bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–09–14
sixteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Molecular basis for regulation of the class I phosphoinositide 3-kinases (PI3Ks), and their targeting in human disease.
  2. Scvi-hub: an actionable repository for model-driven single-cell analysis.
  3. SuperGLUE facilitates an explainable training framework for multi-modal data analysis.
  4. HT SpaceM: A high-throughput and reproducible method for small-molecule single-cell metabolomics.
  5. Adrenal lipoma formation via PI(3,4,5)P3/AKT-dependent transdifferentiation of adrenocortical cells into adipocytes.
  6. Multi-omic analysis reveals a key BCAT1 role in mTOR activation by B-cell receptor and TLR9.
  7. Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools.
  8. The mTORC2 subunit RICTOR drives breast cancer progression by promoting ganglioside biosynthesis through transcriptional and epigenetic mechanisms.
  9. Sequential factor delivery enables efficient workflow for universal gene editing in clinical grade iPS cells.
  10. Learning stochastic processes with intrinsic noise from cross-sectional biological data.
  11. Defining breast epithelial cell types in the single-cell era.
  12. A phase I study of AZD8186 in combination with docetaxel in patients with PTEN-mutated or PIK3CB-mutated advanced solid tumors.
  13. Immunosuppression Drugs Exhibit Differential Effects on Endothelial Cell Function.
  14. Sirolimus for Venous Malformations: A Systematic Review of Efficacy and Safety.
  15. Chemogenetic tuning reveals optimal MAPK signaling for cell-fate programming.
  16. Deep visual proteomics reveals an in vivo-like phenotype of orthotopically transplanted human colon organoids.
  1. Biochim Biophys Acta Mol Cell Biol Lipids. 2025 Sep 07. pii: S1388-1981(25)00097-6. [Epub ahead of print]1870(8): 159689
    Molecular basis for regulation of the class I phosphoinositide 3-kinases (PI3Ks), and their targeting in human disease.
    Alexandria L Shaw, Isobel Barlow-Busch, John E Burke.
      The class I phosphoinositide 3-kinase pathway (PI3K) is a master regulator of cellular growth, and plays essential roles in controlling immune cell function, metabolism, chemotaxis and proliferation. Activation of class I PI3Ks generates the signalling lipid PIP3 that activates multiple pro-growth signalling pathways. Class I PI3Ks can be activated by multiple plasma membrane stimuli, including G-protein coupled receptors, Ras superfamily GTPases, and receptor tyrosine kinases. The dysregulation of class I PI3Ks is critical in the progression of many human diseases, including cancers, immunodeficiencies, and developmental disorders. Highlighting this is frequent oncogenic mutations (2nd most frequently mutated gene in all human cancers) in PIK3CA encoding the p110α catalytic subunit of class IA PI3K. The class I PI3Ks are obligate heterodimers composed of a catalytic and regulatory subunit, split into two subclasses, class IA and class IB. Recent elucidation of the structures of class I PI3Ks bound to activating stimuli, with activating disease-linked mutations and bound to allosteric conformational selective inhibitors/activators, has revealed extensive insight into the molecular basis of class I PI3K regulation. This review will summarize our current molecular knowledge of class I PI3K regulation, as well as how this information is being used to generate both small molecules and biologics that can either inhibit or activate kinase activity as potential therapeutic agents and biochemical tools.
    Keywords:  PI3K; PIK3CA; PIK3CD; PIK3CG; PIK3R1; Phosphoinositides
    DOI:  https://doi.org/10.1016/j.bbalip.2025.159689
  2. Nat Methods. 2025 Sep 08.
    Scvi-hub: an actionable repository for model-driven single-cell analysis.
    Can Ergen, Valeh Valiollah Pour Amiri, Martin Kim, Ori Kronfeld, Aaron Streets, Adam Gayoso, Nir Yosef.
      The growing availability of single-cell omics datasets presents new opportunities for reuse, while challenges in data transfer, normalization and integration remain a barrier. Here we present scvi-hub: a platform for efficiently sharing and accessing single-cell omics datasets using pretrained probabilistic models. It enables immediate execution of fundamental tasks like visualization, imputation, annotation and deconvolution on new query datasets using state-of-the-art methods, with massively reduced storage and compute requirements. We show that pretrained models support efficient analysis of large references, including the CZI CELLxGENE Discover Census. Scvi-hub is built within the scvi-tools open-source environment and integrated into scverse. Scvi-hub offers a scalable and user-friendly framework for accessing and contributing to a growing ecosystem of ready-to-use models and datasets, thus putting the power of atlas-level analysis at the fingertips of a broad community of users.
    DOI:  https://doi.org/10.1038/s41592-025-02799-9
  3. Cell Rep Methods. 2025 Aug 29. pii: S2667-2375(25)00203-6. [Epub ahead of print] 101167
    SuperGLUE facilitates an explainable training framework for multi-modal data analysis.
    Tianyu Liu, Jia Zhao, Hongyu Zhao.
      Single-cell multi-modal data integration has been an area of active research in recent years. However, it is difficult to unify the integration process of different omics in a pipeline and evaluate the contributions of data integration. In this article, we revisit the definition and contributions of multi-modal data integration and propose a strong and scalable method based on probabilistic deep learning with an explainable framework powered by statistical modeling to extract meaningful information after data integration. Our proposed method is capable of integrating different types of omics and sensing data. It offers an approach to discovering important relationships among biological features or cell states. We demonstrate that our method outperforms other baseline models in preserving both local and global structures and perform a comprehensive analysis for mining structural relationships in complex biological systems, including inference of gene regulatory networks, extraction of significant biological linkages, and analysis of differentially regulatory relationships.
    Keywords:  CP: Computational biology; CP: Systems biology; embeddings; gene regulatory network inference; multi-omics data analysis; perturbation analysis; single-cell sequencing
    DOI:  https://doi.org/10.1016/j.crmeth.2025.101167
  4. Cell. 2025 Sep 02. pii: S0092-8674(25)00929-8. [Epub ahead of print]
    HT SpaceM: A high-throughput and reproducible method for small-molecule single-cell metabolomics.
    Jeany Delafiori, Mohammed Shahraz, Andreas Eisenbarth, Volker Hilsenstein, Bernhard Drotleff, Alberto Bailoni, Bishoy Wadie, Måns Ekelöf, Alexander Mattausch, Theodore Alexandrov.
      Single-cell metabolomics (SCM) promises to reveal metabolism in its complexity and heterogeneity, yet current methods struggle with detecting small-molecule metabolites, throughput, and reproducibility. Addressing these gaps, we developed HT SpaceM, a high-throughput SCM method combining cell preparation on custom glass slides, small-molecule matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (MS), and batch processing. We propose a unified framework covering quality control, characterization, structural validation, and differential and functional analyses. Profiling HeLa and NIH3T3 cells, we detected 73 small-molecule metabolites validated by bulk liquid chromatography tandem MS (LC-MS/MS), achieving high reproducibility and single-cell resolution. Interrogating nine NCI-60 cancer cell lines and HeLa, we identified cell-type markers in subpopulations and metabolic hubs. Upon inhibiting glycolysis in HeLa cells, we observed emerging glucose-centered metabolic coordination and intra-condition heterogeneity. Overall, we demonstrate how HT SpaceM enables robust, large-scale SCM across over 140,000 cells from 132 samples and provide guidance on how to interpret metabolic insights beyond population averages.
    Keywords:  LC-MS/MS; MALDI-imaging mass spectrometry; NCI-60; SpaceM; co-abundance; heterogeneity; high-throughput; reproducibility; single-cell metabolomics; small-molecule metabolites
    DOI:  https://doi.org/10.1016/j.cell.2025.08.015
  5. Proc Natl Acad Sci U S A. 2025 Sep 16. 122(37): e2510306122
    Adrenal lipoma formation via PI(3,4,5)P3/AKT-dependent transdifferentiation of adrenocortical cells into adipocytes.
    Shogo Yanai, Junko Sasaki, Hyeon-Cheol Lee-Okada, Fumiya Takahashi, Yuto Kikuchi, Shin Morioka, Toshiyoshi Yamamoto, Katsuya Yuguchi, Miko Oikawa, Hiroaki Kajiho, Takashi Baba, Chikako Yokoyama, Ken-Ichirou Morohashi, Akira Suzuki, Takehiko Yokomizo, Takehiko Sasaki.
      Adrenal lipomas are benign tumors containing ectopic adipose tissue in the adrenal gland, an organ that normally lacks both adipocytes and their progenitors. The origin of this ectopic fat remains enigmatic, and the absence of a genetic animal model has hindered its investigation. Phosphatidylinositol 3,4,5-trisphosphate [PI(3,4,5)P3], a key signaling lipid that regulates cellular growth and differentiation, is tightly regulated by the lipid phosphatases PTEN (phosphatase and tensin homolog) and SHIP2 (SH2-containing inositol phosphatase 2). Here, we demonstrate that simultaneous loss of Pten and Ship2 in the adrenal cortex induces adrenal lipoma formation in mice. These lipomatous cells display both adipocyte-like morphology and adipocyte-specific gene expression. Lineage tracing revealed that these lipomas originate from the adrenal cortex. Mechanistically, PI(3,4,5)P3 hyperaccumulation in the adrenal cortex activates AKT (AKT8 virus oncogene cellular homolog), leading to ectopic PPARγ (peroxisome proliferator activated receptor gamma) expression, a key driver of adipocyte differentiation. This study suggests that the PI(3,4,5)P3/AKT-driven transdifferentiation of adrenocortical cells may represent a central mechanism underlying adrenal lipoma formation, thereby providing insights into lipoma pathogenesis and cellular reprogramming in vivo.
    Keywords:  adipocyte; adrenal lipoma; phosphoinositide; phospholipid; transdifferentiation
    DOI:  https://doi.org/10.1073/pnas.2510306122
  6. J Clin Invest. 2025 Sep 09. pii: e186258. [Epub ahead of print]
    Multi-omic analysis reveals a key BCAT1 role in mTOR activation by B-cell receptor and TLR9.
    Rui Guo, Yizhe Sun, Matthew Y Lim, Hardik Shah, Joao A Paulo, Rahaman A Ahmed, Weixing Li, Yuchen Zhang, Haopeng Yang, Liang Wei Wang, Daniel Strebinger, Nicholas A Smith, Meng Li, Merrin Man Long Leong, Michael Lutchenkov, Jin-Hua Liang, Zhixuan Li, Yin Wang, Rishi Puri, Ari Melnick, Michael R Green, John M Asara, Adonia E Papathanassiu, Duane R Wesemann, Steven P Gygi, Vamsi K Mootha, Benjamin E Gewurz.
      B-lymphocytes play major adaptive immune roles, producing antibody and driving T-cell responses. However, how immunometabolism networks support B-cell activation and differentiation in response to distinct receptor stimuli remains incompletely understood. To gain insights, we systematically investigated acute primary human B-cell transcriptional, translational and metabolomic responses to B-cell receptor (BCR), Toll-like receptor 9 (TLR9), CD40-ligand (CD40L), interleukin-4 (IL4) or combinations thereof. T-independent BCR/TLR9 co-stimulation, which drives malignant and autoimmune B-cell states highly induced the transaminase branched chain amino acid transaminase 1 (BCAT1), which localized to lysosomal membranes to support branched chain amino acid synthesis and mechanistic target of rapamycin complex 1 (mTORC1) activation. BCAT1 inhibition blunted BCR/TLR9, but not CD40L/IL4-triggered B-cell proliferation, IL10 expression and BCR/TLR pathway-driven lymphoma xenograft outgrowth. These results provide a valuable resource, reveal receptor-mediated immunometabolism remodeling to support key B-cell phenotypes and identify BCAT1 as an activated B-cell therapeutic target.
    Keywords:  Adaptive immunity; Amino acid metabolism; Cell biology; Lymphomas; Metabolism
    DOI:  https://doi.org/10.1172/JCI186258
  7. J Vis Exp. 2025 Aug 19.
    Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools.
    Shijie He, Fangfei Zhang.
      Mass spectrometry (MS)-based proteomics data, including Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA), are widely used in biological research. However, the application of these datasets in validation studies is still limited due to the lack of clear demonstrations on how to effectively search and analyze proteomic data. To fill this gap, we selected one DDA and one DIA dataset deposited in the PRoteomics IDEntifications Database (PRIDE) data repository to better illustrate the proteomic data analysis workflow and downstream post-processing of protein search results. For demonstration purposes, we used two free computational tools: FragPipe (v22.0) for DDA datasets and DIA-NN (2.1.0) for DIA datasets. Post-processing steps, such as generating volcano plots and lists of dysregulated proteins, were demonstrated using R code. This study provides basic protocols for searching and analyzing proteomic data, serving as an essential beginner's guide to effectively handle proteomic datasets. Through this work, we aim to empower researchers with the knowledge necessary to leverage proteomic data in their biological investigations.
    DOI:  https://doi.org/10.3791/68707
  8. PLoS Biol. 2025 Sep;23(9): e3003362
    The mTORC2 subunit RICTOR drives breast cancer progression by promoting ganglioside biosynthesis through transcriptional and epigenetic mechanisms.
    Mohammad Nafees Ansari, Somesh K Jha, Ali Khan, Kajal Rajput, Nishant Pandey, Dolly Jain, Rajeshwari Tripathi, Nihal Medatwal, Pankaj Sharma, Sudeshna Datta, Animesh Kar, Trishna Pani, Sk Asif Ali, Kaushavi Cholke, Kajal Rana, Valiya P Snijesh, Geetashree Mukherjee, Suryanarayana V S Deo, Soumen Basak, Ashutosh Mishra, Jyothi S Prabhu, Arnab Mukhopadhyay, Avinash Bajaj, Ujjaini Dasgupta.
      Sphingolipid and ganglioside metabolic pathways are crucial components of cell signaling, having established roles in cancer cell proliferation, invasion, and migration. However, regulatory mechanisms controlling sphingolipid and ganglioside biosynthesis in mammalian cells are less known. Here, we show that RICTOR, the regulatory subunit of mTORC2, regulates the synthesis of sphingolipids and gangliosides in human luminal breast cancer-specific MCF-7 and BT-474 cells through transcriptional and epigenetic mechanisms. We observe that RICTOR regulates glucosylceramide levels by modulating the expression of UDP-Glucose Ceramide Glucosyl transferase (UGCG). We identify Zinc Finger protein X-linked (ZFX) as a RICTOR-responsive transcription factor whose recruitment to the UGCG promoter is regulated by DNA methyltransferase 1 and histone demethylase (KDM5A), which are known AKT substrates. We further demonstrate that RICTOR regulates the synthesis of GD3 gangliosides through ZFX and UGCG, and triggers the activation of the EGFR signaling pathway, thereby promoting tumor growth. In line with our findings in human cell culture and mouse models, we observe an elevated expression of RICTOR, ZFX, and UGCG in Indian luminal breast cancer tissues and in TCGA and METABRIC datasets. Together, we establish a key regulatory circuit, RICTOR-AKT-ZFX-UGCG-Ganglioside-EGFR-AKT, and elucidate its contribution to breast cancer progression.
    DOI:  https://doi.org/10.1371/journal.pbio.3003362
  9. Sci Rep. 2025 Sep 12. 15(1): 32514
    Sequential factor delivery enables efficient workflow for universal gene editing in clinical grade iPS cells.
    Thomas Berger, Elitsa Borisova, Anna Gamerschlag, Daniel Terheyden-Keighley, Soraia Martins, Boris Greber.
      Human induced pluripotent stem cells (iPSCs) are gaining momentum as a powerful starting material in cell therapy. To fully harness their potential, CRISPR technology permits endogenous gene modifications as well as the introduction of advanced features, to increase the immune compatibility of the cells or insert suicide genes for enhancing therapeutic safety, for instance. However, genetic manipulation of iPSCs, in particular the generation of knock-in lines, remains relatively inefficient. Conventional mitigation strategies, such as enriching for positive cells using antibiotic selection or complex instrumentation, may, however, cause conflicts with good manufacturing practice (GMP) requirements. To address this challenge, we have systematically optimized a basic gene editing procedure using both Cas9 and Cas12a-based ribonucleoprotein (RNP) complexes. Based on the sequential delivery of RNPs and donor plasmids as a critical hallmark, this virus-free approach permits knock-ins of full-length transgenes at above 30% efficiency, while readily identifying positive clones through random screening at small scale. We exemplify these advances by creating and characterizing homozygous iPSC lines depleted of HLA class I and carrying an inducible caspase-9 suicide gene. Isolated clones from independent GMP iPSC lines retained genomic integrity, differentiation capability, and functionality of the safety switch in the differentiated state. This improved methodology will form a flexible platform for custom gene editing universally applicable both in basic iPSC research and therapy.
    DOI:  https://doi.org/10.1038/s41598-025-17876-4
  10. Proc Natl Acad Sci U S A. 2025 Sep 16. 122(37): e2420621122
    Learning stochastic processes with intrinsic noise from cross-sectional biological data.
    Suryanarayana Maddu, Victor Chardès, Michael J Shelley.
      Inferring dynamical models from data continues to be a significant challenge in computational biology, especially given the stochastic nature of many biological processes. We explore a common scenario in omics, where statistically independent cross-sectional samples are available at a few time points, and the goal is to infer the underlying diffusion process that generated the data. Existing inference approaches often simplify or ignore noise intrinsic to the system, compromising accuracy for the sake of optimization ease. We circumvent this compromise by inferring the phase-space probability flow that shares the same time-dependent marginal distributions as the underlying stochastic process. Our approach, probability flow inference (PFI), disentangles force from intrinsic stochasticity while retaining the algorithmic ease of ordinary differential equation (ODE) inference. Analytically, we prove that for Ornstein-Uhlenbeck processes the regularized PFI formalism yields a unique solution in the limit of well-sampled distributions. In practical applications, we show that PFI enables accurate parameter and force estimation in high-dimensional stochastic reaction networks, and that it allows inference of cell differentiation dynamics with molecular noise, outperforming state-of-the-art approaches.
    Keywords:  gene regulation; generative modeling; intrinsic noise; probability flow; single-cell omics
    DOI:  https://doi.org/10.1073/pnas.2420621122
  11. Dev Cell. 2025 Sep 08. pii: S1534-5807(25)00410-1. [Epub ahead of print]60(17): 2218-2236
    Defining breast epithelial cell types in the single-cell era.
    G Kenneth Gray, Eric G Carlson, Tatyana Lev, Bailey Marshall, Austin D Reed, Alex P Sánchez-Covarrubias, Alecia-Jane Twigger, Aleix Puig-Barbe, Aatish Thennavan, Ayodele Omotoso, Lyndsay M Murrow, Deeptiman Chatterjee, Siyuan He, Sara Pensa, Brian Aevermann, Norbert K Tavares, Natalie Chen, Jason A Hilton, Kerrigan Blake, Yunlong Liu, Kiet Phong, Zev J Gartner, Devon A Lawson, Alexander Swarbrick, Camila O Dos Santos, Sophia H L George, Joan S Brugge, Mark A LaBarge, Harikrishna Nakshatri, Nicholas Navin, Kai Kessenbrock, Walid T Khaled.
      Single-cell studies on breast tissue have contributed to a change in our understanding of breast epithelial diversity that has, in turn, precipitated a lack of consensus on breast cell types. The confusion surrounding this issue highlights a possible challenge for advancing breast atlas efforts. In this perspective, we present our consensus on the identities, properties, and naming conventions for breast epithelial cell types and propose goals for future atlas endeavors. Our proposals and their underlying thought processes aim to catalyze the adoption of a shared model for this tissue and to serve as guidance for other investigators facing similar challenges.
    Keywords:  breast; hierarchical differentiation; human biology; lactation; mammary gland; nomenclature; single-cell biology; tissue organization
    DOI:  https://doi.org/10.1016/j.devcel.2025.06.032
  12. ESMO Open. 2025 Sep 11. pii: S2059-7029(25)01438-3. [Epub ahead of print]10(9): 105569
    A phase I study of AZD8186 in combination with docetaxel in patients with PTEN-mutated or PIK3CB-mutated advanced solid tumors.
    A M Schram, N Takebe, A Chen, Q Zhou, A Iasonos, J Silber, M Reynolds, S Hussain, M Gavriliuc, L M Smyth, D Garrison, E E Dumbrava.
       BACKGROUND: Loss of PTEN activity is common in solid tumors and promotes cancer growth through activation of the PI3K pathway. PTEN-deficient tumors have increased dependence on PI3Kβ and are sensitive to PI3Kβ inhibition in preclinical models. Efficacy is further enhanced by the addition of taxane chemotherapy. We conducted a phase I trial of AZD8186, a small molecule inhibitor of PI3Kβ and PI3Kδ, in combination with docetaxel (Taxotere) (NCI 10131; NCT03218826).
    MATERIAL AND METHODS: Patients with advanced PTEN- or PIK3CB-mutated solid tumors identified through local testing were eligible. Treatment included docetaxel intravenously every 21 days and AZD8186 orally twice daily, 5 days on and 2 days off. Primary objectives were safety, tolerability, and maximum tolerated dose (MTD) as determined by a 3 + 3 dose-escalation design. Secondary objectives included assessment of antitumor activity.
    RESULTS: Twenty-three patients were enrolled with 11 distinct tumor types across 5 dose levels. Clinically significant neutropenia led to dose-level adjustment and the addition of prophylactic growth factor. The MTD was not reached and AZD8186 120 mg twice daily with docetaxel 75 mg/m2 was named the recommended phase II dose. The most common treatment-emergent adverse events (TEAEs) were anemia (57%), diarrhea (43%), and fatigue (43%). The most common grade ≥3 TEAE was neutropenia (30%). One patient with docetaxel-naive prostate cancer had a prolonged partial response (overall response ratio 5.6%); clinical benefit rate was 22.2%.
    CONCLUSIONS: The combination of AZD8186 and docetaxel was generally well tolerated, with the exception of neutropenia, which was effectively managed with the use of growth factor. Limited clinical activity was observed.
    Keywords:  AZD8186; PIK3CB; PTEN; basket trial; docetaxel; neutropenia; solid tumor
    DOI:  https://doi.org/10.1016/j.esmoop.2025.105569
  13. J Vasc Res. 2025 Sep 11. 1-22
    Immunosuppression Drugs Exhibit Differential Effects on Endothelial Cell Function.
    Aly Elezaby, Ryan Dexheimer, David Wu, Sze Yu Chan, Ines Ross Tacco, Ian Y Chen, Nazish Sayed, Karim Sallam.
      Immunosuppressive medications are widely used to treat patients with neoplasms, autoimmune conditions, and solid organ transplants. Prior studies indicate that immunosuppression drugs can cause adverse vascular remodeling. Given the systemic effects of the drugs, elucidating cell-type specific drug effects has been challenging. We utilized induced pluripotent stem-cell derived endothelial cells to investigate the role of widely used immunosuppression drugs on endothelial function. We found that among immunosuppression agents, sirolimus reduced basic endothelial cell functions including cell migration, proliferation, acetylated LDL uptake, mitochondrial respiration, and angiogenesis properties; while tacrolimus only reduced nitric oxide release. This model allows for investigation of differential effect of immunosuppression drugs on endothelial function that can elucidate mechanisms contributing to adverse vascular profiles observed clinically.
    DOI:  https://doi.org/10.1159/000548353
  14. Lymphat Res Biol. 2025 Sep 10.
    Sirolimus for Venous Malformations: A Systematic Review of Efficacy and Safety.
    Joyce Teng, Jeff Martini, Michael Kelly, Megha Tollefson, Alexander Greer.
      Background: Venous malformations can cause substantial morbidity and long-term complications. There are no Food and Drug Administration (FDA)-approved therapies for the treatment of venous malformations. However, off-label use of sirolimus has demonstrated clinical benefit in these patients. This systematic review evaluates the efficacy and safety of sirolimus in the management of venous malformations. Methods and Results: A systematic literature search identified 26 studies comprising 98 patients treated with sirolimus for venous malformations. Most studies were case reports or case series (77%), with 15% prospective trials and 8% retrospective analyses. Sirolimus, primarily administered orally, yielded some level of clinical improvement in 72% of reported patients, with consistent symptomatic relief observed in coagulopathy, bleeding, anemia, pain, and improved function. However, reduction in the size of the malformation varied and treatment-limiting side effects were observed. Conclusions: Oral sirolimus is a promising treatment option for venous malformations, especially for those with deep venous malformations. A direct, targeted topical treatment could provide clinical benefit for the cutaneous manifestation without the risk of off-target effects as occur with oral sirolimus. Further prospective, controlled studies are warranted to elucidate sirolimus's role in managing venous malformations.
    Keywords:  phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR); signaling pathway; sirolimus; systemic therapy; vascular anomalies; venous malformations
    DOI:  https://doi.org/10.1177/15578585251377562
  15. Cell Rep. 2025 Sep 04. pii: S2211-1247(25)00997-0. [Epub ahead of print]44(9): 116226
    Chemogenetic tuning reveals optimal MAPK signaling for cell-fate programming.
    Brittany A Lende-Dorn, Jane C Atkinson, Yunbeen Bae, Kate E Galloway.
      Cell states evolve through the combined activity of signaling pathways and gene networks. While transcription factors can direct cell fate, these factors rely on a receptive cell state. How signaling levels contribute to the emergence of receptive cell states remains poorly defined. Using a well-defined model of direct conversion, we examined how levels of the mitogen-activated protein kinase (MAPK)-activating oncogene HRASG12V influence direct conversion of primary fibroblasts to induced motor neurons. The rates of direct conversion respond biphasically to increasing HRASG12V levels. An optimal "Goldilocks" level of MAPK signaling efficiently drives cell-fate programming, whereas high levels of HRASG12V induce senescence. Through chemogenetic tuning, we set the optimal MAPK activity for high rates of conversion in the absence of HRAS mutants. In addition to proliferation, MAPK signaling influences conversion by regulating Ngn2 activity. Our results highlight the need to tune therapeutic interventions within a non-monotonic landscape that is shaped by genetics and levels of gene expression.
    Keywords:  CP: Developmental biology; MAPK; Ngn2; RAS; cell fate; direct conversion; p53; proliferation; senescence; transdifferentiation
    DOI:  https://doi.org/10.1016/j.celrep.2025.116226
  16. Cell Syst. 2025 Sep 10. pii: S2405-4712(25)00229-7. [Epub ahead of print] 101396
    Deep visual proteomics reveals an in vivo-like phenotype of orthotopically transplanted human colon organoids.
    Frederik Post, Annika Hausmann, Sonja Kabatnik, Sophia Steigerwald, Alexandra Brand, Ditte L Clement, Jonathan Skov, Kadi Lõhmussaar, Hjalte L Larsen, Martti Maimets, Theresa L Boye, Gabriela Jez, Toshiro Sato, Casper Steenholdt, Florian Rosenberger, Andreas Mund, Ole H Nielsen, Kim B Jensen, Matthias Mann.
      Intestinal epithelial damage predisposes to disorders like inflammatory bowel disease (IBD), with organoid transplantation emerging as a potential treatment. However, it is not known how well organoids recapitulate in vivo intestinal epithelial cells (IECs). We employed deep visual proteomics (DVP), integrating AI-guided cell classification, laser microdissection, and ultra-high-sensitivity proteomics at the single-cell level to generate an in-depth proteome resource of IECs directly isolated from the human colon and organoids. While in vitro organoids display high proliferation and low functional signatures, xenotransplantation induces a remarkable shift toward an in vivo-like phenotype. We recapitulated this transition by modifying culture conditions. Our data provide a comprehensive spatial proteomics resource and validate xenotransplanted organoids as suitable models for studying human IEC behavior with unprecedented molecular detail and demonstrate their clinical potential for patients with IBD and other intestinal disorders. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  IBD; colon; mass spectrometry; organoids; proteomics; spatial proteomics
    DOI:  https://doi.org/10.1016/j.cels.2025.101396
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