bims-pideca 2026-03-01 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2026–03–01
twenty-one papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Coexistent PTEN and PIK3CA alterations hyperactivate mTORC1 signaling in endometrial cancers and cause their selective sensitivity to mTORC1 inhibition.
Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions.
A cellular basis for the mammalian nocturnal-diurnal switch.
Single-cell protein activity analysis reveals aberrant myogenesis and IGF2-PI3K pathway dependencies in MYOD1-mutant rhabdomyosarcoma.
Untargeted metabolomic profiling reveals mTORC1-dependent regulation of amino acid utilization in lymphatic endothelial cells.
Genome-wide single-cell perturbation screens with VIPerturb-seq.
Highly Sensitive Chemigenetic FRET-Based Kinase Biosensors.
Partial truncation of the C-terminal domain of PTCH1 in cancer promotes tumourigenesis by non-canonical activation of a GLI-PI3K loop.
Hyperinsulinemia drives glomerular podocyte injury and albuminuria via a self-perpetuating GSK3β-IRS1 insulin desensitization circuit.
Cell jamming transition is regulated by mitochondrial pyruvate transport and endocytosis.
Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.
Advances in genetics, signaling, and modeling of venous malformations.
Virtual Cells Need Context, Not Just Scale.
ROR1-PI3K/AKT signaling drives adaptive resistance to cell cycle blockade in TP53 mutated ovarian cancer.
The GENEVA platform models tumor mosaicism to reveal variations of responses to KRAS inhibitors and identify improved drug combinations.
The Stochastic System Identification Toolkit (SSIT) to model, fit, predict, and design experiments.
SenNet Portal: Build, Optimization and Usage.
Genetic resonance in the p53 signaling network.
Comparing the impact of sample multiplexing approaches for single-cell RNA-sequencing on downstream analysis using cerebellar organoids.
Temporal proteomic and phosphoproteomic dynamics during neuronal differentiation in the reference iPSC line KOLF2.1J.
The Nemp1-Nesprin complex mediates cellular responses to matrix mechanics.

bioRxiv. 2026 Feb 14. pii: 2026.02.12.705558. [Epub ahead of print]

Coexistent PTEN and PIK3CA alterations hyperactivate mTORC1 signaling in endometrial cancers and cause their selective sensitivity to mTORC1 inhibition.

Hilla Solomon, Radha Mukherjee, Yu Chi Yang, Julia Meredith, Alison M Schram, Sang Ah Yi, Xiaoping Chen, Michael Tribuzio, Harika Gundlapalli, Justin Meyerowitz, Elisa de Stanchina, Britta Weigelt, Heeseon An, Simon T Barry, Jacqueline A M Smith, Mallika Singh, Neal Rosen.

In approximately half of endometrial carcinoma (EC), PTEN loss-of-function and activating PI3K mutants coexist. Unlike cells with either single mutation, PTEN / PIK3CA coexistent alterations result in elevated membrane phosphatidylinositol (3,4,5)-trisphosphate (PIP3) levels and mTORC1 hyperactivation, rendering PI3K or AKT inhibition ineffective in blocking mTORC1 activity and tumor growth. The bi-steric mTORC1 kinase inhibitor, RMC-6272, suppresses mTORC1 activity and cell growth by reducing protein translation and cell cycle progression. In vivo , RMC-6272, but not PI3K inhibitors, effectively suppressed mTORC1 and growth of EC PDXs with coexistent PTEN/PIK3CA lesions. These findings are consistent with a phase I trial of bi-steric mTORC1 inhibitor RMC-5552, showing anti-tumor activity in patients with EC. PDXs with KRAS co-mutations regrew after RMC-6272 treatment, which was prevented by the addition of the RAS(ON) multi-selective inhibitor RMC-7977. Overall, these data suggest that mTORC1 hyperactivation drives ECs with coexistent PTEN/PIK3CA mutations, explain the limited antitumor activity of PI3K and AKT inhibitors, and support clinical evaluation of mTORC1 inhibitors as potential therapy for EC.
Significance: We have found the mechanistic consequences of PTEN/PIK3CA co-alterations in endometrial tumors and that these mutations result in a profound hyperactivation of mTORC1 signaling. Single mutant tumors are sensitive to PI3K inhibition but those with both mutations are insensitive to PI3K or AKT inhibition but are exquisitely dependent on mTORC1 kinase. This provides strong preclinical rationale for targeting mTORC1, alone or combined with RAS inhibition (in RAS co-mutant tumors), as an effective therapeutic strategy.

DOI: https://doi.org/10.64898/2026.02.12.705558
Nat Commun. 2026 Feb 26. pii: 2071. [Epub ahead of print]17(1):

Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions.

Martin Garrido-Rodriguez, Clement Potel, Mira Lea Burtscher, Isabelle Becher, Pablo Rodriguez-Mier, Sophia Müller-Dott, Mikhail M Savitski, Julio Saez-Rodriguez.

Signaling pathways are useful models for interpreting molecular data, but their coverage has long been constrained by classic biochemistry methods. The growing corpus of kinase-substrate interactions, coupled to phosphoproteomics improvements, pave the way to revisit classic signaling pathways. In this study, we explore context-specific signaling pathway inference from phosphoproteomics and kinase-substrate networks. Focusing on epidermal growth factor (EGF), we conduct a meta-analysis and generate three datasets representing the most comprehensive characterization of the EGF response to date. We infer kinase-kinase pathways and compare them to different ground truth sets. Literature-curated networks consistently yield the highest recovery of ground-truth interactions, with modest gains from network propagation methods. Up to 90% of interactions are absent from current ground truth sets, indicating many unexplored interactions supported by data and knowledge. Our results demonstrate the limitations of traditional views on signaling pathways and point to opportunities for generating better mechanistic hypotheses.

DOI: https://doi.org/10.1038/s41467-026-69332-0
Science. 2026 Feb 26. 391(6788): eady2822

A cellular basis for the mammalian nocturnal-diurnal switch.

Andrew D Beale, Matthew J Christmas, Nina M Rzechorzek, Andrei Mihut, Aiwei Zeng, Christopher Ellis, Nathan R James, Nicola J Smyllie, Violetta Pilorz, Rose Richardson, Mads F Bertelsen, Shaline V Fazal, Zanna Voysey, Kevin Moreau, Jerry Pelletier, Priya Crosby, Sew Y Peak-Chew, Rachel S Edgar, Madeline A Lancaster, Roelof A Hut, John S O'Neill.

Early mammals were nocturnal while dinosaurs dominated the daytime. Mammalian transition to daytime activity accelerated after the Cretaceous-Paleogene extinction, but the underlying mechanisms remain unclear. We identified a conserved cell-intrinsic, thermodynamic mechanism that likely facilitated this shift. In cells from diurnal mammals, protein synthesis, phosphorylation, and circadian timing were less sensitive to temperature changes than were cells from nocturnal mammals. Comparative genomics revealed accelerated evolution within essential signaling pathways, including mechanistic target of rapamycin (mTOR), that increase the robustness of diurnal cellular clocks to thermal and osmotic perturbation. In nocturnal mice, mTOR inhibition shifted cells, tissues, and behavior toward diurnal activity. These findings uncover a genetic and biochemical basis for nocturnal-diurnal switching, emphasizing how cellular signaling networks can encode complex phenotypes such as temporal niche selection.

DOI: https://doi.org/10.1126/science.ady2822
Sci Adv. 2026 Feb 27. 12(9): eaea6453

Single-cell protein activity analysis reveals aberrant myogenesis and IGF2-PI3K pathway dependencies in MYOD1-mutant rhabdomyosarcoma.

Josephine K Dermawan, Fabio Vanoli, Henry Traux de Wardi, Jonathan N Levi, Glorymar Ibanez Sanchez, Armaan Siddiquee, Samantha Brosius, Daoqi You, Franck Tirode, Patricia Sung, Marie Karanian, Daniel Pissaloux, Leonard H Wexler, Andrew Kung, Alice Soragni, Filemon S Dela Cruz, Jovana Pavisic, Cristina R Antonescu.

Myogenic differentiation 1 (MYOD1)L122R-mutant spindle cell rhabdomyosarcoma (SRMS) is an ultrarare, treatment-resistant sarcoma with dismal outcomes. We performed regulatory network analysis of single-nucleus RNA sequencing (snRNA-seq) from six patient tumors, revealing disrupted myogenesis and actionable master regulator (MR) dependencies across three coexisting tumor cell states, also conserved in patient-derived xenografts: (i) a MYOD1-enriched progenitor-like state, (ii) a proliferative transition state, and (iii) a partially differentiated state with reduced MYOD1 activity. Ligand-receptor analysis uncovered paracrine insulin-like growth factor 2 (IGF2)-IGF1 receptor (IGF1R)-phosphatidylinositol 3-kinase (PI3K) signaling from progenitor to transition/differentiated states, whose inhibition demonstrated therapeutic potential in ex vivo drug screens, and significantly improved disease control in a patient-derived xenograft model. Oncogenic MRs were recapitulated in 24 bulk RNA profiles, while 20 DNA profiles revealed recurrent IGF2/PI3K/AKT alterations, reinforcing shared transcriptional vulnerabilities. These findings characterize aberrant, mutant MYOD1-driven myogenesis sustained by IGF2 and nominate IGF1R-PI3K/AKT/mammalian target of rapamycin inhibitors for therapeutic translation in MYOD1L122R-mutant SRMS, underscoring the utility of single-cell regulatory network analysis for uncovering actionable dependencies in rare, transcriptionally complex cancers.

DOI: https://doi.org/10.1126/sciadv.aea6453
bioRxiv. 2026 Feb 18. pii: 2026.02.17.706183. [Epub ahead of print]

Untargeted metabolomic profiling reveals mTORC1-dependent regulation of amino acid utilization in lymphatic endothelial cells.

Jie Zhu, Felix Darko, Fei Han, Summer Simeroth, Lingjun Li, Haiwei Gu, Pengchun Yu.

The lymphatic vascular system plays essential roles in tissue fluid drainage, dietary fat absorption and transport, and immune cell trafficking. To support these physiological functions, the lymphatic vasculature forms an extensive and highly organized network throughout the body. We have recently discovered that the mechanistic target of rapamycin complex 1 (mTORC1), with RAPTOR as an indispensable component, directs glycolysis and glutaminolysis in lymphatic endothelial cells (LECs) to promote lymphatic vessel formation. However, the role of mTORC1 in regulating LEC metabolism remains incompletely understood. Here, by conducting untargeted metabolomic profiling of control and RAPTOR-deficient LECs, we uncover a global impact of mTORC1 inhibition on amino acid utilization. Specifically, RAPTOR deficiency impairs the conversion of glutamine to glutamic acid, resulting in decreased levels of glutamic acid and aspartic acid, as well as reduced abundance of N-acetyl-glutamic acid and N-acetyl-aspartic acid-two metabolites unexpectedly detected in LECs. Integrated metabolomic and transcriptomic analyses further reveal that impaired glutaminolysis in RAPTOR-depleted LECs is accompanied by an increase in intracellular asparagine, arginine, and metabolites associated with arginine catabolism, potentially driven by upregulation of their respective transporters. In addition, RAPTOR depletion results in abnormal accumulation of branched-chain amino acids (BCAAs) and other essential amino acids primarily involved in protein synthesis. Mechanistically, our data suggest that defective BCAA catabolism and impaired translational control contribute to these metabolic alterations. Collectively, these findings reveal an important role of mTORC1 signaling in coordinating amino acid utilization and suggest that this regulation is critical for lymphatic vessel formation.

DOI: https://doi.org/10.64898/2026.02.17.706183
bioRxiv. 2026 Feb 13. pii: 2026.02.12.705613. [Epub ahead of print]

Genome-wide single-cell perturbation screens with VIPerturb-seq.

Alexandra Bradu, John D Blair, Isabella N Grabski, Isabella Mascio, Junsuk Lee, Cecilia McCormick, Rahul Satija.

CRISPR-based screening combined with single-cell sequencing (i.e. Perturb-seq) enables systematic mapping of genetic perturbations to molecular phenotypes. While Perturb-seq is well-suited to profile targeted subsets of regulators, scaling to genome-wide screens presents substantial cost and throughput challenges. Here we introduce VIPerturb-seq, a platform to facilitate routine genome-wide Perturb-seq experiments using probe-based detection workflows. We describe a split probe strategy for detection of genome-wide CRISPR libraries in fixed cells that enables (i) optional support for phenotypic enrichment of Very Important Perturbations (VIP) prior to single-cell profiling, and (ii) compatibility with combinatorial indexing workflows to further improve Perturb-seq throughput by 50-fold. Using a genome-wide CRISPRi library (GuEST-List), we demonstrate VIPerturb-seq on two genome-wide screens representing both unbiased and phenotypically enriched workflows. Our results demonstrate how the sensitivity, scalability, and efficiency of VIPerturb-seq can enable both individual labs with targeted research questions and large data generation platforms aiming to construct virtual cells.

DOI: https://doi.org/10.64898/2026.02.12.705613
bioRxiv. 2026 Feb 09. pii: 2026.02.06.702961. [Epub ahead of print]

Highly Sensitive Chemigenetic FRET-Based Kinase Biosensors.

Xinchang He, Daojia R Zhou, Yu Huan, Zachary Berriman-Rozen, Sohum Mehta, Yao Chen, Michelle S Frei, Jin Zhang.

Fluorescent protein-based biosensors have transformed the study of cell physiology and pathology by enabling direct, live-cell measurements of biochemical activities with spatiotemporal precision. FRET-based biosensors offer a quantitative and well-defined readout mechanism popular among researchers, but have struggled to break free of characteristically low dynamic ranges and overall dependence on the cyan-yellow spectral region. Chemigenetic approaches that combine synthetic fluorophores with self-labeling protein tags represent an attractive solution to these longstanding constraints. Here, we pair different fluorescent protein donors with a HaloTag acceptor conjugated to a far-red fluorophore to obtain a suite of highly sensitive, chemigenetic FRET-based kinase activity biosensors with red-shifted emission and unprecedented dynamic range. We demonstrate the generalizability of this chemigenetic platform by developing biosensors for multiple kinases, as well as small GTPases and second messengers, all while maintaining high sensitivity. The high sensitivity and spectral tunability of these chemigenetic tools enabled us to perform robust multiplexed activity imaging of receptor-mediated signaling networks to quantitatively map isoform-specific coupling by GPCRs, as well as clear visualization of kinase activity in acute brain slices via two-photon fluorescence lifetime imaging. Our chemigenetic sensor toolkit thus provides the sensitivity and dimensionality needed to illuminate the spatiotemporal regulation of signaling networks in cells and tissues.

DOI: https://doi.org/10.64898/2026.02.06.702961
Oncogene. 2026 Feb 26.

Partial truncation of the C-terminal domain of PTCH1 in cancer promotes tumourigenesis by non-canonical activation of a GLI-PI3K loop.

Begoña Caballero-Ruiz, Rosa Bordone, Sonia Coni, Danai S Gkotsi, Eva Gonzalez, Gianluca Canettieri, Natalia A Riobo-Del Galdo.

Loss of function mutations of the Hedgehog receptor PTCH1 are oncogenic drivers in some skin and brain cancers. We recently reported mutations in exons encoding the C-terminal tail of PTCH1 in colon cancer, which result in premature truncation but do not impair canonical Hedgehog signalling. In this study, we show that colon cancer cells engineered by CRISPR/Cas9 to express endogenous truncated PTCH1 have enhanced proliferation, colony formation, anchorage-independent growth and form larger tumours in vivo than isogenic cells expressing wild-type PTCH1. Analysis of the mechanisms underlying this growth advantage revealed profound transcriptional changes and unexpectedly, upregulation of GLI1 and GLI2 by a Smoothened-independent route, which proved to be necessary for the proliferative advantage. Furthermore, we found that truncation of PTCH1 C-tail upregulated several cancer-related pathways, including EGFR and Ras signalling and led to enhanced GLI-dependent PI3K activation, which exerted a positive feedback regulation on GLI expression and activity. Accordingly, PTCH1 mutant cells were highly sensitive to PI3K and GLI inhibitors and were only partially sensitive to EGFR and MEK inhibitors. Altogether, these findings reveal that PTCH1 C-tail truncating mutations promote colon cancer tumourigenesis through a non-canonical GLI-PI3K positive loop.

DOI: https://doi.org/10.1038/s41388-026-03698-9
Metabolism. 2026 Feb 24. pii: S0026-0495(26)00081-8. [Epub ahead of print] 156571

Hyperinsulinemia drives glomerular podocyte injury and albuminuria via a self-perpetuating GSK3β-IRS1 insulin desensitization circuit.

Mengxuan Chen, Yudong Fang, Mingzhuo Zhang, Yan Ge, Shoaib Junejo, Rujun Gong.

  Epidemiological evidence indicates that hyperinsulinemia is an independent risk factor for albuminuria and renal impairment, yet its molecular basis remains unclear. In prediabetic db/db mice, hyperinsulinemia coincided with albuminuria, podocyte injury, and impaired glomerular insulin signaling, characterized by insulin receptor exhaustion and hypoactivity of the IRS1/PI3K/Akt insulin signaling. This led to diminished inhibitory phosphorylation of GSK3βS9 in podocytes, denoting GSK3β hyperactivity. Notably, GSK3β co-localized and physically interacted with IRS1 in glomerular podocytes, phosphorylating IRS1S332 as a direct substrate. In cultured podocytes, prolonged high insulin exposure induced insulin receptor depletion, GSK3β hyperactivity, and increased inhibitory phosphorylation of IRS1S332, forming a self-perpetuating cycle of insulin desensitization and podocyte injury. GSK3β appears to play a key role, as ectopic expression of a constitutively active GSK3β mutant GSK3βS9A enhanced inhibitory phosphorylation of IRS1S332, desensitized insulin signaling, and exacerbated podocyte injury. In contrast, forced expression of a kinase-dead mutant of GSK3β or inhibition of GSK3β with a selective small-molecule inhibitor tideglusib abrogated inhibitory phosphorylation of IRS1S332, restored insulin sensitivity and protected podocytes. In vivo, GSK3βS9Aknock-in mice exhibited impaired insulin signaling and podocyte injury with albuminuria. Conversely, tideglusib treatment in prediabetic db/db mice attenuated podocyte injury and insulin resistance, thereby improving albuminuria. Collectively, hyperinsulinemia directly elicits albuminuria and renal impairment via a cascade of molecular events involving insulin receptor exhaustion, reduced insulin signaling, and GSK3β hyperactivity, which promotes IRS1 inhibition and thereby forms a self-amplifying GSK3β-IRS1 circuit of insulin desensitization and podocyte injury. Targeting GSK3β could disrupt this pathogenic loop and mitigate hyperinsulinemia-induced renal injury.

Keywords:  insulin pathway; insulin resistance; metabolic dysfunction–associated kidney disease; podocytopathy

DOI:  https://doi.org/10.1016/j.metabol.2026.156571
bioRxiv. 2026 Feb 10. pii: 2026.02.09.704880. [Epub ahead of print]

Cell jamming transition is regulated by mitochondrial pyruvate transport and endocytosis.

Alexandra Bermudez, Zoe Latham, Johnny Diaz, Weihong Yan, Jerry Chen, Dapeng Bi, Andrew Goldstein, Jimmy K Hu, Neil Y C Lin.

Epithelial tissues undergo dynamic transitions between fluid-like collective motion and mechanically jammed states during development, injury repair, and disease progression. However, the cellular programs that drive these transitions and regulate collective behavior remain unclear. Using a controlled crowding model integrated with live-cell imaging and time-resolved multi-omics, we demonstrate that epithelial crowding triggers early metabolic changes characterized by increased mitochondrial pyruvate anaplerosis that precedes the jamming transition. Functional inhibition of mitochondrial pyruvate import is sufficient to sustain collective cell motility, impeding jamming transition in crowded cells. This unjammed state is driven by enhanced cytoskeletal remodeling and requires RhoA-myosin II activity. Mechanistically, we show that elevated cytoskeletal signaling promotes macropinocytic uptake, which serves as a required feedback loop to maintain motility. These findings identify mitochondrial pyruvate utilization as a key regulator that links metabolic remodeling to the endocytic control of epithelial fluidity.

DOI: https://doi.org/10.64898/2026.02.09.704880
Bioinformatics. 2026 Feb 26. pii: btag089. [Epub ahead of print]

Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.

Jacob T Mitchell, Orian Stapleton, Kavita Krishnan, Sushma Nagaraj, Dmitrijs Lvovs, Christopher Cherry, Amanda Poissonnier, Andrew Adey, Varun Rao, Amanda Huff, Jacquelyn W Zimmerman, Luciane T Kagohara, Neeha Zaidi, Lisa M Coussens, Elizabeth M Jaffee, Jeniffer H Elisseeff, Elana J Fertig.

MOTIVATION: Algorithms for ligand-receptor network inference have emerged as commonly used tools to estimate cell-cell communication from reference single-cell data. Many studies employ these algorithms to compare signaling between conditions and lack methods to statistically identify signals that are significantly different. We previously developed the cell communication inference algorithm Domino, which considers ligand and receptor gene expression in association with downstream transcription factor activity scoring. We developed the dominoSignal software to innovate upon Domino and extend its functionality to test statistically differential cellular signaling.
RESULTS: This new functionality includes the compilation of active signals as linkages from multiple subjects in a single-cell data set and testing condition-dependent signaling linkage. The software is applicable for analysis of single-cell data sets with multiple subjects as biological replicates as well as with bootstrapped replicates from data sets with few or pooled subjects. We use simulation studies to benchmark the number of subjects in compared groups and cells within an annotated cell type sufficient to accurately identify differential linkages. We demonstrate the application of the Differential Cell Signaling Test (DCST) in the dominoSignal software to investigate consequences of cancer cell phenotypes and immunotherapy on cell-cell communication in tumor microenvironments. These applications in cancer studies demonstrate the ability of differential cell signaling analysis to infer changes to cell communication networks from therapeutic or experimental perturbations, which is broadly applicable across biological systems.
AVAILABILITY: dominoSignal is available through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/dominoSignal.html.
SUPPLEMENTARY INFORMATION: Analysis code and supplemental information are available through Zenodo at https://zenodo.org/records/18329130 and at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btag089
Front Cardiovasc Med. 2026 ;13 1770126

Advances in genetics, signaling, and modeling of venous malformations.

Komal Sagar, Elisa Boscolo.

  Vascular anomalies are defects resulting from the abnormal development or growth of the vasculature. Among these, venous malformations (VMs) are predominantly caused by mutations in the TIE2 or PIK3CA genes, which disrupt endothelial cell morphogenesis and vessel maturation. VM lesions are typically diagnosed during infancy or childhood and often persist and enlarge throughout adulthood, causing chronic complications such as pain, deformity, and coagulopathy. Despite available treatments such as sclerotherapy and mTOR inhibitors like sirolimus, achieving complete and long-term resolution of VMs remains a significant challenge. This review examines the genetic basis of VMs, explores the underlying molecular signaling mechanisms, and compares various experimental models-including in vitro, 3D, and in vivo systems-that have advanced our understanding of VM and provided platforms for testing potential therapies. Future research should prioritize the development of more precise and personalized models to drive improved strategies and better outcomes for patients with VMs.

Keywords:  PIK3CA; TIE2; mouse model; vascular malformations; venous malformation

DOI:  https://doi.org/10.3389/fcvm.2026.1770126
bioRxiv. 2026 Feb 09. pii: 2026.02.04.703804. [Epub ahead of print]

Virtual Cells Need Context, Not Just Scale.

Payam Dibaeinia, Sudarshan Babu, Mei Knudson, Ali ElSheikh, Yibo Wen, Han Liu, Jason Perera, Aly A Khan.

The intersection of AI and biology has entered a phase of explosive growth, driven by the ambition to build "Virtual Cells" or computational models capable of predicting cellular responses to any perturbation. Following the success of structural biology (e.g., AlphaFold) and large language models, the field has converged on training massive, high-capacity models on large-scale single-cell data. This position paper argues that scaling model capacity is insufficient to solve the Virtual Cell problem because the primary failure mode is a lack of adequate coverage over diverse biological contexts , not insufficient model expressivity. We support this claim by reviewing recent studies showing that simple baselines perform on par with sophisticated architectures within a given biological context, and current models fail to consistently generalize across contexts. We connect this finding to the causal inference literature on transportability and contrast it with domains where scaling has succeeded. We substantiate our argument through analysis of a state-of-the-art model on a 22-million-cell immunology dataset. We conclude that the community faces a causal transport problem that cannot be solved by accumulating more data from the same distributions. Instead, we argue that contextual diversity and causal representation learning deserve increased emphasis, complementing ongoing scaling of model capacity and data volume.

DOI: https://doi.org/10.64898/2026.02.04.703804
Cell Death Dis. 2026 Feb 27.

ROR1-PI3K/AKT signaling drives adaptive resistance to cell cycle blockade in TP53 mutated ovarian cancer.

Juuli Raivola, Frida Rantanen, Alice Dini, Emilia Piki, Harlan Barker, Elina Multamäki, Franziska Bentz, Pia Sunkel, Aino-Maija Kiiski, Lassi Paavolainen, Astrid Murumägi, Daniela Ungureanu.

Drug resistance remains a major challenge to durable responses in ovarian cancer, the fifth leading cause of cancer-related death among women. In this study, we developed long-term resistant (lt-res, several months) pre-clinical models of two drugs inducing mitotic arrest in TP53-mutated cells: adavosertib (ADA), an investigational WEE1 inhibitor targeting the DNA damage response and currently evaluated in clinical trials, and paclitaxel (PTX), a widely used chemotherapeutic agent in cancer care targeting microtubules. Through integrated multi-omics functional profiling, we identify a shared PI3K/AKT-regulated signaling node that governs drug adaptation across all lt-res models. This node modulates the activity of DNA-damage responses and genotoxic stress to toggle between two adaptive states: activated PI3K/AKT driving a proliferative "fast-bypass" program with sustained cell cycle progression and mitotic evasion, or reduced PI3K/AKT signaling initiating a "slow-repair" state characterized by DNA damage checkpoint engagement, replication slowdown, and increased drug efflux. Notably, upregulation of receptor tyrosine kinases, such as ROR1, was observed in both ADA and PTX lt-res models with activated PI3K/AKT signaling. Targeting ROR1 with zilovertamab-vedotin, a monoclonal antibody-drug conjugate, resulted in enhanced cytotoxicity, demonstrating a new approach against recurrent drug-resistant ovarian cancer.

DOI: https://doi.org/10.1038/s41419-026-08501-x
Nat Cancer. 2026 Feb 24.

The GENEVA platform models tumor mosaicism to reveal variations of responses to KRAS inhibitors and identify improved drug combinations.

Johnny X Yu, Jung Min Suh, Katerina D Popova, Kristle Garcia, Tanvi Joshi, Bruce Culbertson, Jessica B Spinelli, Vishvak Subramanyam, Kevin Lou, Trey Charbonneau, Kevan M Shokat, Jonathan Weissman, Hani Goodarzi.

The clinical success of cancer drug candidates depends on efficacy across many different individuals. Because xenografts are challenging to scale, we currently rely on a limited set of in vivo preclinical models. Here, to address this limitation, we introduce GENEVA, a scalable single-cell-resolution platform for measuring responses to drug perturbations. GENEVA models cancer genetic diversity by combining multiple patient-derived cell lines and cancer cell lines into pooled three-dimensional cultures and xenograft models, allowing us to study drug responses across a wide range of genetic backgrounds within a single experiment. We apply GENEVA to investigate KRAS-G12C inhibitors and demonstrate that mitochondrial activation is a key driver of cell death following KRAS inhibition, while epithelial-to-mesenchymal transition is a prominent resistance mechanism. These findings highlight the utility of GENEVA to identify therapeutic targets and optimize combination therapies with the potential to bridge the gap between preclinical cancer models and patient outcomes.

DOI: https://doi.org/10.1038/s43018-026-01130-5
bioRxiv. 2026 Feb 22. pii: 2026.02.20.707039. [Epub ahead of print]

The Stochastic System Identification Toolkit (SSIT) to model, fit, predict, and design experiments.

Alex N Popinga, Jack Forman, Dmitri Svetlov, Huy Vo, Brian Munsky.

Biological data is prone to both intrinsic and extrinsic noise and variability between experimental replicas. That same stochasticity and heterogeneity can carry information about underlying biochemical mechanisms but, if not incorporated in modeling and probabilistic inference, can also bias parameter estimates and misguide predictions and, subsequently, experiment design. Mechanistic inference typically requires lengthy simulations (e.g., the Stochastic Simulation Algorithm (SSA)); approximations to chemical master equation (CME) solutions that lack rigorous error tracking; or deterministic averaging that lacks the complexity necessary to reflect the data. We introduce the Stochastic System Identification Toolkit (SSIT) - a fast, flexible, and open-source software package available on GitHub that makes use of MATLAB's efficient and diverse computational architecture. The SSIT is designed for building, simulating, and solving chemical reaction models using ODEs, moments, SSA, Finite State Projection truncations of the CME, or hybrid methods; sensitivity analysis and Fisher information quantification; parameter fitting using likelihood-or Bayesian-based methods; handling of experimental noise and measurement errors using probabilistic distortion operators; and sequential experiment design that empowers users to save time and resources while gaining the most information possible out of their data. The SSIT also offers advanced modeling tools, including model reduction methods for increased efficiency and joint fitting of models and datasets with overlapping reactions/parameters. To facilitate the ease and speed of use, the SSIT provides a graphical user interface and ready-made, adaptable pipelines that can be run in the background from commandline or high-performance computing clusters. We demonstrate features of the SSIT on two experimental datasets: the first consists of published mRNA count data that reflect Saccharomyces cerevisiae yeast cell response to osmotic shock using single-cell single-molecule fluorescence in situ hybridization; the second consists of single-cell RNA sequencing measurements of 151 activating genes in breast cancer cells following treatment with dexamethasone.
Author summary: We present the Stochastic System Identification Toolkit (SSIT) to model, fit, and predict any data that can be interpreted as changing populations or counts through time, including but not limited to single-cell experiments, economics, epidemiology, ecology, sociology, agriculture, and biotechnology. The SSIT was constructed particularly for stochastic modeling, which is important for systems whose states may experience significant fluctuations from mean behavior, thus affecting the inference of the underlying rate parameters and predictions of subsequent behavior. The SSIT provides statistical inference tools for parameter estimation; sensitivity analysis and information calculation; handling of distortions to probability distributions caused by experimental and/or measurement processes (e.g., dropout in single-cell RNA sequence data and total fluorescence intensities versus spot counting/puncta analysis); and quantitative experimental design. The SSIT also offers a variety of complex modeling tools, including model reduction methods and fitting of combined models/datasets that share some behavior but remain distinct (e.g., different genes responding a single stimulus). The SSIT generates pipelines for easy, efficient analyses to run in the MATLAB environment, in the background on commandline, or on high-performance computing clusters, thus facilitating users to make informed, time- and cost-effective decisions about their next set of experiments.

DOI: https://doi.org/10.64898/2026.02.20.707039
bioRxiv. 2026 Feb 09. pii: 2026.02.06.704469. [Epub ahead of print]

SenNet Portal: Build, Optimization and Usage.

SenNet Team

Cellular senescence is a hallmark of aging and a driver of functional decline across tissues, yet its heterogeneity and context dependence have limited systematic study. The Common Fund's Cellular Senescence Network (SenNet) Program addresses this challenge by generating multimodal, multi-tissue datasets that profile senescent cells across the human lifespan and complementary mouse models. The SenNet Data Portal ( https://data.sennetconsortium.org ) serves as the public gateway to these resources, providing open access to harmonized single-cell, spatial, imaging, transcriptomic, and proteomic data; senescence biomarker catalogs; and standardized protocols that can be used to comprehensively identify and characterize senescent cells in mouse and human tissue. As of January 2026, the portal hosts 1,753 publicly available human and mouse datasets across 15 organs using 6 general assay types. Experts from 13 Tissue Mapping Centers (TMCs) and 12 Technology Development and Application (TDAs) components contribute tissue data, analyze data, identify senescent biomarkers, and agree on panels for cross-tissue antibody harmonization. They also register human tissue data into the Human Reference Atlas (HRA) and develop user interfaces for the multiscale and multimodal exploration of this data. Built on a scalable hybrid cloud microservices architecture by the Consortium Organization and Data Coordinating Center (CODCC), the Portal enables data submission, management, integrated analysis, spatial context mapping, and cross-species senescence mapping critical for aging research. This paper presents user needs, the Portal's architecture, data processing workflows, and senescence-focused analytical tools. The paper also presents usage scenarios illustrating applications in biomarker discovery, quality benchmarking, hypothesis generation, spatial analysis, cost-efficient profiling, and cell distance distribution analysis. Current limitations and planned extensions-including expanded spatial-omics releases and improved tools for senotype characterization-are discussed. SenNet protocols, code, and user interfaces are freely available on https://docs.sennetconsortium.org/apis .

DOI: https://doi.org/10.64898/2026.02.06.704469
Cell Syst. 2026 Feb 26. pii: S2405-4712(25)00347-3. [Epub ahead of print] 101514

Genetic resonance in the p53 signaling network.

Mathias S Heltberg, Alba Jimenez, Galit Lahav, Mogens H Jensen.

  Resonance allows systems to amplify their response to periodic stimuli and is well established in physics but not yet described in gene regulatory networks. Here, we asked whether resonance exists in the dynamics of p53, a tumor suppressor that oscillates after DNA damage to activate growth-inhibitory pathways. We developed a mathematical framework predicting that p53 exhibits damped oscillations after a single stimulus and frequency-dependent amplitudes under periodic stimulation, both hallmarks of resonance. Using live single-cell imaging, we confirmed these predictions: a single drug pulse that stabilizes p53 produced damped oscillations, while periodic pulses triggered frequency-dependent responses with maximal amplitudes at the natural p53 oscillation frequency as well as minor peaks. Finally, theoretical analysis suggested that resonance may enhance transcriptional responses and selectively activate downstream targets. Together, our results identify resonance as a regulatory principle in gene networks, potentially linking oscillations of transcription factors with selective gene activation through signal amplification.

Keywords:  cellular regulation; damped oscillations; enhanced transcription; genetic oscillations; non-linear resonance; p53 network; resonance; selective gene expression; signal amplification

DOI:  https://doi.org/10.1016/j.cels.2025.101514
iScience. 2026 Feb 20. 29(2): 114780

Comparing the impact of sample multiplexing approaches for single-cell RNA-sequencing on downstream analysis using cerebellar organoids.

Kseniia Sarieva, Theresa Kagermeier, Vladislav Lysenkov, Francesco Castagnetti, Zeynep Yentuer, Katharina Becker, Julia Matilainen, Nicolas Casadei, Simone Mayer.

  Multiplexing overcomes limited throughput in single-cell RNA sequencing (scRNA-seq). Commercial strategies include Parse Biosciences combinatorial barcoding (Parse) and 10x Genomics CellPlex with microfluidic capture (10x). It is currently unknown how these techniques differ when characterizing complex tissues. Cerebellar organoids are a highly relevant model for studying cerebellar evolution, development, and disease. Yet, their extensive characterization through scRNA-seq is ongoing. Therefore, we compared the two multiplexing techniques using cerebellar organoids. While both strategies demonstrated technical reproducibility and revealed comparable cellular diversity, we found more stressed cells in 10x than in Parse. Additionally, Parse covered a higher gene biotype diversity and showed lower mitochondrial and ribosomal protein-coding transcript fractions. In summary, we demonstrate that both techniques provide similar insight into cerebellar organoid biology, but the flexibility of experimental design, capture of long transcripts, and the level of cell stress caused by the two workflows differ.

Keywords:  biological sciences; cell biology; cellular neuroscience; natural sciences

DOI:  https://doi.org/10.1016/j.isci.2026.114780
Sci Signal. 2026 Feb 24. 19(926): eadx8680

Temporal proteomic and phosphoproteomic dynamics during neuronal differentiation in the reference iPSC line KOLF2.1J.

Ying Hao, Ziyi Li, Erika Lara, Daniel M Ramos, Marianita Santiana, Benjamin Jin, Jacob Epstein, Isabelle Kowal, Jasmin Camacho, Nicole Carmiol, Jae-Hyeon Park, Aleksandra Beylina, Linda G Yang, Jessica T Root, Dylan C Sacks, Paige Jarreau, Cory A Weller, Sydney Klaisner, Laurel A Screven, Caroline B Pantazis, Mike A Nalls, Priyanka Narayan, Luigi Ferrucci, Andrew B Singleton, Michael E Ward, Mark R Cookson, Yue Andy Qi.

Induced pluripotent stem cell (iPSC)-derived neurons are a powerful tool with which to investigate both neuronal development and neurodegenerative diseases. Here, we applied quantitative proteomic and phosphoproteomic analyses to profile the neuronal differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphorylated peptides, which revealed molecular signatures during the differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, whereas phosphoproteomic data revealed specific regulatory dynamics in GTPase-mediated signaling pathways and microtubule proteins. Additionally, phosphosite dynamics were not correlated to changes in protein abundance, particularly in processes related to axon functions and RNA transport. We measured the dynamic changes in kinases that are critical for neuronal development and maturation and developed an interactive web app to visualize the temporal landscape dynamics of protein and phosphosite abundance. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset is a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line.

DOI: https://doi.org/10.1126/scisignal.adx8680
Proc Natl Acad Sci U S A. 2026 Mar 03. 123(9): e2521253123

The Nemp1-Nesprin complex mediates cellular responses to matrix mechanics.

Abira Ganguly, Hannah Zmuda, Javier Abello, Danielle Illy, Christopher Walter, Yonit Tsatskis, Nattapon Thanintorn, Ying Zhang, Bilal Ahmad Hakim, Didier Hodzic, Amber N Stratman, Andrea Jurisicova, Amit Pathak, Helen McNeill.

  Nuclear Envelope Membrane Protein 1 (NEMP1) is crucial for metazoan fertility; loss of Nemp1 causes death of primordial oocytes that reside in the mechanically challenging ovarian cortex. Here, we show that softening the ovary rescues oocyte loss and restores fertility in Nemp1 knockout (KO) mice. In cell culture, NEMP1 depletion on stiff substrates leads to death, while cells remain viable on soft substrates. We further show that NEMP1 regulates YAP nuclear translocation, essential for mechanotransduction. Mechanistically, Nemp1-depleted cells on stiff substrates or subjected to stretching exhibit reduced nuclear YAP localization, and expressing nuclear YAP5SA restores cell viability. Loss of NEMP1 disrupts actin organization. Inducing actin polymerization partially rescues nuclear YAP, indicating a role for F-actin in NEMP1 mediated mechanotransduction. NEMP1 forms a complex with NESPRIN's Klarsicht, Anchorage (ANC)-1, Syne Homology (KASH) domain, strengthening the actin cytoskeleton to withstand mechanical forces, independent of SUN proteins. Thus, the Nemp1-Nesprin complex supports a mechanosensitive pathway parallel to the LINC complex, enabling cellular response to mechanical stress in vitro and in vivo.

Keywords:  KASH domain; Nemp1; YAP nuclear translocation; cellular responses to mechanical stress; nuclear mechanotransduction

DOI:  https://doi.org/10.1073/pnas.2521253123