bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2025–02–09
23 papers selected by
Ralitsa Radostinova Madsen, MRC-PPU
  1. Phospho-seq: integrated, multi-modal profiling of intracellular protein dynamics in single cells.
  2. Human iPSCs offer an alternative for modeling vascular malformation.
  3. NetworkCommons: bridging data, knowledge and methods to build and evaluate context-specific biological networks.
  4. Uncoupling of Akt and mTOR signaling drives resistance to Akt inhibition in PTEN loss prostate cancers.
  5. Clinical, genomic, and histopathologic diversity in cerebral cavernous malformations.
  6. PI3K regulates TAZ/YAP and mTORC1 axes that can be synergistically targeted.
  7. Endothelial insulin resistance induced by adrenomedullin mediates obesity-associated diabetes.
  8. Biophysical model for joint analysis of chromatin and RNA sequencing data.
  9. A practical guide to FAIR data management in the age of multi-OMICS and AI.
  10. 20 years of stemness: From stem cells to hypertranscription and back.
  11. Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells.
  12. Haploinsufficient phenotypes promote selection of PTEN and ARID1A-deficient clones in human colon.
  13. Phase II Study of Copanlisib in Patients With PTEN Loss: Results From NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols Z1G and Z1H.
  14. When everything is a master regulator, nothing is.
  15. Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks.
  16. Same same but different? How blood and lymphatic vessels induce cell contact inhibition.
  17. Flow, sense and divide.
  18. Structural requirements of isoform-specific inhibitors of Akt: Implications in the development of effective cancer treatment strategies.
  19. Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.
  20. Combinatorial mapping of E3 ubiquitin ligases to their target substrates.
  21. Translational regulation of SND1 governs endothelial homeostasis during stress.
  22. Transcriptome size matters for single-cell RNA-seq normalization and bulk deconvolution.
  23. Protein codes promote selective subcellular compartmentalization.
  1. Nat Commun. 2025 Feb 04. 16(1): 1346
    Phospho-seq: integrated, multi-modal profiling of intracellular protein dynamics in single cells.
    John D Blair, Austin Hartman, Fides Zenk, Philipp Wahle, Giovanna Brancati, Carol Dalgarno, Barbara Treutlein, Rahul Satija.
      Cell signaling plays a critical role in neurodevelopment, regulating cellular behavior and fate. While multimodal single-cell sequencing technologies are rapidly advancing, scalable and flexible profiling of cell signaling states alongside other molecular modalities remains challenging. Here we present Phospho-seq, an integrated approach that aims to quantify cytoplasmic and nuclear proteins, including those with post-translational modifications, and to connect their activity with cis-regulatory elements and transcriptional targets. We utilize a simplified benchtop antibody conjugation method to create large custom neuro-focused antibody panels for simultaneous protein and scATAC-seq profiling on whole cells, alongside both experimental and computational strategies to incorporate transcriptomic measurements. We apply our workflow to cell lines, induced pluripotent stem cells, and months-old retinal and brain organoids to demonstrate its broad applicability. We show that Phospho-seq can provide insights into cellular states and trajectories, shed light on gene regulatory relationships, and help explore the causes and effects of diverse cell signaling in neurodevelopment.
    DOI:  https://doi.org/10.1038/s41467-025-56590-7
  2. Cell Stem Cell. 2025 Feb 06. pii: S1934-5909(25)00008-6. [Epub ahead of print]32(2): 177-178
    Human iPSCs offer an alternative for modeling vascular malformation.
    Stefanie DeFronzo, Guohao Dai.
      In this issue of Cell Stem Cell, Pan et al. generated human induced pluripotent stem cell (iPSC)-derived venous endothelial cells (iVECs) by manipulating cell-cycle dynamics and Notch signaling and demonstrated that TIE2-mutant iVECs recapitulate the pathogenesis of venous malformations.1 Their study provides a model for further mechanistic studies and drug discovery.
    DOI:  https://doi.org/10.1016/j.stem.2025.01.008
  3. Bioinformatics. 2025 Feb 05. pii: btaf048. [Epub ahead of print]
    NetworkCommons: bridging data, knowledge and methods to build and evaluate context-specific biological networks.
    Victor Paton, Denes Türei, Olga Ivanova, Sophia Müller-Dott, Pablo Rodriguez-Mier, Veron I Ca Venafra, Livia Perfetto, Martin Garrido-Rodriguez, Julio Saez-Rodriguez.
       SUMMARY: We present NetworkCommons, a platform for integrating prior knowledge, omics data, and network inference methods, facilitating their usage and evaluation. NetworkCommons aims to be an infrastructure for the network biology community that supports the development of better methods and benchmarks, by enhancing interoperability and integration.
    AVAILABILITY AND IMPLEMENTATION: NetworkCommons is implemented in Python and offers programmatic access to multiple omics datasets, network inference methods, and benchmarking setups. It is a free software, available at https://github.com/saezlab/networkcommons, and deposited in Zenodo at https://doi.org/10.5281/zenodo.14719118  .
    SUPPLEMENTARY DATA: Contribution guidelines, additional figures, and descriptions for data, knowledge, methods, evaluation strategies and their implementation are available in the Supplementary Data and in the NetworkCommons documentation at https://networkcommons.readthedocs.io/.
    DOI:  https://doi.org/10.1093/bioinformatics/btaf048
  4. Sci Adv. 2025 Feb 07. 11(6): eadq3802
    Uncoupling of Akt and mTOR signaling drives resistance to Akt inhibition in PTEN loss prostate cancers.
    Ninghui Mao, Young Sun Lee, Nazifa Salsabeel, Zeda Zhang, Dan Li, Harmanpreet Kaur, Xiaoping Chen, Qing Chang, Sanjay Mehta, Jesse Barnes, Elisa de Stanchina, Ralph Garippa, Yu Chen, Charles Sawyers, Brett S Carver.
      Recent phase 3 clinical trial showed improved radiographic progression-free survival in PTEN-deficient prostate cancers treated with combined Akt and AR inhibition. Building on this and our previous research into PI3K and AR signaling interactions, we aimed to define the mechanisms of response and resistance to Akt inhibition. We discovered that restoration of mTOR signaling was the early dominant driver of resistance to Akt inhibition. Mechanistically, this can be achieved through molecular alterations, resulting in loss of negative regulators of mTOR. Unexpectedly, we discovered that this was dominated by restoration of mTOR signaling through the nutrient sensing arm. This can be achieved by loss of the components of the GATOR/KICSTOR complexes or through cellular processes, leading to the recycling of amino acids. The addition of an mTOR inhibitor restored sensitivity to Akt inhibition and represents a precision-based strategy to overcome resistance in the clinic.
    DOI:  https://doi.org/10.1126/sciadv.adq3802
  5. Acta Neuropathol Commun. 2025 Feb 05. 13(1): 23
    Clinical, genomic, and histopathologic diversity in cerebral cavernous malformations.
    Jian Ren, Daochao Wang, Leiming Wang, Chendan Jiang, An Tian, Ziwei Cui, Yeqing Ren, Lisong Bian, Gao Zeng, Guolu Meng, Yongzhi Shan, Jiantao Liang, Xinru Xiao, Jie Tang, Yukui Wei, Chuan He, Liyong Sun, Yongjie Ma, Jiaxing Yu, Guilin Li, Ming Ye, Peng Hu, Jingwei Li, Ye Li, Lijian Niu, Qianwen Li, Feng Ling, Jan-Karl Burkhardt, Hongqi Zhang, Tao Hong.
      Cerebral cavernous malformations (CCMs) are hemorrhagic vascular disorders with varied clinical and radiological presentations, occurring sporadically due to MAP3K3 or PIK3CA mutations or through inherited germline mutations of CCM genes. This study aimed to clarify the clinical, genetic, and pathological features of CCMs using a multicenter cohort across three Chinese centers. We analyzed 290 surgical specimens from symptomatic CCM patients, utilizing whole-exome sequencing, droplet digital PCR, and targeted panel sequencing, alongside immunohistology to examine genotypic and phenotypic differences. Among 290 cases, 201 had somatic MAP3K3, PIK3CA, or germline CCM mutations, each associated with distinct clinical parameters: hemorrhage risk (P < 0.001), lesion size (P = 0.019), non-hemorrhagic epilepsy (P < 0.001), Zabramski classifications (P < 0.001), developmental venous anomaly presence (P < 0.001), and MRI-detected edema (P < 0.001). PIK3CA mutations showed a higher hemorrhage risk than MAP3K3 and combined MAP3K3 & PIK3CA mutations (P < 0.001). Within PIK3CA mutations, the p.H1047R variant correlated with higher bleeding risk than p.E545K (P = 0.007). For non-hemorrhagic epilepsy, patients with single MAP3K3 mutations or combined MAP3K3 & PIK3CA mutations were at greater risk than those with PIK3CA mutations alone. Histopathologically, lesions with PIK3CA mutations displayed cyst walls, pS6-positive dilated capillaries, and fresh blood cells, while MAP3K3 and double mutation lesions exhibited classic CCM pathology with SMA-positive and KLF4-positive vessels, collagen, and calcification. PIK3CA lesions had fewer KLF4-positive cells than double mutations lesions (P < 0.001), and EndMT (SMA-positive) cells compared to double mutation lesions (P < 0.05) and MAP3K3 mutations (P < 0.001), with more pS6 compared to MAP3K3 mutations (P < 0.05). This study underscores the diverse clinical, genomic, and histopathological characteristics in CCMs, suggesting potential predictive markers based on mutation subtypes and MRI features.
    Keywords:   MAP3K3; PIK3CA ; Epilepsy; Hemorrhage; Vascular malformations
    DOI:  https://doi.org/10.1186/s40478-025-01940-1
  6. bioRxiv. 2025 Jan 22. pii: 2025.01.21.634138. [Epub ahead of print]
    PI3K regulates TAZ/YAP and mTORC1 axes that can be synergistically targeted.
    Keith C Garcia, Ali A Khan, Krishnendu Ghosh, Souradip Sinha, Nicholas Scalora, Gillian DeWane, Colleen Fullenkamp, Nicole Merritt, Yuliia Drebot, Samuel Yu, Mariah Leidinger, Michael D Henry, Patrick Breheny, Michael S Chimenti, Munir R Tanas.
       Purpose: Sarcomas are a heterogeneous group of cancers with few shared therapeutic targets. PI3K signaling is activated in various subsets of sarcomas, representing a shared oncogenic signaling pathway. Oncogenic PI3K signaling has been challenging to target therapeutically. An integrated view of PI3K and Hippo pathway signaling is examined to determine if this could be leveraged therapeutically.
    Experimental design: A tissue microarray containing sarcomas of various histological types was evaluated for PTEN loss and correlated with levels of activated TAZ and YAP. PI3K and Hippo pathways were dissected in sarcoma cell lines. The role of TAZ and YAP were evaluated in a PI3K-driven mouse model. The efficacy of mTORC1 inhibition and TEAD inhibition were evaluated in sarcoma cell lines and in vivo .
    Results: PI3K signaling is frequently activated in sarcomas due to PTEN loss (in 30-60%), representing a common therapeutic target. TAZ and YAP are transcriptional co-activators regulated by PI3K and drive a transcriptome necessary for tumor growth in a PI3K-driven sarcoma mouse model. Combination therapy using IK-930 (TEAD inhibitor) and everolimus (mTORC1 inhibitor) synergistically diminished proliferation and anchorage independent growth of PI3K-activated sarcoma cell lines at low, physiologically achievable doses. Furthermore, this combination therapy showed a synergistic effect in vivo , reducing tumor proliferation and size.
    Conclusions: TAZ and YAP are transcriptional co-activators downstream of PI3K signaling, a pathway that has lacked a well-defined oncogenic transcription factor. This PI3K-TAZ/YAP axis exists in parallel to the known PI3K-Akt-mTORC1 axis allowing for synergistic combination therapy targeting the TAZ/YAP-TEAD interaction and mTORC1 in sarcomas.
    DOI:  https://doi.org/10.1101/2025.01.21.634138
  7. Science. 2025 Feb 07. 387(6734): 674-682
    Endothelial insulin resistance induced by adrenomedullin mediates obesity-associated diabetes.
    Haaglim Cho, Chien-Cheng Lai, Rémy Bonnavion, Mohamad Wessam Alnouri, ShengPeng Wang, Kenneth Anthony Roquid, Haruya Kawase, Diana Campos, Min Chen, Lee S Weinstein, Alfredo Martínez, Mario Looso, Miloslav Sanda, Stefan Offermanns.
      Insulin resistance is a hallmark of obesity-associated type 2 diabetes. Insulin's actions go beyond metabolic cells and also involve blood vessels, where insulin increases capillary blood flow and delivery of insulin and nutrients. We show that adrenomedullin, whose plasma levels are increased in obese humans and mice, inhibited insulin signaling in human endothelial cells through protein-tyrosine phosphatase 1B-mediated dephosphorylation of the insulin receptor. In obese mice lacking the endothelial adrenomedullin receptor, insulin-induced endothelial nitric oxide-synthase activation and skeletal muscle perfusion were increased. Treating mice with adrenomedullin mimicked the effect of obesity and induced endothelial and systemic insulin resistance. Endothelial loss or blockade of the adrenomedullin receptor improved obesity-induced insulin resistance. These findings identify a mechanism underlying obesity-induced systemic insulin resistance and suggest approaches to treat obesity-associated type 2 diabetes.
    DOI:  https://doi.org/10.1126/science.adr4731
  8. Phys Rev E. 2024 Dec;110(6-1): 064405
    Biophysical model for joint analysis of chromatin and RNA sequencing data.
    Catherine Felce, Gennady Gorin, Lior Pachter.
      The assay for transposase-accessible chromatin using sequencing (ATAC-seq) can be used to identify open chromatin regions, providing complementary information to RNA-seq which measures gene expression by sequencing. Single-cell multiome methods offer the possibility of measuring both modalities simultaneously in cells, raising the question of how to analyze them jointly, and also the extent to which the information they provide is better than unregistered data, where single-cell ATAC-seq and single-cell RNA-seq are performed on the same sample, but on different cells. We propose and motivate a biophysical model for chromatin dynamics and subsequent transcription that can be used to parametrize multiome data, and use it to assess the benefits of multiome data over unregistered single-cell RNA-seq and single-cell ATAC-seq. We also show that our model provides a biophysically grounded approach to the integration of chromatin accessibility data with other modalitie, and apply the model to single-cell ATAC-seq data.
    DOI:  https://doi.org/10.1103/PhysRevE.110.064405
  9. Front Immunol. 2024 ;15 1439434
    A practical guide to FAIR data management in the age of multi-OMICS and AI.
    Douaa Mugahid, Jared Lyon, Charlie Demurjian, Nathan Eolin, Charlie Whittaker, Mark Godek, Douglas Lauffenburger, Sarah Fortune, Stuart Levine.
      Multi-cellular biological systems, including the immune system, are highly complex, dynamic, and adaptable. Systems biologists aim to understand such complexity at a quantitative level. However, these ambitious efforts are often limited by access to a variety of high-density intra-, extra- and multi-cellular measurements resolved in time and space and across a variety of perturbations. The advent of automation, OMICs and single-cell technologies now allows high dimensional multi-modal data acquisition from the same biological samples multiplexed at scale (multi-OMICs). As a result, systems biologists -theoretically- have access to more data than ever. However, the mathematical frameworks and computational tools needed to analyze and interpret such data are often still nascent, limiting the biological insights that can be obtained without years of computational method development and validation. More pressingly, much of the data sits in silos in formats that are incomprehensible to other scientists or machines limiting its value to the vaster scientific community, especially the computational biologists tasked with analyzing these vast amounts of data in more nuanced ways. With the rapid development and increasing interest in using artificial intelligence (AI) for the life sciences, improving how biologic data is organized and shared is more pressing than ever for scientific progress. Here, we outline a practical approach to multi-modal data management and FAIR sharing, which are in line with the latest US and EU funders' data sharing policies. This framework can help extend the longevity and utility of data by allowing facile use and reuse, accelerating scientific discovery in the biomedical sciences.
    Keywords:  FAIR data; OMICs; Science administration; artificial intelligence; immunology; modeling; multi-modal data; systems biology
    DOI:  https://doi.org/10.3389/fimmu.2024.1439434
  10. Stem Cell Reports. 2025 Feb 03. pii: S2213-6711(25)00010-4. [Epub ahead of print] 102406
    20 years of stemness: From stem cells to hypertranscription and back.
    Yun-Kyo Kim, Miguel Ramalho-Santos.
      Transcriptional profiling of stem cells came of age at the beginning of the century with the use of microarrays to analyze cell populations in bulk. Since then, stem cell transcriptomics has become increasingly sophisticated, notably with the recent widespread use of single-cell RNA sequencing. Here, we provide a perspective on how an early signature of genes upregulated in embryonic and adult stem cells, identified using microarrays over 20 years ago, serendipitously led to the recent discovery that stem/progenitor cells across organs are in a state of hypertranscription, a global elevation of the transcriptome. Looking back, we find that the 2002 stemness signature is a robust marker of stem cell hypertranscription, even though it was developed well before it was known what hypertranscription meant or how to detect it. We anticipate that studies of stem cell hypertranscription will be rich in novel insights in physiological and disease contexts for years to come.
    Keywords:  RNA-seq; absolute scaling; adult stem cells; cell number normalization; embryonic stem cells; hypertranscription; regeneration; single-cell RNA-seq; stemness
    DOI:  https://doi.org/10.1016/j.stemcr.2025.102406
  11. bioRxiv. 2025 Jan 23. pii: 2025.01.21.633969. [Epub ahead of print]
    Benchmarking and optimizing Perturb-seq in differentiating human pluripotent stem cells.
    Sushama Sivakumar, Yihan Wang, Sean C Goetsch, Vrushali Pandit, Lei Wang, Huan Zhao, Anjana Sundarrajan, Daniel Armendariz, Chikara Takeuchi, Mpathi Nzima, Wei-Chen Chen, Ashley E Dederich, Lauretta El Hayek, Taosha Gao, Renad Ghazawi, Ashlesha Gogate, Kiran Kaur, Hyung Bum Kim, Melissa K McCoy, Hanspeter Niederstrasser, Seiya Oura, Carolos A Pinzon-Arteaga, Menaka Sanghvi, Daniel A Schmitz, Leqian Yu, Yanfeng Zhang, Qinbo Zhou, W Lee Kraus, Lin Xu, Jun Wu, Bruce A Posner, Maria H Chahrour, Gary C Hon, Nikhil V Munshi.
      Perturb-seq is a powerful approach to systematically assess how genes and enhancers impact the molecular and cellular pathways of development and disease. However, technical challenges have limited its application in stem cell-based systems. Here, we benchmarked Perturb-seq across multiple CRISPRi modalities, on diverse genomic targets, in multiple human pluripotent stem cells, during directed differentiation to multiple lineages, and across multiple sgRNA delivery systems. To ensure cost-effective production of large-scale Perturb-seq datasets as part of the Impact of Genomic Variants on Function (IGVF) consortium, our optimized protocol dynamically assesses experiment quality across the weeks-long procedure. Our analysis of 1,996,260 sequenced cells across benchmarking datasets reveals shared regulatory networks linking disease-associated enhancers and genes with downstream targets during cardiomyocyte differentiation. This study establishes open tools and resources for interrogating genome function during stem cell differentiation.
    DOI:  https://doi.org/10.1101/2025.01.21.633969
  12. EMBO Rep. 2025 Feb 07.
    Haploinsufficient phenotypes promote selection of PTEN and ARID1A-deficient clones in human colon.
    Nefeli Skoufou-Papoutsaki, Sam Adler, Shenay Mehmed, Claire Tume, Cora Olpe, Edward Morrissey, Richard Kemp, Anne-Claire Girard, Elisa B Moutin, Chandra Sekhar Reddy Chilamakuri, Jodi L Miller, Cecilia Lindskog, Fabian Werle, Kate Marks, Francesca Perrone, Matthias Zilbauer, David S Tourigny, Douglas J Winton.
      Cancer driver mutations are defined by their high prevalence in cancers and presumed rarity in normal tissues. However, recent studies show that positive selection in normal epithelia can increase the prevalence of some cancer drivers. To determine their true cancer-driving potential, it is essential to evaluate how frequent these mutations are in normal tissues and what are their phenotypes. Here, we explore the bioavailability of somatic variants by quantifying age-related mutational burdens in normal human colonic epithelium using immunodetection in FFPE samples (N = 181 patients). Positive selection of variants of tumour suppressor genes PTEN and ARID1A associates with monoallelic gene loss as confirmed by CRISPR/Cas9 mutagenesis and changes in their downstream effectors. Comparison of the mutational burden in normal tissue and colorectal cancers allows quantification of cancer driver potency based on relative representation. Additionally, immune exclusion, a cancer hallmark feature, is observed within ARID1A-deficient clones in histologically normal tissue. The behaviour resulting from haploinsufficiency of PTEN and ARID1A demonstrates how somatic mosaicism of tumour suppressors arises and can predispose to cancer initiation.
    Keywords:  ARID1A; Clone Dynamics; Haploinsufficency; Normal Tissue; PTEN
    DOI:  https://doi.org/10.1038/s44319-025-00373-0
  13. JCO Precis Oncol. 2025 Feb;9 e2400451
    Phase II Study of Copanlisib in Patients With PTEN Loss: Results From NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols Z1G and Z1H.
    Mohamed A Gouda, Zihan Wei, Jordi Rodon, Michael A Davies, Filip Janku, Robert J Gray, Victoria Wang, Lisa M McShane, Larry V Rubinstein, David R Patton, P Mickey Williams, Stanley R Hamilton, Raymond Liu, Daniela A Bota, Paul L Swiecicki, Gary L Buchschacher, James V Tricoli, Barbara A Conley, Carlos L Arteaga, Lyndsay N Harris, Peter J O'Dwyer, Alice P Chen, Keith T Flaherty.
       PURPOSE: Copanlisib, a pan-class phosphatidylinositol 3-kinase (PI3K) inhibitor with activity predominantly against the PI3K-delta and PI3K-alpha isoforms, has shown promising results in preclinical cancer models with PTEN loss. Herein, we report the activity and safety data from the Z1G and Z1H subprotocols, which included patients with PTEN loss, of the National Cancer Institute Molecular Analysis for Therapy Choice trial.
    METHODS: Patients with complete loss of cytoplasmic and nuclear PTEN as determined by immunohistochemistry regardless of PTEN mutation or deletion status were included in subprotocol Z1G, and patients with a deleterious mutation in the PTEN gene and retained expression of PTEN were included in subprotocol Z1H. Copanlisib was given intravenously over 1 hour at a dose of 60 mg on days 1, 8, and 15 in a 21-day-on and 7-day-off schedule in 28-day cycles. Patients continued treatment until disease progression or unacceptable toxicity.
    RESULTS: Overall, 49 patients (20 patients in Z1G and 29 in Z1H) were included in the primary efficacy analyses. The objective response rates in both cohorts were 0% (Z1G; 90% CI, 0 to 13.9) and 3.4% (Z1H; 90% CI, 0.2 to 15.3), respectively. The median progression-free and overall survival durations were 1.8 months (90% CI, 1.4 to 3.9 months) and 13.7 months (90% CI, 6.8 to 18.3 months) for the Z1G cohort and 1.8 months (90% CI, 1.8 to 2.1 months) and 9.0 months (90% CI, 5.4 to 13.3 months) for the Z1H cohort, respectively.
    CONCLUSION: Our results do not support the antitumor activity of single-agent copanlisib in tumors with PTEN loss regardless of mutation or deletion status or PTEN deleterious mutations with PTEN expression.
    DOI:  https://doi.org/10.1200/PO-24-00451
  14. Mol Biol Cell. 2025 Mar 01. 36(3): pe3
    When everything is a master regulator, nothing is.
    Robert S Krauss, Michael Kyba.
      The term "master regulator" emerged in the 1960s and 1970s and referred to autoregulatory transcription factors that sat atop a developmental lineage. Since that time, usage of the term has increased and broadened to the point where it has lost clear meaning. Here we discuss the term "master regulator" with the goals of developing a consensus view of its definition and stimulating discussion on use of similar terms. We propose that the designation "master regulator" be reserved for transcription factors that are: 1) positioned at the top of a regulatory hierarchy specifying a cell lineage (and potentially specific cell states, such as hypoxia); and 2) sufficient to drive the transcriptional program characterizing that lineage or state. It is hoped that this piece will provide a precedent for use of additional terms applied to incompletely understood biological processes, resulting in experimentation that sheds light on such processes.
    DOI:  https://doi.org/10.1091/mbc.E24-11-0494
  15. iScience. 2025 Feb 21. 28(2): 111730
    Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks.
    Kishore Hari, Pradyumna Harlapur, Aashna Saxena, Kushal Haldar, Aishwarya Girish, Tanisha Malpani, Herbert Levine, Mohit Kumar Jolly.
      Cell-fate decisions involve coordinated genome-wide expression changes, typically leading to a limited number of phenotypes. Although often modeled as simple toggle switches, these rather simplistic representations often disregard the complexity of regulatory networks governing these changes. Here, we unravel design principles underlying complex cell decision-making networks in multiple contexts. We show that the emergent dynamics of these networks and corresponding transcriptomic data are consistently low-dimensional, as quantified by the variance explained by principal component 1 (PC1). This low dimensionality in phenotypic space arises from extensive feedback loops in these networks arranged to effectively enable the formation of two teams of mutually inhibiting nodes. We use team strength as a metric to quantify these feedback interactions and show its strong correlation with PC1 variance. Using artificial networks of varied topologies, we also establish the conditions for generating canalized cell-fate landscapes, offering insights into diverse binary cellular decision-making networks.
    Keywords:  Systems biology
    DOI:  https://doi.org/10.1016/j.isci.2024.111730
  16. Biochem Soc Trans. 2025 Feb 06. pii: BST20240573. [Epub ahead of print]53(1):
    Same same but different? How blood and lymphatic vessels induce cell contact inhibition.
    Claudia Carlantoni, Leon M H Liekfeld, Manu Beerens, Maike Frye.
      Endothelial cells (ECs) migrate, sprout, and proliferate in response to (lymph)angiogenic mitogens, such as vascular endothelial growth factors. When ECs reach high confluency and encounter spatial confinement, they establish mature cell-cell junctions, reduce proliferation, and enter a quiescent state through a process known as contact inhibition. However, EC quiescence is modulated not only by spatial confinement but also by other mechano-environmental factors, including blood or lymph flow and extracellular matrix properties. Changes in physical forces and intracellular signaling can disrupt contact inhibition, resulting in aberrant proliferation and vascular dysfunction. Therefore, it is critical to understand the mechanisms by which endothelial cells regulate contact inhibition. While contact inhibition has been well studied in blood endothelial cells (BECs), its regulation in lymphatic endothelial cells (LECs) remains largely unexplored. Here, we review the current knowledge on extrinsic stimuli and intrinsic molecular pathways that govern endothelial contact inhibition and highlight nuanced differences between BECs and LECs. Furthermore, we provide perspectives for future research on lymphatic contact inhibition. A deeper understanding of the BEC and LEC-specific pathways underlying contact inhibition may enable targeted modulation of this process in blood or lymphatic vessels with relevance to lymphatic or blood vascular-specific disorders.
    Keywords:  (lymph)angiogenesis; CIP; Hippo pathway; Notch; PDE2A; blood endothelial cells; cadherins; cell cycle; contact inhibition; contact inhibition of proliferation; lymphatic endothelial cells; proliferation; vascular development
    DOI:  https://doi.org/10.1042/BST20240573
  17. Nat Cell Biol. 2025 Jan 31.
    Flow, sense and divide.
    Nicoletta I Petridou.
      
    DOI:  https://doi.org/10.1038/s41556-024-01591-9
  18. Eur J Med Chem. 2025 Jan 27. pii: S0223-5234(25)00099-6. [Epub ahead of print]287 117334
    Structural requirements of isoform-specific inhibitors of Akt: Implications in the development of effective cancer treatment strategies.
    Tenzin Adon, Sanyukta Bhattacharya, SubbaRao V Madhunapantula, Honnavalli Yogish Kumar.
      Akt, also known as protein kinase-B, is an important therapeutic target in the treatment of cancer due to its pivotal roles in the signaling pathways that regulate various hall-mark features of cancer cells such as cell growth, survival, migration, differentiation, and metabolism. The three closely related isoforms of Akt viz., Akt1, Akt2, and Akt3 exhibit distinct physiological roles that affect cellular behavior and tumor development, making isoform selectivity a crucial driving factor in the design and development of inhibitors. This review outlines key amino acids and their structural traits in Akt isoforms, potentially dictating isoform selectivity. We present an analysis of existing structure-activity relationship data of covalent-allosteric Akt inhibitors to shed light on isoform selectivity. Additionally, a brief review of potential predictive biomarkers in enhancing the therapeutic efficacy of Akt inhibitors is presented. Identifying biomarkers that can reliably predict patient response to treatment is crucial for personalizing cancer therapies and improving overall treatment outcomes. By integrating predictive biomarker identification with the ongoing development of isoform-selective Akt inhibitors, it is plausible to establish a foundation for more precise and efficacious interventions in cancer therapy.
    Keywords:  Akt; Covalent-allosteric Akt inhibitors; Isoform selectivity; Predictive biomarker
    DOI:  https://doi.org/10.1016/j.ejmech.2025.117334
  19. Cell Syst. 2025 Jan 31. pii: S2405-4712(25)00028-6. [Epub ahead of print] 101195
    Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.
    Shang Li, Qunlun Shen, Shihua Zhang.
      Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  data integration; single-cell RNA sequencing; spatial localization; spatial transcriptomics; supervised auto-encoder
    DOI:  https://doi.org/10.1016/j.cels.2025.101195
  20. Mol Cell. 2025 Feb 03. pii: S1097-2765(25)00051-6. [Epub ahead of print]
    Combinatorial mapping of E3 ubiquitin ligases to their target substrates.
    Chase C Suiter, Diego Calderon, David S Lee, Melodie Chiu, Shruti Jain, Florence M Chardon, Choli Lee, Riza M Daza, Cole Trapnell, Ning Zheng, Jay Shendure.
      E3 ubiquitin ligases (E3s) confer specificity of protein degradation through ubiquitination of substrate proteins. Yet, the vast majority of the >600 human E3s have no known substrates. To identify proteolytic E3-substrate pairs at scale, we developed combinatorial mapping of E3 targets (COMET), a framework for testing the role of many E3s in degrading many candidate substrates within a single experiment. We applied COMET to SCF ubiquitin ligase subunits that mediate degradation of target substrates (6,716 F-box-ORF [open reading frame] combinations) and E3s that degrade short-lived transcription factors (TFs) (26,028 E3-TF combinations). Our data suggest that many E3-substrate relationships are complex rather than 1:1 associations. Finally, we leverage deep learning to predict the structural basis of E3-substrate interactions and probe the strengths and limits of such models. Looking forward, we consider the practicality of transposing this framework, i.e., computational structural prediction of all possible E3-substrate interactions, followed by multiplex experimental validation.
    Keywords:  benchmarking; deep learning; high-throughput screening; machine learning; proteolysis; structure prediction; ubiquitin; ubiquitin ligases
    DOI:  https://doi.org/10.1016/j.molcel.2025.01.016
  21. J Clin Invest. 2025 Feb 03. pii: e168730. [Epub ahead of print]135(3):
    Translational regulation of SND1 governs endothelial homeostasis during stress.
    Zhenbo Han, Gege Yan, Jordan Jousma, Sarath Babu Nukala, Mehdi Amiri, Stephen Kiniry, Negar Tabatabaei, Youjeong Kwon, Sen Zhang, Jalees Rehman, Sandra Pinho, Sang-Bing Ong, Pavel V Baranov, Soroush Tahmasebi, Sang-Ging Ong.
      Translational control shapes the proteome and is particularly important in regulating gene expression under stress. A key source of endothelial stress is treatment with tyrosine kinase inhibitors (TKIs), which lowers cancer mortality but increases cardiovascular mortality. Using a human induced pluripotent stem cell-derived endothelial cell (hiPSC-EC) model of sunitinib-induced vascular dysfunction combined with ribosome profiling, we assessed the role of translational control in hiPSC-ECs in response to stress. We identified staphylococcal nuclease and tudor domain-containing protein 1 (SND1) as a sunitinib-dependent translationally repressed gene. SND1 translational repression was mediated by the mTORC1/4E-BP1 pathway. SND1 inhibition led to endothelial dysfunction, whereas SND1 OE protected against sunitinib-induced endothelial dysfunction. Mechanistically, SND1 transcriptionally regulated UBE2N, an E2-conjugating enzyme that mediates K63-linked ubiquitination. UBE2N along with the E3 ligases RNF8 and RNF168 regulated the DNA damage repair response pathway to mitigate the deleterious effects of sunitinib. In silico analysis of FDA-approved drugs led to the identification of an ACE inhibitor, ramipril, that protected against sunitinib-induced vascular dysfunction in vitro and in vivo, all while preserving the efficacy of cancer therapy. Our study established a central role for translational control of SND1 in sunitinib-induced endothelial dysfunction that could potentially be therapeutically targeted to reduce sunitinib-induced vascular toxicity.
    Keywords:  Cancer; Cardiovascular disease; Endothelial cells; Vascular biology
    DOI:  https://doi.org/10.1172/JCI168730
  22. Nat Commun. 2025 Feb 01. 16(1): 1246
    Transcriptome size matters for single-cell RNA-seq normalization and bulk deconvolution.
    Songjian Lu, Jiyuan Yang, Lei Yan, Jingjing Liu, Judy Jiaru Wang, Rhea Jain, Jiyang Yu.
      The variation of transcriptome size across cell types significantly impacts single-cell RNA sequencing (scRNA-seq) data normalization and bulk RNA-seq cellular deconvolution, yet this intrinsic feature is often overlooked. Here we introduce ReDeconv, a computational algorithm that incorporates transcriptome size into scRNA-seq normalization and bulk deconvolution. ReDeconv introduces a scRNA-seq normalization approach, Count based on Linearized Transcriptome Size (CLTS), which corrects differential expressed genes typically misidentified by standard count per 10 K normalization, as confirmed by orthogonal validations. By maintaining transcriptome size variation, CLTS-normalized scRNA-seq enhances the accuracy of bulk deconvolution. Additionally, ReDeconv mitigates gene length effects and models expression variances, thereby improving deconvolution outcomes, particularly for rare cell types. Evaluated with both synthetic and real datasets, ReDeconv surpasses existing methods in precision. ReDeconv alters the practice and provides a new standard for scRNA-seq analyses and bulk deconvolution. The software packages and a user-friendly web portal are available.
    DOI:  https://doi.org/10.1038/s41467-025-56623-1
  23. Science. 2025 Feb 06. eadq2634
    Protein codes promote selective subcellular compartmentalization.
    Henry R Kilgore, Itamar Chinn, Peter G Mikhael, Ilan Mitnikov, Catherine Van Dongen, Guy Zylberberg, Lena Afeyan, Salman F Banani, Susana Wilson-Hawken, Tong Ihn Lee, Regina Barzilay, Richard A Young.
      Cells have evolved mechanisms to distribute ~10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must assemble. Here, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. A protein language model, ProtGPS, was developed that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in the nucleolus. ProtGPS identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code, but also a previously unrecognized code governing their distribution to diverse subcellular compartments.
    DOI:  https://doi.org/10.1126/science.adq2634
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