bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2026–08–30
fourteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Atypical PI3Ks coordinate chemotaxis, signaling dynamics, and multicellular development in Dictyostelium.
  2. Next-generation multiplexed targeted proteomics quantifies post-translational modifications in disease and compound-protein interactions with high throughput.
  3. Inferring feedback regulation from static snapshots of a single signal.
  4. Proliferation and differentiation in intestinal organoids are balanced by ligand-modulated EGFR trafficking.
  5. PROFET predicts continuous gene expression dynamics from scRNA-seq data to elucidate heterogeneity of cancer treatment responses.
  6. Combinatorial group testing for efficient scaling across biological applications.
  7. Dynamic Landscape Analysis of cell fate decisions provides predictive models of neural development from single-cell data.
  8. PTEN regulates microtubule polymerization via mTORC2, but not mTORC1, in peripheral sensory neurons.
  9. Senescent cells maintain viability through adhesion-dependent fragmentation that promotes debris deposition.
  10. GAMclust: identification of regulated metabolic modules in bulk, single cell and spatial gene expression data.
  11. Insulin-like growth factor-binding protein 7 is a soluble cell adhesion molecule.
  12. Single-cell and in vivo profiling reveal heterogeneous and organ-specific CRISPR-Cas9 off-target and translocation outcomes.
  13. Induced pluripotent stem cells from discovery to translation.
  14. Ultrafast and reference-free sequence discovery in single-cell data.
  1. J Cell Sci. 2026 Aug 27. pii: jcs.265041. [Epub ahead of print]
    Atypical PI3Ks coordinate chemotaxis, signaling dynamics, and multicellular development in Dictyostelium.
    Laith Bahlouli, Erik Zhang, Eric Jung, Taylor Brentjens, Elizabeth Rose, Harrison Drebin, Ben Edwards, Isabella Wischik, Alyssa Huynh, Will Callahan, Jacqueline Shen, Susanna Li, Kevin Zhangxu, Marc Edwards.
      Phosphoinositide 3-kinase (PI3K) signaling regulates protrusion, polarity, membrane uptake, and multicellular development in Dictyostelium discoideum, but these functions have been interpreted largely through canonical Class I PI3Ks and PI(3,4,5)P₃ production. This framework does not fully explain how PI3K-dependent pathways restrain Ras activity, organize relay signaling, or coordinate the transition from single-cell migration to multicellular aggregation. Here, we show that three atypical PI3K-family enzymes, PikF, PikG, and PikH, define genetically separable functions within this broader PI3K signaling network. PikF attenuates Ras-phosphoinositide-actin signaling, limiting protrusive activity so that chemotactic responses remain spatially and temporally constrained. PikG is required for aggregation and supports ACA-dependent cAMP relay, coupling cellular polarity to the collective signaling needed for streaming and multicellular development. PikH separates uptake from these chemotactic and developmental functions by supporting efficient phagocytosis with little effect on acute cAMP-stimulated signaling. Together, these findings expand the Dictyostelium PI3K framework beyond a Class I PI(3,4,5)P₃-centered pathway and identify atypical PI3Ks as specialized regulators of signal attenuation, cAMP relay organization, and membrane uptake.
    Keywords:  Cell migration; Chemotaxis; Dictyostelium; PI3K; Signaling
    DOI:  https://doi.org/10.1242/jcs.265041
  2. Nat Commun. 2026 08 25. pii: 9048. [Epub ahead of print]17(1):
    Next-generation multiplexed targeted proteomics quantifies post-translational modifications in disease and compound-protein interactions with high throughput.
    Steven R Shuken, Geordon A Frere, Charlotte R Beard, Christopher D McGann, Jesse D Canterbury, Nathan R Zuniga, Brandon M Gassaway, Shane L Dawson, Kean Hean Ooi, João A Paulo, M Windy McNerney, Steven P Gygi, Qing Yu.
      The GoDig platform enables sensitive, multiplexed targeted pathway proteomics without manual scheduling or synthetic standards. Here we present GoDig 2.0, which increases sample multiplexing to 35-fold, improves time efficiency and reduces scan delays for higher success rates, and allows flexible spectral and elution library generation from different mass spectrometry data types. GoDig 2.0 measures 2.4× more targets than GoDig 1.0, quantifying >99% of 800 peptides in a single run. We compile a library of 23,989 human phosphorylation sites from a phosphoproteomic dataset and use it to profile kinase signaling differences across cell lines. In human brain tissue, we establish a hyperphosphorylated tau assay including pTau127, revealing potential biomarkers for Alzheimer's disease. We also quantify diglycyl-lysine peptides to assess polyubiquitin branching. Finally, we build a library of 20,946 reactive cysteines and profile covalent compound-protein interactions spanning diverse pathways. GoDig 2.0 enables high-throughput analyses of site-specific protein modifications across many biological contexts.
    DOI:  https://doi.org/10.1038/s41467-026-76929-y
  3. Biochem Biophys Rep. 2026 Sep;47 102747
    Inferring feedback regulation from static snapshots of a single signal.
    Miriam Ginzberg, Ceryl Tan, Nish Patel, Ran Kafri.
      Direct measurement of feedback regulation remains difficult because it usually relies on pathway perturbations and prior knowledge of circuit topology. We introduce AoF (Assay of Feedback), a single-cell imaging framework that combines fixed-cell measurements of a target (together with DNA and Geminin as cell-cycle ordering markers) with ergodic rate analysis to reconstruct target dynamics in steady-state proliferating populations and quantify how a target's inferred rate of change depends on its own level. AoF therefore estimates feedback sign, magnitude, and state dependence from snapshot data without resolving surrounding circuitry. As a proof of concept, we applied AoF to map Akt phosphorylation across the cell cycle, unmasking a highly localized negative feedback loop restricted to the G1/S transition. Biochemical experiments point to an mTORC1/S6K1-dependent inhibitory phosphorylation of IRS1, which would stabilize Akt activation during early S phase, as the likeliest source of this snapshot-derived signature, but they do not establish that edge uniquely. AoF provides a rapid, scalable, and perturbation-free methodology to map context-specific feedback control.
    Keywords:  Akt; Cell cycle; Ergodic rate analysis; Rapamycin; Single-cell imaging; mTORC1
    DOI:  https://doi.org/10.1016/j.bbrep.2026.102747
  4. Life Sci Alliance. 2026 Nov;pii: e202603733. [Epub ahead of print]9(11):
    Proliferation and differentiation in intestinal organoids are balanced by ligand-modulated EGFR trafficking.
    Mario O Caracci, Sabrina Seidler, Luis M Muñoz-Nava, Birga Soetje, Kirsten Michel, Philippe Ih Bastiaens.
      Epidermal growth factor (EGF) signaling is associated with proliferation and tumorigenesis. Conversely, EGF-family ligands can also trigger a differentiation program, an effect attributed to ligand affinity and EGF receptor (EGFR) activity. Most of these observations have been made in immortalized cell culture experiments, whereas the mechanisms underlying EGF/EGFR-driven proliferation-differentiation dynamics in complex development and tissue self-renewal have not been addressed. We show that culturing mouse small intestinal organoids (mSIOs) without EGF enhanced EGFR expression and basal phosphorylation while maintaining a balanced development of proliferative crypts and differentiated villi. Addition of EGF or Epiregulin (EREG) triggered receptor endocytosis, reducing cell-surface levels and expression. While EGF promoted crypt proliferation, EREG promoted both proliferation and villus differentiation compared with untreated controls. Removal or re-introduction of EGF or EREG proved sufficient to induce development comparable to the constant presence of ligands over 96 h. Sub-saturating concentrations of EGF led to increased villus differentiation, resembling EREG treatments, suggesting that control over EGFR endocytic cycle regulates its plasma membrane localization shaping the balance of proliferation and differentiation in mSIOs.
    DOI:  https://doi.org/10.26508/lsa.202603733
  5. Cell Syst. 2026 Aug 28. pii: S2405-4712(26)00192-4. [Epub ahead of print] 101710
    PROFET predicts continuous gene expression dynamics from scRNA-seq data to elucidate heterogeneity of cancer treatment responses.
    Yu-Chen Cheng, Hyemin Gu, Thomas O McDonald, Wenbo Wu, Shubham Tripathi, Cristina Guarducci, Douglas Russo, Daniel L Abravanel, Madeline Bailey, Yue Wang, Yun Zhang, Yannis Pantazis, Herbert Levine, Rinath Jeselsohn, Markos A Katsoulakis, Franziska Michor.
      Single-cell RNA sequencing (scRNA-seq) profiles cellular heterogeneity but captures only static snapshots, limiting inference of gene expression dynamics. We developed PROFET (particle-based reconstruction of generative force-matched expression trajectories), a framework that reconstructs continuous, nonlinear single-cell trajectories from sparsely sampled scRNA-seq time series. PROFET combines a particle-based gradient-flow algorithm with simulation-free force matching to accurately infer cellular dynamics. Across mouse and human in vitro datasets and an in vivo axolotl regeneration dataset, PROFET achieved 2.6-12.5× lower prediction error than ten state-of-the-art trajectory inference methods. Applying PROFET to newly generated scRNA-seq data from a palbociclib-treated MCF7 cell line and three published breast cancer patient datasets, we reconstructed treatment-response trajectories and identified a resistant cell subpopulation exhibiting large phenotypic shifts and enrichment of the surface markers UNC5B, TLR3, PCDH19, PROCR, SLITRK6, and SEMA6B. PROFET provides a biologically grounded framework for reconstructing cell-state dynamics from static single-cell data across development, regeneration, and therapeutic response. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  CDK4/6 inhibitor response; breast cancer resistance; cell-state transitions; force matching; gene expression dynamics; gradient-flow modeling; phenotypic heterogeneity; single-cell RNA sequencing; trajectory inference
    DOI:  https://doi.org/10.1016/j.cels.2026.101710
  6. Nat Commun. 2026 Aug 25. pii: 9146. [Epub ahead of print]17(1):
    Combinatorial group testing for efficient scaling across biological applications.
    Lorenzo Talamanca, Julian Trouillon.
      Combinatorial group testing can reduce experimental costs and turnaround time by strategically pooling samples to minimize the number of measurements needed for a given experiment. Despite broad potential utility, it remains underutilized due to its intrinsic complexity and the lack of implementation tools. Here we present PoolPy, a unified end-to-end framework and web platform to benchmark, automate, and decode combinatorial group testing strategies. PoolPy tailors pooling designs to application-specific constraints, such as time, cost, or signal dilution, across experiment types. By implementing ten different pooling algorithms, which we comprehensively benchmark in silico across >100,000 conditions, we identify key design trade-offs that define pooling applicability to specific use cases. We experimentally validate PoolPy across diverse applications, including protein-ligand interaction screening, RT-qPCR viral testing and genome-wide protein-DNA interaction profiling, achieving a 60 to 93% reduction in number of measurements needed. Overall, PoolPy provides a scalable, user-friendly ecosystem to increase throughput and reduce costs across biological applications. PoolPy is available at https://poolpy.trouillonlab.org  for open use.
    DOI:  https://doi.org/10.1038/s41467-026-77055-5
  7. PLoS Biol. 2026 Aug 26. 24(8): e3003953
    Dynamic Landscape Analysis of cell fate decisions provides predictive models of neural development from single-cell data.
    Marine Fontaine, M Joaquina Delás, Meritxell Sáez, Rory J Maizels, Elizabeth Finnie, James Briscoe, David A Rand.
      Building a mechanistic understanding of cell fate decisions remains a fundamental goal of developmental biology, with implications for stem cell therapies, regenerative medicine and understanding disease mechanisms. Single-cell transcriptomics provides a detailed picture of the cellular states observed during these decisions, but building dynamic and predictive models from these data remains a challenge. Here, we present dynamic landscape analysis (DLA), an integrative framework that applies dynamical systems theory to identify stable cell states, map transition pathways, and generate a predictive cell fate decision landscape from single-cell data. Applying this framework to vertebrate neural tube development revealed that progenitor specification by Sonic Hedgehog (Shh) can be captured in a landscape with an unexpected topology in which initially divergent lineages converge to the same fate through multiple distinct routes. The model accurately predicted cellular responses and cell fate allocation for unseen dynamic signalling regimes. Cross-species validation using human embryonic organoid data demonstrated conservation of this decision-making architecture. By modelling the dynamic responses that drive cell fate decisions, the DLA framework provides a quantitative and generative framework for extracting mechanistic insights from high-dimensional single-cell data.
    DOI:  https://doi.org/10.1371/journal.pbio.3003953
  8. eNeuro. 2026 Aug 25. pii: ENEURO.0116-26.2026. [Epub ahead of print]
    PTEN regulates microtubule polymerization via mTORC2, but not mTORC1, in peripheral sensory neurons.
    Simone Evans, Julia Reglewski, Haley Rose, Cara Lewis, Anika Nayak, Cole Minsky, Evan McNeil, Brizha Knowles, Wei Wang, Meijie Li, Bryan W Luikart, Jennifer Hong.
      Peripheral neuropathy affects over 18 million adults in the U.S. (Hicks et al 2021), but therapeutic outcomes are poor due to a lack of regenerative treatments. Development of novel, disease-modifying therapies is hindered by poor understanding of the mechanisms promoting axonal regeneration in peripheral neurons. Pten is a strong negative regulator of cell growth, and Pten-KO drives axonal regeneration in various neuronal subtypes potentially via downstream regulation of stability of the microtubule (MT) cytoskeleton, a vital component of axonal growth. While Pten-KO accelerates MT polymerization rates in the axonal growth cone, it remains unknown whether this action is dependent on mTORC1 or mTORC2 signaling, and whether regeneration under Pten-KO is dependent on MT activation. Here, we perform in vitro codeletions of either Raptor (mTORC1) or Rictor (mTORC2) alongside Pten-KO in mouse peripheral sensory neuron cultures of either sex to isolate the effects of each pathway on the MT cytoskeleton. We use Pten-KO to increase MT polymerization and neuronal outgrowth, and then show that suppression of mTORC2, but not mTORC1, is sufficient to reduce the accelerated MT polymerization and neuronal hypertrophy to wild-type levels. These results are specific to the axonal growth cone, and MT dynamics in the proximal axon shaft are not impacted by Pten-KO, mTORC1 suppression, or mTORC2 suppression. Our results help elucidate the mechanism by which Pten regulates the MT cytoskeleton and axonal outgrowth in peripheral sensory neurons, localize where this occurs in the axon, and highlight the MT cytoskeleton as a potential molecular target for regenerative therapies.Significance statement Pten-KO promotes neuron growth, but Pten has several downstream effectors, and it is unclear which effectors drive axonal regeneration. One of these downstream targets is the microtubule cytoskeleton, which is vital for normal axonal growth and development. We demonstrate that Pten-KO increases MT polymerization rates in the growth cone, but not proximal shaft, in axons of peripheral sensory neurons. This effect is reversed by co-deletion of mTORC2, but not mTORC1, and the loss of mTORC2 primarily inhibits elongation of the distal axon, suggesting that the regulation of MT polymerization is specific to the growth cone. These results highlight MT dynamics in the axonal growth cone as a vital component of peripheral neuron regeneration and a potential therapeutic target.
    DOI:  https://doi.org/10.1523/ENEURO.0116-26.2026
  9. Dev Cell. 2026 Aug 28. pii: S1534-5807(26)00290-X. [Epub ahead of print]
    Senescent cells maintain viability through adhesion-dependent fragmentation that promotes debris deposition.
    Matej Durik, Mona Karout, Daniel Sampaio Gonçalves, Tania Knauer-Meyer, Coralie Spiegelhalter, Nadia Messaddeq, Marco Seehawer, Pauline Stephan, Dmitry V Bulavin, Yann Herault, Lars Zender, William M Keyes.
      Cellular senescence is a state of stable arrest and secretion linked to aging and disease. Here, we identify that senescent cells dispose of large fragments through cell-to-cell adhesion, which we term "senescent-cell adhesion fragments" (SCAFs). Found in many senescent states, including human and mouse cells, and mouse tissues, SCAFs lack nuclear material but contain organelles, including damaged mitochondria. Disrupting adherens junctions decreases SCAF formation but induces senescent-cell death, due to an inability to shed damaged mitochondria. Live imaging and proteomics show that SCAFs ultimately rupture, releasing a complex proteome, including damage-associated molecular patterns (DAMPs) and proteins linked to neurodegenerative disease. Functionally, SCAFs activate wound-healing and cancer-related programs, promoting migration and invasion. Immunostaining also reveals amyloid-like material in senescent cells that can be externalized through fragmentation. Altogether, these findings identify a feature that facilitates senescent cell survival but also externally deposits damaged intracellular contents, with implications for cancer and neurodegeneration.
    Keywords:  DAMPs; aging; amyloid; cancer; cell-cell adhesion; debris; mitochondria; senescence
    DOI:  https://doi.org/10.1016/j.devcel.2026.08.002
  10. Bioinformatics. 2026 Aug 22. pii: btag639. [Epub ahead of print]
    GAMclust: identification of regulated metabolic modules in bulk, single cell and spatial gene expression data.
    Anastasiia Gainullina, Evgeniia Chikina, Maxim Artyomov, Alexey Sergushichev.
       MOTIVATION: Metabolism operates as a highly interconnected biochemical network, and its regulation emerges from coordinated changes across many reactions and metabolites. The integration of gene expression profiling data with organism-scale metabolic networks has proven to be a valuable tool for understanding cellular metabolic regulation. However, the increasing complexity of profiling technologies and experimental designs requires the development of specialized tools.
    RESULTS: Here, we present GAMclust, an R package implementing and extending the previously published GAM-clustering pipeline for identifying transcriptionally regulated metabolic modules in complex gene expression datasets. GAMclust supports bulk, single-cell, and spatial gene expression profiling. It includes built-in KEGG and Rhea metabolic networks for human and mouse, with options to expand these networks for the analysis of other species. The package also offers a suite of post-processing and visualization tools, facilitating the exploration and interpretation of results.
    AVAILABILITY: GAMclust is freely available at https://github.com/alserglab/GAMclust and https://doi.org/10.5281/zenodo.21432552 under the MIT license. Documentation is available at https://alserglab.github.io/GAMclust. Source code for supplementary materials is available at https://github.com/alserglab/GAMclust-paper.
    SUPPLEMENTARY INFORMATION: Supplementary data are available online.
    Keywords:  gene expression; metabolism; network analysis; single cell
    DOI:  https://doi.org/10.1093/bioinformatics/btag639
  11. Sci Adv. 2026 Aug 28. 12(35): eaeg1148
    Insulin-like growth factor-binding protein 7 is a soluble cell adhesion molecule.
    Kai Cai, Xuewu Zhang, Xiao-Chen Bai.
      Insulin-like growth factor-binding protein 7 (IGFBP7) is a secreted protein with diverse roles in angiogenesis, cell differentiation, tissue remodeling, and regulating cell signaling and is linked to numerous human diseases. The molecular basis of the multifunctionality of IGFBP7 remains unclear. Using cryo-electron microscopy, we show that IGFBP7 assembles into a barrel-shaped dodecamer in the presence of heparin. The carboxyl-terminal IgC2 domain forms the central core of the barrel, which is capped by the amino-terminal heparin-binding IB domain at both ends. This homo-oligomer can simultaneously engage heparan sulfate proteoglycans on adjacent cells, functioning as a soluble "cell glue" to drive cell-cell adhesion. Furthermore, IGFBP7 enhances and prolongs signaling of receptor tyrosine kinases, including insulin receptor and c-MET, through its adhesion activity. These findings reveal a structural mechanism for IGFBP7's pleiotropy and establish it as a universal adhesion factor.
    DOI:  https://doi.org/10.1126/sciadv.aeg1148
  12. Nat Commun. 2026 08 26. pii: 9067. [Epub ahead of print]17(1):
    Single-cell and in vivo profiling reveal heterogeneous and organ-specific CRISPR-Cas9 off-target and translocation outcomes.
    Alexandra Madsen, Niklas Selfjord, Marta Martinez-Lage, Anna-Lena Loyd, Gavin Kurgan, Mikaela Ståhlberg, Julia Lindgren, Julia Liz Touza, Leif Wigge, Mike Firth, Karl Nordström, Joseph Collin, Daniel Jachimowicz, Bastian Schiffthaler, Inken Dillmann, Panagiotis Antoniou, Aikaterini Emmanouilidi, Jonna Hellsten, Johan Forsström, Kerstin Magnell, Ashley Jacobi, Mark Behlke, Michelle Porritt, Katja Madeyski-Bengtson, Marcello Maresca, Pinar Akcakaya.
      CRISPR-Cas9 holds promise for treating genetic disease, but rare off-target mutations and structural variants remain as key safety concerns, especially at scales relevant to therapy. Here, we establish workflows to resolve Cas9 off-target activity in vitro at single-cell resolution and in vivo across different tissues. Using clonally expanded electroporated mouse embryos and embryonic stem cells, we reveal that individual cells exhibit unique off-target and translocation profiles, including events missed in bulk analyses. Integrating single-cell editing with chromatin accessibility, transcription, and DNA methylation measurements suggest that sequence-independent features modulate Cas9 access and cleavage, with preferential editing in regions characterized by open chromatin and lower methylation. In Cas9-inducible mouse models, editing analyses reveal organ-distinct off-target spectra, DNA repair pathway usage, indel patterns, and markedly varying translocation propensity between tissues. These findings demonstrate that off-target activity is heterogeneous across cells and context-dependent across organs, motivating sensitive single-cell analyses and organ-specific evaluation in preclinical development to more accurately assess risk and improve the safety of CRISPR-based genomic medicines.
    DOI:  https://doi.org/10.1038/s41467-026-77144-5
  13. Nat Med. 2026 Aug 27.
    Induced pluripotent stem cells from discovery to translation.
    Jaecheol Lee, Todd Herron, Lorenz Studer, Christine L Mummery, Joseph C Wu.
      Two decades after the introduction of induced pluripotent stem cell (iPSC) technology, the field has evolved from a seminal biological discovery into a transformative clinical platform. This maturation reflects a convergence of nonintegrating cellular reprogramming, efficient differentiation protocols, high-fidelity tissue engineering and precise genome editing-which together have established a platform-level framework for recapitulating and probing human disease biology in human cell-based systems. While these milestones have enabled the first wave of iPSC-based therapeutic clinical trials and recent early approvals, the transition to standardized, widely deployable therapies remains constrained by inherent biological variability, manufacturing complexities and the need for long-term safety surveillance. This Review evaluates the technological and translational trajectories that have defined the iPSC era and analyzes the operational barriers to therapeutic development. Looking forward, we discuss how integrating automation and artificial intelligence could redefine iPSC workflows as scalable systems. We present a roadmap for the next 20 years, envisioning a paradigm shift in which iPSC-derived interventions transition from bespoke experimental models toward standardized, engineered biological medicines.
    DOI:  https://doi.org/10.1038/s41591-026-04584-3
  14. Nature. 2026 Aug 26.
    Ultrafast and reference-free sequence discovery in single-cell data.
    Daniel León-Periñán, Nikos Karaiskos, Nikolaus Rajewsky.
      Knowledge of RNA sequences, expression, splicing, isoforms, structure and modifications is central for understanding and targeting cellular processes. Revolutionary single-cell and spatial transcriptomics technologies-for example, as deployed by consortia such as the Human Cell Atlas-partially capture this diversity and generate cellular profiles that expand at petabyte scale each year1-5. Yet researchers cannot search sequences across these datasets: standard pipelines do not scale or rely on references, retaining only gene or isoform counts, whereas accessing raw sequences requires collecting, downloading and processing millions of large files. Here we present Malva, a computational platform that enables ultrafast, species-agnostic and reference-free interrogation of the raw sequence space, enabling searching for any sequence, mutation, splice junction or pathogen, or spatial location of arbitrary transcripts. The continuously expanding Malva Index currently comprises around 74 million cells from thousands of experiments in health and disease. Malva enables reference-free discovery-researchers can, for example, identify cell types and predict cell-cell similarity directly from sequence composition. Building on Malva's speed and accuracy, we demonstrate how Malva can be flexibly connected to state-of-the-art neural networks and how to execute complex searches and enable automated analyses. Malva transforms single-cell atlases from static gene count tables into dynamic, sequence-resolved resources that may help to bridge human-machine reasoning about biology.
    DOI:  https://doi.org/10.1038/s41586-026-10975-w
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