bims-pideca 2025-06-08 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2025–06–08
fourteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

A systems view of cellular heterogeneity: Unlocking the "wheel of fate".
CoSiDeX: A hyperspectral fluorescent protein resource for highly multiplexed imaging.
Single-Cell Trajectory Inference for Detecting Transient Events in Biological Processes.
Quantifying the nuclear localization of fluorescently tagged proteins.
Hyperinsulinemia-induced upregulation of adipocyte TPH2 contributes to peripheral serotonin production, metabolic dysfunction, and obesity.
High-throughput differentiation of human blood vessel organoids reveals overlapping and distinct functions of the cerebral cavernous malformation proteins.
Cell shapes decode molecular phenotypes in image-based spatial proteomics.
R2HaPpY: Rapid-robust phosphotyrosine peptide enrichment using HaloTag-Src SH2 pY superbinder.
Barcoded monoclonal embryoids are a potential solution to confounding bottlenecks in mosaic organoid screens.
Acquired resistance in cancer: towards targeted therapeutic strategies.
Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics.
Mechanism by which the molecular glue-like verteporfin induces IRE1α dimerization and activation to synergize with AKT inhibition in breast cancer.
PML1-Mediated Feedforward Loop Through PI3K and MAPK Axes Drives Endocrine Resistance.
Autocrine TGF-β signaling promotes cell motility and chemokine secretion in an angiomyolipoma-derived cell model of lymphangioleiomyomatosis.

Cell Syst. 2025 Jun 02. pii: S2405-4712(25)00133-4. [Epub ahead of print] 101300

A systems view of cellular heterogeneity: Unlocking the "wheel of fate".

Hourieh Movasat, Enzo Giacopino, Ali Shahdoost, Yeganeh Dorri Nokoorani, Ali Houshyar Abrbekouh, Yaser Tahamtani, Nika Shakiba.

  Systems biology offers a view of the cell as an input-output device: a biochemical network (or cellular "processor") that interprets cues from the microenvironment to drive cell fate. Advancements in single-cell technologies are unlocking the cellular black box, revealing heterogeneity in seemingly homogeneous cell populations. But are these differences technical variability or biology? In this review, we explore this question through a systems biology lens, offering a framework for conceptualizing heterogeneity from the cell's perspective and summarizing systems and synthetic biology tools for capturing heterogeneity. While cellular inputs shape the probability of attaining particular fates, each cell spins a stochastic "wheel of fate." Applying this framework, we explore heterogeneity in two case studies: human pluripotent stem cell (hPSC) culture and beta cell differentiation. Looking forward, we discuss how a systems approach to heterogeneity may enable more predictable outcomes in stem cell research, with broad implications for developmental biology and regenerative medicine.

Keywords:  cell fate; cell state; differentiation; fate bias; heterogeneity; pluripotent stem cells; single cell

DOI:  https://doi.org/10.1016/j.cels.2025.101300
bioRxiv. 2025 May 14. pii: 2025.05.09.652935. [Epub ahead of print]

CoSiDeX: A hyperspectral fluorescent protein resource for highly multiplexed imaging.

Alejandra V Patino, Henry Chapman, Joshua D Ginzel, Joelle E Sills, Herbert Kim Lyerly, Bruce W Rogers, Joaquin E Drut, Joshua C Snyder.

Fluorescent proteins (FPs) have revolutionized spatiotemporal observations in biology. Yet, the design of multiplexed assays remains constrained by limited spectral characterization and palette validation. Although over 1,000 FPs have been catalogued, systematic resources for characterizing their use in multiplexed approaches are lacking. Here we present a resource and methodology for selecting and decoding FPs in multiplexed imaging experiments. A library of forty-four FPs was built for rapid assembly into mammalian expression vectors and transposase-mediated integration. Hyperspectral imaging was performed for each FP and spectral space was characterized mathematically. To support experimental design and data interpretation, we developed the Cosine Similarity Decoder of XFP ( CoSiDeX ) toolbox, to predict spectrally resolvable FP palettes and decode and re-color hyperspectral images. Using this approach, we demonstrate live-cell imaging of 12 uniquely labeled clones. Our work offers a scalable platform for selecting optimal FP palettes for multiplex experiments, with broad utility across diverse biological systems and hyperspectral imaging techniques.

DOI: https://doi.org/10.1101/2025.05.09.652935
bioRxiv. 2025 May 13. pii: 2025.05.07.652753. [Epub ahead of print]

Single-Cell Trajectory Inference for Detecting Transient Events in Biological Processes.

Alexandre Hutton, Jesse G Meyer.

Transient surges in gene or protein expression often mark the key regulatory checkpoints that propel cells from one functional state to the next, yet they are easy to miss in sparse, noisy single-cell omics data. We introduce scTransient , a trajectory-inference pipeline integrated into our cloud-based single-cell analysis platform PSCS. scTransient transforms single-cell expression profiles into continuous pseudotime signals and couples them with wavelet-based signal processing to isolate short-lived but biologically meaningful bursts of activity. After ordering cells with unsupervised graph trajectories or supervised psupertime, scTransient windows expression values along pseudotime, applies a continuous wavelet transform, and assigns every gene a Transient-Event Score (TES) that rewards sharp, isolated coefficients while penalizing background fluctuations. Synthetic benchmarks show TES robustly recovers transient events across a wide range of cell numbers, signal-to-noise ratios, and event widths. Applying scTransient to three public datasets- hematopoietic differentiation, monocyte-to-macrophage maturation, and single-cell proteomic cell-cycle progression-uncovers previously unreported, process-specific expression spikes. These include erythropoiesis regulators (e.g., Nfe2), membrane-raft remodeling proteins during macrophage differentiation, and S-phase DNA-replication factors in A549 cells. Functional enrichment confirms that top-scoring genes cluster into pathways directly pertinent to each transition. By extending trajectory inference from descriptive ordering to quantitative detection of fleeting regulatory programs, scTransient-now readily accessible via the PSCS web interface-offers researchers a practical route to uncovering transient molecular events that drive development, differentiation, and disease.

DOI: https://doi.org/10.1101/2025.05.07.652753
Bioinform Adv. 2025 ;5(1): vbaf114

Quantifying the nuclear localization of fluorescently tagged proteins.

Julien Hurbain, Pieter Rein Ten Wolde, Peter S Swain.

Motivation: Cells are dynamic, continually responding to intra- and extracellular signals. Measuring the response to these signals in individual cells is challenging. Signal transduction is fast, but reporters for downstream gene expression are slow: fluorescent proteins must be expressed and mature. An alternative is to fluorescently tag and monitor the intracellular locations of transcription factors and other effectors. These proteins enter or exit the nucleus in minutes, after upstream signalling modifies their phosphorylation state. Although such approaches are increasingly popular, there is no consensus on how to quantify nuclear localization.
Results: Using budding yeast, we developed a convolutional neural network that determines nuclear localization from fluorescence and, optionally, bright-field images. Focusing on changing extracellular glucose, we generated ground-truth data using strains with a transcription factor and a nuclear protein tagged with fluorescent markers. We showed that the neural network-based approach outperformed seven published methods, particularly when predicting single-cell time series, which are key to determining how cells respond. Collectively, our results are conclusive-using machine learning to automatically determine the appropriate image processing consistently outperforms ad hoc approaches. Adopting such methods promises to both improve the accuracy and, with transfer learning, the consistency of single-cell analyses.
Availability and implementation: We performed our analysis in Python; code is available at https://git.ecdf.ed.ac.uk/v1jhurba/neunet-nucloc.git.

DOI: https://doi.org/10.1093/bioadv/vbaf114
J Clin Invest. 2025 May 30. pii: e190765. [Epub ahead of print]

Hyperinsulinemia-induced upregulation of adipocyte TPH2 contributes to peripheral serotonin production, metabolic dysfunction, and obesity.

Brian I Park, Andrew R Reeves, Ying Zhu, Robin A Wilson, Sophia C Fernandes, Kimberly K Buhman, Kelli A Lytle, Michael D Jensen, Andrew S Greenberg.

  Tryptophan hydroxylase (TPH) is a rate-limiting enzyme for serotonin or 5-hydroxytryptamine (5-HT) synthesis. Previously, adipocyte TPH1 has been linked to increased adipose 5-HT, reduced BAT thermogenesis, and obesity. However, the role of TPH2, a neural isoform highly expressed in obese adipose tissue, is unknown. Here, we report that adipose tissue expression of TPH2 is significantly elevated in both diet-induced obese (DIO) and ob/ob mice, as well as in obese humans. In high-fat diet (HFD)-fed mice, adipocyte TPH2 deficiency improves DIO-induced metabolic complications, enhances BAT thermogenesis, and increases intestinal energy harvesting efficiency without affecting adiposity. Conversely, TPH2 overexpression in epididymal adipocytes of chow-fed mice raises adipose and plasma 5-HT levels, suppresses BAT thermogenesis, and exacerbates obesity and metabolic dysfunction. We found that obesity-induced hyperinsulinemia upregulates adipocyte TPH2 expression via activation of mechanistic target of rapamycin complex 1 (mTORC1) and sterol regulatory element binding protein 1 (SREBP1). In humans, TPH2 mRNA levels in subcutaneous adipose tissue, but not TPH1, is positively correlated with fasting plasma insulin concentrations. In summary, our study demonstrates that obesity-associated increases in adipocyte TPH2 can regulate distal tissue physiology and energy metabolism, suggesting that TPH2 could be a potential therapeutic target for obesity and its associated complications.

Keywords:  Adipose tissue; Endocrinology; Insulin; Metabolism; Obesity

DOI:  https://doi.org/10.1172/JCI190765
Angiogenesis. 2025 Jun 06. 28(3): 32

High-throughput differentiation of human blood vessel organoids reveals overlapping and distinct functions of the cerebral cavernous malformation proteins.

Dariush Skowronek, Robin A Pilz, Valeriia V Saenko, Lara Mellinger, Debora Singer, Silvia Ribback, Anja Weise, Kevin Claaßen, Christian Büttner, Emily M Brockmann, Christian A Hübner, Thiha Aung, Silke Haerteis, Sander Bekeschus, Arif B Ekici, Ute Felbor, Matthias Rath.

  Cerebral cavernous malformations (CCMs) are clusters of thin-walled enlarged blood vessels in the central nervous system that are prone to recurrent hemorrhage and can occur in both sporadic and familial forms. The familial form results from loss-of-function variants in the CCM1, CCM2, or CCM3 gene. Despite a better understanding of CCM pathogenesis in recent years, it is still unclear why CCM3 mutations often lead to a more aggressive phenotype than CCM1 or CCM2 variants. By combining high-throughput differentiation of blood vessel organoids from human induced pluripotent stem cells (hiPSCs) with a CCM1, CCM2, or CCM3 knockout, single-cell RNA sequencing, and high-content imaging, we uncovered both shared and distinct functions of the CCM proteins. While there was a significant overlap of differentially expressed genes in fibroblasts across all three knockout conditions, inactivation of CCM1, CCM2, or CCM3 also led to specific gene expression patterns in neuronal, mesenchymal, and endothelial cell populations, respectively. Taking advantage of the different fluorescent labels of the hiPSCs, we could also visualize the abnormal expansion of CCM1 and CCM3 knockout cells when differentiated together with wild-type cells into mosaic blood vessel organoids. In contrast, CCM2 knockout cells showed even reduced proliferation. These observations may help to explain the less severe clinical course in individuals with a pathogenic variant in CCM2 and to decode the molecular and cellular heterogeneity in CCM disease. Finally, the excellent scalability of blood vessel organoid differentiation in a 96-well format further supports their use in high-throughput drug discovery and other biomedical research studies.

Keywords:  Blood vessel organoids; CRISPR/Cas9 genome editing; Cerebral cavernous malformations; Human induced pluripotent stem cells; Single-cell RNA sequencing

DOI:  https://doi.org/10.1007/s10456-025-09985-5
bioRxiv. 2025 May 16. pii: 2025.05.13.653868. [Epub ahead of print]

Cell shapes decode molecular phenotypes in image-based spatial proteomics.

Trang Le, William D Leineweber, Matheus P Viana, Anthony Cesnik, Jan N Hansen, Wei Ouyang, Susanne M Rafelski, Emma Lundberg.

The diversity of cellular and tissue structures can arise from a few basic cell shapes, which undergo various transformations based on biophysical constraints on cytoskeletal organization. While cellular geometry has been linked with selected biological processes such as polarity, signaling or morphogenesis, the orchestration of the whole proteome in association to cell shape is still poorly understood. In this study, using more than 1 million images of single cells stained for 11,998 proteins across 10 cell lines in the Human Protein Atlas database, we performed an integrated analysis of organelle, pathway and single protein levels in association to a 2D cellular shapespace. We found that cell and nuclear shapes across cell lines exist in a shared continuum. We also found that the subcellular organelle topology varies across cell lines, but remains robust within each cell line's shapespace. At the single protein level, we found that cells of different shapes in the same cell cycle phase might be preparing for different fates, and that many non-cell cycle proteins expressed shape-based abundance variation. Using the same coordinate framework defined by shape, we could analyze the distribution shift of protein spatial localization under drug perturbation.

DOI: https://doi.org/10.1101/2025.05.13.653868
bioRxiv. 2025 May 17. pii: 2025.05.14.653984. [Epub ahead of print]

R2HaPpY: Rapid-robust phosphotyrosine peptide enrichment using HaloTag-Src SH2 pY superbinder.

Alexis Chang, Ricard A Rodriguez-Mias, Matthew D Berg, Sophie Moggridge, Judit Villén.

Phosphotyrosine signaling plays a critical role in many biological processes, from cell proliferation to immune response. Despite its importance, systems-level analysis of phosphotyrosine signaling remains a challenge due to costly enrichment reagents and labor-intensive protocols. We previously established an automated phosphotyrosine enrichment method for preparing 96 samples in parallel. Here, we further optimize this method by fusing an SH2 phosphotyrosine superbinder to the HaloTag protein. This allows simple and cost-effective preparation of enrichment beads directly from bacterial lysate, expediting reagent preparation from days to hours. Additionally, our new reagent binds phosphotyrosine peptides at higher efficiency than other enrichment reagents. Using this reagent, we detect and quantify 1,651 unique phosphotyrosine sites from EGF stimulated HeLa cells using only ∼1 mg of input peptides per replicate. These include 878 regulated pY sites, many of which are low abundance and not previously detected or annotated as EGF-responsive. This streamlined and sensitive method facilitates comprehensive, quantitative mapping of tyrosine phosphorylation dynamics, enabling broader integration of phosphotyrosine signaling into multiomic and network-level models across diverse biological systems and disease states.

DOI: https://doi.org/10.1101/2025.05.14.653984
bioRxiv. 2025 May 24. pii: 2025.05.23.655669. [Epub ahead of print]

Barcoded monoclonal embryoids are a potential solution to confounding bottlenecks in mosaic organoid screens.

Samuel G Regalado, Chengxiang Qiu, Jean-Benoît Lalanne, Beth K Martin, Madeleine Duran, Cole Trapnell, Aidan Keith, Silvia Domcke, Jay Shendure.

Genetic screens in organoids hold tremendous promise for accelerating discoveries at the intersection of genomics and developmental biology. Embryoid bodies (EBs) are self-organizing multicellular structures that recapitulate aspects of early mammalian embryogenesis. We set out to perform a CRISPR screen perturbing all transcription factors (TFs) in murine EBs. Specifically, a library of TF-targeting guide RNAs (gRNAs) was used to generate mouse embryonic stem cells (mESCs) bearing single TF knockouts. Aggregates of these mESCs were induced to form mouse EBs, such that each resulting EB was 'mosaic' with respect to the TF perturbations represented among its constituent cells. Upon performing single cell RNA-seq (scRNA-seq) on cells derived from mosaic EBs, we found many TF perturbations exhibiting large and seemingly significant effects on the likelihood that individual cells would adopt certain fates, suggesting roles for these TFs in lineage specification. However, to our surprise, these results were not reproducible across biological replicates. Upon further investigation, we discovered cellular bottlenecks during EB differentiation that dramatically reduce clonal complexity, curtailing statistical power and confounding interpretation of mosaic screens. Towards addressing this challenge, we developed a scalable protocol in which each individual EB is monoclonally derived from a single mESC and genetically barcoded. In a proof-of-concept experiment, we show how these monoclonal EBs enable us to better quantify the consequences of TF perturbations as well as 'inter-individual' heterogeneity across EBs harboring the same genetic perturbation. Looking forward, monoclonal EBs and EB-derived organoids may be powerful tools not only for genetic screens, but also for modeling Mendelian disorders, as their underlying genetic lesions are overwhelmingly constitutional ( i.e. present in all somatic cells), yet give rise to phenotypes with incomplete penetrance and variable expressivity.

DOI: https://doi.org/10.1101/2025.05.23.655669
Nat Rev Cancer. 2025 Jun 03.

Acquired resistance in cancer: towards targeted therapeutic strategies.

National Cancer Institute (NCI) Acquired Resistance to Therapy Network (ARTNet)

Development of acquired therapeutic resistance limits the efficacy of cancer treatments and accounts for therapeutic failure in most patients. How resistance arises, varies across cancer types and differs depending on therapeutic modalities is incompletely understood. Novel strategies that address and overcome the various and complex resistance mechanisms necessitate a deep understanding of the underlying dynamics. We are at a crucial time when innovative technologies applied to patient-relevant tumour models have the potential to bridge the gap between fundamental research into mechanisms and timing of acquired resistance and clinical applications that translate these findings into actionable strategies to extend therapy efficacy. Unprecedented spatial and time-resolved high-throughput platforms generate vast amounts of data, from which increasingly complex information can be extracted and analysed through artificial intelligence and machine learning-based approaches. This Roadmap outlines key mechanisms that underlie the acquisition of therapeutic resistance in cancer and explores diverse modelling strategies. Clinically relevant, tractable models of disease and biomarker-driven precision approaches are poised to transform the landscape of acquired therapy resistance in cancer and its clinical management. Here, we propose an integrated strategy that leverages next-generation technologies to dissect the complexities of therapy resistance, shifting the paradigm from reactive management to predictive and proactive prevention.

DOI: https://doi.org/10.1038/s41568-025-00824-9
bioRxiv. 2025 May 14. pii: 2025.05.09.653038. [Epub ahead of print]

Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics.

Erick Armingol, James Ashcroft, Magda Mareckova, Martin Prete, Valentina Lorenzi, Cecilia Icoresi Mazzeo, Jimmy Tsz Hang Lee, Marie Moullet, Omer Ali Bayraktar, Christian Becker, Krina Zondervan, Luz Garcia-Alonso, Nathan E Lewis, Roser Vento-Tormo.

Metabolism supplies energy, building blocks, and signaling molecules vital for cell function and communication, but methods to directly measure it at single-cell and/or spatial resolutions remain technically challenging and inaccessible for most researchers. Single-cell and spatial transcriptomics offer high-throughput data alternatives with a rich ecosystem of computational tools. Here, we present scCellFie, a computational framework to infer metabolic activities from human and mouse transcriptomic data at single-cell and spatial resolution. Applied to ~30 million cell profiles, we generated a comprehensive metabolic atlas across human organs, identifying organ- and cell-type-specific activities. In the endometrium, scCellFie reveals metabolic programs contributing to healthy tissue remodeling during the menstrual cycle, with temporal patterns replicated in data from in vitro cultures. We also uncover disease-associated metabolic alterations in endometriosis and endometrial carcinoma, linked to proinflammatory macrophages, and metabolite-mediated epithelial cell communication, respectively. Ultimately, scCellFie provides a scalable toolbox for extracting interpretable metabolic functionalities from transcriptomic data.

DOI: https://doi.org/10.1101/2025.05.09.653038
Cell Chem Biol. 2025 Jun 03. pii: S2451-9456(25)00165-5. [Epub ahead of print]

Mechanism by which the molecular glue-like verteporfin induces IRE1α dimerization and activation to synergize with AKT inhibition in breast cancer.

Yongliang Liu, Hui Hua, Yalan Cao, Minjing Li, Hongying Zhang, Shan Du, Jieya Liu, Ting Luo, Yangfu Jiang.

  Inositol-requiring enzyme 1α (IRE1α) signaling is one of three arms of the unfolded protein response, playing a vital role in maintaining endoplasmic reticulum homeostasis. Pharmacological modulation of this pathway offers potential therapeutic strategies for various diseases. Molecular glues may regulate protein stability and activity by inducing protein-protein interaction. Here, we find that verteporfin functions as a molecular glue, promoting IRE1α dimerization and activation. Specifically, verteporfin binds to IRE1α, facilitating its dimerization, which relies on the His692 residue. This activation of IRE1α triggers XBP1 splicing and miR-153-mediated downregulation of PTEN, along with AKT phosphorylation. Additionally, we identify the pro-metastasis gene BACH1 as a novel target of miR-153, which is downregulated by IRE1α and verteporfin. While verteporfin inhibits breast cancer cell viability and invasion, its combination with an AKT inhibitor synergistically suppresses breast cancer progression. Our findings establish a mechanistic link between IRE1α and PI3K/AKT signaling, highlighting a possibility for therapeutic intervention.

Keywords:  AKT; BACH1; IRE1α; PTEN; cancer; inositol-requiring enzyme 1α; miR-153; molecular glue; unfolded protein response; verteporfin

DOI:  https://doi.org/10.1016/j.chembiol.2025.05.004
bioRxiv. 2025 May 16. pii: 2025.05.15.653365. [Epub ahead of print]

PML1-Mediated Feedforward Loop Through PI3K and MAPK Axes Drives Endocrine Resistance.

Han Wang, Zixi Yun, Yuan Cao, Xinyue Li, Zhenghao Liu, Chun-Peng Pai, Chen Wu, Jiangan Yue, Gina Lin, Jackie Cai, Belinda Willard, Sichun Yang, Ruth A Keri, William P Schiemann, J Alan Diehl, Hung-Ying Kao.

Treatment of estrogen receptor-positive (ER+) breast cancer is significantly hindered by endocrine resistance. We identified PML1 as a key therapeutic entity that can be targeted to overcome resistance. Endocrine-resistant breast cancer cells share three key characteristics: elevated PML1 protein levels, enhanced activity of PI3K, MAPK, or both signaling pathways, and reduced ER activity. We developed a PML1 gene signature that predicts poor prognosis and correlates strongly with PI3K, MAPK, and endocrine resistance gene signatures, as evident by cellular studies, scRNA-seq analysis, and spatial transcriptomics of endocrine therapy-treated tumors. This signature is present in endocrine-resistant breast cancer cells harboring the Y537S ER mutation. We consistently demonstrate high PML1 protein levels across cells resistant to various treatments, including 4-hydroxytamoxifen, fulvestrant, elacestrant, and CDK4/6 inhibitors. Furthermore, treatments with these therapeutic agents or knockdown of ESR1 mRNA also increase PML1 protein levels. Mechanistically, we show that ER inhibition through fulvestrant treatment activates PI3K and MAPK signaling, which enhance PML1 protein stability and synthesis. PML1 then drives a feedforward loop by stimulating the expression of cytokine and growth factor mRNAs, including CCL5 and HBEGF , further amplifying PI3K and MAPK signaling. Consequently, in endocrine-resistant cells, endocrine therapies, while inactivating ER, paradoxically reinforce this loop through increased PI3K/MAPK activation and PML1 protein accumulation, ultimately compromising therapeutic efficacy. Finally, we demonstrated that arsenic trioxide, an FDA-approved, PML-reducing drug, effectively disrupts this feedforward loop, offering a promising strategy for treating resistant metastatic breast cancer.
STATEMENT OF SIGNIFICANCE: Endocrine resistance remains a major obstacle in treating estrogen receptor-positive metastatic breast cancer. Our study identifies PML1 as a central mediator of this resistance, revealing how it maintains a self-reinforcing signaling network through PI3K and MAPK pathways by enhancing the production of cytokines and growth factors. The clinical significance of our findings is threefold: we establish PML1 as a biomarker for therapy resistance, demonstrate its mechanistic role in treatment failure, and show that FDA-approved arsenic trioxide can disrupt PML1-driven resistance. These insights provide a direct path to clinical translation, as combining arsenic trioxide with existing therapies could benefit patients with limited treatment options.

DOI: https://doi.org/10.1101/2025.05.15.653365
Am J Pathol. 2025 May 30. pii: S0002-9440(25)00182-8. [Epub ahead of print]

Autocrine TGF-β signaling promotes cell motility and chemokine secretion in an angiomyolipoma-derived cell model of lymphangioleiomyomatosis.

Anna Moskal, Rafał Myrczek, Mateusz Wawro, Lara Ruiz Auladell, Alexandra Baiges, Irene Garcia, Francesca Mateo Gonzalez, Miquel Angel Pujana, Jakub Kochan, Alicja Hinz, Elżbieta Radzikowska, Sophie Lucas, Joanna Bereta, Renata Mezyk-Kopec.

Lymphangioleiomyomatosis (LAM) is a rare systemic disease that affects young women and is classified as a low-grade metastasizing neoplasm. It is characterized by uncontrolled proliferation of LAM cells within the lung parenchyma, which results from loss-of-function mutations in tuberous sclerosis complex 2 (TSC2) or 1 (TSC1) and activation of the mechanistic target of rapamycin complex 1 (mTORC1). Abnormal cell growth leads to cyst formation and lung damage. Rapamycin-based therapy is the only approved treatment. Although it stabilizes the lung function in most patients, it has several limitations. Therefore, new therapeutic strategies are needed. This study examined the role of transforming growth factor β (TGF-β), a pleiotropic cytokine with well-established pro-tumorigenic activity, in LAM cell biology. Using a TSC2-deficient angiomyolipoma-derived cell line, it was found that TSC2-/- cells exhibited a higher expression of TGFβ1 and TGFβ3 than cells with restored TSC2 expression. Additionally, TSC2-/- cells expressed glycoprotein A repetitions predominant (GARP) and integrin β8, which promote TGF-β activation. Inhibition of TGF-β signaling in TSC2-/- cells reduced their migration in a wound healing assay, impaired transmigration through a 3D matrix, and decreased the expression of monocyte chemoattractant protein-1 (MCP-1). These findings provide new insights into the regulation of processes contributing to LAM progression and point to TGF-β as one of the potential targets for LAM treatment.

DOI: https://doi.org/10.1016/j.ajpath.2025.04.019