bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–04–13
twenty papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Diet induced insulin resistance is due to induction of PTEN expression.
  2. Clonal memory of colitis accumulates and promotes tumor growth.
  3. Structures of the PI3Kα/KRas complex on lipid bilayers reveal the molecular mechanism of PI3Kα activation.
  4. omicsGMF: a multi-tool for dimensionality reduction, batch correction and imputation applied to bulk- and single cell proteomics data.
  5. Reduced Notch signaling in hypothalamic endothelial cells mediates obesity-induced alterations in glucose uptake and insulin signaling.
  6. Perturb-tracing enables high-content screening of multi-scale 3D genome regulators.
  7. mTORC1 shutdown unleashes TFEB to drive triple-negative breast cancer invasion.
  8. Fluid Shear Stress-Regulated Vascular Remodeling: Past, Present, and Future.
  9. Sequential orthogonal assays for longitudinal and endpoint characterization of three-dimensional spheroids.
  10. Overcoming Analytical Challenges in Proximity Labeling Proteomics.
  11. Multimodal cell maps as a foundation for structural and functional genomics.
  12. Explainable modeling of single-cell perturbation data using attention and sparse dictionary learning.
  13. Practical considerations for data exploration in quantitative cell biology.
  14. MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.
  15. Protocol for the functional evaluation of genetic variants using saturation genome editing.
  16. TMT-based Multiplexed (Chemo)proteomics on the Orbitrap Astral Mass Spectrometer.
  17. HLA class II-restricted T cell epitopes in public neoantigens of ESR1 and PIK3CA in breast cancer.
  18. Dyr726, a brain-penetrant inhibitor of PI3Kα, Type III receptor tyrosine kinases, and WNT signaling.
  19. Bright and photostable yellow fluorescent proteins for extended imaging.
  20. Lignature: A Comprehensive Database of Ligand Signatures to Predict Cell-Cell Communication.
  1. bioRxiv. 2025 Mar 26. pii: 2025.03.25.645201. [Epub ahead of print]
    Diet induced insulin resistance is due to induction of PTEN expression.
    Radha Mukherjee, Priya Pancholi, Malvika Sharma, Hilla Solomon, Merna N Timaul, Claire Thant, Rory McGriskin, Omar Hayatt, Vladimir Markov, John D'Allara, Simona Bekker, Jacqueline Candelier, Sebastian E Carrasco, Elisa de Stanchina, Kiran Vanaja, Neal Rosen.
      Insulin resistance is a condition associated with obesity, type 2 diabetes(T2D), hyperinsulinemia, hyperglycemia and defined by reduced sensitivity to insulin signaling. Molecular causes and early signaling events underlying insulin resistance are not well understood. Here we show that insulin activation of PI3K/AKT/mTOR signaling in insulin target tissues, causes mTORC1 induction of PTEN translation, a negative regulator of PI3K signaling. We hypothesized that insulin resistance is due to insulin dependent induction of PTEN that prevents further increases in PI3K signaling. In a diet induced animal model of obesity and insulin resistance, we show that PTEN levels are increased in fat, muscle, and liver. Hyperinsulinemia and PTEN induction are followed by hyperglycemia, severe glucose intolerance, and hepatic steatosis. In response to chronic hyperinsulinemia, PTEN remains increased, while AKT activity is induced transiently before settling down to a PTEN-high and AKT-low state in the tissues, predicted by computational modeling of the PTEN-AKT feedback loop. Treatment with PTEN and mTORC1 inhibitors prevent and reverse the effect of PTEN induction, rescue insulin resistance and increase PI3K/AKT signaling. Thus, we show that PTEN induction by increased insulin levels elevates feedback inhibition of the pathway causing insulin resistance, its associated phenotypes, and is a potential therapeutic target.
    DOI:  https://doi.org/10.1101/2025.03.25.645201
  2. Res Sq. 2025 Mar 27. pii: rs.3.rs-6081101. [Epub ahead of print]
    Clonal memory of colitis accumulates and promotes tumor growth.
    Jason Buenrostro, Surya Nagaraja, Lety Ojeda-Miron, Ruochi Zhang, Ena Oreskovic, Yan Hu, Daniel Zeve, Karina Sharma, Roni Hyman, Qiming Zhang, Andrew Castillo, David Breault, Omer Yilmaz.
      Chronic inflammation is a well-established risk factor for cancer, but the underlying molecular mechanisms remain unclear. Using a mouse model of colitis, we demonstrate that colonic stem cells retain an epigenetic memory of inflammation following disease resolution, characterized by a cumulative gain of activator protein 1 (AP-1) transcription factor activity. Further, we develop SHARE-TRACE, a method that enables simultaneous profiling of gene expression, chromatin accessibility and clonal history in single cells, enabling high resolution tracking of epigenomic memory. This reveals that inflammatory memory is propagated cell-intrinsically and inherited through stem cell lineages, with certain clones demonstrating dramatically stronger memory than others. Finally, we show that colitis primes stem cells for amplified expression of regenerative gene programs following oncogenic mutation that accelerate tumor growth. This includes a subpopulation of tumors that have exceptionally high AP-1 activity and the additional upregulation of pro-oncogenic programs. Together, our findings provide a mechanistic link between chronic inflammation and malignancy, revealing how long-lived epigenetic alterations in regenerative tissues may contribute to disease susceptibility and suggesting potential therapeutic strategies to mitigate cancer risk in patients with chronic inflammatory conditions.
    DOI:  https://doi.org/10.21203/rs.3.rs-6081101/v1
  3. bioRxiv. 2025 Mar 25. pii: 2025.03.22.644753. [Epub ahead of print]
    Structures of the PI3Kα/KRas complex on lipid bilayers reveal the molecular mechanism of PI3Kα activation.
    Hayarpi Torosyan, Michael D Paul, Allison Maker, Brigitte G Meyer, Natalia Jura, Kliment A Verba.
      PI3Kα is a potent oncogene that converts PIP2 to PIP3 at the plasma membrane upon activation by receptor tyrosine kinases and Ras GTPases. In the absence of any structures of activated PI3Kα, the molecular details of its activation remain unknown. Here, we present cryo-EM structures of the PI3Kα/KRas complex embedded in lipid nanodiscs, revealing a rich ensemble of PI3Kα states adopted at the membrane surface. The sequential addition of a lipid bilayer, PIP2 and an activating phosphopeptide leads to the progressive release of key inhibitory domains from the PI3Kα catalytic core, which directly correlates with the reorganization of its active site. While association with POPC/POPS nanodiscs partially relieves PI3Kα autoinhibition, incorporation of PIP2 triggers near-complete displacement of PI3Kα inhibitory domains and significant restructuring of active site regulatory motifs. The addition of the activating phosphopeptide induces dimerization of the PI3Kα/KRas complex through a p110α catalytic subunit-mediated interface that is sterically occluded in autoinhibited PI3Kα. In cells, this dimeric PI3Kα complex amplifies Akt signaling in response to growth factor stimulation. Collectively, our structures map the conformational landscape of PI3Kα activation and reveal previously unexplored interfaces for potential therapeutic targeting.
    DOI:  https://doi.org/10.1101/2025.03.22.644753
  4. bioRxiv. 2025 Mar 28. pii: 2025.03.24.644996. [Epub ahead of print]
    omicsGMF: a multi-tool for dimensionality reduction, batch correction and imputation applied to bulk- and single cell proteomics data.
    Alexandre Segers, Cristian Castiglione, Christophe Vanderaa, Elfride De Baere, Lennart Martens, Davide Risso, Lieven Clement.
      The unprecedented speed and sensitivity of mass spectrometry (MS) unlocked large-scale applications of proteomics and even enabled proteome profiling of single cells. However, this fast-evolving field is hindered by a lack of scalable dimensionality reduction tools that can compensate for substantial batch effects and missingness across MS runs. Therefore, we present omicsGMF, a fast, scalable, and interpretable matrix factorization method, tailored for bulk and single-cell proteomics data. Unlike current workflows that sequentially apply imputation, batch correction, and principal component analysis, omicsGMF integrates these steps into a unified framework, dramatically enhancing data processing and dimensionality reduction. Additionally, omicsGMF provides robust imputation of missing values, outperforming bespoke state-of-the-art imputation tools. We further demonstrate how this integrated approach increases statistical power to detect differentially abundant proteins in the downstream data analysis. Hence, omicsGMF is a highly scalable approach to dimensionality reduction in proteomics, that dramatically improves many important steps in proteomics data analysis.
    DOI:  https://doi.org/10.1101/2025.03.24.644996
  5. Cell Rep. 2025 Apr 03. pii: S2211-1247(25)00293-1. [Epub ahead of print]44(4): 115522
    Reduced Notch signaling in hypothalamic endothelial cells mediates obesity-induced alterations in glucose uptake and insulin signaling.
    Yiyi Zhu, Oliver Mehlkop, Heiko Backes, Anna Lena Cremer, Marta Porniece, Paul Klemm, Lukas Steuernagel, Weiyi Chen, Ronja Johnen, F Thomas Wunderlich, Alexander Jais, Jens C Brüning.
      Short-term transition to high-fat diet (HFD) feeding causes rapid changes in the molecular architecture of the blood-brain barrier (BBB), BBB permeability, and brain glucose uptake. However, the precise mechanisms responsible for these changes remain elusive. Here, we detect a rapid downregulation of Notch signaling after short-term HFD feeding. Conversely, Notch activation restores HFD-fed mouse serum-induced reduction of Glut1 expression and glycolysis in cultured brain microvascular endothelial cells (BMECs). Selective, inducible expression of the Notch intracellular domain (IC) in BMECs prevents HFD-induced reduction of Glut1 expression and hypothalamic glucose uptake. Caveolin (Cav)-1 expression in BMECs is increased upon short-term HFD feeding. However, NotchICBMECs mice display reduced caveola formation and BBB permeability. This ultimately translates into reduced hypothalamic insulin transport, action, and systemic insulin sensitivity. Collectively, we highlight a critical role of Notch signaling in the pleiotropic effects of short-term dietary transitions on BBB functionality.
    Keywords:  CP: Metabolism; CP: Neuroscience; Notch signaling; glucose transport; hypothalamus; insulin action; obesity; vascular endothelial cells
    DOI:  https://doi.org/10.1016/j.celrep.2025.115522
  6. Nat Methods. 2025 Apr 10.
    Perturb-tracing enables high-content screening of multi-scale 3D genome regulators.
    Yubao Cheng, Mengwei Hu, Bing Yang, Tyler B Jensen, Yuan Zhang, Tianqi Yang, Ruihuan Yu, Zhaoxia Ma, Jonathan S D Radda, Shengyan Jin, Chongzhi Zang, Siyuan Wang.
      Three-dimensional (3D) genome organization becomes altered during development, aging and disease, but the factors regulating chromatin topology are incompletely understood and currently no technology can efficiently screen for new regulators of multi-scale chromatin organization. Here, we developed an image-based high-content screening platform (Perturb-tracing) that combines pooled CRISPR screens, a cellular barcode readout method (BARC-FISH) and chromatin tracing. We performed a loss-of-function screen in human cells, and visualized alterations to their 3D chromatin folding conformations, alongside perturbation-paired barcode readout in the same single cells. We discovered tens of new regulators of chromatin folding at different length scales, ranging from chromatin domains and compartments to chromosome territory. A subset of the regulators exhibited 3D genome effects associated with loop extrusion and A-B compartmentalization mechanisms, while others were largely unrelated to these known 3D genome mechanisms. Finally, we identified new regulators of nuclear architectures and found a functional link between chromatin compaction and nuclear shape. Altogether, our method enables scalable, high-content identification of chromatin and nuclear topology regulators that will stimulate new insights into the 3D genome.
    DOI:  https://doi.org/10.1038/s41592-025-02652-z
  7. Dev Cell. 2025 Apr 07. pii: S1534-5807(25)00153-4. [Epub ahead of print]60(7): 979-981
    mTORC1 shutdown unleashes TFEB to drive triple-negative breast cancer invasion.
    Michalis Gounis, Hellyeh Hamidi, Johanna Ivaska.
      The PI3K/AKT/mTOR pathway is considered a key therapeutic target in triple-negative breast cancer (TNBC). In this issue of Developmental Cell, Remy et al. challenge this idea by demonstrating that mTORC1 inhibition activates TFEB, promoting MT1-MMP exocytosis, ECM degradation, and increased cell invasion, especially when combined with chemotherapy.
    DOI:  https://doi.org/10.1016/j.devcel.2025.03.006
  8. Arterioscler Thromb Vasc Biol. 2025 Apr 10.
    Fluid Shear Stress-Regulated Vascular Remodeling: Past, Present, and Future.
    Hanqiang Deng, Anne Eichmann, Martin A Schwartz.
      The vascular system remodels throughout life to ensure adequate perfusion of tissues as they grow, regress, or change metabolic activity. Angiogenesis, the sprouting of new blood vessels to expand the capillary network, versus regression, in which endothelial cells die or migrate away to remove unneeded capillaries, controls capillary density. In addition, upstream arteries adjust their diameters to optimize blood flow to downstream vascular beds, which is controlled primarily by vascular endothelial cells sensing fluid shear stress (FSS) from blood flow. Changes in capillary density and small artery tone lead to changes in the resistance of the vascular bed, which leads to decreased or increased flow through the arteries that feed these small vessels. The resultant changes in FSS through these vessels then stimulate their inward or outward remodeling, respectively. This review summarizes our knowledge of endothelial FSS-dependent vascular remodeling, offering insights into potential therapeutic interventions. We first provide a historical overview, then discuss the concept of set point and mechanisms of low-FSS-mediated and high-FSS-mediated inward and outward remodeling. We then cover in vivo animal models, molecular mechanisms, and clinical implications. Understanding the mechanisms underlying physiological endothelial FSS-mediated vascular remodeling and their failure due to mutations or chronic inflammatory and metabolic stresses may lead to new therapeutic strategies to prevent or treat vascular diseases.
    Keywords:  capillaries; cardiovascular diseases; endothelial cells; mutation; vascular remodeling
    DOI:  https://doi.org/10.1161/ATVBAHA.125.322557
  9. Nat Protoc. 2025 Apr 08.
    Sequential orthogonal assays for longitudinal and endpoint characterization of three-dimensional spheroids.
    Eva Blondeel, Sam Ernst, Felix De Vuyst, Ákos Diósdi, Cláudio Pinheiro, Diogo Estêvão, Pekka Rappu, Robin Boiy, Sándor Dedeyne, Ligia Craciun, Vera Goossens, Jonas Dehairs, Tânia Cruz, Dominique Audenaert, Wim Ceelen, Michael Linnebacher, Tom Boterberg, Jo Vandesompele, Pieter Mestdagh, Johan Swinnen, Jyrki Heino, Peter Horvath, Maria José Oliveira, An Hendrix, Pieter De Metter, Olivier De Wever.
      Spheroids are reaggregated multicellular three-dimensional structures generated from cells or cell cultures of healthy as well as pathological tissue. Basic and translational spheroid application across academia and industry have led to the development of multiple setups and analysis methods, which mostly lack the modularity to maximally phenotype spheroids. Here we present the self-assembly of single-cell suspensions into spheroids by the liquid overlay method, followed by a modular framework for a multifaceted phenotyping of spheroids. Cell seeding, supernatant handling and compound administration are elaborated by both manual and automated procedures. The phenotyping modules contain a suite of orthogonal assays to analyze spheroids longitudinally and/or at an endpoint. Longitudinal analyses include morphometry with or without spheroid or cell state specific information and supernatant evaluation (nutrient consumption and metabolite/cytokine production). Spheroids can also be used as a starting point to monitor single and collective cell migration and invasion. At an endpoint, spheroids are lysed, fixed or dissociated into single cells. Endpoint analyses allow the investigation of molecular content, single-cell composition and state and architecture with spatial cell and subcellular specific information. Each module addresses time requirements and quality control indicators to support reproducibility. The presented complementary techniques can be readily adopted by researchers experienced in cell culture and basic molecular biology. We anticipate that this modular protocol will advance the application of three-dimensional biology by providing scalable and complementary methods.
    DOI:  https://doi.org/10.1038/s41596-025-01150-y
  10. J Mass Spectrom. 2025 May;60(5): e5134
    Overcoming Analytical Challenges in Proximity Labeling Proteomics.
    Haorong Li, Wan Nur Atiqah Binti Mazli, Ling Hao.
      Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.
    Keywords:  biotinylation; mass spectrometry; proximity labeling
    DOI:  https://doi.org/10.1002/jms.5134
  11. Nature. 2025 Apr 09.
    Multimodal cell maps as a foundation for structural and functional genomics.
    Leah V Schaffer, Mengzhou Hu, Gege Qian, Kyung-Mee Moon, Abantika Pal, Neelesh Soni, Andrew P Latham, Laura Pontano Vaites, Dorothy Tsai, Nicole M Mattson, Katherine Licon, Robin Bachelder, Anthony Cesnik, Ishan Gaur, Trang Le, William Leineweber, Aji Palar, Ernst Pulido, Yue Qin, Xiaoyu Zhao, Christopher Churas, Joanna Lenkiewicz, Jing Chen, Keiichiro Ono, Dexter Pratt, Peter Zage, Ignacia Echeverria, Andrej Sali, J Wade Harper, Steven P Gygi, Leonard J Foster, Edward L Huttlin, Emma Lundberg, Trey Ideker.
      Human cells consist of a complex hierarchy of components, many of which remain unexplored1,2. Here we construct a global map of human subcellular architecture through joint measurement of biophysical interactions and immunofluorescence images for over 5,100 proteins in U2OS osteosarcoma cells. Self-supervised multimodal data integration resolves 275 molecular assemblies spanning the range of 10-8 to 10-5 m, which we validate systematically using whole-cell size-exclusion chromatography and annotate using large language models3. We explore key applications in structural biology, yielding structures for 111 heterodimeric complexes and an expanded Rag-Ragulator assembly. The map assigns unexpected functions to 975 proteins, including roles for C18orf21 in RNA processing and DPP9 in interferon signalling, and identifies assemblies with multiple localizations or cell type specificity. It decodes paediatric cancer genomes4, identifying 21 recurrently mutated assemblies and implicating 102 validated new cancer proteins. The associated Cell Visualization Portal and Mapping Toolkit provide a reference platform for structural and functional cell biology.
    DOI:  https://doi.org/10.1038/s41586-025-08878-3
  12. Cell Syst. 2025 Mar 31. pii: S2405-4712(25)00078-X. [Epub ahead of print] 101245
    Explainable modeling of single-cell perturbation data using attention and sparse dictionary learning.
    Yang Xu, Stephen Fleming, Matthew Tegtmeyer, Steven A McCarroll, Mehrtash Babadi.
      Single-cell transcriptomics, in conjunction with genetic and compound perturbations, offers a robust approach for exploring cellular behaviors in diverse contexts. Such experiments allow uncovering cell-state-specific responses to perturbations and unraveling the intricate molecular mechanisms governing cellular behavior. However, prevailing computational methods predominantly focus on predicting average cellular responses, disregarding inherent response heterogeneity associated with cell state diversity and model explainability. In this study, we present CellCap, a deep generative model designed for the end-to-end analysis of single-cell perturbation experiments. CellCap employs sparse dictionary learning in a latent space to deconstruct cell-state-specific perturbation responses into a set of transcriptional response programs and utilizes an attention mechanism to capture correspondence between cell state and perturbation response. We thoroughly evaluate CellCap's interpretability using multiple simulated scenarios as well as two real single-cell perturbation datasets. Our results demonstrate that CellCap successfully uncovers the relationship between cell state and perturbation response, unveiling insights overlooked in previous analyses.
    Keywords:  Bayesian dictionary learning; deep generative model; explainable machine learning; perturbation analysis; single-cell transcriptomics
    DOI:  https://doi.org/10.1016/j.cels.2025.101245
  13. J Cell Sci. 2025 Apr 01. pii: jcs263801. [Epub ahead of print]138(7):
    Practical considerations for data exploration in quantitative cell biology.
    Joanna W Pylvänäinen, Hanna Grobe, Guillaume Jacquemet.
      Data exploration is an essential step in quantitative cell biology, bridging raw data and scientific insights. Unlike polished, published figures, effective data exploration requires a flexible, hands-on approach that reveals trends, identifies outliers and refines hypotheses. This Opinion offers simple, practical advice for building a structured data exploration workflow, drawing on the authors' personal experience in analyzing bioimage datasets. In addition, the increasing availability of generative artificial intelligence and large language models makes coding and improving data workflows easier than ever before. By embracing these practices, researchers can streamline their workflows, produce more reliable conclusions and foster a collaborative, transparent approach to data analysis in cell biology.
    Keywords:  Data analysis; Data exploration; Data management; Microscopy
    DOI:  https://doi.org/10.1242/jcs.263801
  14. Genome Biol. 2025 Apr 08. 26(1): 90
    MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.
    Salvatore Milite, Giulio Caravagna, Andrea Sottoriva.
      High-throughput multi-omic molecular profiling allows the probing of biological systems at unprecedented resolution. However, integrating and interpreting high-dimensional, sparse, and noisy multimodal datasets remains challenging. Deriving new biological insights with current methods is difficult because they are not rooted in biological principles but prioritise tasks like dimensionality reduction. Here, we introduce a framework that combines archetypal analysis, an approach grounded in biological principles, with deep learning. Using archetypes based on evolutionary trade-offs and Pareto optimality, MIDAA finds extreme data points that define the geometry of the latent space, preserving the complexity of biological interactions while retaining an interpretable output. We demonstrate that these extreme points represent cellular programmes reflecting the underlying biology. Moreover, we show that, compared to alternative methods, MIDAA can identify parsimonious, interpretable, and biologically relevant patterns from real and simulated multi-omics.
    DOI:  https://doi.org/10.1186/s13059-025-03530-9
  15. STAR Protoc. 2025 Apr 07. pii: S2666-1667(25)00116-9. [Epub ahead of print]6(2): 103710
    Protocol for the functional evaluation of genetic variants using saturation genome editing.
    Sofia Obolenski, Rebeca Olvera-León, Dijue Sun, David J Adams, Andrew J Waters.
      Saturation genome editing (SGE) employs CRISPR-Cas9 and homology-directed repair (HDR) to introduce exhaustive nucleotide modifications at specific genomic sites in multiplex, enabling the functional analysis of genetic variants while preserving their native genomic context. Here, we present a protocol for SGE-based variant evaluation in HAP1-A5 cells. We describe the steps for designing variant libraries, single-guide RNAs (sgRNAs), and oligonucleotide primers for PCR. We also detail the sample preparation before the SGE screen, the cellular screening process, and subsequent next-generation sequencing (NGS) library preparation. For complete details on the use and execution of this protocol, please refer to Radford et al.,1 Waters et al.,2 and Olvera-León et al.3.
    Keywords:  CRISPR; Genetics; Genomics; High-Throughput Screening
    DOI:  https://doi.org/10.1016/j.xpro.2025.103710
  16. Mol Cell Proteomics. 2025 Apr 08. pii: S1535-9476(25)00066-0. [Epub ahead of print] 100968
    TMT-based Multiplexed (Chemo)proteomics on the Orbitrap Astral Mass Spectrometer.
    Yuchen He, Ka Yang, Shaoxian Li, Martin Zeller, Graeme C McAlister, Hamish I Stewart, Christian Hock, Eugen Damoc, Vlad Zabrouskov, Steven P Gygi, Joao A Paulo, Qing Yu.
      Ongoing advancements in instrumentation has established mass spectrometry (MS) as an essential tool in proteomics research and drug discovery. The newly released Asymmetric Track Lossless (Astral) analyzer represents a major step forward in MS instrumentation. Here, we evaluate the Orbitrap Astral mass spectrometer in the context of tandem mass tag-based multiplexed proteomics and activity-based proteome profiling, highlighting its sensitivity boost relative to the Orbitrap Tribrid platform-50% at the peptide and 20% at the protein level. We compare TMT DDA and label-free DIA on the same instrument, both of which quantify over 10,000 human proteins per sample within one hour. TMT offers higher quantitative precision and data completeness, while DIA is free of ratio compression and is thereby more accurate. Our results suggest that ratio compression is prevalent with the high-resolution MS2-based quantification on the Astral, while real-time search-based MS3 quantification on the Orbitrap Tribrid platform effectively restores accuracy. Additionally, we benchmark TMT-based activity-based proteome profiling by interrogating cysteine ligandability. The Astral measures over 30,000 cysteines in a single-shot experiment, a 54% increase relative to the Orbitrap Eclipse. We further leverage this remarkable sensitivity to profile the target engagement landscape of FDA-approved covalent drugs, including Sotorasib and Adagrasib. We herein provide a reference for the optimal use of the advanced MS platform.
    DOI:  https://doi.org/10.1016/j.mcpro.2025.100968
  17. BMC Cancer. 2025 Apr 04. 25(1): 610
    HLA class II-restricted T cell epitopes in public neoantigens of ESR1 and PIK3CA in breast cancer.
    Yukari Ando, Hiroko Miyadera, Hiroko Bando, Sachie Hashimoto, Emiko Noguchi, Hisato Hara.
       BACKGROUND: The high occurrence of treatment resistance in patients with hormone receptor-positive (HR +) breast cancer is a global health concern. Thus, effective immunotherapy must be developed. The public neoantigens, estrogen receptor 1 (ESR1) and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), shared by HR + and endocrine-resistant breast cancer, could be ideal targets for immunotherapy; however, their presentation by human leukocyte antigen class II (HLA II) and recognition by CD4 + T cells remain largely unknown.
    METHODS: Seven mutations in ESR1 and ten mutations in PIK3CA were subjected to major histocompatibility complex (MHC)-peptide binding analysis and enzyme-linked immunospot (ELISPOT) assays using peripheral blood mononuclear cells (PBMCs) from healthy donors carrying DRB4*01:03, or DRB4*01:03 and DPA1*02:02-DPB1*05:01 (DP5). DRB4*01:03- or DP5-restricted peptides were inferred from binding measurements and ELISPOT assays. Other DRB1 alleles that can also present these mutant peptides were identified using binding measurements.
    RESULTS: Positive IFN-γ responses by CD4 + T cells were detected for most peptides. The peptides that contain ESR1 (E380Q) and PIK3CA (N345K, E542K, E545K/A, E726K, H1047R/L/Y, and G1049R) are presumably restricted by DRB4*01:03, which is frequently found globally (carrier frequency: 35-63%), or by DRB4*01:03 and DRB1*04 alleles. Some PIK3CA (H1047R/L/Y) peptides can also be presented by DRB1*01:01, DRB1*09:01, DRB1*11:01, and DRB1*15:02. ESR1 (Y537S/N, D538G) peptides are potentially restricted by DP5, a frequently found allele in East Asian populations, and DRB1*01:01 and DRB1*15:01.
    CONCLUSIONS: Mutations in ESR1 and PIK3CA were recognized by CD4 + T cells from healthy donors through potential restriction by common HLA II alleles. Further studies are warranted to elucidate the landscape of HLA II presentation and validate the clinical applicability of these mutations for the immunotherapy of patients with endocrine-resistant breast cancer.
    Keywords:  Breast neoplasms; Cancer vaccines; Epitopes; Histocompatibility antigen class II; Neoantigen; T-Lymphocyte
    DOI:  https://doi.org/10.1186/s12885-025-13992-6
  18. bioRxiv. 2025 Mar 29. pii: 2025.03.26.645490. [Epub ahead of print]
    Dyr726, a brain-penetrant inhibitor of PI3Kα, Type III receptor tyrosine kinases, and WNT signaling.
    Vasudha Tandon, Alessandra Fistrovich, Joaquina Nogales, Febe Ferro, Samantha N Rokey, Carly Cabel, Amy Dunne Miller, Mary Yagel, Christina Duncan, Aditi Atmasidha, Ira Sharma, Gerrit Wilms, Karin Williams, Richard Elliott, Timothy Chavez, Yeng Shaw, Aidan McMahon, Sean Ginn, L Emilia Basantes, Nathan Bedard, Vijay Gokhale, Nathan Ellis, Alan R Prescott, Stuart J Smith, Ruman Rahman, Walter Becker, Kevin D Read, Anthony J Chalmers, Neil Carragher, Glenn R Masson, William Montfort, Curtis Thorne, Christopher Hulme, Sourav Banerjee.
      The vast majority of clinical small molecule multi-kinase inhibitors (mKI) report abject failures in targeting cancers with high stem cell contents like high-grade glioma and colorectal cancers. The FDA-approved mKIs to date ablate receptor tyrosine kinase signaling but do not target the paradoxical WNT signaling which is a key survival driver for the self-renewing cancer stem cells. The WNT pathway enhances cancer plasticity and triggers relapse of highly heterogenous tumours. Using de novo synthesis and structure-activity-relationship (SAR) studies with blood-brain-barrier (BBB) penetrant mKI scaffolds, we designed a highly potent and selective small molecule inhibitor of PI3Kα, PDGFR/KIT, and the WNT pathway denoted Dyr726. Dyr726 is superior to clinical mKIs and inhibits PI3K-AKT-mTOR and WNT-pathway signaling at multiple nodes thereby impeding proliferation, invasion, and tumour growth. Phospho-proteomic, structural, and target engagement analyses, combined with in vitro , in vivo efficacy, and pharmacokinetic studies reveal that Dyr726 is a brain-penetrant small molecule which effectively reduces tumour volume and extends survival of murine orthotopic models. Our current work establishes a first-in-class brain penetrant small molecule mKI which simultaneously antagonize the PI3K-AKT-mTOR and WNT pathways in preclinical cancer stem cell cultures, adult and pediatric primary organoids, and orthotopic murine models with positive efficacy in combination with clinical standard of care.
    DOI:  https://doi.org/10.1101/2025.03.26.645490
  19. Nat Commun. 2025 Apr 04. 16(1): 3241
    Bright and photostable yellow fluorescent proteins for extended imaging.
    Jihwan Lee, Shujuan Lai, Shuyuan Yang, Shiqun Zhao, Francisco A Blanco, Anne C Lyons, Raquel Merino-Urteaga, John F Ahrens, Nathan A Nguyen, Haixin Liu, Zhuohe Liu, Gerard G Lambert, Nathan C Shaner, Liangyi Chen, Kimberley F Tolias, Jin Zhang, Taekjip Ha, François St-Pierre.
      Fluorescent proteins are indispensable molecular tools for visualizing biological structures and processes, but their limited photostability restricts the duration of dynamic imaging experiments. Yellow fluorescent proteins (YFPs), in particular, photobleach rapidly. Here, we introduce mGold2s and mGold2t, YFPs with up to 25-fold greater photostability than mVenus and mCitrine, two commonly used YFPs, while maintaining comparable brightness. These variants were identified using a high-throughput pooled single-cell platform, simultaneously screening for high brightness and photostability. Compared with our previous benchmark, mGold, the mGold2 variants display a ~4-fold increase in photostability without sacrificing brightness. mGold2s and mGold2t extend imaging durations across diverse modalities, including widefield, total internal reflection fluorescence (TIRF), super-resolution, single-molecule, and laser-scanning confocal microscopy. When incorporated into fluorescence resonance energy transfer (FRET)-based biosensors, the proposed YFPs enable more reliable, prolonged imaging of dynamic cellular processes. Overall, the enhanced photostability of mGold2s and mGold2t enables high-sensitivity imaging of subcellular structures and cellular activity over extended periods, broadening the scope and precision of biological imaging.
    DOI:  https://doi.org/10.1038/s41467-025-58223-5
  20. bioRxiv. 2025 Mar 25. pii: 2025.03.22.644770. [Epub ahead of print]
    Lignature: A Comprehensive Database of Ligand Signatures to Predict Cell-Cell Communication.
    Ying Xin, Md Amanullah, Cheng Qian, Chingmo Zhou, Jiang Qian.
      Ligand-receptor interactions mediate intercellular communication, inducing transcriptional changes that regulate physiological and pathological processes. Ligand-induced transcriptomic signatures can be used to predict active ligands; however, the absence of a comprehensive set of ligand-response signatures has limited their practical application in predicting ligand-receptor interactions. To bridge this gap, we developed Lignature, a curated database encompassing intracellular transcriptomic signatures for 362 human ligands, significantly expanding the repertoire of ligands with available intracellular response signatures. Lignature compiles signatures from published transcriptomic datasets and established resources such as CytoSig and ImmuneDictionary, generating both gene- and pathway-based signatures for each ligand. We applied Lignature to predict active ligands driving transcriptomic changes in controlled in vitro experiments and real-world single-cell sequencing datasets. Lignature outperformed existing methods such as NicheNet, achieving higher accuracy in identifying active ligands at both the gene and pathway levels. These results establish Lignature as a robust platform for ligand signaling inference, providing a powerful tool to explore ligand-receptor interactions across diverse experimental and physiological contexts.
    DOI:  https://doi.org/10.1101/2025.03.22.644770
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