bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–05–11
fourteen papers selected by
Xiao Qin, University of Oxford
  1. ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysis.
  2. The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution.
  3. Comparative analysis of gene regulation in single cells using Compass.
  4. Deconvoluting single-cell transcriptomics reveals cellular programs regulated by cell-cell communication in colorectal cancer.
  5. Stemness in flux: Dissecting intestinal crypt organization with multimodal approaches.
  6. Coupling the 3D epigenome to the transcriptome in single cells.
  7. Molecular basis of cell fate plasticity - insights from the privileged cells.
  8. ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types.
  9. Molecular circuits for genomic recording of cellular events.
  10. Spatial and multiomics analysis of human and mouse lung adenocarcinoma precursors reveals TIM-3 as a putative target for precancer interception.
  11. Understanding the logic and grammar of cis-regulatory elements.
  12. Blocking a key node in cancer signalling unlocks therapeutic potential.
  13. All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics.
  14. Protocol for the imputation of stimulus-induced single-cell gene expression trajectories from time-series scRNA-seq data.
  1. Genome Biol. 2025 May 08. 26(1): 117
    ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysis.
    Wen Wang, Shiwei Zheng, Sujung Crystal Shin, Joselyn Cristina Chávez-Fuentes, Guo-Cheng Yuan.
      Recent technological advances enable mapping of tissue spatial organization at single-cell resolution, but methods for analyzing spatially continuous microenvironments are still lacking. We introduce ONTraC, a graph neural network-based framework for constructing spatial trajectories at niche-level. Through benchmarking analyses using multiple simulated and real datasets, we show that ONTraC outperforms existing methods. ONTraC captures both normal anatomical structures and disease-associated tissue microenvironment changes. In addition, it identifies tissue microenvironment-dependent shifts in gene expression, regulatory network, and cell-cell interaction patterns. Taken together, ONTraC provides a useful framework for characterizing the structural and functional organization of tissue microenvironments.
    DOI:  https://doi.org/10.1186/s13059-025-03588-5
  2. Nat Cancer. 2025 May 08.
    The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution.
    Michael Tyler, Avishai Gavish, Chaya Barbolin, Roi Tschernichovsky, Rouven Hoefflin, Michael Mints, Sidharth V Puram, Itay Tirosh.
      Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.
    DOI:  https://doi.org/10.1038/s43018-025-00957-8
  3. Cell Rep Methods. 2025 Apr 30. pii: S2667-2375(25)00071-2. [Epub ahead of print] 101035
    Comparative analysis of gene regulation in single cells using Compass.
    Changxin Wan, Yilong Qu, Zhiyou Ye, Tianbei Zhang, Huifang Ma, Ming Chen, Wenpin Hou, Zhicheng Ji.
      Single-cell multi-omics is a transformative technology that measures both gene expression and chromatin accessibility in individual cells. However, most studies concentrate on a single tissue and are unable to determine whether a gene is regulated by a cis-regulatory element (CRE) in just one tissue or across multiple tissues. We developed Compass for comparative analysis of gene regulation across a large number of human and mouse tissues. Compass consists of a database, CompassDB, and an open-source R software package, CompassR. CompassDB contains processed single-cell multi-omics data of more than 2.8 million cells from hundreds of cell types. Building upon CompassDB, CompassR enables visualization and comparison of gene regulation across multiple tissues. We demonstrated that CompassR can identify CRE-gene linkages specific to a tissue type and their associated transcription factors in real examples.
    Keywords:  CP: Systems biology; cis-regulatory elements; gene regulation; single-cell ATAC-seq; single-cell multi-omics
    DOI:  https://doi.org/10.1016/j.crmeth.2025.101035
  4. bioRxiv. 2025 Apr 15. pii: 2025.04.09.648030. [Epub ahead of print]
    Deconvoluting single-cell transcriptomics reveals cellular programs regulated by cell-cell communication in colorectal cancer.
    Han Zhang, Binfeng Lu, Gregory F Cooper, Anwaar Saeed, John W Paisley, Xinghua Lu, Lujia Chen.
      Cells within a tissue microenvironment communicate through intricate cell-cell communication (CCC) networks. In this meta-analysis of eight single-cell cohorts encompassing 153 patients and 279 samples, we advance the understanding of CCC networks in colorectal cancers through a novel analytical framework. Employing hierarchical language modeling, we identify gene expression modules (GEMs) that mirror single-cell signaling states, crucial for deciphering the complexity of intercellular interactions. By applying causal discovery methods, we systematically uncover GEMs likely regulated by ligand-receptor signaling and cross-cell-type communication. This analysis reveals cross-cell-type CCC programs, marked by highly correlated GEMs across various cell types, shedding light on the intricate CCC networks within the tumor microenvironment. Spatial transcriptomics further validate these findings by demonstrating the co-localization of GEMs within CCC programs in distinct spatial domains, emphasizing the spatial dynamics of tumor intercellular communication. Our interactive website ( http://44.192.10.166:3838/ ) and analytical framework equip researchers with powerful tools to explore these complex mechanisms, potentially uncovering novel drug targets and refining strategies for precision immunotherapies. This comprehensive study not only presents a detailed catalog of CCC networks driven by ligand-receptor interactions in colorectal cancer but also highlights the significance of integrating multi-sample and patient data to unravel the molecular underpinnings of cancer communication pathways.
    DOI:  https://doi.org/10.1101/2025.04.09.648030
  5. Dev Cell. 2025 May 05. pii: S1534-5807(25)00205-9. [Epub ahead of print]60(9): 1275-1276
    Stemness in flux: Dissecting intestinal crypt organization with multimodal approaches.
    Maria Azkanaz, Dimitrios Laskaris, Jacco van Rheenen.
      In this issue of Developmental Cell, Banjac et al. integrate lineage tracing, single-cell RNA sequencing, and mathematical modeling to reveal that stem cells at the crypt base drive the decision between secretory and absorptive lineage commitment. Their findings highlight the central role of crypt-bottom Lgr5+ cells in maintaining intestinal epithelium homeostasis.
    DOI:  https://doi.org/10.1016/j.devcel.2025.04.003
  6. Nat Methods. 2025 May 08.
    Coupling the 3D epigenome to the transcriptome in single cells.
      
    DOI:  https://doi.org/10.1038/s41592-025-02666-7
  7. Curr Opin Genet Dev. 2025 May 05. pii: S0959-437X(25)00046-2. [Epub ahead of print]93 102354
    Molecular basis of cell fate plasticity - insights from the privileged cells.
    Stephen Maxwell Scalf, Qiao Wu, Shangqin Guo.
      In the post-Yamanaka era, the rolling balls on Waddington's hilly landscape not only roll downward, but also go upward or sideways. This new-found mobility implies that the tantalizing somatic cell plasticity fueling regeneration, once only known to planarians and newts, might be sparking in the cells of mice and humans, if only we knew how to fully unlock it. The hope for ultimate regeneration was made even more tangible by the observations that partial reprogramming by the Yamanaka factors reverses many hallmarks of aging [76], even though the underlying mechanism remains unclear. We intend to revisit the milestones in the evolving understanding of cell fate plasticity and glean molecular insights from an unusual somatic cell state, the privileged cell state that reprograms in a manner defying the stochastic model. We synthesize our view of the molecular underpinning of cell fate plasticity, from which we speculate how to harness it for regeneration and rejuvenation. We propose that senescence, aging and malignancy represent distinct cell states with definable biochemical and biophysical parameters.
    DOI:  https://doi.org/10.1016/j.gde.2025.102354
  8. Genome Biol. 2025 May 09. 26(1): 123
    ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types.
    Tevfik Umut Dincer, Jason Ernst.
      We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.
    Keywords:  CRISPR screens; Epigenome; Gene regulation; Genome annotation; Hidden Markov model; Machine learning; Massively parallel reporter assays
    DOI:  https://doi.org/10.1186/s13059-025-03579-6
  9. Trends Genet. 2025 May 06. pii: S0168-9525(25)00079-4. [Epub ahead of print]
    Molecular circuits for genomic recording of cellular events.
    Wei Chen, Junhong Choi.
      Advances in precise genome editing are enabling genomic recordings of cellular events. Since the initial demonstration of CRISPR-based genome editing, the field of genomic recording has witnessed key strides in lineage recording, where clonal lineage relationships among cells are indirectly recorded as synthetic mutations. However, methods for directly recording and reconstructing past cellular events are still limited, and their potential for revealing new insights into cell fate decisions has yet to be realized. The field needs new sensing modules and genetic circuit architectures that faithfully encode past cellular states into genomic DNA recordings to achieve such goals. Here we review recently developed strategies to construct diverse sensors and explore how emerging synthetic biology tools may help to build molecular circuits for genomic recording of diverse cellular events.
    Keywords:  CRISPR; genomic recording; molecular circuits; synthetic biology
    DOI:  https://doi.org/10.1016/j.tig.2025.04.004
  10. Cancer Cell. 2025 May 02. pii: S1535-6108(25)00162-X. [Epub ahead of print]
    Spatial and multiomics analysis of human and mouse lung adenocarcinoma precursors reveals TIM-3 as a putative target for precancer interception.
    Bo Zhu, Pingjun Chen, Muhammad Aminu, Jian-Rong Li, Junya Fujimoto, Yanhua Tian, Lingzhi Hong, Hong Chen, Xin Hu, Chenyang Li, Natalie Vokes, Andre L Moreira, Don L Gibbons, Luisa M Solis Soto, Edwin Roger Parra Cuentas, Ou Shi, Songhui Diao, Jie Ye, Frank R Rojas, Eduardo Vilar, Anirban Maitra, Ken Chen, Nicolas Navin, Monique Nilsson, Beibei Huang, Simon Heeke, Jianhua Zhang, Cara L Haymaker, Vamsidhar Velcheti, Daniel H Sterman, Veena Kochat, William I Padron, Ludmil B Alexandrov, Zhubo Wei, Xiuning Le, Linghua Wang, Junya Fukuoka, J Jack Lee, Ignacio I Wistuba, Harvey I Pass, Mark Davis, Samir Hannash, Chao Cheng, Steven Dubinett, Avrum Spira, Kunal Rai, Scott M Lippman, P Andrew Futreal, John V Heymach, Alexandre Reuben, Jia Wu, Jianjun Zhang.
      How tumor microenvironment shapes lung adenocarcinoma (LUAD) precancer evolution remains poorly understood. Spatial immune profiling of 114 human LUAD and LUAD precursors reveals a progressive increase of adaptive response and a relative decrease of innate immune response as LUAD precursors progress. The immune evasion features align the immune response patterns at various stages. TIM-3-high features are enriched in LUAD precancers, which decrease in later stages. Furthermore, single-cell RNA sequencing (scRNA-seq) and spatial immune and transcriptomics profiling of LUAD and LUAD precursor specimens from 5 mouse models validate high TIM-3 features in LUAD precancers. In vivo TIM-3 blockade at precancer stage, but not at advanced cancer stage, decreases tumor burden. Anti-TIM-3 treatment is associated with enhanced antigen presentation, T cell activation, and increased M1/M2 macrophage ratio. These results highlight the coordination of innate and adaptive immune response/evasion during LUAD precancer evolution and suggest TIM-3 as a potential target for LUAD precancer interception.
    Keywords:  TIM-3; cancer prevention; imaging mass cytometry; immune landscape; lung adenocarcinoma evolution; precancer; spatial single cell; stage dependent
    DOI:  https://doi.org/10.1016/j.ccell.2025.04.003
  11. Nat Rev Genet. 2025 May 07.
    Understanding the logic and grammar of cis-regulatory elements.
    Juan I Fuxman Bass.
      
    DOI:  https://doi.org/10.1038/s41576-025-00847-w
  12. Nature. 2025 May 07.
    Blocking a key node in cancer signalling unlocks therapeutic potential.
    Hugo Lavoie, Marc Therrien.
      
    Keywords:  Cancer; Molecular biology; Therapeutics
    DOI:  https://doi.org/10.1038/d41586-025-01136-6
  13. Cell Syst. 2025 May 05. pii: S2405-4712(25)00124-3. [Epub ahead of print] 101291
    All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics.
    Yiheng Mao, Yuan Li, Zhendong Zheng, Yanfen Xu, Mi Ke, An He, Fuchao Liang, Keren Zhang, Xi Wang, Weina Gao, Ruijun Tian.
      Spatial proteomics enables in-depth mapping of tissue architectures, mostly achieved by laser microdissection-mass spectrometry (LMD-MS) and antibody-based imaging. However, trade-offs among sampling precision, throughput, and proteome coverage still limit the applicability of these strategies. Here, we propose proximity labeling for spatial proteomics (PSPro) by combining precise antibody-targeted biotinylation and efficient affinity purification for all-at-once cell-type proteome capture with sub-micrometer resolution from single tissue slice. With fine-tuned labeling parameters, PSPro shows reliable performance in benchmarking against flow cytometry- and LMD-based proteomic workflows. We apply PSPro to tumor and spleen slices, enriching thousands of proteins containing known markers from ten cell types. We further incorporate LMD into PSPro to facilitate comparison of cell subpopulations from the same tissue slice, revealing spatial proteome heterogeneity of cancer cells and immune cells in pancreatic tumor. Collectively, PSPro converts the traditional "antibody-epitope" paradigm to an "antibody-cell-type proteome" for spatial biology in a user-friendly manner. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  affinity purification-mass spectrometry; laser microdissection; proximity labeling; spatial proteomics; tissue slice
    DOI:  https://doi.org/10.1016/j.cels.2025.101291
  14. STAR Protoc. 2025 May 07. pii: S2666-1667(25)00217-5. [Epub ahead of print]6(2): 103811
    Protocol for the imputation of stimulus-induced single-cell gene expression trajectories from time-series scRNA-seq data.
    Katherine M Sheu, Alexander Hoffmann.
      Single-cell RNA sequencing (scRNA-seq) measures cell-to-cell heterogeneous mRNA abundance but destroys the cell and precludes tracking of heterogeneous gene expression trajectories. Here, we present an approach to impute single-cell gene expression trajectories (scGETs) from time-series scRNA-seq measurements. We describe four main computational steps: dimensionality reduction, calculation of transition probability matrices, spline interpolation, and deconvolution to scGETs. Imputing scGETs can aid in studying heterogeneous stimulus responses over time, such as cancer cell responses to drugs or immune cell responses to pathogens. For complete details on the use and execution of this protocol, please refer to Sheu et al.1.
    Keywords:  RNA-seq; bioinformatics; gene expression; molecular biology
    DOI:  https://doi.org/10.1016/j.xpro.2025.103811
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