Biology subjects

Ren, S.

Publications and source records attributed to Ren, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Neutrophils orchestrate pre-metastatic immunosuppressive bone marrow remodeling during prostate cancer metastasis

The dynamic reprogramming of the bone marrow (BM) microenvironment during metastatic progression is poorly defined. Through single-cell profiling of BM samples spanning benign conditions, high-risk bone metastatic potential localized prostate cancer (HMP) and established bone metastatic prostate cancer (PCa), we uncovered a primary tumor-to-BM signaling axis that orchestrates niche formation through neutrophil-mediated remodeling. Tumor-associated neutrophils (TANs) emerge during the HMP stage, persist throughout metastatic progression, correlate with poor patient prognosis, and exhibit direct immunosuppressive activity that contributes to a BM environment permissive to metastatic colonization. Functional and genetic studies showed that tumor-associated systemic IGF1 reprogrammed BM neutrophils through IGF1R-MAPK/ERK-KLF4 signaling, with IL-1{beta}, reactive oxygen species and nitric oxide contributing to TAN-mediated T cell suppression. Tumor-cell Igf1 perturbation, IGF1R blockade and neutrophil-specific Igf1r deletion attenuated TAN-associated BM remodeling, and reduced subsequent bone metastatic progression. In bone-metastasis models, combined IGF1R and PD-1 blockade suppressed bone-metastatic progression. Translationally, our investigator-initiated clinical trial (NCT06866548) of teprotumumab plus tislelizumab in patients with established metastatic castration-resistant prostate cancer (mCRPC) provided initial safety data and exploratory clinical observations. Together, these findings identify IGF1R-dependent neutrophil reprogramming as a functionally important component of the evolving PCa bone metastatic microenvironment and provide a rationale for therapeutic targeting of IGF1R signaling together with immune checkpoint blockade.

cancer biology↗

bioRxiv2026

A biologically supported global RNA architecture of cucumber mosaic virus satellite RNA

Satellite RNAs (satRNAs) are parasitic subviral agents whose biological activities are mediated largely by specific sequence determinants and structured RNA elements. Establishing biologically supported global RNA structures is therefore essential for understanding how RNA architecture underlies satRNA functions. Cucumber mosaic virus (CMV) satRNA is one of the best-characterized models for investigating satRNA structure-function relationships; however, a biologically supported global RNA architecture of CMV satRNA has yet to be established. Here, we applied AlphaFold3 modeling to predict the global structure of CMV satRNA T1 (sat-T1). Initial full-length structure modeling generated multiple long-distance interactions that lacked biological support. We therefore used fragment-based modeling, combined with chemical probing, evolutionary covariation, and compensatory mutagenesis, to derive a biologically supported global secondary structure. To determine whether structurally distant regions could interact in the context of the full-length RNA, we engineered a structure-guided T1-ZD mutant that preserved the supported secondary structure while reducing alternative base-pairing possibilities. Full-length AlphaFold3 modeling of T1-ZD largely recapitulated the proposed architecture, while one predicted model revealed a long-distance interaction that was subsequently supported by compensatory mutagenesis analysis. These findings suggest that the 3' terminus of sat-T1 may undergo conformational switching between alternative structural states. Together, our work establishes a biologically supported global RNA architecture for CMV sat-T1 and provides a structural framework for investigating the molecular basis of satRNA function.

microbiology↗

bioRxiv2026

Extracellular injection system combined with peptides for intracellular Staphylococcus aureus treatment

The inaccessibility of intracellular bacteria has long rendered the treatment of Staphylococcus aureus infections an challenge. Studies have demonstrated that the extracellular injection system PVC can accurately deliver proteins into cells, which would not need small molecules, and enables effective intracellular delivery of antimicrobial peptides for treatment. Accordingly, we selected antimicrobial peptides including Cecropin, LL37 and Indolicidin that possess potent bactericidal activity, and established the Directed Antimicrobial Assault platform (DAAT) by leveraging the intracellular delivery capacity of PVC. DAAT Cecropin, DAAT LL37 and DAAT Indolicidin inhibited intracellular bacteria in a dose-dependent manner, with DAAT LL37 reaching 86.76% inhibition; after 72 h of treatment, viable-cell numbers reduse to 66--82-fold those of the control. Tail-fibre retargeting enabled direct extracellular S. aureus killing, while combined DAAT therapy promoted wound healing in mice. These findings expand the utility of PVC-derived nanosyringes and establish DAAT as a modular platform for intracellular antimicrobial peptide therapy.

synthetic biology↗

bioRxiv2026

A brain-tumour axis links chronic stress to gastric cancer progression through NPY signalling

Chronic stress promotes gastric tumour growth, but the central neural pathways remain largely enigmatic. Here, we identify a brain-tumour axis, implicating the central amygdala (CeA) activity in promoting gastric cancer growth through sympathetic neuropeptide Y (NPY) signalling occurring within the tumour. Using clinical datasets, patient samples, pathway tracing, electrophysiology and chemogenetic manipulation, we demonstrate that stress selectively increases NPY Y1 receptor (NPY1R) synthesis in the patients gastric cancer tissue; moreover, the NPY1R density correlates with advanced cancer stage and poor prognosis. In mice, daily constraint chronic stress enhances CeA excitability and promotes sympathetic neurotransmitter norepinephrine release within the tumour microenvironment. Norepinephrine, in turn, increases tumour endogenous NPY/NPY1R production and the activation of downstream MAPK/Erk1/2 signalling pathway, which drives cancer cell proliferation and invasion. Manipulating CeA neuronal activity alone can regulate tumour growth, whereas selectively blocking tumour NPY1R prevents stress-induced tumour progression in vivo and cancer cell migration in vitro. This study identifies a central-to-peripheral circuit linking chronic stress to gastric cancer growth, and highlights NPY1R as a potential therapeutic target.

Cancer Biology↗

bioRxiv2026

Elimination of intramuscular immunoglobulin accumulation alleviates Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a devastating neuromuscular disorder due to loss of dystrophin, a cytoskeletal protein critical for muscle integrity and functionality. Despite recent therapeutic advances, there remains a significant unmet need for more effective and accessible therapeutics. Here, we discovered an early accumulation of immunoglobulin G (IgG) in the sarcolemma, which exacerbates tissue inflammation and disease progression. The IgG accumulation primarily resulted from ectopic localization of Fc{gamma}R1, a high-affinity IgG Fc receptor, on dystrophin-deficient myofibers. In two independent murine models, eliminating IgG accumulation via B cell depletion provided sustained benefit to alleviate DMD progression. Our findings uncover a novel disease accelerator in DMD and demonstrate the potential to target this mechanism as therapeutics for broader population of patients with DMD.

immunology↗

bioRxiv2026

A Cationic Amphiphilic Drug (CAD) Defense System in the Nematode Caenorhabditis elegans

Cationic Amphiphilic Drugs (CADs) severely disrupt lysosomal function, which leads to a cellular pathology characterized by excess phospholipids called phospholipidosis. Through a forward genetic screen and mining of published datasets, we discovered that CADs induce the expression of the CYP-35B family of cytochrome P450s and the PGP-13 p-glycoprotein pump via the nuclear receptors NHR-70 and NHR-107 in the nematode C. elegans. A pgp-13 fluorescent reporter revealed hundreds of human drugs that upregulate the CAD defense system in vivo. Chemoinformatic analyses indicate that the pgp-13 reporter may be useful in identifying CADs that have pathogenic potential in humans. Mutant analyses coupled to metabolomics and structural modeling show that the CYP-35Bs are necessary and sufficient for CAD metabolism, and that CYP-35B2 D311 is key in mediating electrostatic interactions with the positively charged CADs. We also show that CAD metabolites are effluxed via PGP-13 acting partially redundantly with PGP-14 and that an intact defense system is necessary to resist CAD-induced pathology. Finally, we demonstrate that bacteria that likely cohabitate with C. elegans in nature trigger the CAD defense system, providing a plausible explanation for why a pathway that protects against anthropogenic small molecules exists in nematodes.

pharmacology and toxicology↗

bioRxiv2025

Causal Modeling Reveals Cell-Cell Communication Dynamics in the Tumor Microenvironment During Anti-PD-1 Therapy in Breast Cancer Patients

BackgroundImmune checkpoint blockade (ICB) targeting PD-1/PD-L1 plays a crucial role in breast cancer treatment. Despite clinical success, how ICB reshapes the tumor microenvironment (TME) to enhance anti-tumor activity remains unclear. Anti-PD-1 therapy alters TME cells beyond PD-1+ T cells, with extensive cell-cell communication (CCC) playing a key role. Understanding the dynamic CCC changes upon anti-PD-1 treatment can illuminate ICB mechanisms of action and TME dynamics. MethodsWe analyzed single-cell RNA-seq data from 31 breast cancer patients before and after anti-PD-1 (pembrolizumab) treatment (Bassez et al., 2021). We identified differentially expressed genes (DEGs) induced by treatment in major cell types. We then applied an instrumental variable approach to uncover causal relationships between T-cell and non-T-cell DEGs. We further mapped ligand-receptor interactions mediating signal transduction between cells and constructed a CCC network from T to non-T cells. ResultsAnti-PD-1 therapy induced widespread transcriptional changes across multiple cell populations. Key pathways modulated in T cells included NF-{kappa}B, interferon-{gamma}, and interleukin signaling. CD4+ and CD8+ exhausted T cells engaged in distinct ligand-receptor interactions with tumor-associated macrophages (TAMs) and other types of cells, reshaping the TME. Our results indicated CD4+ exhausted T cells activated M1-like TAMs via TNF-TNFRSF1A and TNFSF14-LTBR, while CD8+ exhausted T cells engaged M1-like TAMs through ICAM1-ITGAL/ITGB2 and CCL8-CCR2, promoting anti-tumor immunity. Conversely, immunosuppressive interactions were also observed, such as TNF-TNFRSF1B (TNFR2) and TNFSF14-TNFRSF14 (HVEM) from CD4 T cells, as well as CSF1-CSF1R and RPS19-C5AR1 from CD8 T cells, which likely promote M2-like tumor-associated macrophage (TAM) polarization and contribute to pro-tumor immune regulation and resistance to therapy. Notably, key receptors in the causal CCC networks, such as C5AR1, TNFR2, and CSF1R, emerged as potential targets to enhance anti-PD-1 efficacy. ConclusionsThese findings elucidate TME remodeling during anti-PD-1 therapy and underscore the pivotal role of CCC in treatment response. Our study identifies critical communication networks that may be biomarkers for immunotherapy responsiveness and highlights novel therapeutic targets, including C5AR1 and HVEM. Furthermore, our application of causal inference methodologies provides a robust framework for dissecting CCC mechanisms in immunotherapy.

bioinformatics↗

bioRxiv2025

UniCure: A Foundation Model for Predicting Personalized Cancer Therapy Response

Predicting drug efficacy across diverse patient contexts remains a major challenge in oncology, as models trained on cancer cell lines often fail to capture patient-specific biology. Emerging biological foundation models and patient-derived technologies offer a promising solution. Here, we present UniCure, the first pre-trained foundation model integrating both omics and chemical foundation models (UCE and Uni-mol) to predict transcriptomic responses to drugs across diverse cellular and tissue contexts, enabling personalized cancer therapy and drug prioritization at the individual level. Rather than encoder/decoder used in traditional models, UniCure utilizes parameter-efficient fine-tuning (PEFT) techniques for optimizing the training process, a novel FlexPert module for modeling flexible drug-cell interactions, and a Maximum Mean Discrepancy (MMD) loss for learning unpaired data. Trained on over 1.8 million perturbation RNA-seq profiles over 22,000 compounds, 166 cell types, and 24 tissues, UniCure achieves high accuracy in predicting both dose-dependent responses and drug combination effects, demonstrating strong generalization across bulk and single-cell transcriptomic data. In particular, fine-tuning on our patient-derived tumor-like clusters and real-world data of 800 profiles enables UniCure to generate individualized therapeutic predictions on patients tissue samples. In addition, UniCure enables patient stratification based on the predicted drug responses, providing a new way for subtyping patients. UniCures drug prioritization was validated across over 1000 patients from pan-cancer cohorts and supported by experiments of candidate therapeutics. By enabling the potential to screen millions of compounds per patient at scale, UniCure represents a biologically grounded tool that could advance personalized precision oncology and accelerate drug discovery.

bioinformatics↗

bioRxiv2025

Multitargeted Reduction of Inflammation and Atherosclerosis in Tet2-deficient CHIP via XPO1 Inhibition and Atf3 restoration

TET2 is the second most frequently mutated gene in clonal hematopoiesis of indeterminate potential (CHIP), driving hematopoietic stem cell clonal expansion and increasing the risk of myeloid malignancies. Affected individuals often develop atherosclerotic cardiovascular disease, exacerbated by hyperinflammatory TET2-mutant macrophages. Here, we show that the XPO1 nuclear export inhibitor eltanexor significantly reduces atherosclerotic plaque formation in a mouse model of Tet2-mutant CHIP. In addition, we investigated the mechanisms and gene expression pathways that underlie the proinflammatory phenotype that characterizes Tet2-mutant CHIP. Single-cell CITE-seq identified increased expression of multiple proinflammatory mediators in Tet2-mutant macrophages and in non-hematopoietic cells of the aortic wall, which was reduced by eltanexor treatment. Atf3, which encodes a core transcriptional modulator of inflammation, occupies and regulates the largest enhancer in wild-type macrophages. Tet2 loss diminished ATF3 binding to the regulatory loci of inflammatory mediators, which was restored upon XPO1 inhibition. These results provide new insights into drivers of heightened inflammation in TET2-mutant CHIP and highlight a novel therapeutic strategy for intervention.

immunology↗

bioRxiv2025

Discover the Maze-like Pathway for Glabridin Biosynthesis

Tailoring enzymes diversify plant metabolite scaffolds through complex, context-dependent modifications, generating maze-like biosynthetic networks that complicate metabolic pathway reconstruction. Here, we systematically deconstructed and reconstructed the biosynthetic network of glabridin, a valuable skin-whitening isoflavone from Glycyrrhiza. By integrating metabolic pathway mining with genome and 183 transcriptomes, we identified four functional routes among sixteen theoretical possibilities and uncovered a previously uncharacterized, ladder-like multi-route tailoring network. Reconstruction of such architecture in yeast revealed metabolic redundancy and interconnectivity confer unexpected robustness, enabling higher production efficiencies compared to a single-route design. Further modular engineering enabled the de novo biosynthesis of glabridin in yeast. Our work establishes a framework for reconstructing metabolic mazes and demonstrates that multi-route architectures can be harnessed to enhance the robustness and productivity of cell factories.

synthetic biology↗

bioRxiv2025

Multi-scale simulations of membrane adhesion mediated by CD47-SIRPα complexes

Adhesion of biological cells is essential for various processes, including tissue formation, immune responses, and signaling. It involves multiple length scales, ranging from nanometers to micrometers, which are characteristic of (a) the intercellular receptor-ligand binding that mediates the cell adhesion, (b) the spatial distribution of the receptor and lignad proteins in the membranes of adhering cells, (c) adhesion-induced deformations and thermal undulations of the membranes, (d) the overall size of the interface between adhering cells. Therefore, computer simulations of cell membrane adhesion require multi-scale modeling and suitable approximations that capture the essential physics of the system under study. Here, we introduce such a multi-scale approach to study membrane adhesion mediated by the CD47-SIRP binding, which is an immunologically relevant process. The synergetic use of coarse-grained molecular dynamics simulations and mesoscale kinetic Monte Carlo simulations allows us to explore both equilibrium properties and dynamical behavior of adhering membranes on the relevant length scales between 1 nm and 1 {micro}m on time scales ranging from 0.1 ns all the way up to about 20 s. The multi-scale simulations not only reproduce available experimental data but also give quantitative predictions on binding-induced conformational changes of SIRP and membrane-mediated cooperativity of the CD47-SIRP binding as well as fluctuation-induced interactions between the CD47-SIRP complexes. Our approach is applicable to various membrane proteins and provides invaluable data for comparison with experimental findings.

biophysics↗

bioRxiv2025

Absolute Quantification of Aging-Associated Glycans in IgG for Biological Age Prediction: Insights from Glycomics and Transcriptomics

Immunoglobulin G (IgG) N-glycans have been identified as associated with aging; however, previous studies predominantly quantified changes based on the relative percentages of each glycan within the total glycan pool, neglecting the absolute concentration changes of individual glycans. Additionally, relative quantification can limit practical applications, as these often require absolute concentration measurements for consistent and interpretable biomarker values. In this study, we introduce a novel strategy for discovering aging-associated IgG glycans and establishing a prediction model based on their absolute concentration alteration. We employed a glycome quantification technology to identify the alteration in IgG glycan amount in natural aging and anti-aging (caloric restriction) models, discovering aging-related glycans. The glycomics analysis revealed key features: downregulation of bisected glycan GP3 (F(6)A2B) and upregulation of digalactosylated glycan GP8 (F(6)A2G2). These glycan changes showed significant fold changes from an early stage. Using external standards of these two glycans, we subsequently measured the absolute concentrations of them, allowing us to establish a predictive model, abGlycoAge, for biological aging. The abGlycoAge index suggested a younger state under caloric restriction, with an average age reduction of 3.9-14 weeks. Additionally, we performed RNA sequencing on splenic B cells of mice, suggesting Derl3, Smarcb1, Ankrd55, Tbkbp1 and Slc38a10 could contribute to the alteration of GP3 and GP8 in aging. This analysis enhances our understanding of glycan alterations, accounts for individual variability, and aids in designing effective anti-aging strategies. These findings highlight the crucial roles of the GP3 and GP8 as potential biomarkers for aging and health.

biochemistry↗

bioRxiv2024

Mapping DNA Methylation to Cardiac Pathologies Induced by Beta-Adrenergic Stimulation in a Large Panel of Mice

BackgroundHeart failure (HF) is a leading cause of morbidity and mortality worldwide, with over 18 million deaths annually. Despite extensive research, genetic and environmental factors contributing to HF remain complex and poorly understood. Recent studies suggest that epigenetic modifications, such as DNA methylation, may play a crucial role in regulating HF-associated phenotypes. In this study, we leverage the Hybrid Mouse Diversity Panel (HMDP), a cohort of over 100 inbred mouse strains, to investigate the role of DNA methylation in HF progression. ObjectiveWe aim to identify epigenetic modifications associated with HF by integrating DNA methylation data with gene expression and phenotypic traits. Using isoproterenol (ISO)-induced cardiac hypertrophy and failure in HMDP mice, we explore the relationship between methylation patterns and HF susceptibility. MethodsWe performed reduced representational bisulfite sequencing (RRBS) to capture DNA methylation at single-nucleotide resolution in the left ventricles of 90 HMDP mouse strains under both control and ISO-treated conditions. We identified differentially methylated regions (DMRs) and performed an epigenome-wide association study (EWAS) using the MACAU algorithm. We identified likely candidate genes within each locus through integration of our results with previously reported sequence variation, gene expression, and HF-related phenotypes. In vitro approaches were employed to validate key findings, including gene knockdown experiments in neonatal rat ventricular myocytes (NRVMs). We also examined the effects of preventing DNA methyltransferase activity on HF progression. ResultsOur EWAS identified 56 CpG loci significantly associated with HF phenotypes, including 18 loci where baseline DNA methylation predicted post-ISO HF progression. Key candidate genes, such as Prkag2, Anks1, and Mospd3, were identified based on their epigenetic regulation and association with HF traits. In vitro follow-up on a number of genes confirmed that knockdown of Anks1 and Mospd3 in NRVMs resulted in significant alterations in cell size and blunting of ISO-induced hypertrophy, demonstrating their functional relevance in HF pathology. Furthermore, treatment with the DNA methyltransferase inhibitor RG108 in ISO-treated BTBRT mice significantly reduced cardiac hypertrophy and preserved ejection fraction compared to mice only treated with ISO, highlighting the therapeutic potential of targeting DNA methylation in HF. Differential expression analysis revealed that RG108 treatment restored the expression of several methylation-sensitive genes, further supporting the role of epigenetic regulation in HF. ConclusionOur study demonstrates a clear interplay between DNA methylation, gene expression, and HF-associated phenotypes. We identified several novel epigenetic loci and candidate genes that contribute to HF progression, offering new insights into the molecular mechanisms of HF. These findings underscore the importance of epigenetic regulation in cardiac disease and suggest potential therapeutic strategies for modifying HF outcomes through targeting DNA methylation.

genomics↗

bioRxiv2024

Sirt5 regulates chondrocyte metabolism and osteoarthritis development through protein lysine malonylation

ObjectivesChondrocyte metabolic dysfunction plays an important role in osteoarthritis (OA) development during aging and obesity. Protein post-translational modifications (PTMs) have recently emerged as an important regulator of cellular metabolism. We aim to study one type of PTM, lysine malonylation (MaK) and its regulator Sirt5 in OA development. MethodsHuman and mouse cartilage tissues were used to measure SIRT5 and MaK levels. Both systemic and cartilage-specific conditional knockout mouse models were subject to high-fat diet (HFD) treatment to induce obesity and OA. Proteomics analysis was performed in Sirt5-/- and WT chondrocytes. SIRT5 mutation was identified in the Utah Population Database (UPDB). ResultsWe found that SIRT5 decreases while MAK increases in the cartilage during aging. A combination of Sirt5 deficiency and obesity exacerbates joint degeneration in a sex dependent manner in mice. We further delineate the malonylome in chondrocytes, pinpointing MaKs predominant impact on various metabolic pathways such as carbon metabolism and glycolysis. Lastly, we identified a rare coding mutation in SIRT5 that dominantly segregates in a family with OA. The mutation results in substitution of an evolutionally invariant phenylalanine (Phe-F) to leucine (Leu-L) (F101L) in the catalytic domain. The mutant protein results in higher MaK level and decreased expression of cartilage ECM genes and upregulation of inflammation associated genes. ConclusionsWe found that Sirt5 mediated MaK is an important regulator of chondrocyte cellular metabolism and dysregulation of Sirt5-MaK could be an important mechanism underlying aging and obesity associated OA development.

cell biology↗

bioRxiv2024

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

Penaeid shrimp farming plays a pivotal role in ensuring future food security and promoting economic sustainability. Compared to the extensive long history of domestication observed in terrestrial agriculture species, the domestication and selective breeding of penaeids are relatively recent endeavors. Selective breeding aimed at improving production traits holds significant promise for enhancing efficiency and reducing the environmental impact of shrimp farming, thereby contributing to its long-term sustainability. Assessing genotype-by-environment (G-by-E) interactions is essential in breeding programs to ensure that improved penaeid shrimp strains perform consistently across different production environments, with genomic selection proving more effective than sib-testing alone in mitigating environmental sensitivity. Genome editing tools like CRISPR/Cas9 offer significant potential to accelerate genetic gains in penaeid shrimp by enabling rapid introduction of desired genetic changes, with recent advancements showing promising results in achieving high transfection efficiency in shrimp embryos. Additionally, artificial intelligence and machine learning are being leveraged to streamline phenotyping and enhance decision-making in shrimp breeding and farming, improving efficiency and accuracy in managing traits and predicting disease outbreaks. Herein, we provide an overview and update on the domestication of penaeid shrimp, including the current status of domestication for principal farmed species, key milestones in domestication history, targeted breeding traits in selective breeding programs, the advantages of integrating genomeic selection for enhancing production traits, and future directions for selective breeding of penaeid shrimp.

genetics↗

bioRxiv2024

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples. HIGHLIGHTSO_LIRelapse after remission on TKI can harbor mutations in ABL1, RAS, or neither C_LIO_LIMutations and development-like cell state dictate fitness in residual disease C_LIO_LICo-targeting cell state and ABL1 markedly reduces MRD C_LIO_LIBiophysical measurements provide an integrative, rapid measurement of cell state C_LI

cancer biology↗

bioRxiv2023

When to attend? Temporal attention interacts with expectation

Temporal attention is voluntarily deployed at specific moments, whereas temporal expectation is deployed according to timing probabilities. When the target appears at an expected moment in a sequence, temporal attention improves performance at the attended moments, but the timing and the precision of the attentional window remain unknown. Here we independently and concurrently manipulated temporal attention-via behavioral relevance-and temporal expectation-via session-wise precision and trial-wise hazard rate-to investigate whether and how these mechanisms interact to improve perception. Our results reveal that temporal attention interacts with temporal expectation-the higher the precision, the stronger the attention benefit, but surprisingly this benefit decreased with delayed onset despite the increasing probability of stimulus appearance. When attention was suboptimally deployed to earlier than expected moments, it could not be reoriented to a later time point. These findings provide evidence that temporal attention and temporal expectation are different mechanisms, and highlight their interplay in optimizing visual performance. RelevanceOur ability to process visual information is limited both across space and time. Here we disentangle how two mechanisms-attention and expectation-help us overcome temporal limitations. We concurrently manipulated attention and expectation independently to investigate whether and how they interact. We found that temporal attention interacts with two distinct forms of expectation. Temporal expectation strengthens the benefits of temporal attention on performance for the attended time points, depending on how precise the expectations are. Surprisingly, the advantages of attention decrease when stimuli occur later than expected, suggesting a limitation of attention to reorient from earlier to later time points. This study provides further evidence that humans cannot sustain temporal attention even over short periods, reveals that although temporal attention and expectation interact to improve visual performance, expectation suboptimally guides attention, and highlights that attention and expectation are different temporal mechanisms.

neuroscience↗

bioRxiv2023

An interpretable deep learning framework for genome-informed precision oncology

Cancers result from aberrations in cellular signaling systems, typically resulting from driver somatic genome alterations (SGAs) in individual tumors. Precision oncology requires understanding the cellular state and selecting medications that induce vulnerability in cancer cells under such conditions. To this end, we developed a computational framework consisting of two components: 1) A representation-learning component, which learns a representation of the cellular signaling systems when perturbed by SGAs, using a biologically-motivated and interpretable deep learning model. 2) A drug-response-prediction component, which predicts the response to drugs by leveraging the information of the cellular state of the cancer cells derived by the first component. Our cell-state-oriented framework significantly enhances the accuracy of genome-informed prediction of drug responses in comparison to models that directly use SGAs as inputs. Importantly, our framework enables the prediction of response to chemotherapy agents based on SGAs, thus expanding genome-informed precision oncology beyond molecularly targeted drugs.

bioinformatics↗