bims-pideca 2025-08-03 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2025–08–03
seventeen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

FGF-induced phospholipase Cγ signaling regulates lacrimal gland branching by competing with PI3K in phosphoinositide metabolism.
Transient APC/C inactivation by mTOR boosts glycolysis during cell cycle entry.
Cell cycle dependence of ERK activation dynamics is regulated by PI3K and PAK1 signaling.
PSCS: Unified Sharing of Single-Cell Omics Data, Analyses, and Results.
Proteomic analyses identify targets, pathways, and cellular consequences of oncogenic KRAS signaling.
Safety findings from the phase 1/2 MOSAIC study of miransertib for patients with PIK3CA-related overgrowth spectrum or Proteus syndrome.
Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories.
Aberrant lysosomal dynamics disrupt myogenesis via mTORC1 signalling in X-linked myotubular myopathy.
Engineering fluorescent reporters in human pluripotent stem cells and strategies for live imaging human neurogenesis.
Advances and optimization strategies in prime editing of human pluripotent stem cells.
MOTL: enhancing multi-omics matrix factorization with transfer learning.
Robust consensus nuclear and cell segmentation.
Empowering bioinformatics communities with Nextflow and nf-core.
Drug resistance and tumor heterogeneity: cells and ensembles.
Protocol update to: High-throughput scNMT protocol for multiomics profiling of single cells from mouse brain and pancreatic organoids.
From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.
Principal mechanisms of extracellular matrix-mediated cell-cell communication in physiological and tumor microenvironments.

Cell Rep. 2025 Jul 23. pii: S2211-1247(25)00817-4. [Epub ahead of print]44(8): 116046

FGF-induced phospholipase Cγ signaling regulates lacrimal gland branching by competing with PI3K in phosphoinositide metabolism.

Qian Wang, Chenqi Tao, Yihua Wu, Karen E Anderson, Neoklis Makrides, Abdul Hannan, John Peregrin, Chyuan-Sheng Lin, Zhipeng Ding, Wei Li, Phillip Hawkins, Len Stephens, Xin Zhang.

  Although the regulation of branching morphogenesis by spatially distributed cues is well established, the underlying intracellular signaling mechanisms are not well understood. The development of the lacrimal gland is driven by fibroblast growth factor (FGF) signaling, which activates phospholipase C gamma (PLCγ). Here, we showed that mutating the PLCγ1 binding site on Fgfr2 leads to ectopic branching and hyperplasia in the lacrimal gland, which was phenocopied by either deleting PLCγ1 or disabling any of its SH2 domains. PLCγ1 inactivation did not change the level of Fgfr2 or affect mitogen-activated protein kinase (MAPK) signaling but instead led to sustained AKT phosphorylation due to increased phosphatidylinositol 3,4,5-trisphosphate (PIP3) production. Consistent with this, the PLCγ1 mutant phenotype can be reproduced by the elevation of phosphatidylinositol 3-kinase (PI3K) signaling in Pten knockout and attenuated by blocking AKT signaling. Our findings demonstrate that FGF-activated PLCγ modulates PI3K signaling by shifting phosphoinositide metabolism, revealing the crucial role of PLCγ in branching morphogenesis and organ size control.

Keywords:  AKT; CP: Developmental biology; FGF; PIP3; PLCγ; PTEN; lacrimal gland

DOI:  https://doi.org/10.1016/j.celrep.2025.116046
Nature. 2025 Jul 30.

Transient APC/C inactivation by mTOR boosts glycolysis during cell cycle entry.

Debasish Paul, Derek L Bolhuis, Hualong Yan, Sudipto Das, Xia Xu, Christina C Abbate, Lisa M M Jenkins, Michael J Emanuele, Thorkell Andresson, Jing Huang, John G Albeck, Nicholas G Brown, Steven D Cappell.

Mammalian cells entering the cell cycle favour glycolysis to rapidly generate ATP and produce the biosynthetic intermediates that are required for rapid biomass accumulation1. Simultaneously, the ubiquitin-ligase anaphase-promoting complex/cyclosome and its coactivator CDH1 (APC/CCDH1) remains active, allowing origin licensing and blocking premature DNA replication. Paradoxically, glycolysis is reduced by APC/CCDH1 through the degradation of key glycolytic enzymes2, raising the question of how cells coordinate these mutually exclusive events to ensure proper cell division. Here we show that cells resolve this paradox by transiently inactivating the APC/C during cell cycle entry, which allows a transient metabolic shift favouring glycolysis. After mitogen stimulation, rapid mTOR-mediated phosphorylation of the APC/C adapter protein CDH1 at the amino terminus causes it to partially dissociate from the APC/C. This partial inactivation of the APC/C leads to the accumulation of PFKFB3, a rate-limiting enzyme for glycolysis, promoting a metabolic shift towards glycolysis. Delayed accumulation of phosphatase activity later removes CDH1 phosphorylation, restoring full APC/C activity, and shifting cells back to favouring oxidative phosphorylation. Thus, cells coordinate the simultaneous demands of cell cycle progression and metabolism through an incoherent feedforward loop, which transiently inhibits APC/C activity to generate a pulse of glycolysis that is required for mammalian cell cycle entry.

DOI: https://doi.org/10.1038/s41586-025-09328-w
Sci Rep. 2025 Jul 29. 15(1): 27688

Cell cycle dependence of ERK activation dynamics is regulated by PI3K and PAK1 signaling.

Ryo Yoshizawa, Yasushi Sako.

Growth factor-induced RTK/RAS/MAPK signaling is crucial for cell cycle progression, including G1 to S and G2 to M phase transitions. However, the regulatory mechanism of MAPK (ERK) in the S-G2M phase remains unclear. In this study, we analyzed the nuclear translocation dynamics of fluorescently labeled ERK induced by EGF during cell cycle progression and simultaneously analyzed the membrane translocation dynamics of GRB2 and PI3K. The transient ERK dynamics in a population of cells with a high frequency of G0/G1 cells became sustained with the increase in S-G2M cells. The sustained localization of PI3K, rather than GRB2, showed a stronger correlation with nuclear ERK localization. PI3K-mediated PAK1 activation was essential for ERK translocation. EGFR/PI3K clusters frequently formed on the plasma membrane and were rapidly endocytosed in the high G0/G1 cell population, resulting in transient PI3K localization, whereas dispersed PI3K predominated in the high S-G2M cells, resulting in sustained PI3K localization. On the other hand, PAK1 remained on the plasma membrane. Our results suggest that the sustained spatial colocalization of PI3K and PAK1, particularly in the S-G2M phase, prolonged the PAK1 signaling for ERK activation. Sustained ERK activation was also correlated with a shorter time to cell division.

DOI: https://doi.org/10.1038/s41598-025-13686-w
J Proteome Res. 2025 Aug 01.

PSCS: Unified Sharing of Single-Cell Omics Data, Analyses, and Results.

Alexandre Hutton, Lizhuo Ai, Jesse G Meyer.

  Single-cell omics data analyses are complicated to design and difficult to distribute or reproduce. We present a web platform that enables no-code analysis pipeline design, computing, and the sharing of entire data analysis pipelines, their input data, and interactive results as a unit. We expect this platform to improve the accessibility and reproducibility of single-cell omics.

Keywords:  data analysis; data distribution; proteomics; reproducibility; reuse; transcriptomics

DOI:  https://doi.org/10.1021/acs.jproteome.5c00178
Sci Signal. 2025 Jul 29. 18(897): eadt6552

Proteomic analyses identify targets, pathways, and cellular consequences of oncogenic KRAS signaling.

Nicole Kabella, Florian P Bayer, Konstantinos Stamatiou, Miriam Abele, Amirhossein Sakhteman, Yun-Chien Chang, Vinona Wagner, Antje Gabriel, Johannes Krumm, Maria Reinecke, Melanie Holzner, Michael Aigner, Matthew The, Hannes Hahne, Florian Bassermann, Christina Ludwig, Paola Vagnarelli, Bernhard Kuster.

Mutations that activate the small GTPase KRAS are a frequent genetic alteration in cancer, and drug discovery efforts have led to inhibitors that block KRAS activity. We sought to better understand oncogenic KRAS signaling and the cytostatic effects of drugs that target this system. We performed proteomic analyses to investigate changes in protein abundance and posttranslational modifications in inhibitor-treated human KRAS-mutant pancreatic (KRAS G12C and G12D) and lung cancer (KRAS G12C) cells. The inhibitors used target these mutant forms of KRAS, the downstream effectors MEK and ERK, and the upstream regulators SHP2 and SOS1. Comparisons of phosphoproteomes between cell lines revealed a core KRAS signaling signature and cell line-specific signaling networks. In all cell lines, phosphoproteomes were dominated by different degrees of autonomous, oncogenic KRAS activity. Comparison of phosphoproteomes after short and long drug exposures revealed the temporal dynamics of KRAS-MEK-ERK axis inhibition that resulted in cell cycle exit. This transition to a quiescent state occurred in the absence of substantial proteome remodeling but included broad changes in protein phosphorylation and ubiquitylation. The collective data reveal insights into oncogenic KRAS signaling, place many additional proteins into this functional context, and implicate cell cycle exit as a mechanism by which cells evade death upon KRAS signaling inhibition.

DOI: https://doi.org/10.1126/scisignal.adt6552
Orphanet J Rare Dis. 2025 Jul 25. 20(1): 375

Safety findings from the phase 1/2 MOSAIC study of miransertib for patients with PIK3CA-related overgrowth spectrum or Proteus syndrome.

Whitney Eng, Ionela Iacobas, Jonathan Perkins, Giuseppe Zampino, Chiara Leoni, Paola Sabrina Buonuomo, Alessandra Simonetti, Himanshu Goel, Michael Briones, Mo Huang, Gregory Goldmacher, Danny Liaw, Adrienne Hammill.

   BACKGROUND: PIK3CA-related overgrowth spectrum (PROS) and Proteus syndrome are associated with mosaic tissue overgrowth of varying severity that commonly presents in childhood. The multicenter, open-label, phase 1/2 MOSAIC study (NCT03094832) was designed to evaluate the clinical efficacy and safety of the selective pan-AKT inhibitor miransertib for participants with PROS or Proteus syndrome.
METHODS: Participants ≥ 2 years of age with PROS with documented somatic PIK3CA mutations or Proteus syndrome with documented somatic AKT1 mutations were enrolled to receive oral miransertib at a starting dose of 15 mg/m2 every day for the first 3 cycles (1 cycle = 28 days) and miransertib 25 mg/m2 every day thereafter, provided no clinically significant drug-related toxicities were observed. The initial primary objective of the study was to assess clinical response to miransertib. Due to study design and data collection limitations, evaluating efficacy was no longer considered feasible and the primary objective was updated in 2021 to evaluate the safety and tolerability of miransertib.
RESULTS: Between May 16, 2017 and January 25, 2021, 49 participants were enrolled and received ≥ 1 dose of study drug, comprising the safety analysis population. Forty-five participants had a diagnosis of PROS and four had a diagnosis of Proteus syndrome. The median (range) age at enrollment was 7 years (2-41). Median (range) duration of treatment was 20.5 months (9.9-45.6). A total of 23 (46.9%) participants had a drug-related adverse event, most commonly decreased neutrophil count (n = 6, 12.2%), increased blood insulin (n = 5, 10.2%), and stomatitis (n = 5, 10.2%). One (2.0%) participant experienced a grade 3 drug-related adverse event (deep vein thrombosis). No drug-related adverse events led to early study discontinuation or death. Laboratory assessment values remained generally stable throughout the study.
CONCLUSION: Miransertib was safe and tolerable in participants with a confirmed diagnosis of PROS or Proteus syndrome. Future investigations are needed to determine whether patients receive measurable clinical benefit from miransertib.
TRIAL REGISTRATION: NCT03094832 registered Mar 28, 2017, https://clinicaltrials.gov/ct2/show/NCT03094832 .

Keywords:   AKT ; PIK3CA ; PIK3CA-related overgrowth spectrum; Miransertib; Proteus syndrome

DOI:  https://doi.org/10.1186/s13023-025-03831-z
Cell. 2025 Jul 25. pii: S0092-8674(25)00750-0. [Epub ahead of print]

Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories.

Jeanette A I Johnson, Daniel R Bergman, Heber L Rocha, David L Zhou, Eric Cramer, Ian C Mclean, Yoseph W Dance, Max Booth, Zachary Nicholas, Tamara Lopez-Vidal, Atul Deshpande, Randy Heiland, Elmar Bucher, Fatemeh Shojaeian, Matthew Dunworth, André Forjaz, Michael Getz, Inês Godet, Furkan Kurtoglu, Melissa Lyman, John Metzcar, Jacob T Mitchell, Andrew Raddatz, Jacobo Solorzano, Aneequa Sundus, Yafei Wang, David G DeNardo, Andrew J Ewald, Daniele M Gilkes, Luciane T Kagohara, Ashley L Kiemen, Elizabeth D Thompson, Denis Wirtz, Laura D Wood, Pei-Hsun Wu, Neeha Zaidi, Lei Zheng, Jacquelyn W Zimmerman, Jude M Phillip, Elizabeth M Jaffee, Joe W Gray, Lisa M Coussens, Young Hwan Chang, Laura M Heiser, Genevieve L Stein-O'Brien, Elana J Fertig, Paul Macklin.

  Cells interact as dynamically evolving ecosystems. While recent single-cell and spatial multi-omics technologies quantify individual cell characteristics, predicting their evolution requires mathematical modeling. We propose a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This enables systematic integration of biological knowledge and multi-omics data to generate in silico models, enabling virtual "thought experiments" that test and expand our understanding of multicellular systems and generate new testable hypotheses. This paper motivates and describes the grammar, offers a reference implementation, and demonstrates its use in developing both de novo mechanistic models and those informed by multi-omics data. We show its potential through examples in cancer and its broader applicability in simulating brain development. This approach bridges biological, clinical, and systems biology research for mathematical modeling at scale, allowing the community to predict emergent multicellular behavior.

Keywords:  agent-based modeling; cancer biology; cell behavior hypothesis grammar; cell behaviors; cell interactions; immunology; immunotherapy; mathematical biology; mathematical modeling; modeling language; multi-omics; multicellular systems; multicellular systems biology; physics of multicellular biology; simulation; spatial transcriptomics; tissue dynamics

DOI:  https://doi.org/10.1016/j.cell.2025.06.048
Brain. 2025 Jul 29. pii: awaf278. [Epub ahead of print]

Aberrant lysosomal dynamics disrupt myogenesis via mTORC1 signalling in X-linked myotubular myopathy.

Kengo Kora, Takeshi Yoshida, Atsushi Yokoyama, Kei Fujiwara, Naoko Yano, Taisei Kayaki, Satoshi Kajimoto, Kinuko Nishikawa, Hidetoshi Sakurai, Junko Takita.

  X-linked myotubular myopathy is a severe congenital muscle disorder caused by pathogenic variants in the MTM1 gene, which encodes the phosphoinositide phosphatase myotubularin. Muscle biopsies from patients with X-linked myotubular myopathy exhibit distinctive histopathological features, including small, rounded myofibres with centrally located nuclei, indicating a developmental defect in muscle maturation. While earlier studies have indicated that myotubularin dysfunction causes dysregulation of mechanistic target of rapamycin complex 1 (mTORC1) signalling, the underlying mechanisms and phenotypic impact on human muscle cells remain poorly understood. Currently, there are no approved therapies available for the treatment of this disorder. In this study, we established an induced pluripotent stem cell-based model of X-linked myotubular myopathy using two pairs of isogenic induced pluripotent stem cells: healthy-control versus MTM1-knockout and patient-derived versus gene-corrected induced pluripotent stem cells. Through MyoD-inducible myogenic differentiation, this model successfully recapitulates the key pathological features of X-linked myotubular myopathy, including elevated phosphatidylinositol-3-phosphate levels, hyperactivation of mTORC1 signalling, and increased expression of integrin-β1 and dynamin 2. We identified impaired lysosomal dynamics as a novel pathogenic mechanism in X-linked myotubular myopathy. Our induced pluripotent stem cell-derived X-linked myotubular myopathy myotubes exhibited an abnormal redistribution of lysosomes, with peripheral accumulation, leading to abnormally activated mTORC1 signalling. FYCO1 knockdown, a key regulator of lysosomal trafficking, ameliorated this hyperactivation of mTORC1 signalling. Comprehensive transcriptome analysis revealed distinct gene expression patterns associated with altered mTORC1 signalling and lysosomal localisation in X-linked myotubular myopathy myotubes. Network analysis suggested the central role of the mTORC1 signalling pathway and its connections to disrupted muscle development and differentiation. To investigate the influence of mTORC1 signalling and myotubularin deficiency on myogenic differentiation, we established two mouse myoblast models: one with constitutively activated mTORC1 signalling and another with Mtm1 knockout. Increased mTORC1 signalling in mouse myoblasts impaired myogenic differentiation, and this impairment was reversed by mTORC1 inhibitor rapamycin. Notably, rapamycin treatment also ameliorated the impaired myogenic differentiation observed in Mtm1-knockout mouse myoblasts, supporting the causative role of mTORC1 hyperactivation in X-linked myotubular myopathy pathogenesis. In conclusion, our findings establish the first human cell model of XLMTM, revealing that myotubularin deficiency leads to impaired lysosomal dynamics, which in turn causes mTORC1 dysregulation, a critical factor in the early stage of myogenic differentiation in X-linked myotubular myopathy. These findings provide new insights into the pathogenesis of X-linked myotubular myopathy and suggest that targeting mTORC1 signalling may be a promising therapeutic strategy for this debilitating disorder.

Keywords:  MTM1; X-linked myotubular myopathy; induced pluripotent stem cell; lysosomal dynamics; mTORC1 signalling; myogenic differentiation

DOI:  https://doi.org/10.1093/brain/awaf278
Development. 2025 Aug 01. pii: dev.205082. [Epub ahead of print]

Engineering fluorescent reporters in human pluripotent stem cells and strategies for live imaging human neurogenesis.

Alwyn Dady, Lindsay Davidson, Nicolas Loyer, Sophie Rappich, Greg Findlay, Timothy Sanders, Jens Januschke, Kate G Storey.

  Investigation of cell behaviour and cell biological processes underlying human development is facilitated by creation of fluorescent reporters in human pluripotent stem cells, which can be differentiated into cell types of choice. Here we report use of a piggyBac transposon-mediated stable integration strategy to engineer human pluripotent stem cell reporter lines. These express a plasma membrane localised protein tagged with the fluorescent proteins eGFP or mKate2, the photoconvertible nuclear marker H2B-mEos3.2, or the cytoskeletal protein F-tractin tagged with mKate2. Focussing on neural development these lines were used to live image and quantify cell behaviours, including cell cycle progression and cell division orientation in spinal cord rosettes. Further, lipofection-mediated introduction of piggyBac constructs into human neural progenitors labelled single cells and small cell groups within rosettes, allowing individual cell behaviours including neuronal delamination to be monitored. Finally, using the F-tractin-mKate2 hiPSC line, novel actin dynamics were captured during proliferation in cortical neural rosettes. This study presents and validates new tools and techniques with which to interrogate human cell behaviour and cell biology using live imaging approaches.

Keywords:  Human cortical development; Human pluripotent stem cells; Human spinal cord development; Live cell imaging; PiggyBac-mediated fluorescent reporters

DOI:  https://doi.org/10.1242/dev.205082
Trends Biotechnol. 2025 Jul 24. pii: S0167-7799(25)00256-2. [Epub ahead of print]

Advances and optimization strategies in prime editing of human pluripotent stem cells.

Heran Getachew, Thibaud Metais, Laurence Daheron, Marcela Garita-Hernandez.

  Prime editing, first introduced in 2019, is a precise and efficient genome-editing technique with applications across various organisms and cell lines, including human pluripotent stem cells (hPSCs). Despite its revolutionary potential, prime editing of hPSCs often shows low efficiency, hindered by current delivery methods and DNA repair mechanisms. In this review, we explore prime editing of hPSCs, emphasizing the optimization necessary for creating ex vivo and in vitro disease models, which are critical for developing personalized therapeutics. We discuss key prime-editing methods for hPSCs, optimization strategies, tools available for prime editing, and the rigorous quality control required before and after genome engineering for downstream applications.

Keywords:  cas9 nickase; delivery methods; hPSC; pluripotent stem cells; prime editing; prime-editing efficiency

DOI:  https://doi.org/10.1016/j.tibtech.2025.06.017
Genome Biol. 2025 Jul 25. 26(1): 224

MOTL: enhancing multi-omics matrix factorization with transfer learning.

David P Hirst, Morgane Térézol, Laura Cantini, Paul Villoutreix, Matthieu Vignes, Anaïs Baudot.

  Joint matrix factorization is popular for extracting lower dimensional representations of multi-omics data but loses effectiveness with limited samples. Addressing this limitation, we introduce MOTL (Multi-Omics Transfer Learning), a framework that enhances MOFA (Multi-Omics Factor Analysis) by inferring latent factors for small multi-omics target datasets with respect to those inferred from a large heterogeneous learning dataset. We evaluate MOTL by designing simulated and real data protocols and demonstrate that MOTL improves the factorization of limited-sample multi-omics datasets when compared to factorization without transfer learning. When applied to actual glioblastoma samples, MOTL enhances delineation of cancer status and subtype.

Keywords:  Data integration; Dimensionality reduction; MOFA; Matrix factorization; Multi-omics; Transfer learning

DOI:  https://doi.org/10.1186/s13059-025-03675-7
Front Genet. 2025 ;16 1547788

Robust consensus nuclear and cell segmentation.

Melis O Irfan, Eduardo A González-Solares, Tristan Whitmarsh, Alireza Molaeinezhad, Mohammad Al Sa'd, Claire M Mulvey, Marta Páez Ribes, Atefeh Fatemi, Dario Bressan, Nicholas A Walton.

  Cell segmentation is a crucial step in numerous biomedical imaging endeavors-so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out-of-the-box use. Assessing the strengths and limitations of each method on a tissue sample set and then selecting the optimal method for each research objective and input image are time-consuming and exacting tasks that often monopolize the resources of biologists, biochemists, immunologists, and pathologists, despite not being the primary goal of their research projects. In this work, we present a segmentation software wrapper, coined CellSampler, which runs a selection of established segmentation methods and then combines their individual segmentation masks into a single optimized mask. This so-called "uber mask" selects the best of the established masks across local neighborhoods within the image, where both the neighborhood size and the statistical measure used to define what qualifies as "best" are user-defined.

Keywords:  bioinformatics; computer vision; imaging mass cytometry; multiplexed imaging; single-cell segmentation

DOI:  https://doi.org/10.3389/fgene.2025.1547788
Genome Biol. 2025 Jul 29. 26(1): 228

Empowering bioinformatics communities with Nextflow and nf-core.

Björn E Langer, Andreia Amaral, Marie-Odile Baudement, Franziska Bonath, Mathieu Charles, Praveen Krishna Chitneedi, Emily L Clark, Paolo Di Tommaso, Sarah Djebali, Philip A Ewels, Sonia Eynard, James A Fellows Yates, Daniel Fischer, Evan W Floden, Sylvain Foissac, Gisela Gabernet, Maxime U Garcia, Gareth Gillard, Manu Kumar Gundappa, Cervin Guyomar, Christopher Hakkaart, Friederike Hanssen, Peter W Harrison, Matthias Hörtenhuber, Cyril Kurylo, Christa Kühn, Sandrine Lagarrigue, Delphine Lallias, Daniel J Macqueen, Edmund Miller, Júlia Mir-Pedrol, Gabriel Costa Monteiro Moreira, Sven Nahnsen, Harshil Patel, Alexander Peltzer, Frederique Pitel, Yuliaxis Ramayo-Caldas, Marcel da Câmara Ribeiro-Dantas, Dominique Rocha, Mazdak Salavati, Alexey Sokolov, Jose Espinosa-Carrasco, Cedric Notredame, The Nf-Core Community.

Standardized analysis pipelines contribute to making data bioinformatics research compliant with the paradigm of Findability, Accessibility, Interoperability, and Reusability (FAIR), and facilitate collaboration. Nextflow and Snakemake, two popular command-line solutions, are increasingly adopted by users, complementing GUI-based platforms such as Galaxy. We report recent developments of the nf-core framework with the new Nextflow Domain-Specific Language (DSL2). An extensive library of modules and subworkflows enables research communities to adopt common standards progressively, as resources and needs allow. We present an overview of some of the research communities built around nf-core and showcase its adoption by six EuroFAANG farmed animal research consortia.

DOI: https://doi.org/10.1186/s13059-025-03673-9
Biophys Rev. 2025 Jun;17(3): 759-779

Drug resistance and tumor heterogeneity: cells and ensembles.

Ruth Nussinov, Bengi Ruken Yavuz, Hyunbum Jang.

  The population of cells that make up a tumor, and of their biomolecular conformational ensembles, are heterogeneous at all levels, genetic, epigenetic, and phenotypic. At the cellular level, tumor heterogeneity was described as the "Rosetta Stone of therapy resistance." At the genetic level, tumors consist of divergent tumor (sub)clones. At the phenotypic level, their observed function, clinical attributes, and response to drugs vary. We suggest that the behavior and properties of populations of cells-and of populations of conformational states-are intrinsically connected. This is important. Considering the tumor's disruption of normal cellular processes clarifies why it is crucial to understand the ins and outs of its mechanistic molecular foundation. In reality, the propensities of the tumor's conformational states underly the proliferative potential of its cell populations. These propensities are determined by expression levels, driver mutations, and the tumor cells environment, collectively transforming tumor cells behavior and crucially, drug resistance. We suggest that propensities of the conformations, across the tumor space and over time, shape tumor heterogeneity, and cell plasticity. The conformational states that are preferentially visited can be viewed as phenotypic determinants, and their mutations and altered expression work by allosterically shifting the relative propensities, thus the cell phenotype. Physics (and chemistry) inspire the notion that living things must conform to fundamental laws of science, like dynamic landscapes. Dynamic conformational propensities are at the core of cell life, including tumor cells; their heterogeneity is the formidable, unmet drug resistance challenge.

Keywords:  Allosteric; Allostery; Cancer; Drug resistance; Dynamic conformational ensembles; Heterogeneity

DOI:  https://doi.org/10.1007/s12551-025-01320-y
STAR Protoc. 2025 Jul 24. pii: S2666-1667(25)00386-7. [Epub ahead of print]6(3): 103980

Protocol update to: High-throughput scNMT protocol for multiomics profiling of single cells from mouse brain and pancreatic organoids.

Santiago Cerrizuela, Oguzhan Kaya, Lukas P M Kremer, Andrea Sarvari, Tobias Ellinger, Jannes Straub, Jan Brunken, Andrés Sanz-Morejón, Aylin Korkmaz, Ana Martín-Villalba.

  Single-cell nucleosome, methylome, and transcriptome (scNMT) sequencing is a recently developed method that allows multiomics profiling of single cells. In this scNMT protocol, we describe profiling of cells from mouse brain and pancreatic organoids, using liquid handling platforms to increase throughput from 96-well to 384-well plate format. Our approach miniaturizes reaction volumes and incorporates the latest Smart-seq3 protocol to obtain higher numbers of detected genes and genomic DNA (gDNA) CpGs per cell. We outline normalization steps to optimally distribute per-cell sequencing depth. For complete details on the use and execution of this protocol, please refer to Kremer et al. and other works.1,2,3,4,5,6,7 This protocol is an update to Cerrizuela et al.7.

Keywords:  Bioinformatics; Cell Biology; Genomics; Molecular Biology; Neuroscience; RNA-seq; Sequence analysis; Single Cell

DOI:  https://doi.org/10.1016/j.xpro.2025.103980
Development. 2025 Jul 15. pii: dev204617. [Epub ahead of print]152(14):

From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.

Usha Kadiyala, David Sprinzak, Nicholas A M Monk, Shannon E Taylor, Berta Verd, Katharina F Sonnen, Lauren Moon, Adrienne H K Roeder, Ruben Perez-Carrasco, Pau Formosa-Jordan.

  Developmental biology seeks to unravel the intricate regulatory mechanisms orchestrating the transformation of a single cell into a complex, multicellular organism. Dynamical systems theory provides a powerful quantitative, visual and intuitive framework for understanding this complexity. This Primer examines five core dynamical systems theory concepts and their applications to pattern formation during development: (1) analysis of phase portraits, (2) bistable switches, (3) stochasticity, (4) response to time-dependent signals, and (5) oscillations. We explore how these concepts shed light onto cell fate decision making and provide insights into the dynamic nature of developmental processes driven by signals and gradients, as well as the role of noise in shaping developmental outcomes. Selected examples highlight how integrating dynamical systems with experimental approaches has significantly advanced our understanding of the regulatory logic underlying development across scales, from molecular networks to tissue-level dynamics.

Keywords:  Developmental dynamics; Dynamical systems; Modelling; Signalling; Waddington landscape

DOI:  https://doi.org/10.1242/dev.204617
FEBS J. 2025 Aug 01.

Principal mechanisms of extracellular matrix-mediated cell-cell communication in physiological and tumor microenvironments.

Zoi Piperigkou, Sylvia Mangani, Nikolaos E Koletsis, Christos Koutsakis, Nicholas S Mastronikolis, Marco Franchi, Nikos K Karamanos.

  Cell-cell communication is essential for the regulated exchange of information between cells, coordinating critical cellular processes under physiological and pathological conditions. The extracellular matrix (ECM) is a complex three-dimensional (3D) intercellular macromolecular network that provides structural support to tissues, while actively modulating cellular functions and responses. ECM-mediated intercellular communication is a key player in both homeostasis and disease development. Particularly in cancer, ECM reorganization drives tumor development and progression, shaping dynamic interactions within the tumor microenvironment (TME). In this review, we present and discuss two principal mechanisms of matrix-mediated cell-cell communication in both physiological and cancerous contexts. First, we explore the impact of ECM biomechanical properties in mechanical sensing and communication, which govern key aspects of cell signaling, adhesion, and migration across normal and malignant tissues. Second, we discuss the role of the ECM in facilitating cell-cell communication through the controlled release and navigation of extracellular vesicles (EVs). EVs carry, among other constituents, proteins, enzymes, microRNAs (miRNAs), and signaling molecules that relay information to nearby or distant cells, modulating the initiation of metastasis and pre-metastatic niche formation. Conclusively, in this review, we highlight the critical role of targeting ECM dynamics in cell-cell communication under physiological processes and during cancer progression. Targeted therapies that modulate ECM components and interactions with cells hold promise for future treatment approaches.

Keywords:  biomechanical sensing; cancer targeting; cell–cell communication; extracellular matrix; extracellular vesicles

DOI:  https://doi.org/10.1111/febs.70207