bims-pideca 2025-05-18 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2025–05–18
sixteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Ubiquitous expression of an activating mutation in the Pik3ca gene reprograms glucose and lipid metabolism in mice.
Prediction of protein subcellular localization in single cells.
Programmable gene insertion in human cells with a laboratory-evolved CRISPR-associated transposase.
E-cadherin mechanotransduction activates EGFR-ERK signaling in epithelial monolayers by inducing ADAM-mediated ligand shedding.
Beta cells intrinsically sense and limit their secretory activity via mTORC1-RhoA signaling.
Multi-node inhibition targeting mTORC1, mTORC2 and PI3Kα potently inhibits the PI3K/AKT/mTOR pathway in endometrial and breast cancer models.
An NGS-based approach for precise and footprint-free CRISPR-based gene editing in human stem cells.
Rudhira-mediated microtubule stability controls TGFβ signaling during mouse vascular development.
ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.
Alpelisib in pediatric PIK3CA- and TIE-2-mutant vascular anomalies: a case series on safety, efficacy, and drug exposure.
Systematic optimization of prime editing for enhanced efficiency and versatility in genome engineering across diverse cell types.
Zebrafishology, study design guidelines for rigorous and reproducible data using zebrafish.
Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization.
An integrated transcriptomic cell atlas of human endoderm-derived organoids.
Case Report: Activated PI3-kinase-δ syndrome and ovarian malignancies: a case series from the European ESID-APDS registry.
KINAID: an orthology-based kinase-substrate prediction and analysis tool for phosphoproteomics.

PLoS One. 2025 ;20(5): e0322544

Ubiquitous expression of an activating mutation in the Pik3ca gene reprograms glucose and lipid metabolism in mice.

Sabrina Caiazzo, Matthew J Watt, Garron T Dodd, Jacqueline Bayliss, Helen Thomas, Lorey K Smith, Camilla B Mitchell, Wayne A Phillips.

Mutations in PIK3CA, the gene encoding the p110α catalytic subunit of PI3K, are among the most common mutations in human cancers and overgrowth syndromes. The ubiquitous expression of the activating Pik3caH1047R mutation results in reduced survival, organomegaly, hypoglycaemia and hypoinsulinemia in mice. Here we demonstrate that in vivo expression of Pik3caH1047R attenuates the rise in blood glucose in response to oral glucose administration, stimulates glucose uptake in peripheral tissues, inhibits hepatic gluconeogenesis and pancreatic insulin secretion, and increases adipose lipolysis and white adipose tissue browning. Together, our data reveal that the systemic activation of the PI3K pathway in mice disrupts glucose homeostasis through the regulation of hepatic gluconeogenesis, and leads to increased lipolysis of adipose tissue.

DOI: https://doi.org/10.1371/journal.pone.0322544
Nat Methods. 2025 May 13.

Prediction of protein subcellular localization in single cells.

Xinyi Zhang, Yitong Tseo, Yunhao Bai, Fei Chen, Caroline Uhler.

The subcellular localization of a protein is important for its function, and its mislocalization is linked to numerous diseases. Existing datasets capture limited pairs of proteins and cell lines, and existing protein localization prediction models either miss cell-type specificity or cannot generalize to unseen proteins. Here we present a method for Prediction of Unseen Proteins' Subcellular localization (PUPS). PUPS combines a protein language model and an image inpainting model to utilize both protein sequence and cellular images. We demonstrate that the protein sequence input enables generalization to unseen proteins, and the cellular image input captures single-cell variability, enabling cell-type-specific predictions. Experimental validation shows that PUPS can predict protein localization in newly performed experiments outside the Human Protein Atlas used for training. Collectively, PUPS provides a framework for predicting differential protein localization across cell lines and single cells within a cell line, including changes in protein localization driven by mutations.

DOI: https://doi.org/10.1038/s41592-025-02696-1
Science. 2025 May 15. 388(6748): eadt5199

Programmable gene insertion in human cells with a laboratory-evolved CRISPR-associated transposase.

Isaac P Witte, George D Lampe, Simon Eitzinger, Shannon M Miller, Kiara N Berríos, Amber N McElroy, Rebeca T King, Olivia G Stringham, Diego R Gelsinger, Phuc Leo H Vo, Albert T Chen, Jakub Tolar, Mark J Osborn, Samuel H Sternberg, David R Liu.

Programmable gene integration in human cells has the potential to enable mutation-agnostic treatments for loss-of-function genetic diseases and facilitate many applications in the life sciences. CRISPR-associated transposases (CASTs) catalyze RNA-guided DNA integration but thus far demonstrate minimal activity in human cells. Using phage-assisted continuous evolution (PACE), we generated CAST variants with >200-fold average improved integration activity. The evolved CAST system (evoCAST) achieves ~10 to 30% integration efficiencies of kilobase-size DNA cargoes in human cells across 14 tested genomic target sites, including safe harbor loci, sites used for immunotherapy, and genes implicated in loss-of-function diseases, with undetected indels and low levels of off-target integration. Collectively, our findings establish a platform for the laboratory evolution of CASTs and advance a versatile system for programmable gene integration in living systems.

DOI: https://doi.org/10.1126/science.adt5199
Sci Signal. 2025 May 13. 18(886): eadr7926

E-cadherin mechanotransduction activates EGFR-ERK signaling in epithelial monolayers by inducing ADAM-mediated ligand shedding.

Ronja M Houtekamer, Mirjam C van der Net, Marjolein J Vliem, Tomas E J C Noordzij, Lisa van Uden, Robert M van Es, Joo Yong Sim, Eriko Deguchi, Kenta Terai, Matthew A Hopcroft, Harmjan R Vos, Beth L Pruitt, Michiyuki Matsuda, Willem-Jan Pannekoek, Martijn Gloerich.

The behavior of cells is governed by signals originating from their local environment, including mechanical forces exerted on the cells. Forces are transduced by mechanosensitive proteins, which can impinge on signaling cascades that are also activated by growth factors. We investigated the cross-talk between mechanical and biochemical signals in the regulation of intracellular signaling networks in epithelial monolayers. Phosphoproteomic and transcriptomic analyses on epithelial monolayers subjected to mechanical strain revealed the activation of extracellular signal-regulated kinase (ERK) downstream of the epidermal growth factor receptor (EGFR) as a predominant strain-induced signaling event. Strain-induced EGFR-ERK signaling depended on mechanosensitive E-cadherin adhesions. Proximity labeling showed that the metalloproteinase ADAM17, an enzyme that mediates shedding of soluble EGFR ligands, was closely associated with E-cadherin. A probe that we developed to monitor ADAM-mediated shedding demonstrated that mechanical strain induced ADAM activation. Mechanically induced ADAM activation was essential for mechanosensitive, E-cadherin-dependent EGFR-ERK signaling. Together, our data demonstrate that mechanical strain transduced by E-cadherin adhesion triggers the shedding of EGFR ligands that stimulate downstream ERK activity. Our findings illustrate how mechanical signals and biochemical ligands can operate within a linear signaling cascade.

DOI: https://doi.org/10.1126/scisignal.adr7926
Cell Rep. 2025 May 09. pii: S2211-1247(25)00418-8. [Epub ahead of print]44(5): 115647

Beta cells intrinsically sense and limit their secretory activity via mTORC1-RhoA signaling.

Saar Krell, Amit Hamburg, Ofer Gover, Kfir Molakandov, Gil Leibowitz, Kfir Sharabi, Michael D Walker, Aharon Helman.

  Precise regulation of insulin secretion by pancreatic β cells is essential to prevent excessive insulin release. Here, we show that the nutrient sensor mechanistic Target of Rapamycin Complex 1 (mTORC1) is rapidly activated by glucose in β cells via the insulin secretion machinery, positioning mTORC1 as a sensor of β cell activity. Acute pharmacological inhibition of mTORC1 during glucose stimulation enhances insulin release, suggesting that mTORC1 acts as an intrinsic feedback regulator that restrains insulin secretion. Phosphoproteomic profiling reveals that mTORC1 modulates the phosphorylation of proteins involved in actin remodeling and vesicle trafficking, with a prominent role in the RhoA-GTPase pathway. Mechanistically, mTORC1 promotes RhoA activation and F-actin polymerization, limiting vesicle movement and dampening the second phase of insulin secretion. These findings identify a glucose-mTORC1-RhoA signaling axis that forms an autonomous feedback loop to constrain insulin exocytosis, providing insight into how β cells prevent excessive insulin release and maintain metabolic balance.

Keywords:  CP: Metabolism; CP: Molecular biology; RhoA-GTPase; Torin-1; actin remodeling; activity sensor; autonomous regulation; insulin secretion; mTORC1; negative feedback loop; pancreatic β cell; rapamycin

DOI:  https://doi.org/10.1016/j.celrep.2025.115647
Br J Cancer. 2025 May 13.

Multi-node inhibition targeting mTORC1, mTORC2 and PI3Kα potently inhibits the PI3K/AKT/mTOR pathway in endometrial and breast cancer models.

Petros A Tyrakis, Domen Kampjut, Georgina F Steele, H Jonathan G Lindström, Deborah Chirnomas, Benjamin D Hopkins, Marcus D Goncalves, Siddhartha Mukherjee, Lewis C Cantley, Oliver D K Maddocks.

BACKGROUND: While PI3K/AKT/mTOR signalling plays a critical role in cancer, targeting this pathway with single node inhibitors has limited efficacy due to several known factors such as pathway feedback reactivation, co-occurring pathway mutations, and systemic glucose dysregulation leading to hyperinsulinemia. While multi-node inhibition approaches have shown promising clinical efficacy, they require further mechanistic characterisation.
METHODS: Using models of endometrial and breast cancer, we evaluated the efficacy of a multi-node PI3K/AKT/mTOR pathway inhibitor approach utilising the dual mTORC1/mTORC2 inhibitor sapanisertib, PI3Kα inhibitor serabelisib and an insulin-supressing diet. Pathway signalling inhibition versus a range of single-node inhibitors was measured via S6, AKT and 4E-BP1 phosphorylation.
RESULTS: The serabelisib-sapanisertib combination more effectively suppressed PI3K/AKT/mTOR pathway signalling, particularly 4E-BP1, than single-node inhibitors, including alpelisib, capivasertib, inavolisib, everolimus and mutant-specific PI3K inhibitors RLY-2608 and STX-478. Serabelisib plus sapanisertib combined effectively with a range of other therapeutics, such as chemotherapies, hormone targeted therapies and CDK4/6 inhibitors. In xenograft models, sapanisertib, serabelisib plus paclitaxel/insulin supressing diet achieved complete inhibition of tumour growth/tumour regression.
CONCLUSION: Multi-node PI3K/AKT/mTOR pathway inhibition with serabelisib, sapanisertib and ISD is highly effective in preclinical models of endometrial and breast cancer, supporting continued clinical development in these and other solid tumours.

DOI: https://doi.org/10.1038/s41416-025-03035-z
Methods. 2025 May 13. pii: S1046-2023(25)00119-7. [Epub ahead of print]241 33-42

An NGS-based approach for precise and footprint-free CRISPR-based gene editing in human stem cells.

Bert Vandendriessche, Jolien Huyghebaert, Kirsten Van Rossem, Tycho Canter Cremers, Kevin De Man, Ewa Sieliwonczyk, Hanne Boen, Dogan Akdeniz, Laura Rabaut, Jolien Schippers, Peter Ponsaerts, R Frank Kooy, Bart Loeys, Dorien Schepers, Maaike Alaerts.

  Precise gene editing with conventional CRISPR/Cas9 is often constrained by low knock-in (KI) efficiencies (≈ 2-20 %) in human induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs). This limitation typically necessitates labour-intensive manual isolation and genotyping of hundreds of colonies to identify correctly edited cells. Fluorescence- or antibiotic-based enrichment methods facilitate the identification process but can compromise cell viability and genomic integrity. Here, we present a footprint-free editing strategy that combines low-density seeding with next-generation sequencing (NGS) to rapidly identify cell populations containing precisely modified clones. By optimising the transfection workflow and adhering to CRISPR/Cas9 KI design principles, we achieved high average editing efficiencies of 64 % in hiPSCs (introducing a Brugada syndrome-associated variant) and 51 % in hESCs (introducing a neurodevelopmental disorder (NDD)-associated variant). Furthermore, under suboptimal CRISPR design conditions, this approach successfully identified hESC clones carrying a second NDD-associated variant, despite average KI efficiencies below 1 %. Importantly, genomic integrity was preserved throughout subcloning rounds, as confirmed by Sanger sequencing and single nucleotide polymorphism (SNP) array analysis. Hence, this NGS-based enrichment strategy reliably identifies desired KI clones under both optimal and challenging conditions, reducing the need for extensive colony screening and offering an effective alternative to fluorescence- and antibiotic-based selection methods.

Keywords:  Brugada syndrome; CRISPR/Cas9; Knock-in; NGS; Neurodevelopmental disorders; hESC; hiPSC

DOI:  https://doi.org/10.1016/j.ymeth.2025.05.004
Elife. 2025 May 15. pii: RP98257. [Epub ahead of print]13

Rudhira-mediated microtubule stability controls TGFβ signaling during mouse vascular development.

Divyesh Joshi, Preeti Jindal, Ronak K Shetty, Maneesha S Inamdar.

  The transforming growth factor β (TGFβ) signaling pathway is critical for survival, proliferation, and cell migration, and is tightly regulated during cardiovascular development. Smads, key effectors of TGFβ signaling, are sequestered by microtubules (MTs) and need to be released for pathway function. Independently, TGFβ signaling also stabilizes MTs. Molecular details and the in vivo relevance of this cross-regulation remain unclear, understanding which is important in complex biological processes such as cardiovascular development. Here, we use rudhira/Breast Carcinoma Amplified Sequence 3 (Bcas3), an MT-associated, endothelium-restricted, and developmentally essential proto-oncogene, as a pivot to decipher cellular mechanisms in bridging TGFβ signaling and MT stability. We show that Rudhira regulates TGFβ signaling in vivo, during mouse cardiovascular development, and in endothelial cells in culture. Rudhira associates with MTs and is essential for the activation and release of Smad2/3 from MTs. Consequently, Rudhira depletion attenuates Smad2/3-dependent TGFβ signaling, thereby impairing cell migration. Interestingly, Rudhira is also a transcriptional target of Smad2/3-dependent TGFβ signaling essential for TGFβ-induced MT stability. Our study identifies an immediate early physical role and a slower, transcription-dependent role for Rudhira in cytoskeleton-TGFβ signaling crosstalk. These two phases of control could facilitate temporally and spatially restricted targeting of the cytoskeleton and/or TGFβ signaling in vascular development and disease.

Keywords:  BCAS3; Rudhira; Smad2/3; TGFβ signaling; cell biology; developmental biology; microtubule cytoskeleton; mouse

DOI:  https://doi.org/10.7554/eLife.98257
J Proteome Res. 2025 May 13.

ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.

Esther Olabisi-Adeniyi, Jason A McAlister, Daniela Ferretti, Juergen Cox, Jennifer Geddes-McAlister.

  Mass spectrometry-based proteomics experiments produce complex data sets requiring robust statistical testing and effective visualization tools to ensure meaningful conclusions are drawn. The publicly available proteomics data analysis platform, Perseus, is extensively used to perform such tasks, but opportunities to enhance visualization tools and promote accessibility of the data exist. In this study, we developed ProteoPlotter, a user-friendly, executable tool to complement Perseus for visualization of proteomics data sets. ProteoPlotter is built on the Shiny framework for R programming and enables illustration of multidimensional proteomics data. ProteoPlotter supports mapping of one-dimensional enrichment analyses, enhanced adaptability of volcano plots through incorporation of Gene Ontology terminology, visualization of 95% confidence intervals in principal component analysis plots using data ellipses, and customizable features. ProteoPlotter is designed for intuitive use by biological and computational researchers alike, providing descriptive instructions (i.e., Help Guide) for preparing and uploading Perseus output files. Herein, we demonstrate the application of ProteoPlotter toward microbial proteome remodeling under altered nutrient conditions and highlight the diversity of visualizations enabled with the platform for enhanced biological insights. Through its comprehensive data visualization capabilities, linked to the power of Perseus data handling and statistical analyses, ProteoPlotter facilitates enhanced visualization of proteomics data to drive new biological discoveries.

Keywords:  1D annotation enrichment; Klebsiella pneumoniae; Perseus; UpSet plots; Venn diagrams; data visualization; dynamic range; heat maps; proteomics; volcano plots

DOI:  https://doi.org/10.1021/acs.jproteome.4c00963
Pediatr Hematol Oncol. 2025 May 09. 1-14

Alpelisib in pediatric PIK3CA- and TIE-2-mutant vascular anomalies: a case series on safety, efficacy, and drug exposure.

Albert Etingin, Amandine Remy, Thomas Sonea, Francis Fortin, Josée Dubois, Sandrine Essouri, Sandra Ondrejchak, Chantal Lapointe, Yves Théôret, Audrey Denoncourt, Facundo Garcia-Bournissen, Thierry Ducruet, Jérôme Coulombe, Julie Powell, Thai Hoa Tran, Niina Kleiber.

  Alpelisib was recently approved by the FDA for the management of pediatric patients with PIK3CA-related overgrowth spectrum. However, this medication was approved in the absence of pediatric pharmacokinetic data, as a fixed 50 mg dose, with no consideration of weight, the primary pharmacokinetically relevant covariate. This raises concerns regarding potential under and over-exposure. Given this gap in information, we aimed to assess the effect of alpelisib in relation to drug exposure (clinical response and drug safety). Alpelisib plasma concentrations were obtained from eight patients under treatment for vascular malformations. Drug exposure determined with area under the curve (AUC) was correlated to drug effect determined by a decrease in the size of lesions and grade of adverse events. Analysis was performed retrospectively. Eight patients received oral alpelisib through the compassionate use program of Novartis. AUC revealed substantial variability (3036 to 16620 ug*h/L) and inversely correlated to weight. Alpelisib resulted in marked clinical improvement, reducing pain, resolving coagulopathy, and improving mobility. Volumetric MRI indicated a 17.4% decrease in targeted vascular anomaly volume after 6 months of alpelisib therapy (p < 0.05), although volume decrease did not correlate with AUC. Adverse events including insulin resistance (n = 8/8) and growth restriction (n = 1/8) were documented, with severity directly correlating to drug exposure. We observed significant weight-related variability in alpelisib plasma concentrations, suggesting that the FDA-approved fixed-dose regimen of alpelisib is not optimal for pediatric patients. Weight-based dosing and therapeutic drug monitoring should be considered to enhance alpelisib safety.

Keywords:  Alpelisib; PIK3CA; PROS; pharmacology; targeted treatment; vascular anomalies; venous malformation

DOI:  https://doi.org/10.1080/08880018.2025.2498660
Front Cell Dev Biol. 2025 ;13 1589034

Systematic optimization of prime editing for enhanced efficiency and versatility in genome engineering across diverse cell types.

Huiling Mu, Yeyi Liu, Yijia Chi, Fei Wang, Shuting Meng, Yi Zhang, Xunting Wang, Dongxin Zhao.

  Prime editing offers remarkable versatility in genome editing, but its efficiency remains a major bottleneck. While continuous optimization of the prime editing enzymes and guide RNAs (pegRNAs) has improved editing outcomes, the method of delivery also plays a crucial role in overall performance. To maximize prime editing efficiency, we implemented a series of systematic optimizations, achieving up to 80% editing efficiency across multiple loci and cell lines. Beyond integrating the latest advancements in prime editing, our approach combined stable genomic integration of prime editors via the piggyBac transposon system, selection of integrated single clones, the use of an enhanced promoter, and lentiviral delivery of pegRNAs, ensuring robust, ubiquitous, and sustained expression of both prime editors and pegRNAs. To further assess its efficacy in challenging cell types, we validated our optimized system in human pluripotent stem cells (hPSCs) in both primed and naïve states, achieving substantial editing efficiencies of up to 50%. Collectively, our optimized prime editing strategy provides a highly efficient and versatile framework for genome engineering in vitro, serving as a roadmap for refining prime editing technologies and expanding their applications in genetic research and therapeutic development.

Keywords:  genome engineering; piggyBac transposon system; pluripotent stem cells; prime editing; sustained expression

DOI:  https://doi.org/10.3389/fcell.2025.1589034
Commun Biol. 2025 May 13. 8(1): 739

Zebrafishology, study design guidelines for rigorous and reproducible data using zebrafish.

Victoria M Bedell, Priya Dubey, Han B Lee, Dondra S Bailey, Jennifer L Anderson, Allison Jamieson-Lucy, Rui Xiao, Elvin V Leonard, Marni J Falk, Michael A Pack, Mary Mullins, Steven A Farber, Roderic G Eckenhoff, Stephen C Ekker.

The zebrafish (Danio rerio) is one of the most widely used research model organisms funded by the United States' National Institutes of Health, second only to the mouse. Here, we discuss the advantages and unique qualities of this model organism. Additionally, we discuss key aspects of experimental design and statistical approaches that apply to studies using the zebrafish model organism. Finally, we list critical details that should be considered in the design of zebrafish experiments to enhance rigor and data reproducibility. These guidelines are designed to aid new researchers, journal editors, and manuscript reviewers in supporting the publication of the highest-quality zebrafish research.

DOI: https://doi.org/10.1038/s42003-025-07496-z
Sci Rep. 2025 May 13. 15(1): 16651

Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization.

Kaitlyn M Martinez, Kristen Wilding, Trent R Llewellyn, Daniel E Jacobsen, Makaela M Montoya, Jessica Z Kubicek-Sutherland, Sweta Batni, Carrie Manore, Harshini Mukundan.

  The complexity and variability of biological data has promoted the increased use of machine learning methods to understand processes and predict outcomes. These same features complicate reliable, reproducible, interpretable, and responsible use of such methods, resulting in questionable relevance of the derived. outcomes. Here we systematically explore challenges associated with applying machine learning to predict and understand biological processes using a well- characterized in vitro experimental system. We evaluated factors that vary while applying machine learning classifers: (1) type of biochemical signature (transcripts vs. proteins), (2) data curation methods (pre- and post-processing), and (3) choice of machine learning classifier. Using accuracy, generalizability, interpretability, and reproducibility as metrics, we found that the above factors significantly mod- ulate outcomes even within a simple model system. Our results caution against the unregulated use of machine learning methods in the biological sciences, and strongly advocate the need for data standards and validation tool-kits for such studies.

Keywords:  Biological data; Lipopolysaccharide; Machine learning; Standardization

DOI:  https://doi.org/10.1038/s41598-025-00245-6
Nat Genet. 2025 May;57(5): 1201-1212

An integrated transcriptomic cell atlas of human endoderm-derived organoids.

Quan Xu, Lennard Halle, Soroor Hediyeh-Zadeh, Merel Kuijs, Rya Riedweg, Umut Kilik, Timothy Recaldin, Qianhui Yu, Isabell Rall, Tristan Frum, Lukas Adam, Shrey Parikh, Raphael Kfuri-Rubens, Manuel Gander, Dominik Klein, Fabiola Curion, Zhisong He, Jonas Simon Fleck, Koen Oost, Maurice Kahnwald, Silvia Barbiero, Olga Mitrofanova, Grzegorz Jerzy Maciag, Kim B Jensen, Matthias Lutolf, Prisca Liberali, Jason R Spence, Nikolche Gjorevski, Joep Beumer, Barbara Treutlein, Fabian J Theis, J Gray Camp.

Human pluripotent stem cells and tissue-resident fetal and adult stem cells can generate epithelial tissues of endodermal origin in vitro that recapitulate aspects of developing and adult human physiology. Here, we integrate single-cell transcriptomes from 218 samples covering organoids and other models of diverse endoderm-derived tissues to establish an initial version of a human endoderm-derived organoid cell atlas. The integration includes nearly one million cells across diverse conditions, data sources and protocols. We compare cell types and states between organoid models and harmonize cell annotations through mapping to primary tissue counterparts. Focusing on the intestine and lung, we provide examples of mapping data from new protocols and show how the atlas can be used as a diverse cohort to assess perturbations and disease models. The human endoderm-derived organoid cell atlas makes diverse datasets centrally available and will be valuable to assess fidelity, characterize perturbed and diseased states, and streamline protocol development.

DOI: https://doi.org/10.1038/s41588-025-02182-6
Front Immunol. 2025 ;16 1572194

Case Report: Activated PI3-kinase-δ syndrome and ovarian malignancies: a case series from the European ESID-APDS registry.

Maria Pia Esposto, Nizar Mahlaoui, Hassan Abolhassani, Koen Van Aerde, Simone Cesaro, Anita Chandra, Stephan Ehl, Sven Kracker, Felipe Suarez, Vincent Barlogis, Alice Parisi, Maria Elena Maccari, Matteo Chinello.

  Activated phosphoinositide-3-kinase-delta (PI3Kδ) syndrome (APDS) is an autosomal dominant inborn error of immunity (IEI) characterized by combined immunodeficiency and immune dysregulation with increased risk for lymphoma and other non-lymphoid malignancies. We describe five patients with ovarian malignancies among 110 female APDS patients participating in the European Society for Immunodeficiencies (ESID) registry and identified three additional cases in the literature. These findings document a relevant predisposition to these non-hematological malignancies in APDS patients.

Keywords:  IEI; activated PI3-kinase-δ syndrome; cancer predisposition; female; inborn errors of immunity; ovarian cancer; ovarian malignancies

DOI:  https://doi.org/10.3389/fimmu.2025.1572194
Bioinformatics. 2025 May 10. pii: btaf300. [Epub ahead of print]

KINAID: an orthology-based kinase-substrate prediction and analysis tool for phosphoproteomics.

Javed M Aman, Audrey W Zhu, Martin Wühr, Stanislav Y Shvartsman, Mona Singh.

SUMMARY: Proteome-wide datasets of phosphorylated peptides, either measured in a condition of interest or in response to perturbations, are increasingly becoming available for model organisms across the evolutionary spectrum. We introduce KINAID (KINase Activity and Inference Dashboard), an interactive and extensible tool written in Dash/Plotly, that predicts kinase-substrate interactions, uncovers and displays kinases whose substrates are enriched amongst phosphorylated peptides, interactively illustrates kinase-substrate interactions, and clusters phosphopeptides targeted by similar kinases. KINAID is the first tool of its kind that can analyze data from not only H. sapiens but also 10 additional model organisms (including M. musculus, D. rerio, D. melanogaster, C. elegans, and S. cerevisiae). We demonstrate KINAID's utility by applying it to recently published S. cerevisiae phosphoproteomics data.
AVAILABILITY AND IMPLEMENTATION: Webserver at https://kinaid.princeton.edu; open-source python library at https://github.com/Singh-Lab/kinaid; archive at https://doi.org/10.24433/CO.8460107.v1.
SUPPLEMENTARY INFORMATION: Available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btaf300