bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–12–14
25 papers selected by
Xiao Qin, University of Oxford
  1. Spatially defined multicellular functional units in colorectal cancer revealed from single cell and spatial transcriptomics.
  2. Dissecting cellular ecosystem with single-cell CRISPR screens.
  3. The virtual cell.
  4. Inferring cell differentiation maps from lineage tracing data.
  5. Cracking the cancer microbiome.
  6. Human gut M cells resemble dendritic cells and present gluten antigen.
  7. Targeting asymmetric division in cancer stem cells: implications for relapse and resistance.
  8. Generative epigenetic landscapes map the topology and topography of cell fates.
  9. From Cells to Organoids: Approaches, Regulatory Mechanisms, Applications, and Challenges of Organoids.
  10. A next-generation dual guide CRISPR system for genetic interaction library screening.
  11. Method of the Year: EM connectomics.
  12. Targeting ferroptosis in cancer.
  13. Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation.
  14. Single cell transcriptional perturbome in pluripotent stem cell models.
  15. Artificial intelligence agents for biology.
  16. Reconstructing the lifelong history of cells and tissues via somatic mutation analysis.
  17. Method of the Year 2025: electron microscopy-based connectomics.
  18. Causal modelling of gene effects from regulators to programs to traits.
  19. Biomaterial-minimalistic photoactivated bioprinting of cell-dense tissues.
  20. Epigenetic control of metabolic identity across cell types.
  21. Clonal cell states link gastroesophageal junction tissues with metaplasia and cancer.
  22. N6-Methyladenosine: an RNA modification as a central regulator of cancer.
  23. MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data.
  24. Engineering tumor spatial heterogeneity in vitro.
  25. Benchmarking algorithms for generalizable single-cell perturbation response prediction.
  1. Elife. 2025 Dec 12. pii: RP104815. [Epub ahead of print]14
    Spatially defined multicellular functional units in colorectal cancer revealed from single cell and spatial transcriptomics.
    Inbal Avraham-Davidi, Simon Mages, Johanna Klughammer, Noa Moriel, Shinya Imada, Matan Hofree, Evan Murray, Jonathan Chen, Karin Pelka, Arnav Mehta, Genevieve M Boland, Toni Delorey, Leah Caplan, Danielle Dionne, Robert Strasser, Jana Lalakova, Anezka Niesnerova, Hao Xu, Morgane Rouault, Itay Tirosh, Hacohen Nir, Fei Chen, Omer Yilmaz, Jatin Roper, Orit Rozenblatt-Rosen, Mor Nitzan, Aviv Regev.
      While advances in single-cell genomics have helped to chart the cellular components of tumor ecosystems, it has been more challenging to characterize their specific spatial organization and functional interactions. Here, we combine single-cell RNA-seq, spatial transcriptomics by Slide-seq, and in situ multiplex RNA analysis to create a detailed spatial map of healthy and dysplastic colon cellular ecosystems and their association with disease progression. We profiled inducible genetic CRC mouse models that recapitulate key features of human CRC, assigned cell types and epithelial expression programs to spatial tissue locations in tumors, and computationally used them to identify the regional features spanning different cells in the same spatial niche. We find that tumors were organized in cellular neighborhoods, each with a distinct composition of cell subtypes, expression programs, and local cellular interactions. Comparing to scRNA-seq and bulk RNA-seq data from human CRC, we find that both cell composition and layout features were conserved between the species, with mouse neighborhoods correlating with malignancy and clinical outcome in human patient tumors, highlighting the relevance of our findings to human disease. Our work offers a comprehensive framework that is applicable across various tissues, tumors, and disease conditions, with tools for the extrapolation of findings from experimental mouse models to human diseases.
    Keywords:  cancer biology; colorectal cancer; mouse; spatial transcriptomics; tumor microenvironment
    DOI:  https://doi.org/10.7554/eLife.104815
  2. Blood Sci. 2025 Dec;7(4): e00266
    Dissecting cellular ecosystem with single-cell CRISPR screens.
    Zhirui Liu, Zilin Lan, Xiaoli Kang, Yao Yao, Shuquan Rao.
      Clustered regularly interspaced short palindromic repeats (CRISPR) screens represent a transformative force in biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications. Traditional screening approaches predominantly hinge on cell fitness or established markers, which inherently constrain their abilities for unbiased biological discovery. By contrast, single-cell CRISPR screening technologies, which combine pooled CRISPR screens with an array of sophisticated single-cell omics platforms, permit comprehensive profiling of the transcriptome and epigenome following individual genetic manipulations within complex cellular ecosystems. Over the past decade, a panoply of single-cell CRISPR platforms has emerged, each tailored to address specific experimental challenges. Iterative refinements in protocols have bolstered precision, scalability, and reproducibility, thereby enormously advancing functional genomics and translational research. However, technical obstacles such as perturbation efficiency, scalability, and data integration persist, necessitating cross-disciplinary collaboration and innovation. As single-cell CRISPR platforms evolve to incorporate spatial resolution, multi-omics integration, and AI-guided design, they are poised to bridge the gap between genetic perturbation and system-level interpretation. Here, we summarize recent advances in single-cell CRISPR technologies, outline their applications, and provide a comparative framework to guide platform selection (Perturb-seq, CROP-seq, ECCITE-seq, Direct-seq, and Mosaic-seq).
    Keywords:  Functional genomics; Single-cell CRISPR screen
    DOI:  https://doi.org/10.1097/BS9.0000000000000266
  3. Nat Methods. 2025 Dec;22(12): 2493
    The virtual cell.
    Lin Tang.
      
    DOI:  https://doi.org/10.1038/s41592-025-02951-5
  4. Nat Methods. 2025 Dec 08.
    Inferring cell differentiation maps from lineage tracing data.
    Palash Sashittal, Richard Y Zhang, Benjamin K Law, Henri Schmidt, Alexander Strzalkowski, Adriano Bolondi, Michelle M Chan, Benjamin J Raphael.
      During development, cells differentiate through a hierarchy of increasingly restricted cell types, a process that is summarized by a cell differentiation map. Recent technologies profile lineages and cell types at scale, but existing methods to infer cell differentiation maps from these data rely on heuristic models with restrictive assumptions about the developmental process. Here we introduce a quantitative framework to evaluate cell differentiation maps and develop an algorithm, called Carta, that infers an optimal differentiation map from single-cell lineage tracing data. The key insight in Carta is to balance the tradeoff between the complexity of the map and the number of unobserved cell type transitions on the lineage tree. We show that, in models of mammalian trunk development and mouse hematopoiesis, Carta identifies important features of development that are not revealed by other methods, including convergent differentiation of cell types, progenitor differentiation dynamics and new intermediate progenitors.
    DOI:  https://doi.org/10.1038/s41592-025-02903-z
  5. Nat Methods. 2025 Dec;22(12): 2494
    Cracking the cancer microbiome.
    Madhura Mukhopadhyay.
      
    DOI:  https://doi.org/10.1038/s41592-025-02953-3
  6. Nature. 2025 Dec 10.
    Human gut M cells resemble dendritic cells and present gluten antigen.
    Daisong Wang, Sangho Lim, Willine J van de Wetering, Carmen Lopez-Iglesias, Yuu Okura, Yuri Teranishi-Ikawa, Akihiko Mizoroki, Willem Kasper Spoelstra, Talya Dayton, Gijs J F van Son, Apollo Pronk, Niels Smakman, Gieneke B C Gonera-de Jong, Sebo Withoff, Iris H Jonkers, Jeroen S van Zon, Sander J Tans, Peter J Peters, Johan H van Es, Hans Clevers.
      Microfold (M) cells are rare intestinal epithelial cells that reside in the follicle-associated epithelium of Peyer's patches1. M cells transport luminal antigens to submucosal antigen-presenting cells2,3. These insights primarily derive from transmission electron microscopy and studies using genetically modified mice2-4. Here we establish an intestinal organoid model to study human M cells and reconstruct the differentiation trajectory of M cells through transcriptome profiling. The results indicate that as well as facilitating luminal antigen transport, human M cells also directly present antigens via the class II major histocompatibility complex (MHC-II). Notably, the related enterocytes only express MHC-II in chronic inflammatory states and do not express typical dendritic cell markers. Human M cells physiologically express a gene profile that resembles that of dendritic cells. Similar to dendritic cells, M cell development is induced by RANKL and CSF2 and requires the transcription factors SPIB and RUNX2. HLA-DQ2.5 M cells process and present gluten antigen as demonstrated in organoid-T cell co-culture assays. These findings suggest that M cells may have a central role in coeliac disease.
    DOI:  https://doi.org/10.1038/s41586-025-09829-8
  7. Cancer Cell Int. 2025 Dec 08. 25(1): 434
    Targeting asymmetric division in cancer stem cells: implications for relapse and resistance.
    Mona Latifi, Mahsa Sani, Farnaz Sani.
      Cancer stem cells (CSCs) represent a resilient subpopulation within tumors, capable of driving progression, metastasis, and recurrence. One mechanism that enables this plasticity is asymmetric cell division (ACD), a process by which CSCs generate both a self-renewing stem cell and a differentiated daughter cell. While traditionally associated with tissue development, ACD is now recognized as a dynamic and regulated feature of cancer biology, particularly in response to stress conditions such as hypoxia and radiation. In this review, we provide a comprehensive and mechanistic synthesis of how intrinsic factors such as polarity complexes, cell fate determinants (CFDs), spindle orientation cooperate with extrinsic cues from the tumor microenvironment to orchestrate ACD in CSCs. We explore how this process contributes to tumor heterogeneity, therapy resistance, and the emergence of quiescent, drug-tolerant CSCs across multiple malignancies, including brain, breast, colorectal, and hematologic cancers. Importantly, we highlight recent efforts to pharmacologically disrupt or redirect ACD using inhibitors of NOTCH, WNT, AURORA kinases, and MSI1, presenting ACD as a therapeutic vulnerability rather than a static trait. By shifting the focus from CSC markers to division mode, this review introduces a novel conceptual framework for targeting tumor hierarchy and plasticity. Understanding and manipulating ACD offers a promising frontier in precision oncology - one where altering the balance of cell fate decisions could limit relapse, reduce intratumoral complexity, and enhance long-term treatment outcomes.
    Keywords:  Asymmetric cell division; Cancer stem cells; Stemness and differentiation; Tumor heterogeneity
    DOI:  https://doi.org/10.1186/s12935-025-04052-x
  8. Proc Natl Acad Sci U S A. 2025 Dec 16. 122(50): e2514508122
    Generative epigenetic landscapes map the topology and topography of cell fates.
    Victoria Mochulska, Paul François.
      Epigenetic landscapes were proposed by Waddington as the central concept to describe cell fate dynamics in a locally low-dimensional space. In modern landscape models, attractors represent cell types, and stochastic jumps and bifurcations drive cellular decisions, allowing for quantitative and predictive descriptions. However, given a biological problem of interest, we still lack tools to infer and build possible Waddington landscapes systematically. In this study, we propose a generative model for deriving epigenetic landscapes compatible with data. To build the landscapes, we combine gradient and rotational vector fields composed of locally weighted elements that encode "valleys" of the Waddington landscape, resulting in interpretable models. We optimize landscapes through computational evolution and illustrate our approach with two developmental examples: metazoan segmentation and neuromesoderm differentiation. In both cases, we obtain ensembles of solutions that reveal both known and original landscapes in terms of topology and bifurcations. Conversely, topographic features appear strongly constrained by dynamical data, which suggests that our approach can generically derive interpretable and predictive epigenetic landscapes.
    Keywords:  Waddington landscape; cellular differentiation; dynamical systems; evolution; mathematical modeling
    DOI:  https://doi.org/10.1073/pnas.2514508122
  9. Cells. 2025 Nov 29. pii: 1898. [Epub ahead of print]14(23):
    From Cells to Organoids: Approaches, Regulatory Mechanisms, Applications, and Challenges of Organoids.
    Lihong Wang, Anqi Chen, Dong Zhang, Zuping He.
      Organoids refer to three-dimensional (3D) multicellular tissues derived from stem cells or single cells through their self-assembly capacity, and significantly, they mimic structural and functional characteristics of the organ from which they are derived. Organoids can maintain the gene expression profiles and mutational features of parental cells during long-term culture. This makes organoids more relevant to the human bodies than gene knockout or overexpression animal models. Consequently, organoids have been widely used in various kinds of fields, including studies on organ developmental mechanisms, regenerative medicine, organ repair, the construction of disease models, high-throughput drug screening, and personalized medicine. Notably, significant progress has recently been made in organoid construction methodologies and regulatory mechanisms. These include the selections of starting cell sources, optimizing matrix materials, and the related cell signaling pathways. The rapid development of organoid technologies has provided new opportunities for their applications in organ transplantation, drug and toxicity screening, and molecular mechanisms for cell and tissue development. In this review, we discuss organoid construction methods involving the starting cell selection and spatiotemporal mediation, regulatory mechanisms with signaling molecules and pathways, and their applications in unveiling organogenesis mechanisms and disease etiology, drug screening, toxicity testing, personalized medicine, regenerative medicine, and alternatives to animal experiments. We also address the perspectives and challenges in this field with an aim to promote the development of organoids in basic research and translational medicine.
    Keywords:  biomedicine; molecular mechanisms; organoids; regenerative medicine
    DOI:  https://doi.org/10.3390/cells14231898
  10. Nat Commun. 2025 Dec 06.
    A next-generation dual guide CRISPR system for genetic interaction library screening.
    Thomas Burgold, Emre Karakoc, Emanuel Gonçalves, Inigo Barrio-Hernandez, Lisa Dwane, Romina Silva, Emily Souster, Mamta Sharma, Alexandra Beck, Gene Ching Chiek Koh, Lykourgos-Panagiotis Zalmas, Mathew J Garnett, Andrew R Bassett.
      Pairwise perturbation of gene function using the CRISPR/Cas9 system has potential in screening for genetic interactions and synthetic lethal gene pairs to identify combination therapies for cancer. However, existing dual guide expression systems are cumbersome to clone, often result in a large proportion of undesired guide pairs and have an imbalance of guide expression from the two positions. Here, we demonstrate a next-generation system for dual guide delivery based around a tRNA spacer that allows a single-step cloning strategy, as little as 2% of undesired guide pairs, and highly balanced expression of the two guides. This system allows efficient library-scale screening for hundreds of thousands of genetic interactions using the well-understood Streptococcus pyogenes Cas9 (SpCas9) system. We use this to screen a 100,136 guide pair library in colorectal cancer cells and successfully identify synthetic lethal genetic interactions between paralogs or other known interacting genes, establishing our method for performing efficient large-scale genetic interaction screens. This system is versatile and could be used with most guide RNA vector systems, and for other uses of paired guide delivery, such as improving single gene knockout efficiency or improving guide detection in single cell or optical CRISPR screens.
    DOI:  https://doi.org/10.1038/s41467-025-67256-9
  11. Nat Methods. 2025 Dec;22(12): 2470-2475
    Method of the Year: EM connectomics.
    Vivien Marx.
      
    DOI:  https://doi.org/10.1038/s41592-025-02906-w
  12. Nat Genet. 2025 Dec;57(12): 2942
    Targeting ferroptosis in cancer.
    Safia Danovi.
      
    DOI:  https://doi.org/10.1038/s41588-025-02456-z
  13. Genome Res. 2025 Dec 09.
    Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation.
    Kevin Moyung, Yulong Li, Heather K MacAlpine, Alexander J Hartemink, David M MacAlpine.
      Epigenetic mechanisms contribute to gene regulation by altering chromatin accessibility through changes in transcription factor (TF) and nucleosome occupancy across the genome. Despite numerous studies focusing on changes in gene expression, the intricate chromatin-mediated regulatory code remains largely uncharted on a comprehensive scale. We address this by employing a factor-agnostic, reverse-genetics approach that uses MNase-seq to capture genome-wide TF and nucleosome occupancies in response to the individual deletion of 201 transcriptional regulators in Saccharomyces cerevisiae, thereby assaying nearly 1 million mutant-gene interactions. We develop a principled new approach to identify and quantify chromatin changes genome-wide, allowing us to observe differences in TF and nucleosome occupancy that recapitulate well-established pathways identified by gene expression data. We also discover distinct chromatin signatures associated with the up- and downregulation of genes and use these signatures to reveal regulatory mechanisms previously unexplored in expression-based studies. Finally, we demonstrate that chromatin features are predictive of transcriptional activity, and we leverage these features to reconstruct chromatin-based transcriptional regulatory networks. Overall, these results illustrate the power of an approach combining genetic perturbation with high-resolution epigenomic profiling; the latter enables a close examination of the interplay between TFs and nucleosomes genome-wide, providing a deeper, more mechanistic understanding of the complex relationship between chromatin organization and transcription.
    DOI:  https://doi.org/10.1101/gr.279637.124
  14. Mol Syst Biol. 2025 Dec 10.
    Single cell transcriptional perturbome in pluripotent stem cell models.
    Elisa Balmas, Maria L Ratto, Kirsten E Snijders, Silvia Becca, Carla Liaci, Irene Ricca, Giorgio R Merlo, Raffaele A Calogero, Luca Alessandrì, Sasha Mendjan, Alessandro Bertero.
      Functional genomics screens in human induced pluripotent stem cells (hiPSCs) remain challenging despite their transformative potential. We developed iPS2-seq: an inducible, clone-aware screening platform that enables phenotype-agnostic, single-cell resolved dissection of loss-of-function effects in hiPSC derivatives, including complex multicellular models such as organoids. iPS2-seq distinguishes true perturbation effects from genetic and epigenetic variability. It supports pooled and arrayed formats, integrates with microfluidic or split-pool single-cell RNA sequencing, and extends to multi-omic profiling of chromatin and proteins. A dedicated pipeline, catcheR, streamlines design and analysis. The platform enables stage-specific follow-up dissection of screen hits. We demonstrate this by targeting congenital heart disease-associated genes in monolayer cardiomyocytes and organoids. This reveals that epigenetic neuroectodermal priming interferes with germ layer differentiation in specific clones. Accounting for this bias, we show that SMAD2 controls cardiac progenitor specification, with knockdown redirecting cells toward fibroblast and epicardial fates. iPS2-seq unlocks rigorous functional genomics in hiPSC-based models.
    Keywords:  Functional Genomics; Human Pluripotent Stem Cells; Loss of Function; Pooled Screens; Single-cell RNA-seq
    DOI:  https://doi.org/10.1038/s44320-025-00172-8
  15. Nat Methods. 2025 Dec;22(12): 2496-2497
    Artificial intelligence agents for biology.
    Lin Tang.
      
    DOI:  https://doi.org/10.1038/s41592-025-02958-y
  16. Cell Mol Life Sci. 2025 Dec 08. 82(1): 436
    Reconstructing the lifelong history of cells and tissues via somatic mutation analysis.
    Sipontina Faienza, Jean Piero Margaria, Irene Franco.
      During a lifetime, normal cells accumulate thousands of changes in their genome sequence. These changes, termed somatic mutations, have mostly been studied in the context of cancer, but their presence in normal tissues is ubiquitous and widespread. Somatic mutation accompanies the aging process and is influenced by genetic and environmental factors. Differently from gene expression or imaging data, which fluctuate over time, somatic variants are non-reversible marks in the genome and accumulate over time. This property can be exploited to track the history of a cell, from conception to old age, providing information that cannot be acquired via classical histological tissue inspection nor other types of omics data. Mutations can track embryonic development, measure how clones compete in a tissue over time, or report the mutational processes active in cells and tissues throughout life. We discuss selected examples and emphasize how somatic mutation analysis can enable expanding applications at the service of physiology and cell biology, as well as a deeper understanding of the aging process.
    Keywords:  Aging; Genome; Single cell; Somatic mutation
    DOI:  https://doi.org/10.1007/s00018-025-05946-9
  17. Nat Methods. 2025 Dec;22(12): 2463-2464
    Method of the Year 2025: electron microscopy-based connectomics.
      
    DOI:  https://doi.org/10.1038/s41592-025-02988-6
  18. Nature. 2025 Dec 10.
    Causal modelling of gene effects from regulators to programs to traits.
    Mineto Ota, Jeffrey P Spence, Tony Zeng, Emma Dann, Nikhil Milind, Alexander Marson, Jonathan K Pritchard.
      Genetic association studies provide a unique tool for identifying candidate causal links from genes to human traits and diseases. However, it is challenging to determine the biological mechanisms underlying most associations, and we lack genome-scale approaches for inferring causal mechanistic pathways from genes to cellular functions to traits. Here we propose approaches to bridge this gap by combining quantitative estimates of gene-trait relationships from loss-of-function burden tests1 with gene-regulatory connections inferred from Perturb-seq experiments2 in relevant cell types. By combining these two forms of data, we aim to build causal graphs in which the directional associations of genes with a trait can be explained by their regulatory effects on biological programs or direct effects on the trait3. As a proof of concept, we constructed a causal graph of the gene-regulatory hierarchy that jointly controls three partially co-regulated blood traits. We propose that perturbation studies in trait-relevant cell types, coupled with gene-level effect sizes for traits, can bridge the gap between genetic association and biological mechanism.
    DOI:  https://doi.org/10.1038/s41586-025-09866-3
  19. Cell. 2025 Dec 08. pii: S0092-8674(25)01308-X. [Epub ahead of print]
    Biomaterial-minimalistic photoactivated bioprinting of cell-dense tissues.
    Mian Wang, Wanlu Li, Jin Hao, Ling Cai, Xuan Mei, Regina Sanchez Flores, Penélope Cerón Castillo, Carlos Ezio Garciamendez-Mijares, Xuan Mu, Xiao Kuang, Xianbin Yu, Jugal Kishore Sahoo, Guosheng Tang, Zeyu Luo, Guillermo Wells, Zhongmin Liu, Alfredo Quiñones-Hinojosa, Kevin Eggan, Shaorong Gao, Yu Shrike Zhang.
      Conventional hydrogel-based bioprinting methods often suffer from insufficient cell densities, which may limit crucial cell-cell interactions and impair overall tissue functions. Here, we present an approach that modifies cell membranes with acrylate bonds, allowing living cells at physiological densities (up to ∼109 cells mL-1) to serve directly as bioinks, demonstrating photoactivated bioprinting through digital light processing using purely cellular bioinks. Our cell-dense bioinks (CLINKs) rapidly produce tissue constructs that closely mimic native tissues, characterized by strong structural relevancy and robust functionality. The high cellularity and living nature of CLINKs enable the creation of advanced biological models such as connected neural circuits and rhythmically contracting mini-hearts derived entirely from stem cells, effectively capturing essential native-like behaviors. Implants created through this method showcase the capacity to integrate with the host, thereby promoting regeneration. Our CLINK technology holds substantial promise in tissue biofabrication, opening alternative avenues for biomedical applications.
    Keywords:  3D bioprinting; cardiac tissues; cardiomyocytes; cell-dense; digital light processing; liver tissues; neural cells; neural circuits; scaffold-free; skin regeneration
    DOI:  https://doi.org/10.1016/j.cell.2025.11.012
  20. BMC Genomics. 2025 Dec 10.
    Epigenetic control of metabolic identity across cell types.
    Maria Pires Pacheco, Déborah Gerard, Riley J Mangan, Alec R Chapman, Dennis Hecker, Manolis Kellis, Marcel H Schulz, Lasse Sinkkonen, Thomas Sauter.
       BACKGROUND: Constraint-based network modeling is a powerful genomic-scale approach for analyzing cellular metabolism, capturing metabolic variations across tissues and cell types, and defining the metabolic identity essential for identifying disease-associated transcriptional states.
    RESULTS: Using RNA-seq and epigenomic data from the EpiATLAS resource of the International Human Epigenome Consortium (IHEC), we reconstructed metabolic networks for 1,555 samples spanning 58 tissues and cell types. Analysis of these networks revealed the distribution of metabolic functionalities across human cell types and provides a compendium of human metabolic activity. This integrative approach allowed us to define, across tissues and cell types, (i) reactions that fulfil the basic metabolic processes (core metabolism), and (ii) cell type-specific functions (unique metabolism), that shape the metabolic identity of a cell or a tissue. Integration with EpiATLAS-derived cell-type-specific gene-level chromatin states and enhancer-gene interactions identified enhancers, transcription factors, and key nodes contributing to the control of core and unique metabolism. Transport and first reactions of pathways were enriched for high expression, active chromatin state, and Polycomb-mediated repression in cell types where pathways are inactive, suggesting that key nodes are targets of repression.
    CONCLUSION: Integrative analysis forms the basis for identifying putative regulation points that control metabolic identity in human cells.
    Keywords:  Chromatin state; Enhancer-gene interaction; Epigenomics; Metabolic identity; Metabolic networks
    DOI:  https://doi.org/10.1186/s12864-025-12155-y
  21. Nat Commun. 2025 Dec 08. 16(1): 10952
    Clonal cell states link gastroesophageal junction tissues with metaplasia and cancer.
    Rodrigo A Gier, Sydney A Bracht, Jiazhen Rong, Raúl A Reyes Hueros, Madison L Wahlsten, Christopher Cote, Maureen DeMarshall, Tatiana A Karakasheva, Alexandra Strauss Starling, Amanda B Muir, Gary W Falk, Nancy R Zhang, Sydney M Shaffer.
      Barrett's esophagus is a common type of metaplasia and a precursor of esophageal adenocarcinoma. However, the cell states and lineage connections underlying the origin, maintenance, and progression of Barrett's esophagus have not been resolved in humans. Here, we perform single-cell lineage tracing and transcriptional profiling of patient cells isolated from metaplastic and healthy tissue. Our analysis unexpectedly reveals evidence for lineages spanning squamous esophagus, gastric cardia, and transitional basal cells at the tissue junction. We also identify lineages connecting Barrett's esophagus to both esophageal and gastric tissues. Barrett's esophagus biopsies consist of multiple distinct clones, with lineages that contain all progenitor and differentiated cell types. We discover Barrett's esophagus cell types, including tuft, ciliated, and BEST4+ cells, which we validate through both lineage relationships and spatial transcriptomics. In contrast, the precancerous dysplastic lesions show expansion from a single molecularly aberrant Barrett's esophagus clone. Together, these findings provide a single-cell view of the cell dynamics of Barrett's esophagus, linking cell states along the disease trajectory, from its origin to cancer.
    DOI:  https://doi.org/10.1038/s41467-025-66302-w
  22. Nat Rev Cancer. 2025 Dec 08.
    N6-Methyladenosine: an RNA modification as a central regulator of cancer.
    Hanzhi Luo, Michael G Kharas, Samie R Jaffrey.
      N6-Methyladenosine (m6A) is a modified nucleotide in mRNAs and non-coding RNAs that influences gene expression, primarily by promoting the degradation of specific transcripts. Recent studies have highlighted the dynamic and context-dependent roles of this RNA modification in cancer, implicating it in tumorigenesis, immune evasion and therapeutic resistance. In this Review, we discuss the functional roles of m6A writers, erasers and readers in cancer. We highlight how m6A dysregulation contributes to oncogenic processes, including cell differentiation and immune microenvironment remodelling. Using haematological malignancies as an example, we highlight the principles of m6A-dependent regulation that may be broadly relevant across cancer types. Notably, inhibitors targeting the m6A writer methyltransferase-like 3 (METTL3) have emerged as potential cancer therapeutics. METTL3 inhibitors not only disrupt m6A-dependent pathways but also elevate double-stranded RNA levels, activating innate immune responses and antitumour immunity. We emphasize the need for high-resolution quantitative m6A mapping in cancer and mechanistic studies to better understand the specific transcripts that exhibit altered patterns of m6A in cancer and to identify patient subgroups most likely to benefit from METTL3 inhibitors.
    DOI:  https://doi.org/10.1038/s41568-025-00889-6
  23. Microbiome. 2025 Dec 12.
    MCSPACE: inferring microbiome spatiotemporal dynamics from high-throughput co-localization data.
    Gurdip Uppal, Guillaume Urtecho, Miles Richardson, Isin Y Comba, Jeongchan Lee, Thomas Moody, Harris H Wang, Georg K Gerber.
       BACKGROUND: Recent advances in high-throughput approaches for estimating co-localization of microbes, such as SAMPL-seq, allow characterization of the biogeography of the gut microbiome longitudinally and at an unprecedented scale. However, these high-dimensional data are complex and have unique noise properties.
    RESULTS: To address these challenges, we developed MCSPACE, a probabilistic AI method that infers, from microbiome co-localization data, spatially coherent assemblages of taxa, their dynamics over time, and their responses to perturbations. To evaluate MCSPACE's capabilities, we generated the largest longitudinal microbiome co-localization dataset to date, profiling spatial relationships of microbes in the guts of mice subjected to serial dietary perturbations over 76 days. Analyses of these data and two existing human longitudinal datasets demonstrated superior benchmarking performance of MCSPACE over existing methods and moreover yielded insights into the spatiotemporal structuring of the gut microbiome, including identifying temporally persistent and dynamic microbial assemblages in the human gut, and shifts in assemblages in the murine gut induced by specific dietary components.
    CONCLUSIONS: Our results highlight the utility of MCSPACE, which we make available to the community as an open-source software tool, for elucidating the dynamics of microbiome biogeography and gaining insights into the role of spatial relationships in host-microbial ecosystem function. Video Abstract.
    Keywords:  Biogeography; Computational; Generative AI; Longitudinal; Machine learning; Microbiome; Spatial; Spatiotemporal; Time-series
    DOI:  https://doi.org/10.1186/s40168-025-02279-4
  24. Adv Drug Deliv Rev. 2025 Dec 10. pii: S0169-409X(25)00242-X. [Epub ahead of print] 115757
    Engineering tumor spatial heterogeneity in vitro.
    Chang Chong Chen, Zixuan Zhao, Dong Hua Seah, Kenny Zhuoran Wu, Senthilkumar Mohanaselvi, Eliza Li Shan Fong.
      Spatial heterogeneity is a fundamental feature of the tumor microenvironment, characterized by structured variations in cellular composition, phenotypic states, extracellular matrix (ECM) organization, and biochemical and biophysical gradients. These spatial patterns shape tumor evolution, modulate immune infiltration, and underlie resistance to therapy. Advances in spatial transcriptomics and multiplex imaging have revealed dynamic and region-specific niches, such as hypoxic cores, immune-excluded zones, and fibroblast-dense invasive fronts, that correlate with clinical outcomes. However, most in vitro models fail to capture this architectural complexity. Recent engineering technologies, including 3D bioprinting, organoid assembloids, organ-on-a-chip systems, and ECM-mimetic scaffolds, now enable controlled reconstruction of tumor spatial organization and microregional heterogeneity. These technologies allow integration of patient-derived cells, tunable matrix environments, and spatially defined signaling to mimic in vivo pathophysiology. When integrated with spatial transcriptomics and proteomics, these models enable mechanistic exploration of microregional tumor biology, evaluation of therapeutic responses, and investigation of immunotherapy resistance. This review integrates our current understanding of spatial heterogeneity in cancer with enabling engineering strategies to guide future developments in tumor biology and therapeutic innovation.
    Keywords:  Drug development; Engineered tumor models; Spatial heterogeneity; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.addr.2025.115757
  25. Nat Methods. 2025 Dec 11.
    Benchmarking algorithms for generalizable single-cell perturbation response prediction.
    Zhiting Wei, Yiheng Wang, Yicheng Gao, Shuguang Wang, Ping Li, Duanmiao Si, Yuli Gao, Siqi Wu, Danlu Li, Kejing Dong, Xingbo Yang, Chen Tang, Shaliu Fu, Xiaohan Chen, Wannian Li, Yuzhou You, Chen Zhang, Aibin Liang, Guohui Chuai, Qi Liu.
      Single-cell perturbation technologies enable systematic investigation of gene functions and regulatory networks with single-cell resolution. However, performing large-scale and combinatorial perturbation screens poses notable challenges due to their exponentially increased complexity. Computational methods, including foundation models, have been developed to predict perturbation effects. Yet despite claims of promising performance, concerns remain about their true efficacy, particularly when evaluated across diverse and previously unseen cellular contexts and perturbation scenarios. Here, we present a comprehensive benchmark of 27 methods for single-cell perturbation response prediction, evaluated across 29 datasets using 6 complementary performance metrics. By evaluating them under multiple scenarios, we systematically assess their generalizability, including that of emerging foundation models. Our results provide practical guidance for method selection and underscore the need for cellular context embedding approaches to enhance the generalizability of perturbation effect prediction in single-cell research.
    DOI:  https://doi.org/10.1038/s41592-025-02980-0
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