bims-pideca 2025-10-26 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2025–10–26
ten papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

PTEN Oxidation Promotes Constitutive PI3K Signaling and Inducible Macropinocytosis in Pancreatic Cancer.
Reproducible processing of TCGA regulatory networks.
Proteomic Analysis of PTEN-Deficient Cells Reveals Src-Mediated Upregulation of EphA2 and Therapeutic Potential of Dual Inhibition.
Spatiotemporal and quantitative analyses of phosphoinositides - fluorescent probe-and mass spectrometry-based approaches.
TXNIP mediates LAT1/SLC7A5 endocytosis to limit amino acid uptake in cells entering quiescence.
Ligand and integrin-independent mechano-sensitive EGFR activation in lung cancer cells.
p53 drives lung cancer regression through a TSC2/TFEB-dependent senescence program.
Detection of PIP2 distributions in biological membranes using a peptide-based sensor.
How to get the most out of your cancer spatial transcriptomics data.
Improved gene regulatory network inference from single cell data with dropout augmentation.

Cancer Res. 2025 Oct 24. OF1-OF14

PTEN Oxidation Promotes Constitutive PI3K Signaling and Inducible Macropinocytosis in Pancreatic Cancer.

Rachel A Burge, Lucas Bialousow, Amanda J Linke, Hannah S Coalson, Sara J Adair, Kamala Sundararaj, Merissa Smith, Cameron Bumbleburg, Todd W Bauer, David F Kashatus, G Aaron Hobbs.

Pancreatic ductal adenocarcinoma (PDAC) is defined by the near universal occurrence of KRAS mutations. The KRASG12R mutation is detected in approximately 15% to 20% of patients with PDAC and rare in other KRAS-mutant cancers. KRASG12R is unable to activate the lipid kinase PIK3CA, suggesting that alternative mechanisms might be employed to activate KRASG12R-independent PI3K signaling in PDAC. In this study, we detected elevated expression of all four PI3K isoforms in PDAC cell lines, with the PIK3CG isoform showing higher overall expression in KRASG12R-mutant PDAC. All four PI3K isoforms contributed to global PI3K signaling, and inhibition of any single isoform was insufficient to limit PDAC proliferation. The combined inhibition of all PI3K isoforms was required to limit proliferation, providing a potential explanation for the limited efficacy of PI3K inhibitors in the clinic. Additionally, PTEN, a negative regulator of PI3K signaling, was inactivated in PDAC by the formation of an intramolecular disulfide, which elevated overall PI3K signaling and reduced the dependency of PI3K signaling on KRAS. Oxidation of PTEN was independent of KRAS mutation status. Finally, nutrient-limiting conditions mimicking the PDAC tumor microenvironment further elevated PTEN oxidation and significantly increased macropinocytosis. Thus, this study uncovered a mechanism that supports elevated PI3K signaling in PDAC, thereby reducing the need for KRAS to directly activate the PI3K pathway.
SIGNIFICANCE: PTEN inactivation by intramolecular disulfide bond formation and elevated expression of PI3K isoforms in pancreatic cancer leads to unchecked KRAS-independent PI3K signaling, highlighting the need for therapeutic approaches targeting constitutive PI3K signaling.

DOI: https://doi.org/10.1158/0008-5472.CAN-24-4501
Gigascience. 2025 Oct 20. pii: giaf126. [Epub ahead of print]

Reproducible processing of TCGA regulatory networks.

Viola Fanfani, Katherine H Shutta, Panagiotis Mandros, Jonas Fischer, Enakshi Saha, Soel Micheletti, Chen Chen, Marouen Ben Guebila, Camila M Lopes-Ramos, John Quackenbush.

   BACKGROUND: Technological advances in sequencing and computation have allowed deep exploration of the molecular basis of diseases. Biological networks have proven to be a valuable framework for analyzing omics data and modeling regulatory interactions between genes and proteins. Large collaborative projects, such as The Cancer Genome Atlas (TCGA), have provided a rich resource for building and validating new computational methods, resulting in a plethora of open-source software for downloading, pre-processing, and analyzing those data. However, for an end-to-end analysis of regulatory networks, a coherent and reusable workflow is essential to integrate all relevant packages into a robust pipeline.
FINDINGS: We developed tcga-data-nf, a Nextflow workflow that allows users to reproducibly infer regulatory networks from the thousands of samples in TCGA using a single command. The workflow can be divided into three main steps: multi-omic data, such as RNA-seq and methylation, are (i) downloaded, (ii) pre-processed, and (iii) analyzed to infer regulatory network models with the Network Zoo. The workflow is powered by the NetworkDataCompanion R package, a standalone collection of functions for managing, mapping, and filtering TCGA data. Here, we demonstrate how the pipeline can be used to investigate the differences between colon cancer subtypes attributed to epigenetic mechanisms. Lastly, we provide a database of pre-generated networks for the 10 most common cancer types that can be readily accessed by the public.
CONCLUSIONS: tcga-data-nf is a complete, yet flexible and extensible, framework that enables the reproducible inference and analysis of cancer regulatory networks, bridging a gap in the current universe of software tools for analyzing TCGA data.

Keywords:  ”Cancer”; ”Gene Regulatory Network”; ”NetworkDataCompanion”; ”Nextflow”; ”The Cancer Genome Atlas”; ”reproducibility” (3 to 10 keywords)

DOI:  https://doi.org/10.1093/gigascience/giaf126
Mol Cell Proteomics. 2025 Oct 21. pii: S1535-9476(25)00415-3. [Epub ahead of print] 101316

Proteomic Analysis of PTEN-Deficient Cells Reveals Src-Mediated Upregulation of EphA2 and Therapeutic Potential of Dual Inhibition.

Qiong Wang, Xiangyi Kong, Hongming Song, Li Wang, Lingrui Li, Xiaonan Hou, Santosh Renuse, Muhammad Saddiq Zahari, Ran Cheng, Md Kamrul Hasan Khan, Jidong Wang, Kiran Mangalaparthi, Lin Fang, Tamara Levin Lotan, Ben Ho Park, S John Weroha, Huaijun Zhou, Akhilesh Pandey, Xinyan Wu.

Loss of the tumor suppressor PTEN is frequently observed in various cancers and promotes tumorigenesis by activating the PI3K-AKT pathway. However, the effectiveness of therapies targeting this pathway is limited by complex signaling crosstalk and compensatory mechanisms. Here, we employed quantitative proteomic and phosphoproteomic analyses using MCF10A PTEN knockout models to comprehensively map the signaling alterations induced by PTEN loss. Our analyses revealed that PTEN deficiency not only activates canonical PI3K-AKT signaling but also induces widespread changes in cytoskeleton organization, cell cycle regulation, and central carbon metabolism. PTEN loss also substantially elevates the activity of a variety of tyrosine kinases, including Src kinase and EphA2, a receptor tyrosine kinase (RTK) implicated in cancer progression. Mechanistic studies demonstrated that Src activation, rather than the canonical AKT signaling pathway, drives the upregulation of the receptor tyrosine kinase EphA2. The activation of the noncanonical tyrosine kinase signaling renders AKT inhibition alone insufficient in PTEN-deficient cancers. Importantly, combined treatment with the FDA-approved AKT inhibitor capivasertib and the Src inhibitor dasatinib synergistically induced apoptosis and suppressed the tumor cell growth in various PTEN-deficient cell lines as well as in three-dimensional cultures of endometrial cancer patient-derived xenograft models. Our study reveals that PTEN loss drives oncogenic signaling via dual activation of PI3K-AKT and tyrosine kinase pathways. Specifically, Src-mediated upregulation of EphA2 in PTEN-deficient cells highlights a therapeutic vulnerability that can be exploited by combined AKT and Src inhibition. This approach addresses the resistance associated with AKT inhibition alone and enhances therapeutic efficacy in PTEN-deficient cancers, supporting its potential application in targeted combination therapies.

DOI: https://doi.org/10.1016/j.mcpro.2025.101316
FEBS Lett. 2025 Oct 22.

Spatiotemporal and quantitative analyses of phosphoinositides - fluorescent probe-and mass spectrometry-based approaches.

Hiroaki Kajiho, Shin Morioka, Junko Sasaki, Takehiko Sasaki.

  Comprehensive understanding of phosphoinositide signaling requires both spatiotemporal visualization and precise quantitative analysis of individual lipid species. Phosphoinositides, a family of phosphorylated derivatives of phosphatidylinositol (PI), are structurally diverse lipid messengers that orchestrate a wide range of cellular functions, including membrane trafficking, cytoskeletal dynamics, and signal transduction. Due to their dynamic metabolism and compartment-specific localization, their analysis demands complementary strategies that integrate live-cell imaging with molecular quantification. In this review, we first summarize the development and application of fluorescence-based probes designed to monitor the distribution and dynamics of phosphoinositides in living cells, highlighting their specificity, targeting mechanisms, and limitations. We then provide an overview of recent advances in mass spectrometry-based methodologies that enable high-sensitivity, isomer-resolved quantification of phosphoinositides in biological specimens, including improvements in lipid extraction, derivatization, and chromatographic separation. Together, these dual approaches offer synergistic insights into the biochemical and cellular regulation of phosphoinositide signaling.

Keywords:  PH domain; fluorescent probe; intracellular localization; lipidomics; mass spectrometry; phosphoinositide

DOI:  https://doi.org/10.1002/1873-3468.70200
EMBO J. 2025 Oct 20.

TXNIP mediates LAT1/SLC7A5 endocytosis to limit amino acid uptake in cells entering quiescence.

Jennifer Kahlhofer, Nikolas Marchet, Kristian Zubak, Brigitta Seifert, Madlen Hotze, Anna-Sophia Egger-Hörschinger, Lucija Kucej, Claudia Manzl, Yannick Weyer, Sabine Weys, Martin Offterdinger, Sebastian Herzog, Veronika Reiterer, Chiara Volani, Marcel Kwiatkowski, Saskia B Wortmann, Siamak Nemati, Johannes A Mayr, Johannes Zschocke, Bernhard Radlinger, Kathrin Thedieck, Leopold Kremser, Bettina Sarg, Lukas A Huber, Hesso Farhan, Mariana E G de Araujo, Susanne Kaser, Sabine Scholl-Bürgi, Daniela Karall, David Teis.

  Entry into and exit from cellular quiescence require dynamic adjustments in nutrient acquisition, yet the mechanisms by which quiescent cells downregulate amino acid (AA) transport remain poorly understood. Here we show that cells entering quiescence selectively target plasma membrane-resident amino acid transporters for endocytosis and lysosomal degradation. This process matches amino acid uptake with reduced translational demand and promotes survival during extended periods of quiescence. Mechanistically, we identify the α-arrestin TXNIP as a key regulator of this metabolic adaptation, since it mediates the endocytosis of the SLC7A5-SLC3A2 (LAT1-4F2hc) AA transporter complex in response to reduced AKT signaling. To promote transporter ubiquitination, TXNIP interacts with NEDD4L and other HECT-type ubiquitin ligases. Loss of TXNIP disrupts this regulation, resulting in dysregulated amino acid uptake, sustained mTORC1 signaling, and ultimately cell death under prolonged quiescence. The characterization of a novel TXNIP loss-of-function variant in a patient with a severe metabolic disease further supports its role in nutrient homeostasis and human health. Together, these findings highlight TXNIP's central role in controlling nutrient acquisition and metabolic plasticity with implications for quiescence biology and diseases.

Keywords:  Amino Acids Uptake; Endocytosis; Quiescence; SLC7A5/LAT1; TXNIP

DOI:  https://doi.org/10.1038/s44318-025-00608-9
J Cell Sci. 2025 Oct 23. pii: jcs.264107. [Epub ahead of print]

Ligand and integrin-independent mechano-sensitive EGFR activation in lung cancer cells.

Aneesa Shaikh, Aarmann Mohan, Milan Collins, George Santis, Maddy Parsons.

  Epidermal Growth Factor Receptor (EGFR) is a transmembrane receptor tyrosine kinase that plays important roles in cell proliferation, differentiation, and migration. EGFR overexpression or mutation is a hallmark of some cancers, leading to hyperactivation of downstream signalling. Co-regulation between EGF-dependent EGFR signalling and extracellular matrix (ECM) adhesion occurs in both healthy and malignant cells. Increasing ECM stiffness can contribute to lung cancer progression and is sensed by integrins to promote proliferation and invasion. Emerging evidence suggests non-canonical roles for EGFR in mechano-sensing, but the molecular mechanisms and functional consequences remain unclear. Here we demonstrate that EGFR is activated in human lung cancer cells upon early adhesion to ECM substrates with physiologically relevant stiffness (28 kPa vs. 1.5 kPa), independently of canonical ligands and integrins. Mechano-induced EGFR activation correlates with and requires active Src, F-actin and is coupled to stiffness-dependent plasma membrane retention of EGFR within disordered lipid microdomains. Early stiffness-dependent EGFR activation is required for enhanced migration. These findings uncover a non-canonical role for EGFR in early adhesion related mechano-sensing with potential implications for treatment of lung cancer.

Keywords:  Cytoskeleton; EGFR; Membrane domains; Migration; Src; Substrate stiffness

DOI:  https://doi.org/10.1242/jcs.264107
Cancer Discov. 2025 Oct 21.

p53 drives lung cancer regression through a TSC2/TFEB-dependent senescence program.

Mengxiong Wang, Kathryn T Bieging-Rolett, Alyssa M Kaiser, Colleen A Brady, John H Lockhart, Sofia Ferreira, Kha T Nguyen, Arati Rajeevan, Simone A Evans, Tianyu Zhao, Nitin Raj, Arielle Elkrief, Sam E Tischfield, Marc Ladanyi, Michael G Ozawa, Nam Q Bui, Christopher T Chen, Elsa R Flores, Laura D Attardi.

Pharmacological restoration of p53 tumor suppressor function is a conceptually appealing therapeutic strategy for the many deadly cancers with compromised p53 activity, including lung adenocarcinoma (LUAD). However, the p53 pathway has remained undruggable, partly because of insufficient understanding of how to drive effective therapeutic responses without toxicity. Here, we use mouse and human models to deconstruct the transcriptional programs and sequelae underlying robust therapeutic responses in LUAD. We show that p53 drives potent tumor regression by direct Tsc2 transactivation, leading to mTORC1 inhibition and TFEB nuclear accumulation, which in turn triggers lysosomal gene expression programs, autophagy, and cellular senescence. Senescent LUAD cells secrete factors to recruit macrophages, precipitating cancer cell phagocytosis and tumor regression. Collectively, our analyses reveal a surprisingly complex cascade of events underlying a p53 therapeutic response in LUAD and illuminate targetable nodes for p53 combination therapies, thus establishing a critical framework for optimizing p53-based therapeutics.

DOI: https://doi.org/10.1158/2159-8290.CD-25-0525
J Biol Chem. 2025 Oct 16. pii: S0021-9258(25)02678-X. [Epub ahead of print] 110826

Detection of PIP2 distributions in biological membranes using a peptide-based sensor.

Vinay K Menon, Joy Wu, Alex J Alonzo, Kevin L Scrudders, Kaitlyn A Rogers, Suriya Selvarajan, Andrew Walke, Jennifer Pellicier-Caraballo, Rajasree Kundu, Samsuzzoha Mondal, Ankona Datta, Shalini T Low-Nam.

  Organization and composition of the plasma membrane are important modulators of many cellular programs. Phosphatidylinositol phosphate (PIP) lipids are low abundance membrane constituents with different arrangements of phosphate groups around an inositol head group and that regulate many signaling pathways. Numerous strategies have been developed to detect and track PIP species to monitor their clustering, mobility, and interactions with binding partners. We implement a peptide-based, ratiometric sensor for the detection of PI(4,5)P2 lipids in reconstituted membrane systems that permit absolute quantification of PI(4,5)P2 densities down to physiological levels less than four mole percent. The sensor is membrane permeable and easily transferable to measurements in living cells. Application of calibrated sensors to cells expressing common mutations in the small GTPase, Ras, showed a reshaping of surface PI(4,5)P2 levels and distributions in a mutation-specific manner. Brief treatment of G12C mutant Ras cells with the specific inhibitor, Sotorasib, resulted in alterations to surface PI(4,5)P2 arrangements that resemble the wild-type (WT) Ras. Thus, the rapid redistribution of PI(4,5)P2 lipids upon drug treatment emphasizes the tight coupling between membrane composition, organization, and downstream signaling outcomes. Tools and strategies to monitor membrane composition alongside cellular behaviors could provide pipelines to characterize therapeutics and improve the mechanistic understanding of how protein-lipid coupling drives cellular programs.

Keywords:  Ras protein; fluorescence; membrane biophysics; membrane reconstitution; peptide-based sensor; phosphoinositide

DOI:  https://doi.org/10.1016/j.jbc.2025.110826
Semin Cell Dev Biol. 2025 Oct 17. pii: S1084-9521(25)00067-9. [Epub ahead of print]175 103657

How to get the most out of your cancer spatial transcriptomics data.

David I Kaplan, Xiang Guo, Sasuni D Hirimuthugoda, Lachlan Cain, Sirui Weng, David Le, James Comben, Anna S Trigos.

  Spatial transcriptomics (ST) has emerged as a powerful tool in cancer research, significantly expanding our capacity to study the complexity of tumour ecosystems. Together with the diversity of ST platforms, a plethora of analysis approaches and tools have been developed with the goal of extracting distinct aspects of biological information contained in the data. From visualizing gene expression in the context of tissue structure and cell morphology, to the exploitation of machine learning and spatial statistics to identify cell neighbourhoods, quantify tumour heterogeneity and map cell-cell signalling networks, there is a current explosion of novel analyses techniques. Unfortunately, this makes it challenging to develop workflows and strategies for data analysis, especially for those new to the field. This review serves to offer a path to cancer researchers who recognise the potential of ST and would like to start their data analysis journey. We cover the main analysis approaches used to address common research questions associated with ST data in cancer, highlighting commonly used tools, as well as discuss emerging analysis techniques that hold the potential to leverage the richness of the data at an unprecedented scale. Finally, we end by highlighting considerations when designing ST projects, from experimental design, to assembling teams and managing the rapid flux of ST technologies. We anticipate this review will be useful resource for researchers to not just seek analysis strategies to answer their current research questions, but also provide inspiration to further take advantage of the wealth of information provided by ST data.

Keywords:  Bioinformatics; Cancer; Data analysis; Spatial transcriptomics

DOI:  https://doi.org/10.1016/j.semcdb.2025.103657
PLoS Comput Biol. 2025 Oct 24. 21(10): e1013603

Improved gene regulatory network inference from single cell data with dropout augmentation.

Hao Zhu, Donna K Slonim.

A major challenge in working with single-cell RNA sequencing data is the prevalence of "dropout," when some transcripts' expression values are erroneously not captured. Addressing this issue, which produces zero-inflated count data, is crucial for many downstream data analyses including the inference of gene regulatory networks (GRNs). In this paper, we introduce two novel contributions. First, we propose Dropout Augmentation (DA), a simple but effective model regularization method to improve resilience to zero inflation in single-cell data by augmenting the data with synthetic dropout events. DA offers a new perspective to solve the "dropout" problem beyond imputation. Second, we present DAZZLE, a stabilized and robust version of the autoencoder-based structure equation model for GRN inference using the DA concept. Benchmark experiments illustrate the improved performance and increased stability of the proposed DAZZLE model over existing approaches. The practical application of the DAZZLE model on a longitudinal mouse microglia dataset containing over 15,000 genes illustrates its ability to handle real-world single cell data with minimal gene filtration. The improved robustness and stability of DAZZLE make it a practical and valuable addition to the toolkit for GRN inference from single-cell data. Finally, we propose that Dropout Augmentation may have wider applications beyond the GRN-inference problem. Project website: https://bcb.cs.tufts.edu/DAZZLE.

DOI: https://doi.org/10.1371/journal.pcbi.1013603