bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–11–09
nineteen papers selected by
Xiao Qin, University of Oxford
  1. Squidiff: predicting cellular development and responses to perturbations using a diffusion model.
  2. Epigenetically driven and early immune evasion in colorectal cancer evolution.
  3. The Aging Microenvironment is a Determinant of Immune Exclusion and Metastatic Fate in Pancreatic Cancer.
  4. Cellular senescence in precancer lesions and early-stage cancers.
  5. Oligo-CALL: A next-generation barcoding platform for studying resistance to targeted therapy.
  6. Site-specific DNA insertion into the human genome with engineered recombinases.
  7. Connectogenomics: edges-first spatial biology.
  8. Navigating the evolving landscape of colorectal cancer screening with a practical framework: a comprehensive analysis of existing and emerging technologies for informed decision-making.
  9. Decoding the spatial dynamics of tumor and immune cell interactions in solid cancers.
  10. Timing and mechanisms of immune evasion in colorectal cancers.
  11. STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport.
  12. Characterization of Drug-Tolerant Persister Cells in Triple-Negative Breast Cancer Identifies a Shared Persistence Program across Treatments and Patients.
  13. Integrative Multi-Omics and Artificial Intelligence: A New Paradigm for Systems Biology.
  14. Multimodal spatial-omics reveal co-evolution of alveolar progenitors and proinflammatory niches in progression of lung precursor lesions.
  15. Circulating tumor cells: indicators of cancer progression, plasticity and utility for therapies.
  16. Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration.
  17. Decoding the regulatory genome with large-scale deep learning.
  18. Can AI be truly creative?
  19. scCausalVI disentangles single-cell perturbation responses with causality-aware generative model.
  1. Nat Methods. 2025 Nov 03.
    Squidiff: predicting cellular development and responses to perturbations using a diffusion model.
    Siyu He, Yuefei Zhu, Daniel Naveed Tavakol, Haotian Ye, Yeh-Hsing Lao, Zixian Zhu, Cong Xu, Shradha Chauhan, Guy Garty, Raju Tomer, Gordana Vunjak-Novakovic, James Zou, Elham Azizi, Kam W Leong.
      Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and responses to environmental stimuli. However, mapping transcriptomic changes across diverse cell types in response to various stimuli and elucidating underlying disease mechanisms remains challenging. Here we present Squidiff, a diffusion model-based generative framework that predicts transcriptomic changes across diverse cell types in response to environmental changes. We demonstrate the robustness of Squidiff across cell differentiation, gene perturbation and drug response prediction. Through continuous denoising and semantic feature integration, Squidiff learns transient cell states and predicts high-resolution transcriptomic landscapes over time and conditions. Furthermore, we applied Squidiff to model blood vessel organoid development and cellular responses to neutron irradiation and growth factors. Our results demonstrate that Squidiff enables in silico screening of molecular landscapes and cellular state transitions, facilitating rapid hypothesis generation and providing valuable insights into the regulatory principles of cell fate decisions.
    DOI:  https://doi.org/10.1038/s41592-025-02877-y
  2. Nat Genet. 2025 Nov 05.
    Epigenetically driven and early immune evasion in colorectal cancer evolution.
    Eszter Lakatos, Vinaya Gunasri, Luis Zapata, Jacob Househam, Timon Heide, Nicholas Trahearn, Ottilie Swinyard, Luis Cisneros, Claire Lynn, Maximilian Mossner, Chris Kimberley, Inmaculada Spiteri, George D Cresswell, Gerard Llibre-Palomar, Miriam Mitchison, Carlo C Maley, Marnix Jansen, Manuel Rodriguez-Justo, John Bridgewater, Ann-Marie Baker, Andrea Sottoriva, Trevor A Graham.
      Immune system control is a principal hurdle in cancer evolution. The temporal dynamics of immune evasion remain incompletely characterized, and how immune-mediated selection interrelates with epigenome alteration is unclear. Here we infer the genome- and epigenome-driven evolutionary dynamics of tumor-immune coevolution within primary colorectal cancers (CRCs). We utilize a multiregion multiomic dataset of matched genome, transcriptome and chromatin accessibility profiling from 495 single glands (from 29 CRCs) supplemented with high-resolution spatially resolved neoantigen sequencing data and multiplexed imaging of the tumor microenvironment from 82 microbiopsies within 11 CRCs. Somatic chromatin accessibility alterations contribute to accessibility loss of antigen-presenting genes and silencing of neoantigens. Immune escape and exclusion occur at the outset of CRC formation, and later intratumoral differences in immuno-editing are negligible or exclusive to sites of invasion. Collectively, immune evasion in CRC follows a 'Big Bang' evolutionary pattern, whereby it is acquired close to transformation and defines subsequent cancer-immune evolution.
    DOI:  https://doi.org/10.1038/s41588-025-02349-1
  3. Cancer Res. 2025 Nov 07.
    The Aging Microenvironment is a Determinant of Immune Exclusion and Metastatic Fate in Pancreatic Cancer.
    Priyanka Gupta, Rabi Murad, Li Ling, Yijuan Zhang, Karen Duong-Polk, Weiliang Huang, Marzia Scortegagna, Swetha Maganti, Cheska Marie Galapate, Cosimo Commisso.
      Aging is a critical yet understudied determinant in pancreatic ductal adenocarcinoma (PDAC) risk and outcomes. Despite a strong epidemiological association with age, conventional PDAC preclinical models fail to capture the histopathological and stromal complexities that emerge in older organisms. Using an age-relevant syngeneic orthotopic model, we demonstrated that organismal aging accelerates PDAC progression and metastasis. Transcriptomic and secretome profiling identified a conserved extracellular matrix gene signature enriched in cancer-associated fibroblasts (CAFs) from aged tumors, consistent with an augmented fibrotic landscape that supports immunosuppression, metastatic tropism, and poor prognosis. Direct testing of the functional impact of stromal aging in heterochronic co-implantation models revealed that revitalizing the aged tumor stroma with young CAFs restores immune infiltration and attenuates metastasis in older hosts. Conversely, aged CAFs, while immunosuppressive, failed to enhance metastasis in young hosts, suggesting that a youthful microenvironment exerts dominant regulatory control over disease progression. These findings demonstrate that stromal age is a critical modulator of both immune exclusion and metastatic behavior in PDAC. Importantly, this work establishes a conceptual framework for understanding how aging shapes the tumor microenvironment in PDAC and opens a fertile avenue of investigation into age-specific stromal regulation. Moreover, these findings raise compelling questions about the underlying molecular mechanisms and lay the foundation for future efforts to therapeutically target stromal aging in PDAC.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-1904
  4. Cancer Cell. 2025 Nov 06. pii: S1535-6108(25)00447-7. [Epub ahead of print]
    Cellular senescence in precancer lesions and early-stage cancers.
    TBEL Consortium
      Cellular senescence plays dual roles in precancer lesions: initially serving as a tumor-suppressive barrier within the epithelial compartment and later contributing to a pro-tumoral precancer tissue microenvironment (PreTME) via a sustained, paracrine secretome known as senescent-associated secretory phenotype (SASP). This commentary highlights the role of senescence across various PreTME cell types, explores emerging pharmacologic and lifestyle interception strategies, and outlines current challenges for advancing biomarkers and clinical translation.
    DOI:  https://doi.org/10.1016/j.ccell.2025.10.006
  5. Sci Adv. 2025 Nov 07. 11(45): eadw9990
    Oligo-CALL: A next-generation barcoding platform for studying resistance to targeted therapy.
    Yingzhuo Liu, Yi Ban, Dingcheng Gao.
      Understanding therapy resistance requires deconvolving heterogeneous cell populations and tracking clonal trajectories. While CRISPR-based cellular barcoding is powerful for lineage tracing, many platforms suffer from low efficiency and limited compatibility with single-cell transcriptomics. We developed Oligo-CALL (Oligonucleotide-inducible CRISPR transcriptional activator-Assisted Lineage Labeling), an advanced barcoding system enabling precise lineage tracing, live clone isolation, and seamless integration with single-cell RNA sequencing. Applied to lung cancer cells treated with a KRASG12C inhibitor, Oligo-CALL identified clones consistently enriched posttreatment, supporting a model of predestined resistance. Oligo-CALL achieved >95% efficiency in linking lineage identity to transcriptomes, uncovering diverse clone-specific pathways with underlying resistance. Paired analysis of barcode-matched clones from naïve and resistant populations revealed transient and fixed resistance phenotypes. Notably, DNA repair pathways are recurrently altered in resistant clones, and inhibition of poly(adenosine 5'-diphosphate-ribose) polymerase synergizes with KRAS G12C inhibition to overcome resistance. Together, Oligo-CALL provides a versatile platform for dissecting lineage evolution and molecular dynamics of targeted therapy resistance.
    DOI:  https://doi.org/10.1126/sciadv.adw9990
  6. Nat Biotechnol. 2025 Nov 06.
    Site-specific DNA insertion into the human genome with engineered recombinases.
    Alison Fanton, Liam J Bartie, Juliana Q Martins, Vincent Q Tran, Laine Goudy, Courtney Kernick, Matthew G Durrant, Jingyi Wei, Zev Armour-Garb, April Pawluk, Silvana Konermann, Alexander Marson, Luke A Gilbert, Theodore L Roth, Patrick D Hsu.
      Insertions of large DNA sequences into the genome are broadly enabling for research and therapeutic applications. Large serine recombinases (LSRs) can mediate direct, site-specific genomic integration of multi-kilobase DNA sequences without a pre-installed landing pad, albeit with low insertion rates and high off-target activity. Here we present an engineering roadmap for jointly optimizing their DNA recombination efficiency and specificity. We combine directed evolution, structural analysis and computational models to rapidly identify additive mutational combinations. We further enhance performance through donor DNA optimization and dCas9 fusions, enabling simultaneous target and donor recruitment. Our top engineered LSR variants, superDn29-dCas9, goldDn29-dCas9 and hifiDn29-dCas9, achieve up to 53% integration efficiency and 97% genome-wide specificity at an endogenous human locus and effectively integrate large DNA cargoes up to 12 kb for stable expression in non-dividing cells, stem cells and primary human T cells. Rational engineering of DNA recombinases enables precise and efficient single-step genome insertion for diverse applications across gene and cell therapies.
    DOI:  https://doi.org/10.1038/s41587-025-02895-3
  7. Trends Biotechnol. 2025 Nov 06. pii: S0167-7799(25)00419-6. [Epub ahead of print]
    Connectogenomics: edges-first spatial biology.
    Reem Yasser, Mingrui Yu, Nianchao Qian, Han Chang, Joshua A Weinstein.
      Spatial omics maps cell types and spatial context together. Current methods fall into two streams: mapping coordinates (where things are) and measuring connections between cells that are in contact or close proximity. We introduce the term connectogenomics as a practical umbrella for sequencing assays that directly record such contacts as a network. Combining coordinates with measured contacts lets us verify whether apparent neighbors truly interact and turn network features - such as contact density or hub centrality - into quantitative readouts. We propose a framework with four complementary tiers and a feedback loop: directly measured molecular contacts can validate coordinate-based analyses, while coordinate maps guide where to prioritize contact measurements. We illustrate this approach in cancer immunotherapy, development, and pooled genetic screens.
    Keywords:  connectogenomics; graph theory; spatial omics; systems biology; tissue microenvironment
    DOI:  https://doi.org/10.1016/j.tibtech.2025.10.012
  8. Oncol Rev. 2025 ;19 1653617
    Navigating the evolving landscape of colorectal cancer screening with a practical framework: a comprehensive analysis of existing and emerging technologies for informed decision-making.
    Michael Sapienza, Cheryl Davis, Mathieu Boudes.
      The colorectal cancer (CRC) screening landscape has rapidly evolved, introducing new technologies alongside established methods. The lack of head-to-head observational studies comparing these diverse options impairs clinicians' and patients' ability to make informed choices in CRC screening test selection. This manuscript aims to provide a comprehensive review of existing and emerging CRC screening technologies and develop a practical framework for informed decision-making. We conducted a systematic review of current literature on CRC screening methods, including colonoscopy, fecal immunochemical test (FIT), multi-target stool DNA test (mt-sDNA), the next-generation multi-target stool DNA test, multi-target stool RNA test (mt-sRNA), and blood-based tests. We summarized performance characteristics, adherence rates, follow-up colonoscopy rates, accessibility, and costs for each method. Our review revealed significant variations in test performance, patient adherence, and implementation factors across screening modalities. Blood-based tests showed promise in terms of patient acceptance but currently have lower sensitivity for early-stage cancers with a higher participant adherence when screening navigation is provided. Our review led to the development of a comprehensive framework for evaluating CRC screening options, addressing the critical need for informed decision-making in this area. The framework encompasses five key dimensions: test performance (sensitivity and specificity for CRC and precancerous lesions), patient considerations (invasiveness, preparation, and location preferences), adherence and follow-up (real-world rates and diagnostic colonoscopy completion rates), accessibility and cost (insurance coverage, out-of-pocket expenses, and system integration), and screening interval (recommended frequency and long-term impact). By synthesizing data, the framework enables healthcare providers and patients to navigate the complex landscape of screening options, facilitating personalized recommendations tailored to individual risk factors, preferences, and healthcare system constraints. Future research should validate this framework in diverse clinical settings and update it as new technologies emerge, ensuring continued improvement in CRC screening participation, effectiveness, and outcomes.
    Keywords:  colorectal cancer; diagnosis; patients; prevention; screening
    DOI:  https://doi.org/10.3389/or.2025.1653617
  9. Cancer Cell. 2025 Nov 06. pii: S1535-6108(25)00448-9. [Epub ahead of print]
    Decoding the spatial dynamics of tumor and immune cell interactions in solid cancers.
    Eleanor Minogue, Pilar Baldominos, Lauren Hsu, Marcia C Haigis, Judith Agudo.
      The spatial landscape of the tumor immune microenvironment (TIME) is under significant investigation as a driver of immunotherapy resistance in solid tumors. Most work centers on constituent immune cells within intra-tumoral niches, overlooking tumor cell phenotypes. Yet cancer cells shape their milieu by multiple modalities, including secreting and depleting metabolites. Here, we argue that integrating cancer cell phenotypic heterogeneity into spatial analyses is essential to reveal the mechanisms that generate TIME diversity and to better address resistance to immunotherapy.
    DOI:  https://doi.org/10.1016/j.ccell.2025.10.007
  10. Nat Genet. 2025 Nov 07.
    Timing and mechanisms of immune evasion in colorectal cancers.
      
    DOI:  https://doi.org/10.1038/s41588-025-02348-2
  11. Nat Methods. 2025 Nov 03.
    STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport.
    Geert-Jan Huizing, Jules Samaran, Daniele Capocefalo, Anna Audit, Gabriel Peyré, Laura Cantini.
      In dynamic biological processes such as development, spatial transcriptomics is revolutionizing the study of the mechanisms underlying spatial organization within tissues. Inferring cell fate trajectories from spatial transcriptomics profiled at several time points has thus emerged as a critical goal, requiring novel computational methods. Wasserstein gradient flow learning is a promising framework for analyzing sequencing data across time, built around a neural network representing the differentiation potential. However, existing gradient flow learning methods face challenges in analyzing spatially resolved transcriptomic data. Here, we propose STORIES, a method that uses an extension of Optimal Transport to learn a spatially informed potential. We benchmark our approach using three large Stereo-seq spatiotemporal atlases and demonstrate superior spatial coherence compared to existing approaches. Finally, we provide an in-depth analysis of axolotl neural regeneration and mouse gliogenesis, recovering gene trends for known markers such as Nptx1 in neuron regeneration and Aldh1l1 in gliogenesis and additional putative drivers.
    DOI:  https://doi.org/10.1038/s41592-025-02855-4
  12. Cancer Res. 2025 Nov 06. OF1-OF16
    Characterization of Drug-Tolerant Persister Cells in Triple-Negative Breast Cancer Identifies a Shared Persistence Program across Treatments and Patients.
    Léa Baudre, Grégoire Jouault, Pacôme Prompsy, Melissa Saichi, Sarah Gastineau, Christophe Huret, Laura Sourd, Ahmed Dahmani, Elodie Montaudon, Florent Dingli, Damarys Loew, Elisabetta Marangoni, Justine Marsolier, Céline Vallot.
      Acquisition of resistance to anticancer therapies is a multistep process initiated by the survival of drug-tolerant persister cells. Accessibility of drug-tolerant persister cells in patients is limited, which has hindered understanding the mechanisms driving their emergence. In this study, using multiple patient-derived models to isolate persister cells, we showed that these cells are transcriptionally plastic in vivo and return to a common treatment naïve-like state upon relapse, regardless of treatment. Hallmarks of the persister state in triple-negative breast cancer (TNBC) across treatment modalities included high expression of basal keratins together with activation of stress response and inflammation pathways. These hallmarks were also activated in HER2+ breast and lung cancer cells in response to targeted therapies. Analysis of gene regulatory networks identified AP-1, NF-κB, and IRF/STAT as the key drivers of this hallmark persister state. Functionally, FOSL1, an AP-1 member, drove cells to the persister state by binding enhancers and reprogramming the transcriptome of cancer cells. On the contrary, cancer cells without FOSL1 had a decreased ability to reach the persister state. By defining hallmarks of TNBC persistence on multiple therapies, this study provides a resource to design effective combination therapeutic strategies that limit resistance.
    SIGNIFICANCE: Elucidation of the features of the drug-tolerant persister state in triple-negative breast cancer reveals shared programs across patients and treatments that offer opportunities to prevent persistence and delay tumor recurrence.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-0995
  13. OMICS. 2025 Nov 07.
    Integrative Multi-Omics and Artificial Intelligence: A New Paradigm for Systems Biology.
    Shashi Kant, Deepika, Saheli Roy.
      The increasing accessibility of high-throughput omics technologies has represented a paradigm change in systems biology, facilitating the systematic exploration of biological complexity at genomic, transcriptomic, proteomic, and metabolomic levels. Contemporary systems biology more and more depends on integrative multi-omics strategies to unravel the sophisticated, dynamic networks of cellular function and organismal phenotypes. Such methodologies enable scientists to clarify molecular interactions, decipher disease pathology, identify strong biomarkers, and guide precision medicine and synthetic biology initiatives. Recent technological breakthroughs in computational tools, ranging from early or late data integration, network analysis, and machine learning, have overcome obstacles of high-dimensionality, heterogeneity, and perturbations restricted to specific contexts. In this review, we critically assess the principles, methods, and applications of multi-omics integration, with an emphasis on cancer biology, microbial engineering, and synthetic biology. We showcase case studies in which integrative omics provided actionable findings. Finally, we address current limitations (e.g., data heterogeneity, interpretability) and forthcoming solutions (artificial intelligence, single-cell omics, cloud platforms). By closing the gap between molecular layers, multi-omics integration is moving toward predictive models of biological systems and revolutionary biotechnological applications.
    Keywords:  artificial intelligence; data integration; multi-omics; synthetic biology; systems biology
    DOI:  https://doi.org/10.1177/15578100251392371
  14. Cancer Cell. 2025 Nov 06. pii: S1535-6108(25)00445-3. [Epub ahead of print]
    Multimodal spatial-omics reveal co-evolution of alveolar progenitors and proinflammatory niches in progression of lung precursor lesions.
    Fuduan Peng, Ansam Sinjab, Yibo Dai, Warapen Treekitkarnmongkol, Sujuan Yang, Lorena I Gomez Bolanos, Tieling Zhou, Minyue Chen, Alejandra G Serrano, Avantika Krishna, Nastaran Karimi, Manvi Sharma, Akshay Basi, Guangsheng Pei, Jianlong Liao, Yunhe Liu, Jiping Feng, Zahraa Rahal, Yang Liu, Jiahui Jiang, Kai Yu, Tala Noun, Yuejiang Liu, Khaja Khan, Kyung Serk Cho, Jichao Chen, Luisa M Solis, Sarah Mazzilli, Steven Dubinett, Tina Cascone, Avrum E Spira, Stephen Swisher, Naoe Jimbo, Takuo Hayashi, Satsuki Kishikawa, Kazuya Takamochi, Tomoo Itoh, Takashi Yao, Kenji Suzuki, Neda Kalhor, Ignacio I Wistuba, Mingyao Li, Seyed Javad Moghaddam, Junya Fujimoto, Jared Burks, Jeffrey Myers, Kadir Akdemir, Linghua Wang, Humam Kadara.
      The co-evolution of different cell subsets in the progression of precursor lesions to lung adenocarcinoma (LUAD) is incompletely understood. We generated spatial transcriptomic maps of 56 human precursor lesions and LUADs from 25 patients and of an independent cohort of 36 lesions from 19 patients, analyzing a total of 486,519 spots and 5.4 million cells. We identify region-specific programs that distinguish precursors from LUADs. Spatially resolved clonal architectures reveal patient-specific heterogeneity in evolution of precursors to LUADs. We find epithelial alveolar progenitors expressing tumor-associated meta-programs and residing in niches enriched with proinflammatory subsets including IL1B high macrophages. Epithelial-proinflammatory niches are prevalent in precursor lesions but become less frequent in LUADs. These niches are conserved in mice and promote alveolar progenitor growth. Targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase reduces alveolar progenitors. Epithelial-inflammatory niches are stage-specific, shape early LUAD development and represent promising targets for interception.
    Keywords:  IL-1β; LUAD interception; Xenium in situ; alveolar progenitors; epithelial-immune niche; lung adenocarcinoma; lung precursor lesions; proinflammatory pathways; reactive type II pneumocytes; spatial transcriptomics
    DOI:  https://doi.org/10.1016/j.ccell.2025.10.004
  15. Pathol Oncol Res. 2025 ;31 1612181
    Circulating tumor cells: indicators of cancer progression, plasticity and utility for therapies.
    Tamás Richárd Linkner, Zsófia Brigitta Nagy, Alexandra Kalmár, Eszter Farkas, Fruzsina Bányai, Nikolett Szakállas, István Takács, Béla Molnár.
      Cancer is a deadly disease affecting millions of people worldwide. Circulating tumor cells (CTCs) represent a critical link between primary malignancies and metastasis, acting as key players in cancer dissemination, progression, and recurrence. Although rare, CTCs offer a valuable, non-invasive window into tumor biology and the evolution of disease in patients. CTCs can exist as single cells in the circulation, but some are shed and travel in larger groups, referred to as CTC clusters. These clusters possess a greater oncogenic potential compared to individual CTCs. In this review, we aim to provide insight into the dynamic biological processes underlying CTC generation, biology, and survival, with a focus on epithelial-to-mesenchymal transition (EMT) and beyond like cancer stem cells (CSCs), cellular plasticity, and senescence. A crucial aspect of CTC biology is EMT, a process that imparts cancer cells with increased motility, invasiveness, resistance to apoptosis, and the ability to intravasate and evade the immune system. Beyond EMT the cancer cells show further plasticity, allowing epithelial tumor cells to adopt mesenchymal or hybrid phenotypes, which enables adaptation to a changing microenvironment and enhances therapy resistance. Moreover, a subset of cancer cells can acquire stem cell-like properties, including self-renewal and tumor-initiating capacity. EMT, along with processes such as dedifferentiation, contributes to the generation of cancer stem cells. In recent years, studies have also highlighted the complex and paradoxical role of senescence in CTC biology. While senescence typically results in permanent cell cycle arrest, in cancer cells it may be reversible and can promote tumor cell dormancy, immune evasion, and metastatic reactivation. By exploring the connections between CTCs, EMT, CSCs, plasticity, and senescence, we aim to shed light on the unique biology of CTCs, their metastatic potential, and their contributions to tumor heterogeneity. We hope that a better understanding of these processes will help advance the development of novel biomarkers and therapeutic targets for solid tumors beyond EMT.
    Keywords:  EMT; cancer; circulating tumor cells; liquid biopsy; senescence
    DOI:  https://doi.org/10.3389/pore.2025.1612181
  16. Nat Cancer. 2025 Nov 06.
    Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration.
    Jing Han, Xiaoman Lu, Mengmeng Guo, Ruizhe He, Meilian Zhuo, Saisai Wang, Yong Li, Xiangzheng Liu, Di Zou, Jiacheng Wang, Jiangjiao Mao, Qian Chen, Xia Wang, Junya Peng, Wei Xie, Charles J David, Mo Chen.
      Acute pancreatitis-induced acinar-to-ductal metaplasia involves global chromatin remodeling and contributes to normal tissue regeneration. Oncogenic KRAS hijacks this process to promote PDAC formation. Here we show that regeneration and KRASG12D-driven oncogenesis can be decoupled from tissue regeneration through a chromatin remodeler, SMARCA5. We show that SMARCA5 maintains KRASG12D-dependent chromatin accessibility at regions specifically required for malignancy, without affecting chromatin opening that occurs during normal regeneration. Without SMARCA5, regeneration can be restored in the presence of KRASG12D. Mechanistically, regeneration-related or malignancy-related chromatin remodeling activities occur in a time-sensitive manner. The activity of SMARCA5 is controlled spatiotemporally by transcription factor RUNX1, which only accumulates at sufficient levels with sustained MAPK signals. We further show that inhibition of the SMARCA5-containing NoRC complex specifically inhibits the growth of PDAC organoid but not that of normal tissue derived from patients.
    DOI:  https://doi.org/10.1038/s43018-025-01065-3
  17. Nat Rev Genet. 2025 Nov 03.
    Decoding the regulatory genome with large-scale deep learning.
    Peter K Koo.
      
    DOI:  https://doi.org/10.1038/s41576-025-00914-2
  18. Nature. 2025 Nov;647(8088): 24-26
    Can AI be truly creative?
    Jo Marchant.
      
    Keywords:  Arts; Machine learning; Technology
    DOI:  https://doi.org/10.1038/d41586-025-03570-y
  19. Cell Syst. 2025 Nov 05. pii: S2405-4712(25)00276-5. [Epub ahead of print] 101443
    scCausalVI disentangles single-cell perturbation responses with causality-aware generative model.
    Shaokun An, Jae-Won Cho, Kai Cao, Jiankang Xiong, Martin Hemberg, Lin Wan.
      Single-cell RNA sequencing provides detailed insights into cellular heterogeneity and responses to external stimuli. However, distinguishing inherent cellular variation from extrinsic effects induced by external stimuli remains a major analytical challenge. Here, we present scCausalVI, a causality-aware generative model designed to disentangle these sources of variation. scCausalVI decouples intrinsic cellular states from treatment effects through a deep structural causal network that explicitly models the causal mechanisms governing cell-state-specific responses to external perturbations while accounting for technical variations. Our model integrates structural causal modeling with cross-condition in silico prediction to infer gene expression profiles under hypothetical scenarios. Comprehensive benchmarking demonstrates that scCausalVI outperforms existing methods in disentangling causal relationships, quantifying treatment effects, generalizing to unseen cell types, and separating biological signals from technical variation in multi-source data integration. Applied to COVID-19 datasets, scCausalVI effectively identifies treatment-responsive populations and delineates molecular signatures of cellular susceptibility.
    Keywords:  causal disentanglement; cell-state-specific treatment effect; deep structural causal model; in silico perturbation; multi-source data integration; out-of-distribution prediction; perturbational analysis; responsive cell identification
    DOI:  https://doi.org/10.1016/j.cels.2025.101443
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