bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–03–23
thirty-six papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition.
  2. Self-assembly of the insulin-responsive vesicles creates a signaling platform for the insulin action on glucose uptake.
  3. Physiological shear stress suppresses apoptosis in human pulmonary microvascular endothelial cells.
  4. Dynamic cytoskeletal regulation of cell shape supports resilience of lymphatic endothelium.
  5. Emerging Approaches for Studying Lipid Dynamics, Metabolism, and Interactions in Cells.
  6. Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.
  7. Hepatic IR and IGF1R signaling govern distinct metabolic and carcinogenic processes upon PTEN deficiency in the liver.
  8. Extracranial arteriovenous malformations: towards etiology-based therapeutic management.
  9. POT, an optogenetics-based endogenous protein degradation system.
  10. Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.
  11. High resolution profiling of cell cycle-dependent protein and phosphorylation abundance changes in non-transformed cells.
  12. The primate-specific Nedd4-1(NE) localizes to late endosomes in response to amino acids to suppress autophagy.
  13. SPARROW reveals microenvironment-zone-specific cell states in healthy and diseased tissues.
  14. Quantitative characterization of cell niches in spatially resolved omics data.
  15. How the past is shaping the future of life science: The influence of automation and AI on biology.
  16. MOSim: bulk and single-cell multilayer regulatory network simulator.
  17. Integrating -Omic Technologies across Modality, Space, and Time to Decipher Remodeling in Cardiac Disease.
  18. Evaluation of De Vries et al.: Quantifying cellular shapes and how they correlate to cellular responses.
  19. Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.
  20. The end of the genetic paradigm of cancer.
  21. Targeting PI3K inhibitor resistance in breast cancer with metabolic drugs.
  22. Non-serous ovarian cancer in PTEN Hamartoma Tumor Syndrome: additional evidence for increased risk.
  23. Targeted Therapies for Slow-Flow Vascular Malformations.
  24. The pathways for nanoparticle transport across tumour endothelium.
  25. Gene-environment interaction modifies the association between hyperinsulinemia and serum urate levels through SLC22A12.
  26. A single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations.
  27. Epithelial polarization by the planar cell polarity complex is exclusively non-cell autonomous.
  28. A computational pipeline for spatial mechano-transcriptomics.
  29. Why humans have puzzle-shaped cells.
  30. Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions.
  31. Wrestling with the RAS cancer drug pipeline.
  32. Cell-matrix feedback controls stretch-induced cellular memory and fibroblast activation.
  33. Extracellular Vesicles and Cellular Homeostasis.
  34. Tough times for CRISPR startups.
  35. Mapping the transcriptional and epigenetic landscape of organotypic endothelial diversity in the developing and adult mouse.
  36. Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.
  1. Cell Syst. 2025 Mar 17. pii: S2405-4712(25)00072-9. [Epub ahead of print] 101239
    Signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition.
    Cameron T Flower, Chunmei Liu, Hui-Yu Chuang, Xiaoyang Ye, Hanjun Cheng, James R Heath, Wei Wei, Forest M White.
      A major contributor to poor sensitivity to anti-cancer kinase inhibitor therapy is drug-induced cellular adaptation, whereby remodeling of signaling and gene regulatory networks permits a drug-tolerant phenotype. Here, we resolve the scale and kinetics of critical subcellular events following oncogenic kinase inhibition and preceding cell cycle re-entry, using mass spectrometry-based phosphoproteomics and RNA sequencing (RNA-seq) to monitor the dynamics of thousands of growth- and survival-related signals over the first minutes, hours, and days of oncogenic BRAF inhibition in human melanoma cells. We observed sustained inhibition of the BRAF-ERK axis, gradual downregulation of cell cycle signaling, and three distinct, reversible phase transitions toward quiescence. Statistical inference of kinetically defined regulatory modules revealed a dominant compensatory induction of SRC family kinase (SFK) signaling, promoted in part by excess reactive oxygen species, rendering cells sensitive to co-treatment with an SFK inhibitor in vitro and in vivo, underscoring the translational potential for assessing early drug-induced adaptive signaling. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  BRAF; SRC family kinase signaling; cancer systems biology; drug adaptation; gene regulatory network; kinase inhibition; melanoma; multi-omics integration; oncogenic signaling; phosphoproteomics
    DOI:  https://doi.org/10.1016/j.cels.2025.101239
  2. Vitam Horm. 2025 ;pii: S0083-6729(24)00064-5. [Epub ahead of print]128 93-121
    Self-assembly of the insulin-responsive vesicles creates a signaling platform for the insulin action on glucose uptake.
    Konstantin V Kandror.
      In fat and skeletal muscle cells, insulin causes plasma membrane translocation of specialized insulin-responsive vesicles, or IRVs. These vesicles consist of multiple copies of Glut4, sortilin, IRAP, and LRP1 as well as several auxiliary components. Major IRV proteins have relatively long half-life inside the cell and survive multiple rounds of translocation to and from the cell surface. Here, we summarize evidence showing how the IRVs are self-assembled from pre-synthesized Glut4, sortilin, IRAP, and LRP1 after each translocation event. Furthermore, the cytoplasmic tail of sortilin binds Akt while cytoplasmic tails of IRAP and LRP1 interact with the Akt target, TBC1D4. Recruitment of signaling proteins to the IRVs may render insulin responsiveness to this compartment and thus distinguish it from other intracellular membrane vesicles.
    Keywords:  Glut4; IRAP; Insulin; LRP1; Membrane traffic; Signaling; Sortilin; Vesicles
    DOI:  https://doi.org/10.1016/bs.vh.2024.07.001
  3. Physiol Rep. 2025 Mar;13(6): e70269
    Physiological shear stress suppresses apoptosis in human pulmonary microvascular endothelial cells.
    Simin Yan, Nicolas M Philip, Samuel T Murray, Xin Yun, Michael P Croglio, Karthik Suresh, Mahendra Damarla, Larissa A Shimoda, Todd M Kolb.
      Physiological shear stress contributes to maintaining endothelial cell homeostasis, including suppression of apoptosis. In the pulmonary circulation, diseases such as pulmonary embolism and pulmonary hypertension result in alterations in shear stress. Shear stress has been reported to suppress endothelial apoptosis through phosphatidylinositol 3-kinase (PI3K) activation, but evidence from human pulmonary microvascular endothelial cells (PMVECs) is lacking. We hypothesized that physiological shear stress activates PI3K to reduce apoptosis in human PMVECs. We utilized the orbital shaker model of shear stress to test our hypothesis. Apoptosis was evaluated by measuring chromatin condensation, caspase 3/7 activity, and DNA fragmentation. We found that shear stress caused a rapid and sustained increase in protein kinase B (Akt) phosphorylation, a surrogate for activated PI3K, in human PMVECs. Under static conditions, PI3K inhibition with LY294002 or challenge with the kinase inhibitor staurosporine (STS) induced apoptosis in PMVECs. Following exposure to shear stress for 24 h, LY294002- and STS-induced apoptosis was reduced. The anti-apoptotic effect of shear stress in STS-challenged cells was reversed by PI3K inhibition. We conclude that physiological shear stress increases PI3K/Akt activity and suppresses apoptosis in normal human PMVECs.
    Keywords:  apoptosis; human pulmonary microvascular endothelial cells; phosphatidylinositol 3‐kinase; shear stress
    DOI:  https://doi.org/10.14814/phy2.70269
  4. Nature. 2025 Mar 19.
    Dynamic cytoskeletal regulation of cell shape supports resilience of lymphatic endothelium.
    Hans Schoofs, Nina Daubel, Sarah Schnabellehner, Max L B Grönloh, Sebastián Palacios Martínez, Aleksi Halme, Amanda M Marks, Marie Jeansson, Sara Barcos, Cord Brakebusch, Rui Benedito, Britta Engelhardt, Dietmar Vestweber, Konstantin Gaengel, Fabian Linsenmeier, Sebastian Schürmann, Pipsa Saharinen, Jaap D van Buul, Oliver Friedrich, Richard S Smith, Mateusz Majda, Taija Mäkinen.
      Lymphatic capillaries continuously take up interstitial fluid and adapt to resulting changes in vessel calibre1-3. The mechanisms by which the permeable monolayer of loosely connected lymphatic endothelial cells (LECs)4 maintains mechanical stability remain elusive. Here we identify dynamic cytoskeletal regulation of LEC shape, induced by isotropic stretch, as crucial for the integrity and function of dermal lymphatic capillaries. We found that the oak leaf-shaped LECs showed a spectrum of VE-cadherin-based junctional configurations at the lobular intercellular interface and a unique cytoskeletal organization, with microtubules at concave regions and F-actin at convex lobes. Multispectral and longitudinal intravital imaging of capillary LEC shape and actin revealed dynamic remodelling of cellular overlaps in vivo during homeostasis and in response to interstitial fluid volume increase. Akin to puzzle cells of the plant epidermis5,6, LEC shape was controlled by Rho GTPase CDC42-regulated cytoskeletal dynamics, enhancing monolayer stability. Moreover, cyclic isotropic stretch increased cellular overlaps and junction curvature in primary LECs. Our findings indicate that capillary LEC shape results from continuous remodelling of cellular overlaps that maintain vessel integrity while preserving permeable cell-cell contacts compatible with vessel expansion and fluid uptake. We propose a bellows-like fluid propulsion mechanism, in which fluid-induced lumen expansion and shrinkage of LEC overlaps are countered by actin-based lamellipodia-like overlap extension to aid vessel constriction.
    DOI:  https://doi.org/10.1038/s41586-025-08724-6
  5. Annu Rev Biochem. 2025 Mar 18.
    Emerging Approaches for Studying Lipid Dynamics, Metabolism, and Interactions in Cells.
    Lin Luan, Nathan P Frederick, Jeremy M Baskin.
      Lipids are a major class of biological molecules, the primary components of cellular membranes, and critical signaling molecules that regulate cell biology and physiology. Due to their dynamic behavior within membranes, rapid transport between organelles, and complex and often redundant metabolic pathways, lipids have traditionally been considered among the most challenging biological molecules to study. In recent years, a plethora of tools bridging the chemistry-biology interface has emerged for studying different aspects of lipid biology. Here, we provide an overview of these approaches. We discuss methods for lipid detection, including genetically encoded biosensors, synthetic lipid analogs, and metabolic labeling probes. For targeted manipulation of lipids, we describe pharmacological agents and controllable enzymes, termed membrane editors, that harness optogenetics and chemogenetics. To conclude, we survey techniques for elucidating lipid-protein interactions, including photoaffinity labeling and proximity labeling. Collectively, these strategies are revealing new insights into the regulation, dynamics, and functions of lipids in cell biology.
    DOI:  https://doi.org/10.1146/annurev-biochem-083024-110827
  6. Cell Syst. 2025 Mar 19. pii: S2405-4712(25)00062-6. [Epub ahead of print]16(3): 101229
    Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.
    Matt De Vries, Lucas G Dent, Nathan Curry, Leo Rowe-Brown, Vicky Bousgouni, Olga Fourkioti, Reed Naidoo, Hugh Sparks, Adam Tyson, Chris Dunsby, Chris Bakal.
      The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understand cell states. This study introduced MorphoMIL, a computational pipeline combining geometric deep learning and attention-based multiple-instance learning to profile 3D cell and nuclear shapes. We used 3D point-cloud input and captured morphological signatures at single-cell and population levels, accounting for phenotypic heterogeneity. We applied these methods to over 95,000 melanoma cells treated with clinically relevant and cytoskeleton-modulating chemical and genetic perturbations. The pipeline accurately predicted drug perturbations and cell states. Our framework revealed subtle morphological changes associated with perturbations, key shapes correlating with signaling activity, and interpretable insights into cell-state heterogeneity. MorphoMIL demonstrated superior performance and generalized across diverse datasets, paving the way for scalable, high-throughput morphological profiling in drug discovery. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  3D cell shape; cell morphology; cell profiling; cytoskeleton; geometric deep learning; lightsheet microscopy; multiple-instance learning
    DOI:  https://doi.org/10.1016/j.cels.2025.101229
  7. JHEP Rep. 2025 Apr;7(4): 101305
    Hepatic IR and IGF1R signaling govern distinct metabolic and carcinogenic processes upon PTEN deficiency in the liver.
    Monika Gjorgjieva, Nicolas Calo, Cyril Sobolewski, Dorothea Portius, Jean-Luc Pitetti, Flavien Berthou, Anne-Sophie Ay, Marion Peyrou, Lucie Bourgoin, Christine Maeder, Margot Fournier, Marta Correia de Sousa, Etienne Delangre, Laurent Vinet, Xavier Montet, Christine Sempoux, Serge Nef, Michelangelo Foti.
       Background & Aims: Hepatocyte-specific deficiency of the phosphatase and tensin homolog (PTEN) triggers steatosis and the development of hepatic tumors. The hepatoprotective effect of PTEN may partly depend on its ability to block insulin receptor (IR) and insulin-like growth factor 1 receptor (IGF1R) signaling. This study aimed to evaluate the individual/combined contributions of IR and IGF1R to hepatic metabolism and tumorigenesis induced by PTEN deficiency.
    Methods: Mouse models with hepatocyte-specific deletions of Insr, Igf1r, or both, in addition to Pten, were used to investigate the distinct/combined roles of IR and IGF1R. Analyses focused on the impact of these deletions on hepatic steatosis and metabolism, whole-body adiposity, and liver tumor incidence.
    Results: IR and IGF1R signaling contribute to steatosis induced by Pten ablation through distinct mechanisms. Hepatic IGF1R regulates hepatic glucose output and glycogen storage (2.1-fold increase in hepatic glycogen in PTEN-IGF1RKO mice [n = 10], compared with PTENKO mice [n = 7], p <0.0001). In contrast, hepatic IR exerts a stringent regulation on whole-body adiposity (4-fold increase in white adipose tissue volume in PTEN-IRKO mice [n = 5], compared with PTENKO mice [n = 6], p = 0.0004). Interestingly, triple knockout (Insr, Igf1r, and Pten) in hepatocytes of young adult mice is largely asymptomatic, indicating that PTEN deficiency exerts a major overriding control on the effects of Insr and Igf1r deletion. Furthermore, the combined loss of IR and IGF1R signaling in PTEN-deficient livers restrains liver carcinogenesis, but both receptors have individually distinct effects on the malignancy of liver cancers, with IR deficiency reducing overall cancer incidence and IGF1R deficiency promoting malignancy.
    Conclusions: These findings increase our understanding of the intricate interplay between PTEN, IR, and IGF1R signaling and provide valuable insights into potential therapeutic interventions in hepatic disorders and hepatocellular carcinoma.
    Impact and implications: This study underscores the pivotal roles of phosphatase and tensin homolog (PTEN), insulin receptor (IR), and IGF-1 receptor (IGF1R) in controlling liver metabolism, systemic adiposity, and liver cancer progression. Our findings on the distinct and combined effects of these receptors in PTEN-deficient mice offer key insights into the mechanisms driving metabolic dysfunction-associated steatotic liver disease and related hepatocarcinogenesis. In addition, this research reveals the potential of IR and IGF1R as biomarkers in liver cancer development, presenting new opportunities for therapeutic targeting and disease monitoring.
    Keywords:  Hepatic metabolism; Hepatocarcinogenesis; IGF-1 receptor; Insulin receptor; Steatosis
    DOI:  https://doi.org/10.1016/j.jhepr.2024.101305
  8. J Clin Invest. 2025 Mar 17. pii: e172837. [Epub ahead of print]135(6):
    Extracranial arteriovenous malformations: towards etiology-based therapeutic management.
    Julien Coulie, Emmanuel Seront, Miikka Vikkula, Laurence M Boon.
      Anomalies during angiogenesis can initiate the formation of arteriovenous malformations (AVMs), characterized by aberrant connections between arteries and veins and fast lesional blood flow. These anomalies can manifest anywhere in the body, including the brain, and they typically appear at birth and evolve alongside growth of the individual. Depending on their location and size, AVMs can induce progressive deformation, chronic pain, functional impairment, and ulceration and pose life-threatening risks such as hemorrhage and organ dysfunction. The primary treatment modalities entail surgical intervention or embolization followed by surgery. However, these approaches are often challenging and seldom offer definitive resolution. In addition, inadequately performed surgery may trigger angiogenic rebound, fostering AVM recurrence. Advancements in comprehending the molecular pathways underlying AVMs have sparked interest in repurposing targeted therapies initially devised for cancer treatment. The first results are promising, giving new hope to the patients affected with these often devastating and debilitating lesions, the management of which presents major clinical challenges.
    DOI:  https://doi.org/10.1172/JCI172837
  9. Commun Biol. 2025 Mar 18. 8(1): 455
    POT, an optogenetics-based endogenous protein degradation system.
    Yunyue Chen, Siyifei Wang, Luhao Zhang, Dandan Peng, Ke Huang, Baohua Ji, Junfen Fu, Yingke Xu.
      Precise regulation of protein abundance is critical for cellular homeostasis, whose dysfunction may directly lead to human diseases. Optogenetics allows rapid and reversible control of precisely defined cellular processes, which has the potential to be utilized for regulation of protein dynamics at various scales. Here, we developed a novel optogenetics-based protein degradation system, namely Peptide-mediated OptoTrim-Away (POT) which employs expressed small peptides to effectively target endogenous and unmodified proteins. By engineering the light-induced oligomerization of the E3 ligase TRIM21, POT can rapidly trigger protein degradation via the proteasomal pathway. Our results showed that the developed POT-PI3K and POT-GPX4 modules, which used the iSH2 and FUNDC1 domains to specifically target phosphoinositide 3-kinase (PI3K) and glutathione peroxidase 4 (GPX4) respectively, were able to potently induce the degradation of these endogenous proteins by light. Both live-cell imaging and biochemical experiments validated the potency of these tools in downregulating cancer cell migration, proliferation, and even promotion of cell apoptosis. Therefore, we believe the POT offers an alternative and practical solution for rapid manipulation of endogenous protein levels, and it could potentially be employed to dissect complex signaling pathways in cell and for targeted cellular therapies.
    DOI:  https://doi.org/10.1038/s42003-025-07919-x
  10. Nat Commun. 2025 Mar 20. 16(1): 2766
    Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.
    Wen Jiang, Eric J Jaehnig, Yuxing Liao, Zhiao Shi, Tomer M Yaron-Barir, Jared L Johnson, Lewis C Cantley, Bing Zhang.
      Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address this challenge, we integrate machine learning with phosphoproteomic data from 1195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network that maps the co-regulation of 26,280 phosphosites. By incorporating network features from CoPheeMap into a second machine learning model, namely CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA uncovers 24,015 associations between 9399 phosphosites and 104 serine/threonine kinases, shedding light on many unannotated phosphosites and understudied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. Through the application of CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and those associated with cancer, we demonstrate their effectiveness in systematically elucidating phosphosites of interest. These analyses unveil dysregulated signaling processes in human cancer and identify understudied kinases as potential therapeutic targets.
    DOI:  https://doi.org/10.1038/s41467-025-57993-2
  11. Nat Commun. 2025 Mar 16. 16(1): 2579
    High resolution profiling of cell cycle-dependent protein and phosphorylation abundance changes in non-transformed cells.
    Camilla Rega, Ifigenia Tsitsa, Theodoros I Roumeliotis, Izabella Krystkowiak, Maria Portillo, Lu Yu, Julia Vorhauser, Jonathon Pines, Jörg Mansfeld, Jyoti Choudhary, Norman E Davey.
      The cell cycle governs a precise series of molecular events, regulated by coordinated changes in protein and phosphorylation abundance, that culminates in the generation of two daughter cells. Here, we present a proteomic and phosphoproteomic analysis of the human cell cycle in hTERT-RPE-1 cells using deep quantitative mass spectrometry by isobaric labelling. By analysing non-transformed cells and improving the temporal resolution and coverage of key cell cycle regulators, we present a dataset of cell cycle-dependent protein and phosphorylation site oscillation that offers a foundational reference for investigating cell cycle regulation. These data reveal regulatory intricacies including proteins and phosphorylation sites exhibiting cell cycle-dependent oscillation, and proteins targeted for degradation during mitotic exit. Integrated with complementary resources, our data link cycle-dependent abundance dynamics to functional changes and are accessible through the Cell Cycle database (CCdb), an interactive web-based resource for the cell cycle community.
    DOI:  https://doi.org/10.1038/s41467-025-57537-8
  12. Nat Commun. 2025 Mar 18. 16(1): 2682
    The primate-specific Nedd4-1(NE) localizes to late endosomes in response to amino acids to suppress autophagy.
    G Kefalas, A Priya, A Astori, A Persaud, L Jing, A M Sydor, H H Y Yao, N Warner, Y Zhang, J H Brumell, A M Muise, S Sari, H C Su, M J Lenardo, W H A Kahr, B Raught, D Rotin.
      The ubiquitin ligase Nedd4 (Nedd4-1), comprised of C2-WW(n)-HECT domains, regulates protein trafficking. We recently described a primate-specific Nedd4-1 splice isoform with an extended N-terminus replacing the C2 domain, called Nedd4-1(NE). Here, we show that while canonical Nedd4-1 is primarily localized to the cytosol, Nedd4-1(NE) localizes to late endosomes. This localization is mediated by the NE region, is dependent on amino acid availability, is independent of mTORC1, and is inhibited by the autophagy inducer IKKβ. We further demonstrate that VPS16B, which regulates late endosome to lysosome maturation, is a unique Nedd4-1(NE) substrate that co-localizes with Nedd4-1(NE) in the presence of nutrients. Importantly, a potentially pathogenic homozygous variant identified in the NE region (E70Q) of a patient with lymphangiectasia and protein-losing enteropathy leads to reduced VPS16B ubiquitination by Nedd4-1(NE). Finally, we report that Nedd4-1(NE) inhibits autophagy, likely by disrupting late endosome to autophagosome maturation. This work identified an mTORC1-independent, IKK-driven mechanism to regulate Nedd4-1(NE) localization to late endosomes in primates in response to nutrient availability, and uncovered suppression of autophagy by this ubiquitin ligase.
    DOI:  https://doi.org/10.1038/s41467-025-57944-x
  13. Cell Syst. 2025 Mar 19. pii: S2405-4712(25)00068-7. [Epub ahead of print]16(3): 101235
    SPARROW reveals microenvironment-zone-specific cell states in healthy and diseased tissues.
    Peiyao A Zhao, Ruoxin Li, Temi Adewunmi, Jessica Garber, Claire Gustafson, June Kim, Jocelin Malone, Adam Savage, Peter Skene, Xiao-Jun Li.
      Spatially resolved transcriptomics technologies have advanced our understanding of cellular characteristics within tissue contexts. However, current analytical tools often treat cell-type inference and cellular neighborhood identification as separate and hard clustering processes, limiting comparability across scales and samples. SPARROW addresses these challenges by jointly learning latent embeddings and soft clusterings of cell types and cellular organization. It outperformed state-of-the-art methods in cell-type inference and microenvironment zone delineation and uncovered zone-specific cell states in human and mouse tissues that competing methods missed. By integrating spatially resolved transcriptomics and single-cell RNA sequencing (scRNA-seq) data in a shared latent space, SPARROW achieves single-cell spatial resolution and whole-transcriptome coverage, enabling the discovery of both established and unknown microenvironment zone-specific ligand-receptor interactions in the human tonsil. Overall, SPARROW is a computational framework that provides a comprehensive characterization of tissue features across scales, samples, and conditions.
    Keywords:  cell neighborhood; computational biology; immunology; spatial transcriptomics; tissue biology
    DOI:  https://doi.org/10.1016/j.cels.2025.101235
  14. Nat Genet. 2025 Mar 18.
    Quantitative characterization of cell niches in spatially resolved omics data.
    Sebastian Birk, Irene Bonafonte-Pardàs, Adib Miraki Feriz, Adam Boxall, Eneritz Agirre, Fani Memi, Anna Maguza, Anamika Yadav, Erick Armingol, Rong Fan, Gonçalo Castelo-Branco, Fabian J Theis, Omer Ali Bayraktar, Carlos Talavera-López, Mohammad Lotfollahi.
      Spatial omics enable the characterization of colocalized cell communities that coordinate specific functions within tissues. These communities, or niches, are shaped by interactions between neighboring cells, yet existing computational methods rarely leverage such interactions for their identification and characterization. To address this gap, here we introduce NicheCompass, a graph deep-learning method that models cellular communication to learn interpretable cell embeddings that encode signaling events, enabling the identification of niches and their underlying processes. Unlike existing methods, NicheCompass quantitatively characterizes niches based on communication pathways and consistently outperforms alternatives. We show its versatility by mapping tissue architecture during mouse embryonic development and delineating tumor niches in human cancers, including a spatial reference mapping application. Finally, we extend its capabilities to spatial multi-omics, demonstrate cross-technology integration with datasets from different sequencing platforms and construct a whole mouse brain spatial atlas comprising 8.4 million cells, highlighting NicheCompass' scalability. Overall, NicheCompass provides a scalable framework for identifying and analyzing niches through signaling events.
    DOI:  https://doi.org/10.1038/s41588-025-02120-6
  15. N Biotechnol. 2025 Mar 15. pii: S1871-6784(25)00028-7. [Epub ahead of print]88 1-11
    How the past is shaping the future of life science: The influence of automation and AI on biology.
    Carrie Cizauskas, Erika DeBenedictis, Pete Kelly.
      Automation has been a transformative force for many industries, including manufacturing and chemistry. While the term traditionally referred to mechanical operations to produce physical objects, the definition has since expanded: 1) it can now mean both physical and/or information automation; and 2) it can now produce physical and/or conceptual outputs. While automation has yet to fully revolutionize life science research, much of which still relies on manual processes, we show that biology automation is the ultimate mixture of the concepts listed above - it involves automation of physical and data processing, and production of physical samples as well as conceptual data outputs. Here, we explore the history of automation and what it can - and cannot - teach us about the future of automated life science experimentation. We examine the current state of automated biology, its major successes, and the remaining barriers to wider adoption. Unlike in other fields, however, automation is reaching broader integration in life science at a time when both biology and AI are reaching their adolescence. At The Align Foundation, we are anticipating this change and hoping to leverage this inflection as a way to accelerate and democratize research. We anticipate that this novel combination of automation, AI, and life science learning will impact the trajectory of biological research, including the design and execution of high-throughput experiments and the analysis of resulting large-scale data.
    Keywords:  AI; Automation; Biology
    DOI:  https://doi.org/10.1016/j.nbt.2025.03.004
  16. Brief Bioinform. 2025 Mar 04. pii: bbaf110. [Epub ahead of print]26(2):
    MOSim: bulk and single-cell multilayer regulatory network simulator.
    Carolina Monzó, Maider Aguerralde-Martin, Carlos Martínez-Mira, Ángeles Arzalluz-Luque, Ana Conesa, Sonia Tarazona.
      As multi-omics sequencing technologies advance, the need for simulation tools capable of generating realistic and diverse (bulk and single-cell) multi-omics datasets for method testing and benchmarking becomes increasingly important. We present MOSim, an R package that simulates both bulk (via mosim function) and single-cell (via sc_mosim function) multi-omics data. The mosim function generates bulk transcriptomics data (RNA-seq) and additional regulatory omics layers (ATAC-seq, miRNA-seq, ChIP-seq, Methyl-seq, and transcription factors), while sc_mosim simulates single-cell transcriptomics data (scRNA-seq) with scATAC-seq and transcription factors as regulatory layers. The tool supports various experimental designs, including simulation of gene co-expression patterns, biological replicates, and differential expression between conditions. MOSim enables users to generate quantification matrices for each simulated omics data type, capturing the heterogeneity and complexity of bulk and single-cell multi-omics datasets. Furthermore, MOSim provides differentially abundant features within each omics layer and elucidates the active regulatory relationships between regulatory omics and gene expression data at both bulk and single-cell levels. By leveraging MOSim, researchers will be able to generate realistic and customizable bulk and single-cell multi-omics datasets to benchmark and validate analytical methods specifically designed for the integrative analysis of diverse regulatory omics data.
    Keywords:  bulk; multi-omic simulator; single cell; transcriptomics
    DOI:  https://doi.org/10.1093/bib/bbaf110
  17. Curr Cardiol Rep. 2025 Mar 21. 27(1): 74
    Integrating -Omic Technologies across Modality, Space, and Time to Decipher Remodeling in Cardiac Disease.
    John F Mulvey, Emily L Meyer, Mikkel Skjoldan Svenningsen, Alicia Lundby.
       PURPOSE OF REVIEW: Despite significant efforts to understand pathophysiological processes underlying cardiac diseases, the molecular causes for the most part remain unresolved. Rapid advancements in -omics technologies, and their application in cardiac research, offer new insight into cardiac remodeling in disease states. This review aims to provide an accessible overview of recent advances in omics approaches for studying cardiac remodeling, catering to readers without extensive prior expertise.
    RECENT FINDINGS: We provide a methodologically focused overview of current methods for performing transcriptomics and proteomics, including their extensions for single-cell and spatial measurements. We discuss approaches to integrate data across modalities, resolutions and time. Key recent applications within the cardiac field are highlighted. Each -omics modality can provide insight, yet each existing experimental method has technical or conceptual limitations. Integrating data across multiple modalities can leverage strengths and mitigate weaknesses, ultimately enhancing our understanding of cardiac pathophysiology.
    Keywords:  Integrative -omics; Multi-omics; Proteomics; Single cell; Spatial; Transcriptomics
    DOI:  https://doi.org/10.1007/s11886-025-02226-7
  18. Cell Syst. 2025 Mar 19. pii: S2405-4712(25)00075-4. [Epub ahead of print]16(3): 101242
    Evaluation of De Vries et al.: Quantifying cellular shapes and how they correlate to cellular responses.
    Manuel D Leonetti.
      One snapshot of the peer review process for "Geometric deep learning and multiple instance learning for 3D cell shape profiling" (De Vries et al., 2025).1.
    DOI:  https://doi.org/10.1016/j.cels.2025.101242
  19. bioRxiv. 2025 Mar 06. pii: 2025.03.06.637075. [Epub ahead of print]
    Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.
    Mario Acera-Mateos, Xian Adiconis, Jessica-Kanglin Li, Domenica Marchese, Ginevra Caratù, Chung-Chau Hon, Prabha Tiwari, Miki Kojima, Beate Vieth, Michael A Murphy, Sean K Simmons, Thomas Lefevre, Irene Claes, Christopher L O'Connor, Rajasree Menon, Edgar A Otto, Yoshinari Ando, Katy Vandereyken, Matthias Kretzler, Markus Bitzer, Ernest Fraenkel, Thierry Voet, Wolfgang Enard, Piero Carninci, Holger Heyn, Joshua Z Levin, Elisabetta Mereu.
      The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3' and 5' scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. "Horizontal" integration of scRNA and snRNA-seq improved cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.
    DOI:  https://doi.org/10.1101/2025.03.06.637075
  20. PLoS Biol. 2025 Mar;23(3): e3003052
    The end of the genetic paradigm of cancer.
    Sui Huang, Ana M Soto, Carlos Sonnenschein.
      Genome sequencing of cancer and normal tissues, alongside single-cell transcriptomics, continues to produce findings that challenge the idea that cancer is a 'genetic disease', as posited by the somatic mutation theory (SMT). In this prevailing paradigm, tumorigenesis is caused by cancer-driving somatic mutations and clonal expansion. However, results from tumor sequencing, motivated by the genetic paradigm itself, create apparent 'paradoxes' that are not conducive to a pure SMT. But beyond genetic causation, the new results lend credence to old ideas from organismal biology. To resolve inconsistencies between the genetic paradigm of cancer and biological reality, we must complement deep sequencing with deep thinking: embrace formal theory and historicity of biological entities, and (re)consider non-genetic plasticity of cells and tissues. In this Essay, we discuss the concepts of cell state dynamics and tissue fields that emerge from the collective action of genes and of cells in their morphogenetic context, respectively, and how they help explain inconsistencies in the data in the context of SMT.
    DOI:  https://doi.org/10.1371/journal.pbio.3003052
  21. Signal Transduct Target Ther. 2025 Mar 21. 10(1): 92
    Targeting PI3K inhibitor resistance in breast cancer with metabolic drugs.
    Niklas Gremke, Isabelle Besong, Alina Stroh, Luise von Wichert, Marie Witt, Sabrina Elmshäuser, Michael Wanzel, Martin F Fromm, R Verena Taudte, Sabine Schmatloch, Thomas Karn, Mattea Reinisch, Nader Hirmas, Sibylle Loibl, Thomas Wündisch, Anne-Sophie Litmeyer, Paul Jank, Carsten Denkert, Sebastian Griewing, Uwe Wagner, Thorsten Stiewe.
      Activating PIK3CA mutations, present in up to 40% of hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (Her2-) breast cancer (BC) patients, can be effectively targeted with the alpha isoform-specific PI3K inhibitor Alpelisib. This treatment significantly improves outcomes for HR+, Her2-, and PIK3CA-mutated metastatic BC patients. However, acquired resistance, often due to aberrant activation of the mTOR complex 1 (mTORC1) pathway, remains a significant clinical challenge. Our study, using in vitro and orthotopic xenograft mouse models, demonstrates that constitutively active mTORC1 signaling renders PI3K inhibitor-resistant BC exquisitely sensitive to various drugs targeting cancer metabolism. Mechanistically, mTORC1 suppresses the induction of autophagy during metabolic perturbation, leading to energy stress, a critical depletion of aspartate, and ultimately cell death. Supporting this mechanism, BC cells with CRISPR/Cas9-engineered knockouts of canonical autophagy genes showed similar vulnerability to metabolically active drugs. In BC patients, high mTORC1 activity, indicated by 4E-BP1T37/46 phosphorylation, correlated with p62 accumulation, a sign of impaired autophagy. Together, these markers predicted poor overall survival in multiple BC subgroups. Our findings reveal that aberrant mTORC1 signaling, a common cause of PI3K inhibitor resistance in BC, creates a druggable metabolic vulnerability by suppressing autophagy. Additionally, the combination of 4E-BP1T37/46 phosphorylation and p62 accumulation serves as a biomarker for poor overall survival, suggesting their potential utility in identifying BC patients who may benefit from metabolic therapies.
    DOI:  https://doi.org/10.1038/s41392-025-02180-4
  22. Fam Cancer. 2025 Mar 18. 24(2): 28
    Non-serous ovarian cancer in PTEN Hamartoma Tumor Syndrome: additional evidence for increased risk.
    PTEN Study Group
      Increased hereditary cancer risk is one of the hallmarks of PTEN Hamartoma Tumor Syndrome (PHTS) which is caused by a pathogenic germline variant in PTEN. Case reports and some cohort studies have described ovarian cancer (OC) in PHTS patients. Previously, we observed an enrichment of non-serous OC in PHTS compared to sporadic cases (3% vs 1%). However, ovarian cancer is currently not considered a PHTS-related cancer. The aim of this study was to describe five PHTS patients with a pathogenic germline variant in PTEN with non-serous OC. Three of the non-serous OCs were mucinous carcinomas (49, 51 and 52 years) and two were malignant germ cell tumors (8 and 15 years) and all were diagnosed before genetic testing and PHTS diagnosis. In addition to OC, the described patients developed other PHTS-related benign and malignant lesions. We provide further evidence that non-serous ovarian cancer, especially mucinous, endometrioid and malignant germ cell tumors should be further investigated as potential PHTS-related cancers.
    Keywords:  Genetics; Hereditary cancer; Ovarian cancer; PHTS; PTEN; Phenotype
    DOI:  https://doi.org/10.1007/s10689-025-00453-z
  23. Australas J Dermatol. 2025 Mar 17.
    Targeted Therapies for Slow-Flow Vascular Malformations.
    Grace X Li, Deshan F Sebaratnam, James P Pham.
      Advances in genetic sequencing technologies have enabled the identification of key activating somatic variants in cellular signalling pathways involved in the pathogenesis of vascular malformations. Given that these genetic variants are also implicated in the pathogenesis of several cancers, the repurposing of targeted therapies developed in oncology has been increasingly investigated for treating vascular malformations. This review provides an update on the current evidence for targeted therapies in slow-flow vascular malformations, particularly in the context of gain-of-function variants in the PI3K/AKT/mTOR pathway.
    Keywords:  capillary malformations; lymphatic abnormalities; precision medicine; vascular malformations; venous malformations
    DOI:  https://doi.org/10.1111/ajd.14451
  24. Nat Nanotechnol. 2025 Mar 17.
    The pathways for nanoparticle transport across tumour endothelium.
    Jamie L Y Wu, Qin Ji, Colin Blackadar, Luan N M Nguyen, Zachary P Lin, Zahra Sepahi, Benjamin P Stordy, Adrian Granda Farias, Shrey Sindhwani, Wayne Ngo, Katherine Chan, Andrea Habsid, Jason Moffat, Warren C W Chan.
      The active transport and retention principle is an alternative mechanism to the enhanced permeability and retention effect for explaining nanoparticle tumour delivery. It postulates that nanoparticles actively transport across tumour endothelial cells instead of passively moving through gaps between these cells. How nanoparticles transport across tumour endothelial cells remains unknown. Here we show that nanoparticles cross tumour endothelial cells predominantly using the non-receptor-based macropinocytosis pathway. We discovered that tumour endothelial cell membrane ruffles capture circulating nanoparticles, internalize them in intracellular vesicles and release them into the tumour interstitium. Tumour endothelial cells have a higher membrane ruffle density than healthy endothelium, which may partially explain the elevated nanoparticle tumour accumulation. Receptor-based endocytosis pathways such as clathrin-mediated endocytosis contribute to nanoparticle transport to a lesser extent. Nanoparticle size determines the degree of contribution for each pathway. Elucidating the nanoparticle transport mechanism is crucial for developing strategies to control nanoparticle tumour delivery.
    DOI:  https://doi.org/10.1038/s41565-025-01877-5
  25. J Clin Invest. 2025 Mar 18. pii: e186633. [Epub ahead of print]
    Gene-environment interaction modifies the association between hyperinsulinemia and serum urate levels through SLC22A12.
    Wataru Fujii, Osamu Yamazaki, Daigoro Hirohama, Ken Kaseda, Emiko Kuribayashi-Okuma, Motonori Tsuji, Makoto Hosoyamada, Yuta Kochi, Shigeru Shibata.
       BACKGROUND: Hyperinsulinemia and insulin resistance often accompany elevated serum urate levels (hyperuricemia), a highly heritable condition that triggers gout; however, the underlying mechanisms are unclear.
    METHODS: We evaluated the association between the index of hyperinsulinemia and the fractional excretion of urate (FEUA) in 162 outpatients. The underlying mechanisms were investigated through single-cell data analysis and kinase screening combined with cell culture experiments. In 377,358 participants of the UK Biobank (UKBB), we analyzed serum urate, hyperinsulinemia, and salt intake. We also examined gene-environment interactions using single nucleotide variants in SLC22A12, which encodes urate transporter 1 (URAT1).
    RESULTS: The index of hyperinsulinemia was inversely associated with FEUA independently of other covariates. Mechanistically, URAT1 cell-surface abundance and urate transport activity were regulated by URAT1-Thr408 phosphorylation, which was stimulated by hyperinsulinemia via AKT. Kinase screening and single-cell data analysis revealed that SGK1, induced by high salt, activated the same pathway, increasing URAT1. Arg405 was essential for these kinases to phosphorylate URAT1-Thr408. In UKBB participants, hyperinsulinemia and high salt intake were independently associated with increased serum urate levels. We found that SLC22A12 eQTL rs475688 synergistically enhanced the positive association between serum urate and hyperinsulinemia.
    CONCLUSION: URAT1 mediates the association between hyperinsulinemia and hyperuricemia. Our data provide evidence for the role of gene-environment interactions in determining serum urate levels, paving the way for personalized management of hyperuricemia.
    FUNDING: ACRO Research Grants of Teikyo University; JSPS; the Japanese Society of Gout and Uric & Nucleic Acids; Fuji Yakuhin; Nanken-Kyoten; Medical Research Center Initiative for High Depth Omics.
    Keywords:  Genetics; Insulin; Metabolism; Nephrology; Population genetics; Transport
    DOI:  https://doi.org/10.1172/JCI186633
  26. Nat Commun. 2025 Mar 18. 16(1): 2645
    A single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations.
    Mariona Nadal-Ribelles, Carme Solé, Anna Díez-Villanueva, Camille Stephan-Otto Attolini, Yaima Matas, Lars Steinmetz, Eulàlia de Nadal, Francesc Posas.
      Heterogeneity is inherent to living organisms and it determines cell fate and phenotypic variability. Despite its ubiquity, the underlying molecular mechanisms and the genetic basis linking genotype to-phenotype heterogeneity remain a central challenge. Here we construct a yeast knockout library with a clone and genotype RNA barcoding structure suitable for genome-scale analyses to generate a high-resolution single-cell yeast transcriptome atlas of 3500 mutants under control and stress conditions. We find that transcriptional heterogeneity reflects the coordinated expression of specific gene programs, generating a continuous of cell states that can be responsive to external insults. Cell state plasticity can be genetically modulated with mutants that act as state attractors and disruption of state homeostasis results in decreased adaptive fitness. Leveraging on intra-genetic variability, we establish that regulators of transcriptional heterogeneity are functionally diverse and influenced by the environment. Our multimodal perturbation-based single-cell Genotype-to-Transcriptome Atlas in yeast provides insights into organism-level responses.
    DOI:  https://doi.org/10.1038/s41467-025-57600-4
  27. Science. 2025 Mar 21. 387(6740): eads5704
    Epithelial polarization by the planar cell polarity complex is exclusively non-cell autonomous.
    Lena P Basta, Bradley W Joyce, Eszter Posfai, Danelle Devenport.
      For cells to polarize collectively along a tissue plane, asymmetrically localized planar cell polarity (PCP) complexes must form intercellular contacts between neighboring cells. Yet, it is unknown whether asymmetric segregation of PCP complexes requires cell-cell contact, or if cell autonomous, antagonistic interactions are sufficient for polarization. To test this, we generated mouse chimeras consisting of dual PCP-reporter cells mixed with unlabeled cells that cannot form PCP bridges. In the absence of intercellular interactions, PCP proteins failed to polarize cell autonomously. Rather, PCP-mediated contacts along single cell-cell interfaces were sufficient to sort PCP components to opposite sides of the junction, independent of junction orientation. Thus, intercellular binding of PCP complexes is the critical step that initiates sorting of opposing PCP complexes to generate asymmetry.
    DOI:  https://doi.org/10.1126/science.ads5704
  28. Nat Methods. 2025 Mar 17.
    A computational pipeline for spatial mechano-transcriptomics.
    Adrien Hallou, Ruiyang He, Benjamin D Simons, Bianca Dumitrascu.
      Advances in spatial profiling technologies are providing insights into how molecular programs are influenced by local signaling and environmental cues. However, cell fate specification and tissue patterning involve the interplay of biochemical and mechanical feedback. Here we develop a computational framework that enables the joint statistical analysis of transcriptional and mechanical signals in the context of spatial transcriptomics. To illustrate the application and utility of the approach, we use spatial transcriptomics data from the developing mouse embryo to infer the forces acting on individual cells, and use these results to identify mechanical, morphometric and gene expression signatures that are predictive of tissue compartment boundaries. In addition, we use geoadditive structural equation modeling to identify gene modules that predict the mechanical behavior of cells in an unbiased manner. This computational framework is easily generalized to other spatial profiling contexts, providing a generic scheme for exploring the interplay of biomolecular and mechanical cues in tissues.
    DOI:  https://doi.org/10.1038/s41592-025-02618-1
  29. Nature. 2025 Mar 19.
    Why humans have puzzle-shaped cells.
    Shamini Bundell.
      
    Keywords:  Cell biology; Physiology
    DOI:  https://doi.org/10.1038/d41586-025-00846-1
  30. Cell. 2025 Mar 14. pii: S0092-8674(25)00209-0. [Epub ahead of print]
    Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions.
    Wenxue Li, Abhijit Dasgupta, Ka Yang, Shisheng Wang, Nisha Hemandhar-Kumar, Surendhar R Chepyala, Jay M Yarbro, Zhenyi Hu, Barbora Salovska, Eugenio F Fornasiero, Junmin Peng, Yansheng Liu.
      Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications such as phosphorylation are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites in eight mouse tissues and various brain regions using advanced proteomics and stable isotope labeling. We reveal tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discover a remarkable pattern of turnover changes for peroxisome proteins in specific tissues and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides fundamental insights into protein stability, tissue dynamic proteotypes, and functional protein phosphorylation and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.
    Keywords:  DIA-MS; TMT; brain regions; mouse tissues; protein lifetime; protein phosphorylation; protein turnover; proteomics; pulse SILAC
    DOI:  https://doi.org/10.1016/j.cell.2025.02.021
  31. Nat Rev Drug Discov. 2025 Mar 14.
    Wrestling with the RAS cancer drug pipeline.
    Asher Mullard.
      
    DOI:  https://doi.org/10.1038/d41573-025-00043-9
  32. Proc Natl Acad Sci U S A. 2025 Mar 25. 122(12): e2322762122
    Cell-matrix feedback controls stretch-induced cellular memory and fibroblast activation.
    Yuan Hong, Xiangjun Peng, Haomin Yu, Mohammad Jafari, Delaram Shakiba, Yuxuan Huang, Chengqing Qu, Ermia E Melika, Andrew K Tawadros, Aliza Mujahid, Yin-Yuan Huang, Jacob A Sandler, Kenneth M Pryse, Justin M Sacks, Elliot L Elson, Guy M Genin, Farid Alisafaei.
      Mechanical stretch can activate long-lived changes in fibroblasts, increasing their contractility and initiating phenotypic transformations. This activation, critical to wound healing and procedures such as skin grafting, increases with mechanical stimulus for cells cultured in two-dimensional but is highly variable in cells in three-dimensional (3D) tissue. Here, we show that static mechanical stretch of cells in 3D tissues can either increase or decrease fibroblast activation depending upon recursive cell-extracellular matrix (ECM) feedback and demonstrate control of this activation through integrated in vitro and mathematical models. ECM viscoelasticity, signaling dynamics, and cell mechanics combine to yield a predictable, but nonmonotonic, relationship between mechanical stretch and long-term cell activation. Results demonstrate that feedback between cells and ECM determine how cells retain memory of mechanical stretch and have direct implications for improving outcomes in skin grafting procedures.
    Keywords:  cell-matrix feedback; fibroblasts; mechanical memory; mechanobiology; mechanotransduction
    DOI:  https://doi.org/10.1073/pnas.2322762122
  33. Annu Rev Biochem. 2025 Mar 18.
    Extracellular Vesicles and Cellular Homeostasis.
    Jordan Matthew Ngo, Justin Krish Williams, Congyan Zhang, Amr Hosny Saleh, Xiao-Man Liu, Liang Ma, Randy Schekman.
      Extracellular vesicles (EVs) are secreted, membrane-enclosed particles that have been proposed to play a broad role in intercellular communication. Most often, EVs, by analogy to enveloped viruses, are suggested to fuse to or within a target cell to deliver a soluble signaling molecule into the cytoplasm. However, significant evidence supports an alternative model in which EVs are secreted to promote homeostasis. In this model, EVs are loaded with unwanted or toxic cargo, secreted upon cellular or organismal stress, and degraded by other cells. Here, we present evidence supporting this homeostatic EV model and discuss the general inefficiency of EV cargo delivery. While the homeostatic and viral delivery models for EV function are not mutually exclusive, we propose that much of the evidence presented is hard to reconcile with a broad role for EVs in cargo transfer as a means to promote intercellular communication.
    DOI:  https://doi.org/10.1146/annurev-biochem-100924-012717
  34. Nat Biotechnol. 2025 Mar;43(3): 292
    Tough times for CRISPR startups.
      
    DOI:  https://doi.org/10.1038/s41587-025-02609-9
  35. Nat Cardiovasc Res. 2025 Mar 17.
    Mapping the transcriptional and epigenetic landscape of organotypic endothelial diversity in the developing and adult mouse.
    Manuel E Cantu Gutierrez, Matthew C Hill, Gabrielle E Largoza, William B Gillespie, James F Martin, Joshua D Wythe.
      The vascular endothelium features unique molecular and functional properties across different vessel types, such as between arteries, veins and capillaries, as well as between different organs, such as the leaky sinusoidal endothelium of the liver versus the impermeable vessels of the brain. However, the transcriptional networks governing endothelial organ specialization remain unclear. Here we profile the accessible chromatin and transcriptional landscapes of the endothelium from the mouse liver, lung, heart, kidney, brain and retina, across developmental time, to identify potential transcriptional regulators of endothelial heterogeneity. We then determine which of these putative regulators are conserved in human brain endothelial cells, and using single-cell transcriptomic profiling, we define which regulatory networks are active during brain maturation. Finally, we show that the putative transcriptional regulators identified by these three approaches molecularly and functionally reprogram naive endothelial cells. Thus, this resource can be used to identify potential transcriptional regulators controlling the establishment and maintenance of organ-specific endothelial specialization.
    DOI:  https://doi.org/10.1038/s44161-025-00618-0
  36. Nat Commun. 2025 Mar 14. 16(1): 2511
    Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.
    Yongqiang Zheng, Kai Yu, Jin-Fei Lin, Zhuoran Liang, Qingfeng Zhang, Junteng Li, Qi-Nian Wu, Cai-Yun He, Mei Lin, Qi Zhao, Zhi-Xiang Zuo, Huai-Qiang Ju, Rui-Hua Xu, Ze-Xian Liu.
      Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically characterize potential shuttling-attacking mutations (SAMs) across cancers through developing the deep learning model pSAM for the ab initio decoding of the sequence determinants of nucleocytoplasmic shuttling. Leveraging cancer mutations across 11 cancer types, we find that SAMs enrich functional genetic variations and critical genes in cancer. We experimentally validate a dozen SAMs, among which R14M in PTEN, P255L in CHFR, etc. are identified to disrupt the nuclear localization signals through interfering their interactions with importins. Further studies confirm that the nucleocytoplasmic shuttling altered by SAMs in PTEN and CHFR rewire the downstream signaling and eliminate their function of tumor suppression. Thus, this study will help to understand the molecular traits of nucleocytoplasmic shuttling and their dysfunctions mediated by genetic variants.
    DOI:  https://doi.org/10.1038/s41467-025-57858-8
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