancer Cell. 2025 Apr 14. pii: S1535-6108(25)00119-9. [Epub ahead of print]43(4): 708-727
    New horizons at the interface of artificial intelligence and translational cancer research.
    Josephine Yates, Eliezer M Van Allen.
      Artificial intelligence (AI) is increasingly being utilized in cancer research as a computational strategy for analyzing multiomics datasets. Advances in single-cell and spatial profiling technologies have contributed significantly to our understanding of tumor biology, and AI methodologies are now being applied to accelerate translational efforts, including target discovery, biomarker identification, patient stratification, and therapeutic response prediction. Despite these advancements, the integration of AI into clinical workflows remains limited, presenting both challenges and opportunities. This review discusses AI applications in multiomics analysis and translational oncology, emphasizing their role in advancing biological discoveries and informing clinical decision-making. Key areas of focus include cellular heterogeneity, tumor microenvironment interactions, and AI-aided diagnostics. Challenges such as reproducibility, interpretability of AI models, and clinical integration are explored, with attention to strategies for addressing these hurdles. Together, these developments underscore the potential of AI and multiomics to enhance precision oncology and contribute to advancements in cancer care.
    Keywords:  AI-aided diagnostics; artificial intelligence; cancer; machine learning; multiomics; translational oncology
    DOI:  https://doi.org/10.1016/j.ccell.2025.03.018
  8. Nat Rev Genet. 2025 Apr 16.
    Emerging roles of transcriptional condensates as temporal signal integrators.
    Kirstin Meyer, Bo Huang, Orion D Weiner.
      Transcription factors relay information from the external environment to gene regulatory networks that control cell physiology. To confer signalling specificity, robustness and coordination, these signalling networks use temporal communication codes, such as the amplitude, duration or frequency of signals. Although much is known about how temporal information is encoded, a mechanistic understanding of how gene regulatory networks decode signalling dynamics is lacking. Recent advances in our understanding of phase separation of transcriptional condensates provide new biophysical frameworks for both temporal encoding and decoding mechanisms. In this Perspective, we summarize the mechanisms by which transcriptional condensates could enable temporal decoding through signal adaptation, memory and persistence. We further outline methods to probe and manipulate dynamic communication codes of transcription factors and condensates to rationally control gene activation.
    DOI:  https://doi.org/10.1038/s41576-025-00837-y
  9. Brief Bioinform. 2025 Mar 04. pii: bbaf165. [Epub ahead of print]26(2):
    A multi-step completion process model of cell plasticity.
    Chen M Chen, Rosemary Yu.
      Plasticity is the potential for cells or cell populations to change their phenotypes and behaviors in response to internal or external cues. Plasticity is fundamental to many complex biological processes, yet to date there remains a lack of mathematical models that can elucidate and predict molecular behaviors in a plasticity program. Here, we report a new mathematical framework that models cell plasticity as a multi-step completion process, where the system moves from the initial state along a path guided by multiple intermediate attractors until the final state (i.e. a new homeostasis) is reached. Using omics time-series data as model input, we show that our method fits data well; identifies attractor states by their timing and molecular markers which are well-aligned with domain knowledge; and can make quantitative and time-resolved predictions such as the molecular outcomes of blocking a plasticity program from reaching completion, to an R2 of 0.53-0.63. We demonstrate that application of our model to primary patient-derived data can provide quantitative insights and predictions that may be useful in guiding further research and potential biomedical interventions.
    Keywords:  cell plasticity; completion process; mathematical modeling; time-series omics data
    DOI:  https://doi.org/10.1093/bib/bbaf165
  10. Nature. 2025 Apr 16.
    Low overlap of transcription factor DNA binding and regulatory targets.
    Lakshmi Mahendrawada, Linda Warfield, Rafal Donczew, Steven Hahn.
      DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes1,2. How multiple TFs cooperate to regulate individual genes is still unclear. In yeast, most TFs are thought to regulate transcription via binding to upstream activating sequences, which are situated within a few hundred base pairs upstream of the regulated gene3. Although this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way. Here we integrated information on the binding and expression targets for the near-complete set of yeast TFs and show that, contrary to expectations, there are few TFs with dedicated activator or repressor roles, and that most TFs have a dual function. Although nearly all protein-coding genes are regulated by one or more TFs, our analysis revealed limited overlap between TF binding and gene regulation. Rapid depletion of many TFs also revealed many regulatory targets that were distant from detectable TF binding sites, suggesting unexpected regulatory mechanisms. Our study provides a comprehensive survey of TF functions and offers insights into interactions between the set of TFs expressed in a single cell type and how they contribute to the complex programme of gene regulation.
    DOI:  https://doi.org/10.1038/s41586-025-08916-0
  11. Cell Syst. 2025 Apr 09. pii: S2405-4712(25)00094-8. [Epub ahead of print] 101261
    Combining spatial transcriptomics and ECM imaging in 3D for mapping cellular interactions in the tumor microenvironment.
    Tancredi Massimo Pentimalli, Simon Schallenberg, Daniel León-Periñán, Ivano Legnini, Ilan Theurillat, Gwendolin Thomas, Anastasiya Boltengagen, Sonja Fritzsche, Jose Nimo, Lukas Ruff, Gabriel Dernbach, Philipp Jurmeister, Sarah Murphy, Mark T Gregory, Yan Liang, Michelangelo Cordenonsi, Stefano Piccolo, Fabian Coscia, Andrew Woehler, Nikos Karaiskos, Frederick Klauschen, Nikolaus Rajewsky.
      Tumors are complex ecosystems composed of malignant and non-malignant cells embedded in a dynamic extracellular matrix (ECM). In the tumor microenvironment, molecular phenotypes are controlled by cell-cell and ECM interactions in 3D cellular neighborhoods (CNs). While their inhibition can impede tumor progression, routine molecular tumor profiling fails to capture cellular interactions. Single-cell spatial transcriptomics (ST) maps receptor-ligand interactions but usually remains limited to 2D tissue sections and lacks ECM readouts. Here, we integrate 3D ST with ECM imaging in serial sections from one clinical lung carcinoma to systematically quantify molecular states, cell-cell interactions, and ECM remodeling in CN. Our integrative analysis pinpointed known immune escape and tumor invasion mechanisms, revealing several druggable drivers of tumor progression in the patient under study. This proof-of-principle study highlights the potential of in-depth CN profiling in routine clinical samples to inform microenvironment-directed therapies. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  3D; cell-cell interactions; epithelial-to-mesenchymal transition; extracellular matrix; non small cell lung cancer; personalized oncology; second harmonic imaging; spatial transcriptomics; systems medicine; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.cels.2025.101261
  12. Nat Rev Cancer. 2025 Apr 16.
    CRISPR-StAR to transform in vivo functional genomic screening.
    Christopher Lowden.
      
    DOI:  https://doi.org/10.1038/s41568-025-00818-7
  13. Nature. 2025 Apr 16.
    Generation of human adult hepatocyte organoids with metabolic functions.
    Ryo Igarashi, Mayumi Oda, Ryo Okada, Tomoki Yano, Sirirat Takahashi, Strahil Pastuhov, Mami Matano, Norio Masuda, Kazuhiro Togasaki, Yuki Ohta, Saeko Sato, Takako Hishiki, Makoto Suematsu, Manabu Itoh, Masayuki Fujii, Toshiro Sato.
      Proliferating hepatocytes often undergo ductal metaplasia to balance the energy trade-off between cellular functions and replication, hindering the expansion of human adult hepatocytes with functional competency1. Here we demonstrate that the combined activation of Wnt and STAT3 signalling enables long-term self-renewal of human adult hepatocyte organoids. YAP activation facilitates hepatocyte proliferation but commits it towards the biliary duct lineage. By contrast, STAT3 activation by oncostatin M induces hepatocyte proliferation while counteracting ductal metaplasia and maintaining the hepatic identity. Xenotransplanted hepatocyte organoids repopulate the recipient mouse liver and reconstitute the metabolic zonation structure. Upon niche factor removal and hormone supplementation, hepatocyte organoids form cord-like structures with bile canalicular networks and exhibit major liver metabolic functions comparable to those of in vivo hepatocytes. Hepatocyte organoids are amenable to gene editing, prompting functional modelling of inherent metabolic liver diseases. The new culture system offers a promising avenue for developing therapeutic strategies against human liver diseases.
    DOI:  https://doi.org/10.1038/s41586-025-08861-y
  14. PLoS Comput Biol. 2025 Apr;21(4): e1012880
    Limitations and optimizations of cellular lineages tracking.
    Nava Leibovich, Sidhartha Goyal.
      Tracking cellular lineages using genetic barcodes provides insights across biology and has become an important tool. However, barcoding strategies remain ad hoc. We show that elevating barcode insertion probability and thus increasing the average number of barcodes within the cells, adds to the number of traceable lineages but may decrease the accuracy of lineages inference due to reading errors. We establish the trade-off between accuracy in tracing lineages and the total number of traceable lineages, and find optimal experimental parameters under limited resources concerning the populations size of tracked cells and barcode pool complexity.
    DOI:  https://doi.org/10.1371/journal.pcbi.1012880
  15. Sci Rep. 2025 Apr 18. 15(1): 13452
    Impact of enzymatic isolation on the propagation efficiency of patient-derived colorectal cancer organoids.
    Gizem Calibasi-Kocal, Tolga Sever, Aras Emre Canda, Leman Evren Kadioglu, Halil Ates, Yasemin Basbinar, Ender Ellidokuz.
      Cancer organoids are three-dimensional in vitro models that closely replicate the genetic, phenotypic, and heterogeneity characteristics of original tumors, making them valuable tools in cancer research. However, the lack of standardized protocols limits their broader application. This study evaluates the role of enzymatic isolation in generating patient-derived organoids (PDOs) from colorectal cancer tissues by comparing four enzymatic methods: TrypLE, Trypsin-EDTA (T/E), Collagenase, and Hyaluronidase. Colorectal cancer tissues were processed using these enzymes, and cell viability, dissociation efficiency, and isolation quality were assessed via Trypan Blue exclusion assay and 7-AAD staining with flow cytometry. Cancer stem cells marked by LGR5 and CD133 were quantified via flow cytometry, while organoid generation and growth were monitored over 11 days using confocal microscopy. TrypLE and T/E demonstrated superior preservation of cell viability but limited dissociation efficiency, yielding lower cell count per milligram of tissue. In contrast, Collagenase and Hyaluronidase demonstrated superior tissue dissociation, yielding higher total cell counts and the highest proportions of LGR5positive and CD133positive stem cell populations. Collagenase produced the highest organoid counts, while Hyaluronidase supported the largest organoid expansion, with both enzymes generating larger organoid surface areas and a greater number of organoids compared to TrypLE and T/E. These results highlight Collagenase and Hyaluronidase as optimal choices for PDO generation, providing a framework for optimizing dissociation protocols. This study underscores the critical influence of enzymatic dissociation methods on the establishment and reliability of colorectal cancer patient-derived organoids, providing a foundation for optimizing PDO protocols and advancing their translational application in precision oncology.
    Keywords:  Colorectal cancer; Enzymatic cell isolation; Organoid culture
    DOI:  https://doi.org/10.1038/s41598-025-97650-8
  16. Annu Rev Neurosci. 2025 Apr 18.
    From Organoids to Assembloids: Experimental Approaches to Study Human Neuropsychiatric Disorders.
    Rebecca J Levy, Sergiu P Paşca.
      To understand the pathophysiology and develop effective therapeutics for brain disorders, some of which may involve uniquely human features of the nervous system, scalable human models of neural cell diversity and circuit formation are essential. The discovery of cell reprogramming and the development of approaches for generating stem cell-derived neurons and glial cells in 3D preparations known as neural organoids and assembloids, both in vitro and following transplantation in vivo, provide new opportunities to tackle these challenges. Here, we outline strengths and limitations of currently available human experimental models as applied to neurological and psychiatric disorders for both environmental and genetic risk factors, and we discuss how these new tools hold promise for accelerating the development of therapeutics.
    DOI:  https://doi.org/10.1146/annurev-neuro-112723-023232
  17. Nucleic Acids Res. 2025 Apr 10. pii: gkaf297. [Epub ahead of print]53(7):
    Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network.
    Thomas Stuart Wilson, Roberta Noberini, Eirini Moysidou, Ifeyinwa Ojukwu, Marta Milan, Ming Jiang, Gavin Kelly, Michael Howell, Tiziana Bonaldi, Paola Scaffidi.
      The molecular control of epigenetic information relies on hundreds of proteins of diverse function, which cooperate in defining chromatin structure and DNA methylation landscapes. While many individual pathways have been characterized, how different classes of epigenetic regulators interact to build a resilient epigenetic regulatory network (ERN) remains poorly understood. Here, we show that most individual regulators are dispensable for somatic cell fitness, and that robustness emerges from multiple layers of functional cooperation and degeneracy among network components. By disrupting 200 epigenetic regulator genes, individually or in combination, we generated network-wide maps of functional interactions for representative regulators. We found that paralogues represent only a first layer of functional compensation within the ERN, with intra- or inter-class interactions buffering the effects of perturbation in a gene-specific manner: while CREBBP cooperates with multiple acetyltransferases to form a subnetwork that ensures robust chromatin acetylation, ARID1A interacts with regulators from across all functional classes. When combined with oncogene activation, the accumulated epigenetic disorder exposes a synthetic fragility and broadly sensitizes ARID1A-deficient cells to further perturbation. Our findings reveal homeostatic mechanisms through which the ERN sustains somatic cell fitness and uncover how the network remodels as the epigenome is progressively deregulated in disease.
    DOI:  https://doi.org/10.1093/nar/gkaf297
  18. Nat Biotechnol. 2025 Apr;43(4): 466-470
    Turn cold tumors hot by reprogramming the tumor microenvironment.
    Xiangliang Yuan, Yi Xiao, Dihua Yu.
      
    DOI:  https://doi.org/10.1038/s41587-025-02597-w
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