bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–10–05
29 papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells.
  2. Learning cell-specific networks from dynamics and geometry of single cells.
  3. Single-Cell Proteomic Technologies: Tools in the quest for principles.
  4. Tumor-Agnostic AKT Inhibition: Is It Time to AKT?
  5. Stable Cas9 expression regulates cell growth by facilitating mTORC2 activation.
  6. Microtubule architecture connects AMOT stability to YAP/TAZ mechanotransduction and Hippo signalling.
  7. Phosphoinositide dynamics in virus-associated malignancies.
  8. Single-cell foundation models: bringing artificial intelligence into cell biology.
  9. cp_measure: API-first feature extraction for image-based profiling workflows.
  10. Sequencing-free whole-genome spatial transcriptomics at single-molecule resolution.
  11. Targeted RNA sequencing of thyroid tumors from individuals with PTEN hamartoma tumor syndrome reveals a unique transcriptome with a predominantly RAS-like expression profile.
  12. Detection of PIK3CA Mutations in Anal Dysplasia.
  13. Diabetes and insulin resistance alters ligamentum flavum-derived fibroblast responses in an AKT2-dependent manner.
  14. Exploring endothelial cell environments across organs in spatially resolved omics data.
  15. An overlapping phenotype between megalencephaly-capillary malformation and Diffuse Capillary Malformation with Overgrowth: expanding the PIK3CA-related overgrowth spectrum.
  16. Harmony-based data integration for distributed single-cell multi-omics data.
  17. COOKIE-Pro: covalent inhibitor binding kinetics profiling on the proteome scale.
  18. Biphasic control of the B cell transcriptome by mTORC1 and GSK3.
  19. Mechanisms, functions and therapeutic targeting of protein tyrosine phosphatases.
  20. On metrics for subpopulation detection in single-cell and spatial omics data.
  21. Spatially resolving cancer: from cell states to therapy.
  22. Single-cell nascent transcription reveals sparse genome usage and plasticity.
  23. A deep single cell mass cytometry approach to capture canonical and noncanonical cell cycle states.
  24. Artificial intelligence in metabolic research.
  25. Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data.
  26. Mapping cryptic phosphorylation sites in the human proteome.
  27. Association of PIK3CA mutations with brainstem location in sporadic cerebral cavernous malformations.
  28. Homozygous Loss of Function PIK3CD Mutation in Multiple Siblings Leading To B Cell Dysregulation and Autoimmunity.
  29. Precise regulation of RAS-Mediated PI3Kα activation: therapeutic potential of BBO-10203 in cancer treatment.
  1. Nat Cell Biol. 2025 Sep 29.
    Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells.
    Kaitlin P McCreery, Aki Stubb, Rebecca Stephens, Nadezda A Fursova, Andrew Cook, Kai Kruse, Anja Michelbach, Leah C Biggs, Adib Keikhosravi, Sonja Nykänen, Roosa Pulkkanen, Christel Hydén-Granskog, Jizhong Zou, Jan-Wilm Lackmann, Carien M Niessen, Sanna Vuoristo, Yekaterina A Miroshnikova, Sara A Wickström.
      Acquisition of specific cell shapes and morphologies is a central component of cell fate transitions. Although signalling circuits and gene regulatory networks that regulate pluripotent stem cell differentiation have been intensely studied, how these networks are integrated in space and time with morphological changes and mechanical deformations to control state transitions remains a fundamental open question. Here we focus on two distinct models of pluripotency, preimplantation inner cell mass cells of human embryos and primed pluripotent stem cells, to discover that cell fate transitions associate with rapid, compaction-triggered changes in nuclear shape and volume. These phenotypical changes and the associated active deformation of the nuclear envelope arise from growth factor signalling-controlled changes in cytoskeletal confinement and chromatin mechanics. The resulting osmotic stress state triggers global transcriptional repression, macromolecular crowding and remodelling of nuclear condensates that prime chromatin for a cell fate transition by attenuating repression of differentiation genes. However, while this mechano-osmotic chromatin priming has the potential to accelerate fate transitions and differentiation, sustained biochemical signals are required for robust induction of specific lineages. Our findings uncover a critical mechanochemical feedback mechanism that integrates nuclear mechanics, shape and volume with biochemical signalling and chromatin state to control cell fate transition dynamics.
    DOI:  https://doi.org/10.1038/s41556-025-01767-x
  2. Cell Syst. 2025 Oct 01. pii: S2405-4712(25)00232-7. [Epub ahead of print] 101399
    Learning cell-specific networks from dynamics and geometry of single cells.
    Stephen Y Zhang, Michael P H Stumpf.
      Cell dynamics and biological function are governed by intricate networks of molecular interactions. Inferring these interactions from data is a notoriously difficult inverse problem. Most existing network inference methods construct population-averaged representations of gene interaction networks, and they do not naturally allow us to infer differences in interaction activity across heterogeneous cell populations. We introduce locaTE, an information theoretic approach that leverages single-cell, dynamical information, together with geometry of the cell-state manifold, to infer cell-specific, causal gene interaction networks in a manner that is agnostic to the topology of the underlying biological trajectory. Through extensive simulation studies and applications to experimental datasets spanning mouse primitive endoderm formation, pancreatic development, and hematopoiesis, we demonstrate superior performance and the generation of additional insights, compared with standard population-averaged inference methods. We find that locaTE provides a powerful network inference method that allows us to distil cell-specific networks from single-cell data. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  gene regulation networks; network inference; single-cell transcriptomics
    DOI:  https://doi.org/10.1016/j.cels.2025.101399
  3. ArXiv. 2025 Jun 22. pii: arXiv:2506.18198v1. [Epub ahead of print]
    Single-Cell Proteomic Technologies: Tools in the quest for principles.
    Nikolai Slavov.
      Over the last decade, proteomic analysis of single cells by mass spectrometry transitioned from an uncertain possibility to a set of robust and rapidly advancing technologies supporting the accurate quantification of thousands of proteins. We review the major drivers of this progress, from establishing feasibility to powerful and increasingly scalable methods. We focus on the tradeoffs and synergies of different technological solutions within a coherent conceptual framework, which projects considerable room both for throughput scaling and for extending the analysis scope to functional protein measurements. We highlight the potential of these technologies to support the development of mechanistic biophysical models and help uncover new principles.
  4. Clin Cancer Res. 2025 Sep 30.
    Tumor-Agnostic AKT Inhibition: Is It Time to AKT?
    Ricardo Dahmer Tiecher, Alison M Schram.
      Basket trials of AKT-mutated tumors show that pan-AKT inhibitors are active in hormone receptor-positive breast cancer. There is mounting evidence for AKT inhibition in other tumor types, although small sample sizes limit evaluation of the tumor-agnostic potential for AKT inhibition. Emerging AKT1 E17K-specific molecules may improve tolerability and efficacy.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-25-2640
  5. Nucleic Acids Res. 2025 Sep 23. pii: gkaf965. [Epub ahead of print]53(18):
    Stable Cas9 expression regulates cell growth by facilitating mTORC2 activation.
    Le Yu, Yi Jin, Jianfeng Chen, Zhichuan Zhu, Siyuan Su, Emily M Wilkerson, Joanna Gongora, Erica W Cloer, Michael B Major, Pengda Liu.
      Clustered regularly interspaced short palindromic repeats (CRISPR), widely used for gene editing, relies on bacterial endonucleases like Cas9 to study gene functions and develop therapies. However, its potential effects on mammalian cellular behavior remain unclear. Here, we systematically profiled effects of stable Cas9 expression on growth of 32 cell lines spanning 9 cancer types and non-cancerous cells, finding growth alterations in a subset. To investigate mechanisms, we established the SpCas9 interactome in DU145 and MDA-MB-231 cells, both showing Cas9-enhanced growth, and identified ribosomal proteins as the top shared interactors. RNA-seq analysis revealed that Cas9 expression in DU145 cells activated PI3K signaling. Mechanistic studies showed that ribosomal proteins, including RPL26 and RPL23a, bind to Sin1, a core mTORC2 component, leading to mTORC2 activation. Notably, SpCas9 interacts with both RPL26/RPL23a and Sin1, acting as a scaffold to stabilize their association and enhance mTORC2 activation, even in the absence of growth factors. Our study systematically characterizes Cas9's effects on cell growth regulation and uncovers a novel Cas9-ribosome-mTORC2 signaling axis that promotes cell growth. These findings underscore the need to consider unintended cellular effects in CRISPR applications and highlight the importance of engineering safer Cas9 variants for biomedical research and clinical therapies.
    DOI:  https://doi.org/10.1093/nar/gkaf965
  6. Nat Cell Biol. 2025 Oct 01.
    Microtubule architecture connects AMOT stability to YAP/TAZ mechanotransduction and Hippo signalling.
    Giada Vanni, Anna Citron, Ambela Suli, Paolo Contessotto, Robin Caire, Alessandro Gandin, Giovanna Mantovan, Francesca Zanconato, Giovanna Brusatin, Michele Di Palma, Elisa Peirano, Lisa Sofia Pozzer, Carlo Albanese, Roberto A Steiner, Michelangelo Cordenonsi, Tito Panciera, Stefano Piccolo.
      Cellular mechanotransduction is a key informational system, yet its mechanisms remain elusive. Here we unveil the role of microtubules in mechanosignalling, operating downstream of subnuclear F-actin and nuclear envelope mechanics. Upon mechanical activation, microtubules reorganize from a perinuclear cage into a radial array nucleated by centrosomes. This structural rearrangement triggers degradation of AMOT proteins, which we identify as key mechanical rheostats that sequester YAP/TAZ in the cytoplasm. AMOT is stable in mechano-OFF but degraded in mechano-ON cell states, where microtubules allow AMOT rapid transport to the pericentrosomal proteasome in complex with dynein/dynactin. This process ensures swift control of YAP/TAZ function in response to changes in cell mechanics, with experimental loss of AMOT proteins rendering cells insensitive to mechanical modulations. Ras/RTK oncogenes promote YAP/TAZ-dependent tumorigenesis by corrupting this AMOT-centred mechanical checkpoint. Notably, the Hippo pathway fine-tunes mechanotransduction: LATS kinases phosphorylate AMOT, shielding it from degradation, thereby indirectly restraining YAP/TAZ. Thus, AMOT protein stability serves as a hub linking cytoskeletal reorganization and Hippo signalling to YAP/TAZ mechanosignalling.
    DOI:  https://doi.org/10.1038/s41556-025-01773-z
  7. Trends Cell Biol. 2025 Oct 01. pii: S0962-8924(25)00206-5. [Epub ahead of print]
    Phosphoinositide dynamics in virus-associated malignancies.
    Mingchuan Li, Wenbin Zhong, Emilio Hirsch, Daoguang Yan.
      Virus-associated cancers, which account for ~15-20% of the global cancer burden, arise from infections with human oncoviruses. These viruses drive malignant transformation through diverse mechanisms but share common oncogenic features, including reprogramming host membrane signaling and trafficking. Such processes are tightly regulated by phosphoinositides (PPIn), essential organizers of membrane dynamics and signal transduction implicated in cancer development and progression. Oncoviruses exploit host PPIn metabolism to facilitate their replication and persistence, often leading to its dysregulation. In turn, this disruption can activate oncogenic signaling pathways that promote malignant transformation. In this review, we summarize how oncoviruses manipulate PPIn metabolism to sustain their life cycle and drive long-term interactions with host cells, ultimately contributing to tumorigenesis.
    Keywords:  cancer; kinase; lipid transport protein; phosphatase; phosphoinositide; virus-associated cancer
    DOI:  https://doi.org/10.1016/j.tcb.2025.09.002
  8. Exp Mol Med. 2025 Oct 01.
    Single-cell foundation models: bringing artificial intelligence into cell biology.
    Seungbyn Baek, Kyungwoo Song, Insuk Lee.
      A foundation model, a large-scale deep learning model pretrained on vast datasets, has revolutionized data interpretation through self-supervised learning with capacity for various downstream tasks. Concurrently, single-cell genomics is in urgent need of unified frameworks capable of integrating and comprehensively analyzing the rapidly expanding data repositories. Inspired by advances in foundation models, researchers have extended these techniques to single-cell analysis, giving rise to single-cell foundation models (scFMs). Typically, these models use transformer architectures to incorporate diverse omics data and extract latent patterns at both cell and gene/feature levels for the analysis of cellular heterogeneity and complex regulatory networks. Despite their promise, scFMs face challenges including the nonsequential nature of omics data, inconsistency in data quality and the computational intensity required for training and fine-tuning. Furthermore, interpreting the biological relevance of latent embeddings and model representations remains nontrivial. Here we provide an overview of scFMs, highlighting their key concepts and applications across downstream tasks. We critically assess the current limitations and propose future directions aimed at enhancing the robustness, interpretability and scalability of scFMs. Ultimately, addressing these challenges will be crucial for establishing scFMs as pivotal tools in advancing single-cell genomics and unlocking deeper insights into cellular function and disease mechanisms.
    DOI:  https://doi.org/10.1038/s12276-025-01547-5
  9. ArXiv. 2025 Jul 01. pii: arXiv:2507.01163v1. [Epub ahead of print]
    cp_measure: API-first feature extraction for image-based profiling workflows.
    Alán F Muñoz, Tim Treis, Alexandr A Kalinin, Shatavisha Dasgupta, Fabian Theis, Anne E Carpenter, Shantanu Singh.
      Biological image analysis has traditionally focused on measuring specific visual properties of interest for cells or other entities. A complementary paradigm gaining increasing traction is image-based profiling - quantifying many distinct visual features to form comprehensive profiles which may reveal hidden patterns in cellular states, drug responses, and disease mechanisms. While current tools like CellProfiler can generate these feature sets, they pose significant barriers to automated and reproducible analyses, hindering machine learning workflows. Here we introduce cp_measure, a Python library that extracts CellProfiler's core measurement capabilities into a modular, API-first tool designed for programmatic feature extraction. We demonstrate that cp_measure features retain high fidelity with CellProfiler features while enabling seamless integration with the scientific Python ecosystem. Through applications to 3D astrocyte imaging and spatial transcriptomics, we showcase how cp_measure enables reproducible, automated image-based profiling pipelines that scale effectively for machine learning applications in computational biology.
  10. Cell. 2025 Oct 01. pii: S0092-8674(25)01037-2. [Epub ahead of print]
    Sequencing-free whole-genome spatial transcriptomics at single-molecule resolution.
    Yubao Cheng, Shengyuan Dang, Yuan Zhang, Yanbo Chen, Ruihuan Yu, Miao Liu, Shengyan Jin, Ailin Han, Samuel Katz, Siyuan Wang.
      Recent breakthroughs in spatial transcriptomics technologies have enhanced our understanding of diverse cellular identities, spatial organizations, and functions. Yet existing spatial transcriptomics tools are still limited in either transcriptomic coverage or spatial resolution, hindering unbiased, hypothesis-free transcriptomic analyses at high spatial resolution. Here, we develop reverse-padlock amplicon-encoding fluorescence in situ hybridization (RAEFISH), an image-based spatial transcriptomics method with whole-genome coverage and single-molecule resolution in intact tissues. We demonstrate the spatial profiling of transcripts from 23,000 human or 22,000 mouse genes in single cells and tissue sections. Our analyses reveal transcript-specific subcellular localization, cell-type-specific and cell-type-invariant zonation-dependent transcriptomes, and gene programs underlying preferential cell-cell interactions. Finally, we further develop our technology for the direct spatial readout of guide RNAs (gRNAs) in an image-based, high-content CRISPR screen. Overall, these developments offer a broadly applicable technology that enables high-coverage, high-resolution spatial profiling of both long and short, native and engineered RNAs in many biomedical contexts.
    Keywords:  high content CRISPR screen; highly multiplexed RNA imaging; spatial transcriptomics
    DOI:  https://doi.org/10.1016/j.cell.2025.09.006
  11. Surgery. 2025 Sep 29. pii: S0039-6060(25)00549-5. [Epub ahead of print] 109697
    Targeted RNA sequencing of thyroid tumors from individuals with PTEN hamartoma tumor syndrome reveals a unique transcriptome with a predominantly RAS-like expression profile.
    Gilman Plitt, Takae Mitzukami, Lamis Yehia, Laura Rabinowitz, Christopher C Griffith, Gustavo Romero-Velez, Allan Siperstein, Charis Eng.
       BACKGROUND: Differentiated thyroid cancer is typically caused by a single oncogenic driver alteration. In PTEN hamartoma tumor syndrome, a pathogenic germline PTEN alteration results in a predisposition to thyroid cancer and adenomatous thyroid nodules. This provides a unique model to study thyroid carcinogenesis in the setting of a baseline "hit" to the PI3K/AKT/mTOR pathway, implicated in RAS-like thyroid tumors.
    METHODS: RNA sequencing and differential expression analysis were performed on thyroid cancers, adenomatous nodules, and background thyroid tissue in patients with PTEN hamartoma tumor syndrome. BRAFV600E-RAS scores were calculated and compared across histologic subtypes. RNA sequencing data were then integrated with previously published paired exome sequencing data.
    RESULTS: RNA sequencing was performed on 26 cancers, 27 adenomatous nodules, and 15 background thyroid samples from 20 patients with PTEN hamartoma tumor syndrome. This demonstrated 3 expression clusters: papillary architecture tumors, follicular architecture tumors, and background thyroid tissue. The majority (17, 65.4%) of cancers were RAS-like. Follicular architecture cancers were primarily RAS-like (BRAFV600E-RAS score +0.67) and frequently associated with biallelic PTEN alterations. Papillary architecture cancers were BRAF-like (BRAFV600E-RAS score -0.77), often in absence of biallelic PTEN alterations. Adenomatous nodules had indistinguishable expression profiles from follicular architecture cancers.
    CONCLUSIONS: PTEN hamartoma tumor syndrome-associated thyroid tumors most frequently have RAS-like expression profiles. This appears to be caused by baseline dysregulation of the PI3K/AKT/mTOR pathway, with predisposition to biallelic PTEN inactivation promoting follicular adenomatous growth and subsequent malignant transformation to follicular architecture cancers. Better understanding malignant potential and tumor progression in PTEN hamartoma tumor syndrome thyroid tissue is essential for optimizing diagnosis, enhanced surveillance, and treatment in this population.
    DOI:  https://doi.org/10.1016/j.surg.2025.109697
  12. J Surg Res. 2025 Sep 30. pii: S0022-4804(25)00555-4. [Epub ahead of print]315 106-112
    Detection of PIK3CA Mutations in Anal Dysplasia.
    Hillary R Johnson, Elise C Dietmann, Corinne E Praska, Kirsten L Dennison, Stephanie M McGregor, William Suter, Glen Leverson, Muhammed Murtaza, Evie H Carchman.
       INTRODUCTION: The incidence of anal cancer is increasing despite screening and treatment options for anal dysplasia, the precursor to anal cancer. Once anal dysplasia is identified, predicting which patients are at the highest risk of progressing to anal cancer remains challenging, as there are no molecular biomarkers for risk stratification. The most common mutation in anal cancer affects the catalytic subunit of Phosphatidylinositol (3, 4, 5)-trisphosphate Kinase (PI3K). We sought to determine if PIK3CA mutations are detectable in precancerous anal lesions.
    METHODS: DNA was extracted from formalin-fixed, paraffin-embedded anal tissue slides. Digital polymerase chain reaction was performed to test each sample for the presence or absence of three of the most common PIK3CA mutations: E545 K (c.1633 G > A), H1047 R (c.3140 A > G), and H1047 L (c.3140 A > T). Mutation data, histology, and demographic data were compared.
    RESULTS: We analyzed 124 tissue samples from 68 unique patients across the spectrum of anal disease. Forty of these samples were E545 K positive, three were H1047 R positive, and two were H1047 L positive. PIK3CA mutations were detected in 8/42 (19%) low-grade dysplasia samples, 14/45 (31%) high-grade dysplasia samples, and 20/37 (54%) cancer samples. The presence of a mutation was associated with higher grade of disease on per-sample analysis (P = 0.004).
    CONCLUSIONS: PIK3CA mutations can be detected in anal tissue samples across the spectrum of carcinogenesis with increasing incidence with higher grade of disease. Our results warrant further evaluation of PIK3CA mutations as a biomarker for identifying patients with anal dysplasia at highest risk of progression to anal cancer.
    Keywords:  Anal cancer; Anal dysplasia; PIK3CA
    DOI:  https://doi.org/10.1016/j.jss.2025.09.003
  13. J Immunol. 2025 Oct 03. pii: vkaf233. [Epub ahead of print]
    Diabetes and insulin resistance alters ligamentum flavum-derived fibroblast responses in an AKT2-dependent manner.
    Eleni Paflioti, Evangelia Kandylaki, Ioannis Sperelakis, Georgios Kontakis, Christos Tsatsanis.
      Fibroblasts participate in inflammatory responses and play a critical role in the switch from acute to persistent inflammation. Whether fibroblast responses are modulated by signals from their microenvironment is not well established. Insulin signaling and insulin resistance modulate responsiveness of innate immune cells to inflammatory signals. Herein, we investigated whether fibroblast responsiveness is affected by the tissue microenvironment. As a source of fibroblasts, we used ligamentum flavum-derived fibroblasts, being a tissue that is inflamed in the context of ligamentum flavum hypertrophy. The results showed that fibroblasts from patients with ligamentum flavum hypertrophy were hyporesponsive to TLR2 signals. Since ligamentum flavum hypertrophy is associated with obesity, we utilized ligamentum flavum-derived fibroblasts from obese and lean mice. Fibroblasts from insulin-resistant obese mice expressed increased Collagen1a1 and produced more IL-6 in response to TLR2 and TLR4 signals. Insulin signaling was altered in ligamentum flavum-derived fibroblasts from obese mice, resulting in reduced insulin-induced AKT1 phosphorylation and increased insulin-induced AKT2 phosphorylation. Ligamentum flavum-derived fibroblasts from AKT2-deficient mice were hyporesponsive to TLR signals, in contrast to these from obese mice, suggesting that active AKT2 signaling is required to support responsiveness of fibroblasts. Basal respiration and stress-induced glycolysis were elevated in fibroblasts from AKT2-/- and obese mice, suggesting that even though their response to TLR signaling differs, they exhibited similar metabolic changes. The results suggest that responsiveness of fibroblasts is altered in the context of obesity and insulin resistance and is controlled by the balance of AKT1/AKT2 activation, which may be critical to the development of hypertrophy.
    Keywords:  AKT; TLR; fibroblasts; inflammation; metabolism
    DOI:  https://doi.org/10.1093/jimmun/vkaf233
  14. bioRxiv. 2025 Sep 25. pii: 2025.09.23.678129. [Epub ahead of print]
    Exploring endothelial cell environments across organs in spatially resolved omics data.
    Yashvardhan Jain, Jodie Jepson, Roy Chen, Elizabeth Maier, Bruce W Herr, Aleix Puig-Barbe, Ellen M Quardokus, Danial Qaurooni, Clarence Yapp, Samuel L Ewing, Archibald Enninful, Negin Farzad, Andreas Bueckle, Quinn T Easter, Bruno Matuck, Chenchen Zhu, Emma Marie Monte, Jeffrey M Purkerson, Matthew Jehrio, Ravi S Misra, Rong Fan, Fiona Ginty, Arivarasan Karunamurthy, Jean Fan, Martha Campbell-Thompson, Gloria S Pryhuber, Kevin M Byrd, John W Hickey, Katy Börner.
      Endothelial cells are ubiquitously present in the human body and line the luminal surface of blood and lymphatic vessels. The oxygen-dependence of cells impacts their proximity to blood vessels, and consequently, to endothelial cells depending on their functional properties and priorities. This paper presents cell-to-nearest-endothelial-cell distance distributions for various cell types using 399 spatially resolved omics datasets from 14 studies comprising 12 tissue types with a total of 47,349,496 cells. Additionally, we developed an open-source web-based interactive tool, Cell Distance Explorer, that allows researchers to interactively visualize cell graphs and linkages in 2D and 3D datasets. Finally, we present a hierarchical neighborhood analysis focused on the endothelial cell neighborhoods in small and large intestine datasets. This paper provides an open-access resource (datasets, tools, and analyses) to characterize and compare cell distances and cell neighborhoods in spatially resolved omics data.
    DOI:  https://doi.org/10.1101/2025.09.23.678129
  15. Ital J Dermatol Venerol. 2025 Oct;160(5): 461-463
    An overlapping phenotype between megalencephaly-capillary malformation and Diffuse Capillary Malformation with Overgrowth: expanding the PIK3CA-related overgrowth spectrum.
    Filippo Toaiari, Samantha F Berti, Michele Lanzetti, Camilla Salvini, Antonella Cecconi.
      
    DOI:  https://doi.org/10.23736/S2784-8671.25.08276-3
  16. PLoS Comput Biol. 2025 Sep 30. 21(9): e1013526
    Harmony-based data integration for distributed single-cell multi-omics data.
    Ruizhi Yuan, Ziqi Rong, Haoran Hu, Tianhao Liu, Shiyue Tao, Wei Chen, Lu Tang.
      Large-scale single-cell projects generate rapidly growing datasets, but downstream analysis is often confounded by data sources, requiring data integration methods to do correction. Existing data integration methods typically require data centralization, raising privacy and security concerns. Here, we introduce Federated Harmony, a novel method combining properties of federated learning with Harmony algorithm to integrate decentralized omics data. This approach preserves privacy by avoiding raw data sharing while maintaining integration performance comparable to Harmony. Experiments on various types of single-cell data showcase superior results, highlighting a novel data integration approach for distributed multi-omics data without compromising data privacy or analytical performance.
    DOI:  https://doi.org/10.1371/journal.pcbi.1013526
  17. Nat Commun. 2025 Sep 30. 16(1): 8373
    COOKIE-Pro: covalent inhibitor binding kinetics profiling on the proteome scale.
    Hanfeng Lin, Bin Yang, Lang Ding, Yen-Yu Yang, Matthew V Holt, Sung Yun Jung, Bing Zhang, Meng C Wang, Jin Wang.
      Covalent inhibitors are an emerging class of therapeutics, but methods to comprehensively profile their binding kinetics and selectivity across the proteome have been limited. Here we introduce COOKIE-Pro (COvalent Occupancy KInetic Enrichment via Proteomics), an unbiased method for quantifying irreversible covalent inhibitor binding kinetics on a proteome-wide scale. COOKIE-Pro uses a two-step incubation process with mass spectrometry-based proteomics to determine kinact and KI values for covalent inhibitors against both on-target and off-target proteins. We validated COOKIE-Pro using BTK inhibitors spebrutinib and ibrutinib, accurately reproducing known kinetic parameters and identifying both expected and unreported off-targets. The method revealed that spebrutinib has over 10-fold higher potency for TEC kinase compared to its intended target BTK. To demonstrate the method's utility for high-throughput screening, we applied a streamlined two-point strategy to a library of 16 covalent fragments. This approach successfully generated thousands of kinetic profiles, enabling the quantitative decoupling of intrinsic chemical reactivity from binding affinity at scale and validating the method's broad applicability. By providing a comprehensive view of covalent inhibitor binding across the proteome, COOKIE-Pro represents a powerful tool for optimizing the potency and selectivity of covalent drugs during preclinical development.
    DOI:  https://doi.org/10.1038/s41467-025-63491-2
  18. Cell Rep. 2025 Sep 29. pii: S2211-1247(25)01132-5. [Epub ahead of print]44(10): 116361
    Biphasic control of the B cell transcriptome by mTORC1 and GSK3.
    Jens Kalchschmidt, Tomoya Kanno, Solji Park, Wendy D Dubois, Yongbing Zhao, Pawel Trzaskoma, Craig J Thomas, Louis M Staudt, John J O'Shea, Seolkyoung Jung, Rafael Casellas.
      A central question in immune regulation is how cells coordinate transcriptional responses to environmental cues. It remains unclear whether transcriptional regulation is controlled by isolated mechanism or integrated regulatory programs. Here, we develop a high-sensitivity, genome-wide CRISPR-Cas9 screening platform with 47 transcriptional reporters in human B cell lymphoma, identifying 4,440 regulators and 17,638 regulatory interactions. To enable the exploration of these networks, we establish B-LEARN, an interactive portal for data visualization and discovery. Our results reveal a large number of shared regulators across our 47 screens that act as context-dependent activators or repressors. Globally, we uncover a biphasic regulatory architecture in which mTORC1 and GSK3 exert opposing control over the B cell transcriptome. Notably, mTOR inhibition broadly activates key B cell genes, an effect antagonized by GSK3. Thus, B cell transcription is governed by an integrated, pathway-driven circuit, offering new targets to modulate gene expression in lymphoma and autoimmune disease.
    Keywords:  CP: Immunology; GSK3; functional CRISPR screens; gene regulatory network; human B cell lymphoma; immune response gene expression; mTOR; reporter cell lines; small-molecule screening; transcriptional regulation
    DOI:  https://doi.org/10.1016/j.celrep.2025.116361
  19. Nat Rev Mol Cell Biol. 2025 Sep 30.
    Mechanisms, functions and therapeutic targeting of protein tyrosine phosphatases.
    Tony Tiganis, Nicholas K Tonks.
      Aberrations in protein tyrosine phosphorylation-dependent cell signalling contribute to a wide variety of human diseases. Drugs targeting protein tyrosine kinases have had a major impact on human health; by contrast, protein tyrosine phosphatases (PTPs), which serve unique functions and together with protein tyrosine kinases coordinate tyrosine phosphorylation-dependent cell signalling, have been underexploited therapeutically. In this Review, we discuss key breakthroughs in our understanding of how PTPs are regulated, highlight their capacity to coordinate signalling and provide examples of their complex roles in physiology and pathophysiology, including diabetes, obesity and cancer. Also, we discuss the development of PTP-targeted therapeutics that are in clinical trials or poised for clinical translation. We argue that the emergence of this class of enzymes from the shadows lays the foundation for a more complete understanding of the regulation of cell signalling and heralds a new era of drug development opportunities to combat important human diseases.
    DOI:  https://doi.org/10.1038/s41580-025-00882-9
  20. Nucleic Acids Res. 2025 Sep 23. pii: gkaf921. [Epub ahead of print]53(18):
    On metrics for subpopulation detection in single-cell and spatial omics data.
    Siyuan Luo, Pierre-Luc Germain, Ferdinand von Meyenn, Mark D Robinson.
      Benchmarks are crucial to understanding the strengths and weaknesses of the growing number of tools for single-cell and spatial omics analysis. A key task is to distinguish subpopulations within complex tissues, where evaluation typically relies on external clustering validation metrics. Different metrics often lead to inconsistencies between rankings, highlighting the importance of understanding the behavior and biological implications of each metric. In this work, we provide a framework for systematically understanding and selecting validation metrics for single-cell data analysis, addressing tasks such as creating cell embeddings, constructing graphs, clustering, and spatial domain detection. Our discussion centers on the desirable properties of metrics, focusing on biological relevance and potential biases. Using this framework, we not only analyze existing metrics but also develop novel ones. Delving into domain detection in spatial omics data, we develop new external metrics tailored to spatially aware measurements. Additionally, a Bioconductor R package, poem, implements all the metrics discussed. While we focus on single-cell omics, much of the discussion is of broader relevance to other types of high-dimensional data.
    DOI:  https://doi.org/10.1093/nar/gkaf921
  21. Trends Cancer. 2025 Oct 02. pii: S2405-8033(25)00230-4. [Epub ahead of print]
    Spatially resolving cancer: from cell states to therapy.
    Guangsheng Pei, Yang Liu, Linghua Wang.
      Recent advances in spatial multi-omics technologies and analytical methods are transforming our understanding of how cancer cells and their microenvironments interact to drive critical processes such as lineage plasticity, immune evasion, and therapeutic resistance. By linking cancer cell states, lineage plasticity, clonal dynamics, oncogenic pathways, and cellular interactions to their spatial context, these innovations provide deep biological insights and reveal clinically relevant molecular programs and spatial biomarkers. This review highlights key breakthroughs in spatial profiling and computational approaches, including integration with computational pathology, multimodal data, and machine learning to uncover important biological insights. We discuss challenges in spatial multimodal data integration and emerging clinical applications, and we propose a roadmap to accelerate clinical translation and advance precision oncology through spatially resolved, actionable, molecular insights.
    Keywords:  cancer cell state; computational pathology; machine learning; multimodal data integration; spatial multi-omics; spatial profiling
    DOI:  https://doi.org/10.1016/j.trecan.2025.09.002
  22. Cell. 2025 Sep 26. pii: S0092-8674(25)01034-7. [Epub ahead of print]
    Single-cell nascent transcription reveals sparse genome usage and plasticity.
    Shaoqian Ma, Yantao Hong, Junhan Chen, Jingzhao Xu, Xiaohua Shen.
      Understanding cell diversification from a common genome in metazoans requires single-cell transcriptional analysis. We introduce single-cell full-length EU-labeled nascent RNA sequencing (scFLUENT-seq), a single-cell nascent RNA sequencing method using brief 10-min metabolic labeling to capture genome-wide transcription. Surprisingly, individual cells-from splenic lymphocytes to pluripotent stem cells-transcribe only ∼0.02%-3.1% of the genome, versus >80% in bulk, revealing limited genome engagement and profound cell-type and cell-to-cell heterogeneity. Intergenic transcription, especially from heterochromatin, is pervasive and stochastic. Promoter-associated antisense and genic transcription rarely co-occur in the same cell. Proximal intergenic transcription involves both gene readthrough and independent initiation, while distal intergenic transcription is largely independent of neighboring genes and correlates with increased transcriptional diversity, a hallmark of cellular plasticity. Although global RNA synthesis and turnover are coupled in bulk, individual mRNA transcription and decay are poorly coordinated in single cells, suggesting noise-buffering mechanisms. Overall, scFLUENT-seq uncovers complex coding and noncoding transcriptional dynamics that underlie single-cell heterogeneity and state transitions.
    Keywords:  cell state and plasticity; chromatin; heterogeneity; noncoding genome; single-cell nascent RNA-seq; transcription dynamics
    DOI:  https://doi.org/10.1016/j.cell.2025.09.003
  23. Nat Commun. 2025 Oct 03. 16(1): 8821
    A deep single cell mass cytometry approach to capture canonical and noncanonical cell cycle states.
    Meelad Amouzgar, Patricia Favaro, Daniel Ho, Trevor Bruce, Sean C Bendall.
      The cell cycle (CC) underpins diverse cell processes like cell differentiation, cell expansion, and tumorigenesis but current single-cell (sc) strategies study CC as: coarse phases, rely on transcriptomic signatures, use imaging modalities limited to adherent cells, or lack high-throughput multiplexing. To solve this, we develop an expanded, Mass Cytometry (MC) approach with 48 CC-related molecules that deeply phenotypes the diversity of scCC states. Using Cytometry by Time of Flight, we quantify scCC states across suspension and adherent cell lines, and stimulated primary human T cells. Our approach captures the diversity of scCC states, including atypical CC states beyond canonical definitions. Pharmacologically-induced CC arrest reveals that perturbations exacerbate noncanonical states and induce previously unobserved states. Notably, primary cells escaping CC inhibition demonstrated aberrant CC states compared to untreated cells. Our approach enables deeper phenotyping of CC biology that generalizes to diverse cell systems with simultaneous multiplexing and integration with MC platforms.
    DOI:  https://doi.org/10.1038/s41467-025-63883-4
  24. Nat Metab. 2025 Oct 02.
    Artificial intelligence in metabolic research.
    Jens Juul Holst, Camilla Schéele, Philipp E Scherer, Weiping Jia, Eran Segal, Nikolai Slavov, Ruth J F Loos, Golnaz Vahedi, Lei Sun, M Madan Babu, Melissa D McCradden, Peter G Jacobs.
      
    DOI:  https://doi.org/10.1038/s42255-025-01395-7
  25. Nat Commun. 2025 Sep 30. 16(1): 8714
    Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data.
    Jakub Idkowiak, Jonas Dehairs, Jana Schwarzerová, Dominika Olešová, Jacob X M Truong, Aleš Kvasnička, Marios Eftychiou, Ruben Cools, Xander Spotbeen, Robert Jirásko, Vullnet Veseli, Marco Giampà, Vincent de Laat, Lisa M Butler, Wolfram Weckwerth, David Friedecký, Jonas Demeulemeester, Karel Hron, Johannes V Swinnen, Michal Holčapek.
      Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and visualize statistically significant trends and biologically relevant differences. Besides tailored methods developed by individual labs, a solid core of freely accessible tools exists for exploratory data analysis and visualization, which we have compiled here, including preparation of descriptive statistics, annotated box plots, hypothesis testing, volcano plots, lipid maps and fatty acyl chain plots, unsupervised and supervised dimensionality reduction, dendrograms, and heat maps. This review is intended for those who would like to develop their skills in data analysis and visualization using freely available R or Python solutions. Beginners are guided through a selection of R and Python libraries for producing publication-ready graphics without being overwhelmed by the code complexity. This manuscript, along with associated GitBook code repository containing step-by-step instructions, offers readers a comprehensive guide, encouraging the application of R and Python for robust and reproducible chemometric analysis of omics data.
    DOI:  https://doi.org/10.1038/s41467-025-63751-1
  26. EMBO J. 2025 Oct 03.
    Mapping cryptic phosphorylation sites in the human proteome.
    Dino Gasparotto, Annarita Zanon, Valerio Bonaldo, Elisa Marchiori, Massimo Casagranda, Erika Di Domenico, Laura Copat, Tommaso Fortunato Asquini, Marta Rigoli, Sirio Vittorio Feltrin, Nuria Lopez Lorenzo, Graziano Lolli, Maria Pennuto, Jesùs R Requena, Omar Rota Stabelli, Giovanni Minervini, Cristian Micheletti, Giovanni Spagnolli, Pietro Faccioli, Emiliano Biasini.
      Advances in computational and experimental methods have revealed the existence of transient, non-native protein folding intermediates that could play roles in disparate biological processes, from regulation of protein expression to disease-relevant misfolding mechanisms. Here, we tested the possibility that specific post-translational modifications may involve residues exposed during the folding process by assessing the solvent accessibility of 87,138 post-translationally modified amino acids in the human proteome. Unexpectedly, we found that one-third of phosphorylated proteins present at least one phosphosite completely buried within the protein's inner core. Computational and experimental analyses suggest that these cryptic phosphosites may become exposed during the folding process, where their modification could destabilize native structures and trigger protein degradation. Phylogenetic investigation also reveals that cryptic phosphosites are more conserved than surface-exposed phosphorylated residues. Finally, cross-referencing with cancer mutation databases suggests that phosphomimetic mutations in cryptic phosphosites can increase tumor fitness by inactivating specific onco-suppressors. These findings define a novel role for co-translational phosphorylation in shaping protein folding and expression, laying the groundwork for exploring the implications of cryptic phosphorylation in health and disease.
    Keywords:  Co-translational Phosphorylation; Cryptic Phosphosites; Post-translation Modification; Protein Folding; Protein Phosphorylation
    DOI:  https://doi.org/10.1038/s44318-025-00567-1
  27. J Neurosurg. 2025 Oct 03. 1-10
    Association of PIK3CA mutations with brainstem location in sporadic cerebral cavernous malformations.
    Martin Planet, Yohan Ducos, Mélanie Eyries, Pauline Marijon, Franck Bielle, Lucas Rincon de la Rosa, Agusti Alentorn, Bertrand Mathon, Florence Coulet, Michel Kalamarides, Matthieu Peyre.
       OBJECTIVE: Since 2021, there has been a revolution in the understanding of the mutational landscape of sporadic cerebral cavernous malformations (CCMs), with the key discovery of somatic mutations in the PIK3CA and MAP3K3 genes. These genetic alterations have provided new insights into the pathophysiology of CCMs and opened potential venues for personalized treatments. However, establishing robust clinicoradiological and molecular correlations is essential to guide targeted therapeutic approaches and optimize patient outcomes.
    METHODS: This study included a cohort of 89 patients diagnosed with sporadic CCMs. The mutational status of each patient was determined using next-generation sequencing (NGS) targeting known mutations including the PIK3CA, MAP3K3, and CCM genes. NGS findings were confirmed by droplet digital polymerase chain reaction for PIK3CA and MAP3K3 mutations. Clinical and radiological data, including Zabramski classification data, were systematically recorded. Statistical analysis was performed to identify significant clinicoradiological and molecular correlations.
    RESULTS: In the cohort, PIK3CA somatic mutations were identified in 43 patients (48%), while MAP3K3 somatic mutations were found in 29 (33%). Clinically, PIK3CA-mutated lesions were less frequently revealed by intracranial hypertension (9.3% vs 19.6%; adjusted OR 0.09, p = 0.006), while for MAP3K3-mutated lesions, seizure as a mode of onset was significantly more frequent (85.7% vs 51.7%, p = 0.002). Radiologically, midline lesions were significantly more frequent in the PIK3CA-mutated group (19.0% vs 2.2%, p = 0.01). Importantly, in univariate analysis, the presence of a brainstem lesion was a significant independent predictor of PIK3CA somatic mutation (14.3% vs 2.2%; unadjusted OR 7.33, p = 0.03).
    CONCLUSIONS: This study presents new findings linking genetic mutations with clinicoradiological features in sporadic CCMs. The significant association of PIK3CA somatic mutations with brainstem location highlights a potential avenue for personalized therapeutic strategies targeting this mutation, considering the significantly increased morbidity and surgical challenge associated with brainstem lesions. These findings reinforce the importance of integrating genetic data into clinical practice to improve patient outcomes and develop new therapies for CCMs.
    Keywords:  MAP3K3; PIK3CA; brainstem; cavernoma; cerebral cavernous malformation; epilepsy; genetics; vascular disorders
    DOI:  https://doi.org/10.3171/2025.5.JNS25596
  28. J Clin Immunol. 2025 Sep 30. 45(1): 139
    Homozygous Loss of Function PIK3CD Mutation in Multiple Siblings Leading To B Cell Dysregulation and Autoimmunity.
    Huda Alajlan, Amer Al-Mazrou, Hibah Alruwaili, Safia Sumayli, Ali Almehaidib, Khalid Alsaleem, Sawsan Abu Awwad, Hazem Ghebeh, Monther Al-Alwan, Anas M Alazami, Hamoud Al-Mousa.
      Phosphatidylinositol 3-kinases (PI3Ks) are heterodimeric lipid kinases that are involved in a diverse array of cellular functions such as growth, metabolism, and migration. Mutations in PIK3CD, which encodes an immune-specific catalytic subunit of PI3K, cause both dominant (activating) and recessive (loss of function) immune deficiencies in humans. Here we report a family with three affected children carrying a novel bi-allelic, truncating mutation in PIK3CD. All three patients exhibited chronic diarrhea and recurrent sinopulmonary infections. Immunoblot confirmed loss of protein along with reduced expression of the associated p85α regulatory subunit. Immune phenotyping showed B cell dysregulation with abnormally high levels of naïve cells. In vitro functional testing of CD19 + and enriched naïve B cells revealed impaired proliferation, and reduction in class-switch recombination upon CD40L and IL-21 stimulation. Our data raise the possibility that PI3K-related dysregulation in human B cells may be broader than in mouse models, where class-switch recombination can still occur with external T cell help. Our study substantially increases the limited number of patients known to have immune deficiency due to loss of PIK3CD.
    Keywords:  Hypogammaglobulinemia; Loss of function; P110δ; P85; PI3Kδ; Primary immunodeficiency
    DOI:  https://doi.org/10.1007/s10875-025-01938-3
  29. Exp Hematol Oncol. 2025 Sep 29. 14(1): 115
    Precise regulation of RAS-Mediated PI3Kα activation: therapeutic potential of BBO-10203 in cancer treatment.
    Ziyi Fan, Erqing Tan, Bin Song.
      In recent years, the Phosphoinositide-3-Kinase α (PI3Kα) signaling pathway has been increasingly recognized as a critical driver of tumorigenesis, particularly in breast cancer drug resistance and other solid tumors. Although conventional PI3Kα inhibitors (e.g., Alpelisib) have shown efficacy in extending progression-free survival in patients with PI3Kα-mutant breast cancer, their clinical application remains constrained by off-target toxicities, particularly hyperglycemia, which limits dosing and therapeutic feasibility. Building on recent preclinical findings, this study introduces BBO-10203, a first-in-class, orally bioavailable small-molecule inhibitor targeting the RAS-PI3Kα interaction. The compound is rationally designed to selectively and covalently bind to Cysteine 242 (Cys242) within the Rat Sarcoma (RAS)-Binding Domain (RBD) of PI3Kα, thereby effectively disrupting RAS-mediated PI3Kα activation. This unique mechanism confers potent in vivo antitumor activity while preserving insulin-regulated glucose metabolism, thereby mitigating metabolic adverse effects.
    Keywords:  BBO-10203; Protein-Protein interaction inhibitor; RAS-PI3Kα signaling pathway
    DOI:  https://doi.org/10.1186/s40164-025-00706-8
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