bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–04–06
28 papers selected by
Ralitsa Radostinova Madsen, MRC-PPU



  1. Cell. 2025 Mar 26. pii: S0092-8674(25)00275-2. [Epub ahead of print]
      Single-cell proteomics (SCPs) has advanced significantly, yet it remains largely unidimensional, focusing primarily on protein abundances. In this study, we employed a pulsed stable isotope labeling by amino acids in cell culture (pSILAC) approach to simultaneously analyze protein abundance and turnover in single cells (SC-pSILAC). Using a state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from ∼4,000 proteins in single HeLa cells recapitulating known biology. We performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSCs) encompassing 6 sampling times over 2 months and analyzed >1,000 cells. Protein turnover dynamics highlighted differentiation-specific co-regulation of protein complexes with core histone turnover, discriminating dividing and non-dividing cells. Lastly, correlating cell diameter with the abundance of individual proteins showed that histones and some cell-cycle proteins do not scale with cell size. The SC-pSILAC method provides a multidimensional view of protein dynamics in single-cell biology.
    Keywords:  Chip-Tip; Evosep; Orbitrap Astral; cellenONE; histone; iPSC differentiation; mass spectrometry; protein turnover; pulsed SILAC; single-cell proteomics
    DOI:  https://doi.org/10.1016/j.cell.2025.03.002
  2. PLoS Comput Biol. 2025 Apr;21(4): e1012864
      Molecular signaling networks drive a diverse range of cellular decisions, including whether to proliferate, how and when to die, and many processes in between. Such networks often connect hundreds of proteins, genes, and processes. Understanding these complex networks is aided by computational modeling, but these tools require extensive programming knowledge. In this article, we describe a user-friendly, programming-free network simulation tool called Netflux. Over the last decade, Netflux has been used to construct numerous predictive network models that have deepened our understanding of how complex biological networks make cell decisions. Here, we provide a Netflux tutorial that covers how to construct a network model and then simulate network responses to perturbations. Upon completion of this tutorial, you will be able to construct your own model in Netflux and simulate how perturbations to proteins and genes propagate through signaling and gene-regulatory networks.
    DOI:  https://doi.org/10.1371/journal.pcbi.1012864
  3. Metabolism. 2025 Mar 30. pii: S0026-0495(25)00121-0. [Epub ahead of print] 156252
       BACKGROUND: Insulin-induced lipohypertrophy (ILH) is the most frequent injection site side effect of insulin therapy. ILH consists of local adipose tissue overgrowth at the insulin injection site that eventually progresses to lipoma-like masses of a relatively large size, causing discomfort and disfiguration. Insulin injection into ILH areas delays insulin delivery, and the presence of ILH is associated with poor glycemic control and more frequent hypoglycemic events. Although, in principle, the development of ILH can be minimized by avoiding injecting insulin in the same spot, in practice, ILH remains highly prevalent. So far, no molecular mechanism for ILH has been proposed.
    METHODS: We screened a panel of PI3K inhibitors with different specificities for their capacity to reduce insulin signaling and growth of human primary adipocytes exposed to pharmacological doses of insulin. The two most effective inhibitors from the screening above were investigated in an in-vivo model of ILH.
    RESULTS: We identified PI3K inhibitors capable of reducing the hypertrophic (enlargement of lipid droplets) and hyperplastic (adipocyte differentiation) growth of primary human adipocytes exposed to pharmacological doses of insulin. Since preventing ILH development requires only a localized inhibition of PI3K activity, using a low dose of high-affinity PI3K inhibitors, we could prevent the development of ILH in a mouse model without inhibiting the systemic effects of insulin on blood glucose and without causing any apparent adverse reaction.
    CONCLUSION: We now show evidence indicating that ILH is caused by pathological PI3K activation at insulin injection sites and that ILH can be prevented by local inhibition of PI3K activity at the injection site.
    Keywords:  Insulin; Lipohypertrophy; PI3K
    DOI:  https://doi.org/10.1016/j.metabol.2025.156252
  4. Nat Methods. 2025 Mar 28.
      Despite the importance of imaging in biological and medical research, a large body of informative and precious image data never sees the light of day. To ensure scientific rigor as well as the reuse of data for scientific discovery, image data need to be made FAIR (findable, accessible, interoperable and reusable). Image data experts are working together globally to agree on common data formats, metadata, ontologies and supporting tools toward image data FAIRification. With this Perspective, we call on public funders to join these efforts to support their national scientists. What researchers most urgently need are openly accessible resources for image data storage that are operated under long-term commitments by their funders. Although existing resources in Australia, Japan and Europe are already collaborating to enable global image data sharing, these efforts will fall short unless more countries invest in operating and federating their own open data resources. This will allow us to harvest the enormous potential of existing image data, preventing substantial loss of unrealized value from past investments in imaging acquisition infrastructure.
    DOI:  https://doi.org/10.1038/s41592-024-02585-z
  5. iScience. 2025 Apr 18. 28(4): 112146
      Epidermal growth factor receptor (Egfr)-driven signaling regulates fundamental homeostatic processes. Dysregulated signaling via Egfr is implicated in numerous disease pathologies and distinct Egfr-associated disease etiologies are known to be tissue-specific. The molecular basis of this tissue-specificity remains poorly understood. Most studies of Egfr signaling to date have been performed in vitro or in tissue-specific mouse models of disease, which has limited insight into Egfr signaling patterns in healthy tissues. Here, we carried out integrated phosphoproteomic, proteomic, and transcriptomic analyses of signaling changes across various mouse tissues in response to short-term stimulation with the Egfr ligand Egf. We show how both baseline and Egf-stimulated signaling dynamics differ between tissues. Moreover, we propose how baseline phosphorylation and total protein levels may be associated with clinically relevant tissue-specific Egfr-associated phenotypes. Altogether, our analyses illustrate tissue-specific effects of Egf stimulation and highlight potential links between underlying tissue biology and Egfr signaling output.
    Keywords:  bioengineering; molecular biology; systems biology
    DOI:  https://doi.org/10.1016/j.isci.2025.112146
  6. Sci Adv. 2025 Apr 04. 11(14): eadt4955
      Skeletal muscle fibers are classified as glycolytic or oxidative, with differing susceptibilities to muscle wasting. However, the intracellular signaling pathways regulating fiber-specific muscle trophism remain unclear because of a lack of experimental models measuring protein synthesis. We developed a mouse model overexpressing a mutated transfer RNA synthetase in muscle fibers, enabling specific protein labeling using an artificial methionine substitute, which can be revealed through click chemistry. This model revealed that denervation increases protein labeling in oxidative muscle fibers through mammalian target of rapamycin complex 1 (mTORC1) activation, while deleting the mTORC1 scaffold protein Raptor reduces labeling in glycolytic fibers. On the other hand, increased muscle activity acutely decreases protein synthesis, accompanied by reduced mTORC1 signaling, glycogen depletion, and adenosine 5'-monophosphate kinase activation. Our findings identify nerve activity as an inhibitory signal for mTORC1-dependent protein synthesis in skeletal muscle, enhancing the understanding of fiber-specific responses to exercise and pathological conditions.
    DOI:  https://doi.org/10.1126/sciadv.adt4955
  7. bioRxiv. 2025 Mar 14. pii: 2025.03.11.642495. [Epub ahead of print]
      Altered MAPK signaling frequently occurs in human disease. MEK1 and MEK2 (MEK1/2) are central protein kinases in the MAPK signaling cascade that phosphorylate ERK1/2 promoting cell growth. MEK1/2 degraders offer a strategy to characterize both kinase-dependent and independent functions of MEK1/2. Here, we discovered that MEK1/2 degradation, but not kinase inhibition, caused the subsequent degradation of upstream kinase CRAF via a cell-intrinsic mechanism. MEK1/2 binding to CRAF, but not MEK1/2 catalytic activity, was required for CRAF protein stability and maturation to a functional kinase. In the absence of MEK1/2, a minor pool of newly synthesized immature CRAF that had anti-apoptotic functions remained. Finally, we showed that a stable primed CRAF-MEK1/2 signaling complex existed in cells that required RAS binding to potentiate MEK-ERK phosphorylation. Together, we've discovered a previously unrecognized kinase-independent function of MEK1/2, while contextualizing MEK1/2 as an integral component of the CRAF activation cycle beyond the conventional CRAF-MEK kinase- substrate paradigm.
    DOI:  https://doi.org/10.1101/2025.03.11.642495
  8. Nat Rev Cancer. 2025 Apr 03.
      Phosphoinositide kinases, extending beyond the well-known phosphoinositide 3-kinase (PI3K), are key players in the dynamic and site-specific phosphorylation of lipid phosphoinositides. Unlike PI3Ks, phosphatidylinositol 4-kinases (PI4Ks) and phosphatidylinositol phosphate kinases (PIPKs) do not usually exhibit mutational alterations, but mostly show altered expression in tumours, orchestrating a broad spectrum of signalling, metabolic and immune processes, all of which are crucial in the pathogenesis of cancer. Dysregulation of PI4Ks and PIPKs has been associated with various malignancies, which has sparked considerable interest towards their therapeutic targeting. In this Review we summarize the current understanding of the lesser-studied phosphoinositide kinase families, PI4K and PIPK, focusing on their functions and relevance in cancer. In addition, we provide an overview of ongoing efforts driving the preclinical and clinical development of phosphoinositide kinase-targeting molecules.
    DOI:  https://doi.org/10.1038/s41568-025-00810-1
  9. bioRxiv. 2025 Mar 14. pii: 2025.03.12.642795. [Epub ahead of print]
      After administering genome editors, their efficiency is limited by a multi-step process involving cellular uptake, trafficking, and nuclear import of the vector and its payload. These processes vary widely across cell types and differ depending on the nature and structure of the vector, whether it is a lipid nanoparticle or a different synthetic material. We developed a novel genome-wide CRISPR screening strategy to better understand these limitations within human cells to identify genes modulating cellular uptake, payload delivery, and gene editing efficiency. Our screen interrogates the cellular processes controlling genome editing by Cas-based nuclease and base editing strategies in human cells. We designed a genome-wide screen targeting 19,114 genes in HEK293 cells, and we identified six genes whose knockout increased nonviral editing efficiency in human cells by up to five-fold. Further validation through arrayed knockouts of the top hits from our screen boosted the editing efficiency from 5% to 50% when Cas9 was delivered via lipid-based nanoparticles. By designing the guides to target the screen library cassette, we could accurately track the library sgRNA identity and the editing outcome on the same amplicon via short-read sequencing, enabling the identification of rare outcomes via 'computationally' sorting edited from unedited cells within a heterogenous pool of >200M cells. In patient-derived human retinal pigment epithelium cells derived from pluripotent stem cells, BET1L, GJB2, and MS4A13 gene knockouts increased targeted genome editing by over five-fold. We anticipate that this high-throughput screening approach will facilitate the systematic engineering of novel nonviral genome editing delivery methods, where the identified novel gene hits can be further used to increase editing efficiency for other therapeutically relevant cell types.
    DOI:  https://doi.org/10.1101/2025.03.12.642795
  10. Proc Natl Acad Sci U S A. 2025 Apr 08. 122(14): e2417218122
      The phosphoinositide 3-kinase (PI3K) pathway is a major regulator of cell and organismal growth. Consequently, hyperactivation of PI3K and its downstream effector kinase, Akt, is observed in many human cancers. Pleckstrin homology domain leucine-rich repeat-containing protein phosphatases (PHLPP), two paralogous members of the metal-dependent protein phosphatase family, have been reported as negative regulators of Akt signaling and, therefore, tumor suppressors. However, the stoichiometry and identity of the bound metal ion(s), mechanism of action, and enzymatic specificity of these proteins are not known. Seeking to fill these gaps in our understanding of PHLPP biology, we unexpectedly found that PHLPP2 has no catalytic activity in vitro. Instead, we found that PHLPP2 is a pseudophosphatase with a single zinc ion bound in its catalytic center. Furthermore, we found that cancer genomics data do not support the proposed role of PHLPP1 or PHLPP2 as tumor suppressors. Phylogenetic analyses revealed an ancestral phosphatase that arose more than 1,000 Mya, but that lost activity at the base of the metazoan lineage. Surface conservation indicates that while PHLPP2 has lost catalytic activity, it may have retained substrate binding. Finally, using phylogenomics, we identify coevolving genes consistent with a scaffolding role for PHLPP2 on membranes. In summary, our results provide a molecular explanation for the inconclusive results that have hampered research on PHLPP and argue for a focus on the noncatalytic roles of PHLPP1 and PHLPP2.
    Keywords:  Akt; PHLPP; cancer; phosphatase; signaling
    DOI:  https://doi.org/10.1073/pnas.2417218122
  11. Cell Chem Biol. 2025 Mar 25. pii: S2451-9456(25)00067-4. [Epub ahead of print]
      CDK9 coordinates signaling events that regulate transcription and is implicated in oncogenic pathways, making it an actionable target for drug development. While numerous CDK9 inhibitors have been developed, success in the clinic has been limited. Targeted degradation offers a promising alternative. A comprehensive evaluation of degradation versus inhibition is needed to assess when degradation might offer superior therapeutic outcomes. We report a selective and potent CDK9 degrader with rapid kinetics, comparing its downstream effects to those of a conventional inhibitor. We validated that CDK9 inhibition triggers a compensatory feedback mechanism that dampens its anticipated effect on MYC expression and found that this was absent when degraded. Importantly, degradation is more effective at disrupting MYC transcriptional regulation and subsequently destabilizing nucleolar homeostasis, likely by abrogation of both enzymatic and scaffolding functions of CDK9. These findings suggest that CDK9 degradation offers a more robust strategy to overcome limitations associated with its inhibition.
    Keywords:  CDK9; MYC; PROTAC; cancer therapy; degradation vs. inhibition; targeted degradation; transcription
    DOI:  https://doi.org/10.1016/j.chembiol.2025.03.001
  12. bioRxiv. 2025 Mar 21. pii: 2025.02.14.638317. [Epub ahead of print]
      A high therapeutic index (TI), balancing potent oncogenic signaling inhibition in tumor cells with minimal effects on normal cells, is critical for effective cancer therapies. Recent advances have introduced diverse RAS-targeting inhibitors, including mutant-specific inhibitors (e.g., KRAS(G12C) and KRAS(G12D)), as well as paralog- and state-selective inhibitors. Non-mutant-specific RAS inhibition can be accomplished by 1) panRAS-GEF(OFF) inhibitors which inactivate RAS indirectly by inhibiting SHP2 or SOS1, thereby blocking the nucleotide exchange step of RAS activation, 2) direct KRAS(OFF)-selective inhibitors sparing NRAS and HRAS, and 3) panRAS(ON) inhibitors that directly target active RAS, by occluding binding of its effector RAF. However, the signaling inhibition index (SII) - the differential inhibition of oncogenic signaling between RAS-mutant (RAS(MUT)) and normal cells - remains poorly defined for these approaches. In this study, we evaluated the SII of state- and paralog-selective RAS inhibitors across diverse RAS-mutant (RAS(MUT)) and RAS-wild-type (RAS(WT)) models. PanRAS-GEF(OFF) inhibitors exhibited neutral or negative SII, with comparable or reduced MAPK suppression in KRAS(G12X) cells relative to RAS(WT) cells. KRAS(G13D) models showed low sensitivity (negative SII) to panRAS-GEF(OFF) inhibitors, particularly in the context of NF1 loss. Combination treatments with SHP2 and MEK inhibitors resulted in low SII, as pathway suppression was similar in RAS(MUT) and RAS(WT) cells. Furthermore, RAS(Q61X) models were resistant to combined SHP2 inhibitor+MEK inhibitor due to dual mechanisms: MEK inhibitor-induced NRAS(Q61X) reactivation and RAS(MUT)-induced SHP2 conformations impairing inhibitor binding. Overall, panRAS-GEF(OFF) inhibitors exhibited the lowest SII. PanKRAS(OFF) inhibitors demonstrated a higher SII, while panRAS(ON) inhibitors displayed broader activity but relatively narrow SII. We observed that tumors that were sensitive to RAS(MUT)-specific inhibitors, were also sensitive to the state-selective RAS inhibitors (OFF, or ON). In fact, all RAS inhibitors (mutant-specific and state- or paralog-selective) were active in the same portion of RAS(MUT) models, while the majority of RAS(MUT) cell lines were insensitive to all of them. These findings reveal significant SII variability among RAS-targeted inhibitors, depending on the specific RAS driver mutation and cell context and underscore the importance of incorporating SII considerations into the design and clinical application of RAS-targeted therapies to improve therapeutic outcomes.
    Main points: PanRAS-GEF(OFF) inhibitors have limited SII and effectiveness: The Signaling Inhibition Index (SII) - i.e. the differential inhibition of oncogenic signaling between tumor and normal cells - was neutral or negative for panRAS-GEF(OFF) inhibitors, with comparable or reduced MAPK suppression in KRAS(G12X) mutant versus RAS(WT) cells. KRAS(G13D) models showed reduced sensitivity, particularly with NF1 loss. SHP2+MEK inhibitor combinations also had low SII, with RAS(Q61X) models demonstrating resistance due to NRAS(Q61X) reactivation and impaired SHP2 inhibitor binding.PanKRAS(OFF) selective inhibitors have higher SII than panRAS-GEF(OFF) inhibitors: panKRAS(OFF)-selective inhibitors have a higher SII compared to panRAS-GEF(OFF) inhibitors, offering better tumor-versus-normal cell selectivity.PanRAS(ON) inhibitors have broad but modest SII: While panRAS(ON) inhibitors displayed a broader activity profile, their ability to selectively inhibit mutant RAS signaling over normal cells remained relatively narrow (low SII).Most KRAS-mutant tumors will be insensitive to any single RAS-targeted inhibitor: State- and paralog-selective inhibitors have enhanced activity in the same RAS-MUT cancer models that are also sensitive to RAS-MUT-specific inhibitors, suggesting that most KRAS-MUT tumors will not respond uniformly to any one RAS-targeting inhibitor.SII varies across RAS inhibitors, necessitating tailored therapeutic strategies: The effectiveness of paralog- and state-selective inhibitors depends on specific RAS mutations and cell context, highlighting the need to integrate SII considerations into the development and clinical application of RAS-targeted therapies.
    DOI:  https://doi.org/10.1101/2025.02.14.638317
  13. bioRxiv. 2025 Mar 17. pii: 2025.03.16.643448. [Epub ahead of print]
      Manipulating the signaling environment is an effective approach to alter cellular states for broad-ranging applications, from engineering tissues to treating diseases. Such manipulation requires knowing the signaling states and histories of the cells in situ , for which high-throughput discovery methods are lacking. Here, we present an integrated experimental-computational framework that learns signaling response signatures from a high-throughput in vitro perturbation atlas and infers combinatorial signaling activities in in vivo cell types with high accuracy and temporal resolution. Specifically, we generated signaling perturbation atlas across diverse cell types/states through multiplexed sequential combinatorial screens on human pluripotent stem cells. Using the atlas to train IRIS, a neural network-based model, and predicting on mouse embryo scRNAseq atlas, we discovered global features of combinatorial signaling code usage over time, identified biologically meaningful heterogeneity of signaling states within each cell type, and reconstructed signaling histories along diverse cell lineages. We further demonstrated that IRIS greatly accelerates the optimization of stem cell differentiation protocols by drastically reducing the combinatorial space that needs to be tested. This framework leads to the revelation that different cell types share robust signal response signatures, and provides a scalable solution for mapping complex signaling interactions in vivo to guide targeted interventions.
    DOI:  https://doi.org/10.1101/2025.03.16.643448
  14. bioRxiv. 2025 Mar 15. pii: 2025.03.13.643146. [Epub ahead of print]
      Resolving the intricate structure of the cellular state landscape from single-cell RNA sequencing (scRNAseq) experiments remains an outstanding challenge, compounded by technical noise and systematic discrepancies-often referred to as batch effects-across experimental systems and replicate. To address this, we introduce CONCORD (COntrastive learNing for Cross-dOmain Reconciliation and Discovery), a self-supervised contrastive learning framework designed for robust dimensionality reduction and data integration in single-cell analysis. The core innovation of CONCORD lies in its probabilistic, dataset- and neighborhood-aware sampling strategy, which enhances contrastive learning by simultaneously improving the resolution of cell states and mitigating batch artifacts. Operated in a fully unsupervised manner, CONCORD generates denoised cell encodings that faithfully preserve key biological structures, from fine-grained distinctions among closely related cell states to large-scale topological organizations. The resulting high-resolution cell atlas seamlessly integrates data across experimental batches, technologies, and species. Additionally, CONCORD's latent space capture biologically meaningful gene programs, enabling the exploration of regulatory mechanisms underlying cell state transitions and subpopulation heterogeneity. We demonstrate the utility of CONCORD on a range of topological structures and biological contexts, underscoring its potential to extract meaningful insights from both existing and future single-cell datasets.
    DOI:  https://doi.org/10.1101/2025.03.13.643146
  15. bioRxiv. 2025 Mar 10. pii: 2025.03.08.642174. [Epub ahead of print]
      Pericytes stabilize the microvasculature by enhancing endothelial barrier integrity, resulting in functional networks. During retinal development, pericyte recruitment is crucial for stabilizing nascent angiogenic vasculature. However, in adulthood, disrupted endothelial-pericyte interactions lead to vascular dropout and pathological angiogenesis in ocular microvascular diseases, and strategies to stabilize the retinal vasculature are lacking. We demonstrate that direct endothelial-pericyte contact downregulates pVEGFR2 in endothelial cells, which enhances pericyte migration and promotes endothelial cell barrier function. Intravitreal injection of a VEGFR2 inhibitor in mouse models of the developing retina and oxygen-induced retinopathy increased pericyte recruitment and aided vascular stability. The VEGFR2 inhibitor further rescued ischemic retinopathy by enhancing vascularization and tissue growth while reducing vascular permeability. Our findings offer a druggable target to support the growth of functional and mature microvasculature in ocular microvascular diseases and tissue regeneration overall.
    DOI:  https://doi.org/10.1101/2025.03.08.642174
  16. bioRxiv. 2025 Mar 19. pii: 2025.03.18.643983. [Epub ahead of print]
      Breast cancer progression is marked by extracellular matrix (ECM) remodeling, including increased stiffness, faster stress relaxation, and elevated collagen levels. In vitro experiments have revealed a role for each of these factors to individually promote malignant behavior, but their combined effects remain unclear. To address this, we developed alginate-collagen hydrogels with independently tunable stiffness, stress relaxation, and collagen density. We show that these combined tumor-mimicking ECM cues reinforced invasive morphologies and promoted spheroid invasion in breast cancer and mammary epithelial cells. High stiffness and low collagen density in slow-relaxing matrices led to the greatest cell migration speed and displacement. RNA-seq revealed Sp1 target gene enrichment in response to both individual and combined ECM cues, with a greater enrichment observed under multiple cues. Notably, high expression of Sp1 target genes upregulated by fast stress relaxation correlated with poor patient survival. Mechanistically, we found that phosphorylated-Sp1 (T453) was increasingly located in the nucleus in stiff and/or fast relaxing matrices, which was regulated by PI3K and ERK1/2 signaling, as well as actomyosin contractility. This study emphasizes how multiple ECM cues in complex microenvironments reinforce malignant traits and supports an emerging role for Sp1 as a mechanoresponsive transcription factor.
    DOI:  https://doi.org/10.1101/2025.03.18.643983
  17. Nat Genet. 2025 Apr 01.
      The spatial organization of cells in tissues underlies biological function, and recent advances in spatial profiling technologies have enhanced our ability to analyze such arrangements to study biological processes and disease progression. We propose MESA (multiomics and ecological spatial analysis), a framework drawing inspiration from ecological concepts to delineate functional and spatial shifts across tissue states. MESA introduces metrics to systematically quantify spatial diversity and identify hot spots, linking spatial patterns to phenotypic outcomes, including disease progression. Furthermore, MESA integrates spatial and single-cell multiomics data to facilitate an in-depth, molecular understanding of cellular neighborhoods and their spatial interactions within tissue microenvironments. Applying MESA to diverse datasets demonstrates additional insights it brings over prior methods, including newly identified spatial structures and key cell populations linked to disease states. Available as a Python package, MESA offers a versatile framework for quantitative decoding of tissue architectures in spatial omics across health and disease.
    DOI:  https://doi.org/10.1038/s41588-025-02119-z
  18. Biochem Biophys Res Commun. 2025 Mar 25. pii: S0006-291X(25)00417-6. [Epub ahead of print]759 151703
      PIK3CA encodes the catalytic subunit of phosphoinositide 3-kinase (PI3K) enzyme and is the most commonly mutated oncogene in head and neck squamous cell carcinoma (HNSCC). This study aimed to identify potential therapeutic targets in HNSCC harboring mutant PIK3CA. We used CRISPR interference (CRISPRi)-based genome-wide screening methodology to reveal targetable genetic dependencies in PIK3CA-mutated HNSCC. Screening was conducted in an HPV-positive HNSCC cell line, UM-SCC-47, engineered to express the canonical E545K PIK3CA mutant. We identified 34 genes co-dependent on PIK3CA E545K mutation, including 5 genes in the neddylation pathway (NEDD8, NEDD8-MDP-1 and NAE1, USP8, UBA3). Validation experiments confirmed the essential role of NEDD8, NEDD8-MDP-1, and NAE1, indicating a novel regulatory mechanism in PIK3CA E545K-mutated HNSCC. Our findings suggest that PIK3CA mutation may serve as a predictive biomarker for neddylation inhibitor therapy in a subpopulation of HNSCC.
    Keywords:  CRISPR screen; Head and neck cancer; Neddylation; PIK3CA mutation
    DOI:  https://doi.org/10.1016/j.bbrc.2025.151703
  19. Biochim Biophys Acta Rev Cancer. 2025 Mar 31. pii: S0304-419X(25)00049-6. [Epub ahead of print]1880(3): 189307
      Cellular pliancy refers to the unique disposition of different stages of cellular differentiation to transform when exposed to specific oncogenic insults. This concept highlights a strong interconnection between cellular identity and tumorigenesis, and implies overcoming of epigenetic barriers defining cellular states. Emerging evidence suggests that the cell-type-specific response to intrinsic and extrinsic stresses is modulated by accessibility to certain areas of the genome. Understanding the interplay between epigenetic mechanisms, cellular differentiation, and oncogenic insults is crucial for deciphering the complex nature of tumorigenesis and developing targeted therapies. Hence, cellular pliancy relies on a dynamic cooperation between the cellular identity and the cellular context through epigenetic control, including the reactivation of cellular mechanisms, such as epithelial-to-mesenchymal transition (EMT). Such mechanisms and pathways confer plasticity to the cell allowing it to adapt to a hostile environment in a context of tumor initiation, thus changing its cellular identity. Indeed, growing evidence suggests that cancer is a disease of cell identity crisis, whereby differentiated cells lose their defined identity and gain progenitor characteristics. The loss of cell fate commitment is a central feature of tumorigenesis and appears to be a prerequisite for neoplastic transformation. In this context, EMT-inducing transcription factors (EMT-TFs) cooperate with mitogenic oncoproteins to foster malignant transformation. The aberrant activation of EMT-TFs plays an active role in tumor initiation by alleviating key oncosuppressive mechanisms and by endowing cancer cells with stem cell-like properties, including the ability to self-renew, thus changing the course of tumorigenesis. This highly dynamic phenotypic change occurs concomitantly to major epigenome reorganization, a key component of cell differentiation and cancer cell plasticity regulation. The concept of pliancy was initially proposed to address a fundamental question in cancer biology: why are some cells more likely to become cancerous in response to specific oncogenic events at particular developmental stages? We propose the concept of epipliancy, whereby a difference in epigenetic configuration leads to malignant transformation following an oncogenic insult. Here, we present recent studies furthering our understanding of how the epigenetic landscape may impact the modulation of cellular pliancy during early stages of cancer initiation.
    Keywords:  Cell identity; Epigenetic changes; Pliancy; Tumor initiation
    DOI:  https://doi.org/10.1016/j.bbcan.2025.189307
  20. Nat Cell Biol. 2025 Apr 01.
      Cell motility and adhesion are fundamental components for diverse physiological functions, including embryonic development, immune responses and tissue repair. Dysregulation of these processes can lead to a range of diseases, including cancer. Cell motility and adhesion are complex and often require regulation by an intricate network of signalling pathways, with phosphatidylinositol phosphates (PIPs) having a central role. PIPs are derived from phosphatidylinositol phosphorylation and are instrumental in mediating membrane dynamics, intracellular trafficking, cytoskeletal organization and signal transduction, all of which are crucial for cellular responses to environmental stimuli. Here we discuss the mechanisms through which PIPs modulate cell motility and adhesion by examining their roles at focal adhesions, within the cytoskeleton, at protein scaffolds and in the nucleus. By providing a comprehensive overview of PIP signalling, this Review underscores their significance in maintaining cellular homeostasis and highlights their potential as therapeutic targets in diseases characterized by aberrant cell motility and adhesion.
    DOI:  https://doi.org/10.1038/s41556-025-01647-4
  21. Nat Commun. 2025 Mar 29. 16(1): 3069
      Serine-threonine phosphatases have been challenging to study because of the lack of specific inhibitors. Their catalytic domains are druggable, but these are shared or very similar between individual phosphatase complexes, precluding their specific inhibition. Instead, phosphatase complexes often achieve specificity by interacting with short linear motifs (SLiMs) in substrates or their binding partners. We develop here a chemical-genetic system to rapidly inhibit these interactions within the PP2A-B56 family. Drug-inducible recruitment of ectopic SLiMs ("directSLiMs") is used to rapidly block the SLiM-binding pocket on the B56 regulatory subunit, thereby displacing endogenous interactors and inhibiting PP2A-B56 activity within seconds. We use this system to characterise PP2A-B56 substrates during mitosis and to identify a role for PP2A-B56 in allowing metaphase kinetochores to properly sense tension and maintain microtubule attachments. The directSLiMs approach can be used to inhibit any other phosphatase, enzyme or protein that uses a critical SLiM-binding interface, providing a powerful strategy to inhibit and characterise proteins once considered "undruggable".
    DOI:  https://doi.org/10.1038/s41467-025-58185-8
  22. Nucleic Acids Res. 2025 Mar 20. pii: gkaf235. [Epub ahead of print]53(6):
      For genome editing, the use of CRISPR ribonucleoprotein (RNP) complexes is well established and often the superior choice over plasmid-based or viral strategies. RNPs containing dCas9 fusion proteins, which enable the targeted manipulation of transcriptomes and epigenomes, remain significantly less accessible. Here, we describe the production, delivery, and optimization of second generation CRISPRa RNPs (dRNPs). We characterize the transcriptional and cellular consequences of dRNP treatments in a variety of human target cells and show that the uptake is very efficient. The targeted activation of genes demonstrates remarkable potency, even for genes that are strongly silenced, such as developmental master transcription factors. In contrast to DNA-based CRISPRa strategies, gene activation is immediate and characterized by a sharp temporal precision. We also show that dRNPs allow very high-target multiplexing, enabling undiminished gene activation of multiple genes simultaneously. Applying these insights, we find that intensive target multiplexing at single promoters synergistically elevates gene transcription. Finally, we demonstrate in human stem and differentiated cells that the preferable features of dRNPs allow to instruct and convert cell fates efficiently without the need for DNA delivery or viral vectors.
    DOI:  https://doi.org/10.1093/nar/gkaf235
  23. Cardiovasc Res. 2025 Apr 02. pii: cvaf055. [Epub ahead of print]
       AIMS: Progressive deposition of cholesterol in the arterial wall characterizes atherosclerosis, which underpins most cases of myocardial infarction and stroke. Insulin-like growth factor-1 (IGF-1) is a hormone that regulates systemic growth and metabolism and possesses anti-atherosclerotic properties. We asked whether endothelial-restricted augmentation of IGF-1 signaling is sufficient to suppress atherogenesis.
    METHODS AND RESULTS: We generated mice with endothelial-restricted over-expression of human wildtype IGF-1R (hIGFREO/ApoE-/-) or a signaling defective K1003R mutant human IGF-1R (mIGFREO/ApoE-/-) and compared them to their respective ApoE-/- littermates. hIGFREO/ApoE-/- had less atherosclerosis, circulating leukocytes, arterial cholesterol uptake, and vascular leakage in multiple organs, whereas mIGFREO/ApoE-/- did not exhibit these phenomena. Overexpressing wildtype IGF-1R in human umbilical vein endothelial cells (HUVEC) altered the localization of tight junction proteins and reduced paracellular leakage across their monolayers, whilst overexpression of K1003R IGF-1R did not have these effects. Moreover, only overexpression of wildtype IGF-1R reduced HUVEC internalization of cholesterol-rich low density lipoprotein particles and increased their association of these particles with clathrin, but not caveolin-1, implicating it in vesicular uptake of lipoproteins. Endothelial overexpression of wildtype versus K1003R IGF-1R also reduced expression of YAP/TAZ target genes and nuclear localization of TAZ, which may be relevant to its impact on vascular barrier and atherogenesis.
    CONCLUSIONS: Endothelial IGF-1 signaling modulates both para- and trans-cellular vascular barrier function. Beyond reducing atherosclerosis, this could have relevance to many diseases associated with abnormal vascular permeability.
    DOI:  https://doi.org/10.1093/cvr/cvaf055
  24. Bioinform Adv. 2025 ;5(1): vbaf044
       Summary: Modern biological research critically depends on public databases. The introduction and propagation of errors within and across databases can lead to wasted resources as scientists are led astray by bad data or have to conduct expensive validation experiments. The emergence of generative artificial intelligence systems threatens to compound this problem owing to the ease with which massive volumes of synthetic data can be generated. We provide an overview of several key issues that occur within the biological data ecosystem and make several recommendations aimed at reducing data errors and their propagation. We specifically highlight the critical importance of improved educational programs aimed at biologists and life scientists that emphasize best practices in data engineering. We also argue for increased theoretical and empirical research on data provenance, error propagation, and on understanding the impact of errors on analytic pipelines. Furthermore, we recommend enhanced funding for the stewardship and maintenance of public biological databases.
    Availability and implementation: Not applicable.
    DOI:  https://doi.org/10.1093/bioadv/vbaf044
  25. Life Sci Alliance. 2025 Jun;pii: e202403067. [Epub ahead of print]8(6):
      The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research. However, current approaches to cell cycle profiling involve complex interventions that may confound experimental interpretation. We developed CellCycleNet, a machine learning (ML) workflow, to simplify cell cycle staging from fluorescent microscopy data with minimal experimenter intervention and cost. CellCycleNet accurately predicts cell cycle phase using only a fluorescent nuclear stain (DAPI) in fixed interphase cells. Using the Fucci2a cell cycle reporter system as ground truth, we collected two benchmarking image datasets and trained 2D and 3D ML models-of support vector machine and deep neural network architecture-to classify nuclei in the G1 or S/G2 phases. Our results show that 3D CellCycleNet outperforms support vector machine models on each dataset. When trained on two image datasets simultaneously, CellCycleNet achieves the highest classification accuracy (AUROC of 0.94-0.95). Overall, we found that using 3D features, rather than 2D features alone, significantly improves classification performance for all model architectures. We released our image data, models, and software as a community resource.
    DOI:  https://doi.org/10.26508/lsa.202403067
  26. Yale J Biol Med. 2025 Mar;98(1): 69-75
      
    Keywords:  PI3 kinase; clinical investigation; kinase signaling; mutant-selective; targeted therapies
    DOI:  https://doi.org/10.59249/BTHB2229
  27. Methods Mol Biol. 2025 ;2905 163-169
      This chapter describes protein kinase (will be termed here kinase) activity estimation methods and their application to clinical cancer phosphoproteomics datasets, proposing a novel approach for identification of protein kinases as therapeutic targets. Despite significant advances in genomics-based target identification, clinical proteomics and phosphoproteomics remain underutilized. We highlight the growing availability of proteomics data from projects like Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Proteomics Identifications Database (PRIDE), and review key kinase activity estimation algorithms, including PTM-SEA, KSEA, Rokai, KStar, and Kinome Atlas. Applying these methods on clinical phosphoproteomic data, we demonstrate the identification of hyperactivated kinases in specific cancer indications and highlight HER2 and EGFR as benchmarks. Our description underscores the potential of integrating kinase activity estimation with clinical phosphoproteomics to uncover new therapeutic targets and develop precision oncology therapies.
    Keywords:  Kinase; Mass spectrometry; Phosphoproteomics; Proteomics; Target
    DOI:  https://doi.org/10.1007/978-1-0716-4418-8_10