bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–10–19
seventeen papers selected by
Xiao Qin, University of Oxford
  1. sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell-cell interaction studies.
  2. Combining CRISPR perturbations with chromatin profiling.
  3. Tumor-infiltrating bacteria disrupt cancer epithelial cell interactions and induce cell-cycle arrest.
  4. Mathematical Modeling Quantifies "Just-Right" APC Inactivation for Colorectal Cancer Initiation.
  5. A Roadmap for the Future of Systems Biology in Cancer Research.
  6. Pan-cancer spatial characterization of key immune biomarkers in the tumor microenvironment.
  7. Redefining cellular reprogramming with advanced genomic technologies.
  8. BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment.
  9. Tumor microenvironment and macroenvironment: A new perspective on holistic oncology.
  10. Cancer vaccines as enablers of immunotherapy.
  11. In silico biological discovery with large perturbation models.
  12. Deep generative modeling of sample-level heterogeneity in single-cell genomics.
  13. Knowledge for twoWhen Everyone Knows That Everyone Knows… Steven Pinker Scribner, 2025. 384 pp.
  14. Programmable promoter editing for precise control of transgene expression.
  15. Exploiting metabolic cell death for cancer therapy.
  16. The fragile intelligence of GPT-5 in medicine.
  17. Microbial signatures in metastatic cancer.
  1. Genome Biol. 2025 Oct 15. 26(1): 354
    sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell-cell interaction studies.
    Xiaoyu Song, Joselyn C Chavez-Fuentes, Weiping Ma, Weijia Fu, Sujung Crystal Shin, Pei Wang, Guo-Cheng Yuan.
      Spatially resolved transcriptomics (SRT) facilitates the study of cell-cell interactions within native tissue environments. To support method development and benchmarking, we introduce sCCIgen, a real-data-based simulator that generates high-fidelity synthetic SRT data with known interaction features. sCCIgen preserves transcriptomic and spatial characteristics and provides key interaction features, including cell colocalization, spatial dependence of gene expression, and gene-gene interactions between neighboring cells. It supports input from SRT data, single-cell expression data alone, and unpaired expression and spatial data. sCCIgen is interactive, user-friendly, reproducible, and well-documented for studying cellular interactions and spatial biology.
    Keywords:  Cell–cell interaction; Data simulator; Spatially resolved transcriptomics
    DOI:  https://doi.org/10.1186/s13059-025-03762-9
  2. Nat Biotechnol. 2025 Oct;43(10): 1619
    Combining CRISPR perturbations with chromatin profiling.
    Iris Marchal.
      
    DOI:  https://doi.org/10.1038/s41587-025-02873-9
  3. Cancer Cell. 2025 Oct 16. pii: S1535-6108(25)00402-7. [Epub ahead of print]
    Tumor-infiltrating bacteria disrupt cancer epithelial cell interactions and induce cell-cycle arrest.
    Jorge Luis Galeano Niño, Falk Ponath, Victor A Ajisafe, Clara R Becker, Andrew G Kempchinsky, Martha A Zepeda-Rivera, Javier A Gomez, Hanrui Wu, Jessica G Terrazas, Heather Bouzek, Elizabeth Cromwell, Pritha Chanana, Matthew Wong, Ashish Damania, Michael G White, Y Nancy You, Scott Kopetz, Nadim J Ajami, Jennifer A Wargo, Christopher D Johnston, Susan Bullman.
      Tumor-infiltrating bacteria are increasingly recognized as modulators of cancer progression and therapy resistance. We describe a mechanism by which extracellular intratumoral bacteria, including Fusobacterium, modulate cancer epithelial cell behavior. Spatial imaging and single-cell spatial transcriptomics show that these bacteria predominantly localize extracellularly within tumor microniches of colorectal and oral cancers, characterized by reduced cell density, transcriptional activity, and proliferation. In vitro, Fusobacterium nucleatum disrupts epithelial contacts, inducing G0-G1 arrest and transcriptional quiescence. This state confers 5-fluorouracil resistance and remodels the tumor microenvironment. Findings were validated by live-cell imaging, spatial profiling, mouse models, and a 52-patient colorectal cancer cohort. Transcriptomics reveals downregulation of cell cycle, transcription, and antigen presentation genes in bacteria-enriched regions, consistent with a quiescent, immune-evasive phenotype. In an independent rectal cancer cohort, high Fusobacterium burden correlates with reduced therapy response. These results link extracellular bacteria to cancer cell quiescence and chemoresistance, highlighting microbial-tumor interactions as therapeutic targets.
    Keywords:  Fusobacterium; cancer progression; cell-cycle arrest; chemoresistance; colorectal cancer; epithelial cell-to-cell contacts; host-pathogen interactions; intratumoral bacteria; live-cell confocal imaging; spatial single-cell transcriptomics; tumor microenvironment; tumor-infiltrating bacteria
    DOI:  https://doi.org/10.1016/j.ccell.2025.09.010
  4. Cancer Res. 2025 Oct 15.
    Mathematical Modeling Quantifies "Just-Right" APC Inactivation for Colorectal Cancer Initiation.
    Meritxell Brunet Guasch, Nathalie A Feeley, Ignacio Soriano, Steve Thorn, Ian P M Tomlinson, Michael D Nicholson, Tibor Antal.
      Dysregulation of the tumor suppressor gene APC is a canonical step in colorectal cancer development by promoting activation of the WNT/β-catenin pathway. Curiously, most colorectal tumors carry biallelic mutations that result in only partial loss of APC function, suggesting that a "just-right" level of APC inactivation, and hence WNT signaling, provides the optimal conditions for tumorigenesis. Mutational processes act variably across the APC gene, which could contribute to the bias against complete APC inactivation. Here, we proposed a mathematical model to quantify the tumorigenic effect of biallelic APC genotypes, controlling for somatic mutational processes. Analysis of sequence data from >2500 colorectal cancers showed that APC genotypes resulting in partial protein function confer about 50 times higher probability of progressing to cancer compared to complete APC inactivation. The optimal inactivation level varied with anatomical location and additional mutations of WNT pathway regulators. Assessment of the regulatory effects of secondary alterations in WNT drivers in combination with APC in vivo provided evidence that AMER1 mutations increase WNT activity in tumors with suboptimal APC genotypes. The fitness landscape of APC inactivation was consistent across microsatellite unstable and POLE-deficient colorectal cancers and tumors in patients with familial adenomatous polyposis. Together, these findings suggest a general "just-right" optimum for APC inactivation and WNT signaling, pointing to WNT hyperactivation as a potential vulnerability in cancer.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-0445
  5. Cancer Res. 2025 Oct 15.
    A Roadmap for the Future of Systems Biology in Cancer Research.
    H Steven Wiley, Carlos F Lopez, Andrei S Rodin, Russell C Rockne, Thomas E Yankeelov, Herbert M Sauro, Ghmkin Hassan, Sandhya Prabhakaran, Emek Demir, Mengzhou Hu, Juan Fuxman Bass, Kimberly A Luddy, Hannah Newman, Jonathan P Mochel, James C Costello, Jianhua Xing, Said M Afify, Ahmet Acar, Melanie Hayden Gephart, Song Feng, Orion Banks, Jineta Banerjee, Ashley Clayton, David E Hill, Randy F Sweis, Maxine C Umeh-Garcia, Yapeng Su, Aaron S Meyer.
      Cancer systems biology seeks to understand how cancer arises as a system of interconnected molecules, cells, and tissues, with the goal of understanding, predicting, and controlling the disease. In the last decade, the field has rapidly grown as advances in experimental, computational, and analytical technologies have improved our ability to capture and recapitulate the complexities of cancer at multiple scales. However, the field's promise to understand how specific molecular changes give rise to altered cancer outcomes remains incompletely fulfilled. Fortunately, an opportunity exists to accelerate progress by better coordinating modeling and data-gathering efforts across the cancer systems biology community. This will create the foundation for building accurate, multiscale cancer models that can better predict and identify improved therapeutic interventions. Here, we outline some of the current challenges in cancer systems biology research, how they can be addressed, and actions that the community can take to accelerate progress in the field.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-0700
  6. Cell Rep Med. 2025 Oct 14. pii: S2666-3791(25)00491-4. [Epub ahead of print] 102418
    Pan-cancer spatial characterization of key immune biomarkers in the tumor microenvironment.
    James R Lindsay, Jennifer Altreuter, Joao V Alessi, Jason L Weirather, Anita Giobbie-Hurder, Ian Dryg, Katharina Hoebel, Bijaya Sharma, Kristen Felt, F Stephen Hodi, Neal Lindeman, Lynette M Sholl, Ethan Cerami, Jonathan A Nowak, Mark M Awad, Scott J Rodig, William Lotter.
      Deciphering the composition and spatial organization of the tumor immune microenvironment (TIME) is key to understanding cancer progression and treatment response. Spatial biology techniques such as multiplex immunofluorescence (mIF) offer detailed insights but are often limited to retrospective studies of individual cancer types. Here, we provide a pan-cancer spatial characterization of key biomarkers (CD8, FOXP3, PD-1, and PD-L1) using an mIF assay performed prospectively in a clinical setting on 2,019 tumors across 14 major cancer types. By integrating interpretable compositional and spatial metrics, we identify patterns of TIME variation conserved across cancer types and stages. We assess associations between these TIME spatial factors and tumor, genomic, and clinical features, with results extending prior findings and uncovering new links. To accompany the analysis, we provide a curated database of the 39.4 million spatially resolved cells. Altogether, our findings and database offer pan-cancer insights of the TIME to advance spatial biology and cancer immunology.
    Keywords:  immuno-oncology; multiplex immunofluorescence; spatial proteomics; tumor immune microenvironment
    DOI:  https://doi.org/10.1016/j.xcrm.2025.102418
  7. Nat Rev Genet. 2025 Oct 17.
    Redefining cellular reprogramming with advanced genomic technologies.
    Samantha A Morris.
      Manipulating cell identity through transcription factor-mediated reprogramming, induced pluripotency or directed differentiation holds promise for disease modelling and regenerative medicine. Yet the cells produced by these methods often do not fully recapitulate the molecular and functional characteristics of their native counterparts. Immaturity, low fidelity and heterogeneity remain barriers, limiting reliability for modelling human disease and therapeutic use. Recent advances in single-cell genomic technologies, integrative computational frameworks and emerging molecular recording tools are beginning to reveal the mechanisms underlying incomplete or inefficient reprogramming and highlight tractable failure points. Together, these approaches could support mechanism-guided protocol design and stepwise gains in fidelity, maturity and purity, potentially moving engineered cells towards clinical relevance and informing design principles for next-generation reprogramming strategies.
    DOI:  https://doi.org/10.1038/s41576-025-00899-y
  8. Elife. 2025 Oct 15. pii: RP102097. [Epub ahead of print]13
    BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment.
    Emilio Rios-Jimenez, Anoek Zomer, Raphael Collot, Mario Barrera Román, Sandra F Archidona, Hendrikus Ariese, Ravian van Ineveld, Michiel Kleinnijenhuis, Nils Bessler, Hannah Johnson, Caleb A Dawson, Anne Rios, Maria Alieva.
      Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental, and dynamic single-cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data from mouse models. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.
    Keywords:  cancer biology; cell migration; computational biology; confocal microscopy; image analysis; mouse; systems biology
    DOI:  https://doi.org/10.7554/eLife.102097
  9. Cancer Lett. 2025 Oct 11. pii: S0304-3835(25)00648-2. [Epub ahead of print]634 218076
    Tumor microenvironment and macroenvironment: A new perspective on holistic oncology.
    Qun Chen, Kuirong Jiang, Michael S Bronze, Min Li, Courtney W Houchen, Yuqing Zhang.
      The tumor microenvironment (TME) and tumor macroenvironment (TMaE) jointly shape cancer biology by linking local cellular niches with systemic host physiology. The TME provides the immediate soil for tumor initiation, progression, and therapy resistance, whereas the TMaE integrates metabolic, immune, neuroendocrine, microbial, and inflammatory signals that remodel local ecosystems. Recent advances highlight how systemic factors, including aging, energy imbalance, chronic inflammation, cachexia, and psychosocial stress, interact with extracellular matrix remodeling, vascular dynamics, and immune surveillance to influence tumor dormancy, metastatic reactivation, and therapeutic outcomes. However, the conceptual boundaries between TME and TMaE remain unclear, mechanistic insights are limited, and current models insufficiently capture local-systemic crosstalk. Future strategies integrating multi-omics, advanced imaging, and humanized models are essential to map this multidimensional interplay. A deeper understanding of TME-TMaE will be critical to refine precision oncology, advance preventive strategies, and design combinatorial therapies targeting both local and systemic cancer ecosystems. This review highlights the roles of the TME and TMaE in tumor initiation, progression, and heterogeneity, their interactions, and the clinical implications for classification, therapy, and prognosis.
    Keywords:  Immunity; Local-systemic crosstalk; Precise treatment; Tumor macroenvironment; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.canlet.2025.218076
  10. Nat Immunol. 2025 Oct 16.
    Cancer vaccines as enablers of immunotherapy.
    Samir N Khleif, Seema Gupta.
      Immunotherapy has transformed cancer care, but most patients do not respond and ultimately develop resistance. A central barrier to durable efficacy is the absence of robust, tumor-specific T cell responses, particularly in tumors characterized by low antigenicity and an immunosuppressive tumor microenvironment. Cancer vaccines, long explored with limited clinical success as monotherapies, are emerging as enablers of immunotherapy by restoring T cell priming, broadening neoantigen-specific repertoires and converting tumors from 'cold' to 'hot'. Advances in genomics and computational neoantigen prediction have reinvigorated the field. In this Review, we synthesize current knowledge on the immunobiology of T cell priming in cancer, define how cancer vaccines can address the multifaceted mechanisms of immune evasion, and outline principles for designing next-generation vaccine-based combinations. We also propose that integration of vaccines into immunotherapy regimens, guided by tumor-specific immune contexture, antigen selection and treatment sequencing, might expand the benefit of immunotherapy to a broader patient population.
    DOI:  https://doi.org/10.1038/s41590-025-02308-2
  11. Nat Comput Sci. 2025 Oct 15.
    In silico biological discovery with large perturbation models.
    Djordje Miladinovic, Tobias Höppe, Mathieu Chevalley, Andreas Georgiou, Lachlan Stuart, Arash Mehrjou, Marcus Bantscheff, Bernhard Schölkopf, Patrick Schwab.
      Data generated in perturbation experiments link perturbations to the changes they elicit and therefore contain information relevant to numerous biological discovery tasks-from understanding the relationships between biological entities to developing therapeutics. However, these data encompass diverse perturbations and readouts, and the complex dependence of experimental outcomes on their biological context makes it challenging to integrate insights across experiments. Here we present the large perturbation model (LPM), a deep-learning model that integrates multiple, heterogeneous perturbation experiments by representing perturbation, readout and context as disentangled dimensions. LPM outperforms existing methods across multiple biological discovery tasks, including in predicting post-perturbation transcriptomes of unseen experiments, identifying shared molecular mechanisms of action between chemical and genetic perturbations, and facilitating the inference of gene-gene interaction networks. LPM learns meaningful joint representations of perturbations, readouts and contexts, enables the study of biological relationships in silico and could considerably accelerate the derivation of insights from pooled perturbation experiments.
    DOI:  https://doi.org/10.1038/s43588-025-00870-1
  12. Nat Methods. 2025 Oct 13.
    Deep generative modeling of sample-level heterogeneity in single-cell genomics.
    Pierre Boyeau, Justin Hong, Adam Gayoso, Martin Kim, José L McFaline-Figueroa, Michael I Jordan, Elham Azizi, Can Ergen, Nir Yosef.
      Single-cell genomic studies were recently conducted on hundred of samples exhibiting complex designs. These data have tremendous potential for discovering how sample- or tissue-level phenotypes relate to cellular and molecular composition. However, current analyses are often based on simplified representations of these data by averaging information across cells. We present multi-resolution variational inference (MrVI), a deep generative model designed to realize the potential of cohort studies at the single-cell level. MrVI tackles two fundamental, intertwined problems: stratifying samples into groups and evaluating the cellular and molecular differences between groups, without requiring predefined cell states. Leveraging its single-cell perspective, MrVI detects clinically relevant stratifications of cohorts of people with COVID-19 or inflammatory bowel disease that are manifested in only certain cellular subsets, enabling new discoveries that would otherwise be overlooked. MrVI can de novo identify groups of small molecules with similar biochemical properties and evaluate their effects on cellular composition and gene expression in large-scale perturbation studies. MrVI is an open-source tool at scvi-tools.org .
    DOI:  https://doi.org/10.1038/s41592-025-02808-x
  13. Science. 2025 Oct 16. 390(6770): 246
    Knowledge for twoWhen Everyone Knows That Everyone Knows… Steven Pinker Scribner, 2025. 384 pp.
    Jeremy Goodman, Chaz Firestone.
      A psychologist explores common knowledge and coordination.
    DOI:  https://doi.org/10.1126/science.aeb1081
  14. Nat Biotechnol. 2025 Oct 13.
    Programmable promoter editing for precise control of transgene expression.
    Sneha R Kabaria, Yunbeen Bae, Mary E Ehmann, Brittany A Lende-Dorn, Adam M Beitz, Emma L Peterman, Kasey S Love, Deon S Ploessl, Kate E Galloway.
      Subtle changes in gene expression direct cells to distinct cellular states. Identifying and controlling dose-dependent transgenes require tools for precisely titrating expression. Here, we develop a highly modular, extensible framework called DIAL for building editable promoters that allow for fine-scale, heritable changes in transgene expression. Using DIAL, we increase expression by recombinase-mediated excision of spacers between the binding sites of a synthetic zinc finger transcription factor and the core promoter. By nesting varying numbers and lengths of spacers, DIAL generates a tunable range of unimodal setpoints from a single promoter. Through small-molecule control of transcription factors and recombinases, DIAL supports temporally defined, user-guided control of transgene expression that is extensible to additional transcription factors. Lentiviral delivery of DIAL generates multiple setpoints in primary cells and induced pluripotent stem cells. As promoter editing generates stable states, DIAL setpoints are heritable, facilitating mapping of transgene levels to phenotype and fate in direct conversion to induced motor neurons. The DIAL framework opens opportunities for tailoring transgene expression and improving the predictability and performance of gene circuits across diverse applications.
    DOI:  https://doi.org/10.1038/s41587-025-02854-y
  15. Nat Rev Cancer. 2025 Oct 15.
    Exploiting metabolic cell death for cancer therapy.
    Chao Mao, Dadi Jiang, Albert C Koong, Boyi Gan.
      Resistance to cell death is a hallmark of cancer, driving tumour progression and limiting therapeutic efficacy. Metabolic cell death pathways have been identified as unique vulnerabilities in cancer, with ferroptosis being the most extensively studied, alongside the more recently discovered pathways of cuproptosis and disulfidptosis - each triggered by distinct metabolic perturbations. In this Review, we examine the molecular mechanisms and regulatory networks that govern these forms of metabolic cell death in cancer cells. We further examine the potential crosstalk between these pathways and discuss how insights gained and challenges encountered from extensive studies on ferroptosis can guide future research and therapeutic strategies targeting cuproptosis and disulfidptosis in cancer treatment. We highlight the complexity and dual roles of metabolic cell death in cancer and offer our perspective on how to leverage these cell death processes to develop innovative, targeted cancer therapies.
    DOI:  https://doi.org/10.1038/s41568-025-00879-8
  16. Nat Med. 2025 Oct 16.
    The fragile intelligence of GPT-5 in medicine.
    Rebecca Handler, Sonali Sharma, Tina Hernandez-Boussard.
      
    DOI:  https://doi.org/10.1038/s41591-025-04008-8
  17. Front Med (Lausanne). 2025 ;12 1654792
    Microbial signatures in metastatic cancer.
    Jhommara Bautista, María Paula Fuentes-Yépez, Joseth Adatty-Molina, Andrés López-Cortés.
      Metastasis remains the leading cause of cancer-related death, yet the biological determinants that enable tumor cells to disseminate and colonize distant organs are incompletely understood. Emerging evidence identifies the microbiome, not merely as a bystander, but as an active architect of the metastatic cascade. Microbial communities residing in the gut, mucosal barriers, and within tumors shape metastatic progression by modulating immune surveillance, stromal remodeling, oncogenic signaling, and therapy response. Intratumoral and even intracellular microbes regulate epithelial-mesenchymal transition, angiogenesis, and immune escape, while gut-derived metabolites condition pre-metastatic niches and alter systemic immunity. Technological advances in spatial transcriptomics, single-cell multi-omics, and metagenomics have revealed a spatially organized, functionally integrated microbial ecosystem within tumors, challenging long-held assumptions of sterility in cancer biology. This review synthesizes five converging dimensions of this paradigm: microbial interactions in the metastatic tumor microenvironment; microbiome-mediated immunoediting and metastatic escape; the role of intratumoral and intracellular bacteria in dissemination; spatial-multi-omic approaches to map microbial niches; and microbial biomarkers predictive of metastasis and therapy outcomes. Collectively, these findings recast the microbiome as a critical and targetable determinant of metastasis. Deciphering the tumor-microbe-host triad holds transformative potential for biomarker development, therapeutic innovation, and precision oncology.
    Keywords:  immunoediting; intratumoral bacteria; metastasis; metastatic cancer; microbial signatures; microbiome; spatial-multi-omic approaches; tumor microenvironment
    DOI:  https://doi.org/10.3389/fmed.2025.1654792
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