Biology subjects

Ding, L.

Publications and source records attributed to Ding, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Quantitative dissection of the metastatic cascade at single colony resolution

Metastasis is the leading cause of cancer-related deaths. However, the core determinants and mechanistic principles underlying the metastatic cascade remain elusive. Small cell lung cancer (SCLC) is a highly aggressive malignancy with exceptional metastatic potential and limited therapeutic options. Here, we present Metastasis Originated Barcode Sequencing (MOBA-seq), a high-throughput in vivo platform that systematically maps genetic regulators across the metastatic cascade at single-colony resolution. MOBA-seq integrates scalable barcode-based lineage tracing with a computational pipeline that quantitatively deconvolutes genotype-specific effects on metastatic seeding, dormancy, and clonal expansion across hundreds of thousands of metastatic events. Applying this approach to more than 400 candidate regulators of SCLC, we uncovered tissue-specific metastatic suppressors and universal metastatic essential genes. We identified metastatic seeding as the predominant determinant of metastasis. Comparative analysis across recipient mice of distinct genetic backgrounds further revealed that innate immune surveillance constrains metastatic progression by reducing metastatic seeding and enforcing dormancy, with additional modulation by sex and tissue context. We validated the frequently mutated gene CREBBP as a key metastasis suppressor whose loss enhances SCLC metastasis through both tumor-intrinsic and immune-modulatory mechanisms. This work establishes a scalable and quantitative platform for mapping the metastatic fitness landscape at single-colony resolution across hundreds of thousands of in vivo data points. Our approach offers a broadly applicable framework for dissecting the interactions between cancer-intrinsic and microenvironmental factors governing tumor initiation, progression, and therapeutic response.

cancer biology↗

bioRxiv2026

Single-Cell Proteomics of Human Peripheral Blood Mononuclear Cells Exceeding 600 Cells per Day

Single-cell proteomic (scProteomic) measurements of peripheral blood mononuclear cells (PBMCs) are of considerable value in human health, given their involvement in the maintenance of healthy and diseased states. However, the high heterogeneity and relatively small size of immune cell types demand maximal throughput and sensitivity in proteomic measurements that have yet to be fully realized. Here, we describe an approach that addresses sensitivity and throughput through the implementation of Real-Time spectral Library Searching (RTLS), TMTpro 32-plex labelling, an updated nested-nanodroplet processing in One pot for Trace Samples (N2), and a dual-column liquid chromatography system. By prioritizing tandem mass spectrometry (MS2) features with high similarity to library spectra, RTLS enables greater identification depth and feature reproducibility than a standard shotgun MS2 approach in low-input and single-cell samples. The platform permitted 660 single PBMCs to be measured per day, with an average of 750 protein identifications per cell and 1,648 proteins in total, achieving the necessary throughput and depth to characterize immune cell populations. Application of this scProteomic method and a new cell typing informatics approach to 2,130 PBMCs enabled the identification of both major and low-frequency cell types ([~]1-2%), as well as associated proteomic markers.

immunology↗

bioRxiv2026

NanoSimFormer: An end-to-end Transformer-based simulator for nanopore sequencing signal data

Nanopore sequencing has achieved a new standard of accuracy with the advent of R10.4.1 flow cell and high-performance Transformer-based basecalling models. However, existing signal simulators often fail to capture the complex, non-linear dynamics of nanopore current signals, relying on static pore models or lacking optimization objectives linked to basecalling, resulting in synthetic signals with substantially lower accuracy and fidelity than experimental data. To address this, we introduce NanoSimFormer, an end-to-end Transformer-based signal simulator that integrates basecaller guidance during training to generate high-fidelity nanopore signals explicitly optimized for accurate calling. Rigorous evaluation across diverse human, bacterial, and fungal R10.4.1 DNA sequencing datasets demonstrates that NanoSimFormer consistently outperformed competing methods (seq2squiggle and Squigulator), achieving median read accuracies exceeding 99% and Q-scores above 22.8, closely matching experimental baselines. NanoSimFormer faithfully recapitulated experimental variant calling performance on the human HG002 sample, achieving F1-scores of 0.9967 for SNPs and 0.8295 for small indels, and notably minimized false-positive errors in homopolymer and short tandem repeat (STR) regions where other simulators struggled. Furthermore, NanoSimFormer-derived reads enabled high-quality de novo bacterial assembly with consensus error rates below one mismatch per 100 kbp, comparable to experimental assemblies, and preserved fungal mock community structures with high correlation to experimental abundance profiles in metagenomic benchmarks. With tunable parameters for amplitude noise and event duration variance, NanoSimFormer enables the simulation of datasets spanning a wide range of data qualities. Together, these results establish NanoSimFormer as a robust tool for benchmarking and algorithm development in the latest nanopore sequencing era.

bioinformatics↗

bioRxiv2025

Polus: a Transformer-based Soft-decision Codec Enhancement Platform for DNA Storage

DNA storage offers exceptional information density and archival longevity, but is constrained by the complex, heterogeneous errors inherent to synthesis, storage, and sequencing. Conventional error-correction schemes often rely on excessive logical redundancy to mitigate these biochemical imperfections, thereby compromising storage efficiency. Here, we introduce Polus, a deep-learning-enabled platform that bridges the gap between biochemical constraints and digital reliability through soft-decision decoding. At its core is SeqFormer, a Transformer-based channel model that synergizes sequence context with quality signals to characterize platform-specific error profiles, generating calibrated per-base confidence scores. This mechanism transforms uncertain biochemical noise into informative "soft" erasures. In in silico benchmarks, Polus significantly enhances mainstream codecs: it reduces the sequencing coverage required for DNA Fountain by 38.9% --increasing effective physical density by [~]80%--and eliminates persistent indel-induced errors in the Yin-Yang codec. Furthermore, it enables a targeted resequencing strategy that achieves full recovery with 99.9% less overhead than brute-force deepening. To formalize these gains and address the lack of systematic benchmarking in the field, Polus establishes a standardized nine-metric evaluation framework that rigorously quantifies the trade-offs between reliability, density, and cost. This work provides a reproducible, quantitative foundation for next-generation, context-aware DNA storage systems.

bioinformatics↗

bioRxiv2025

Tri-AD: Hippocampal cell-type-specific responses to age, sex and APOE genotype

Alzheimers disease (AD) risk is strongly shaped by age, sex, and the apolipoprotein E {varepsilon}4 (APOE4) allele--the strongest genetic risk factor for late-onset AD. While each factor has been studied independently, their combined impact on cellular and molecular processes remains unclear. Here, we used single-nucleus RNA sequencing (snRNA-seq) to profile hippocampal cell states in a sex-balanced cohort of human APOE4/4 and APOE3/3 knock-in mice across 6, 12, and 18 months of age. We identify sex as the major driver of variation in cell-type abundance and find that oligodendrocytes exhibit pronounced male-biased transcriptional sensitivity to APOE4. Differential expression and cell-cell communication analyses further reveal sex-divergent temporal trajectories in inhibitory neurons, with females showing early APOE4-associated suppression of synaptic pathways and males displaying a delayed but convergent decline. Together, these findings clarify how age, sex, and APOE genotype jointly regulate cell-type-specific gene expression and intercellular communication in the aging hippocampus, providing an innovative and publicly accessible database for aging and AD research and related precision medicine.

bioinformatics↗

bioRxiv2025

De Novo Hepatic Pyrimidine Synthesis Regulates Systemic Energy Homeostasis

Fasting blood uridine is increased in obesity and type 2 diabetes (T2D), but the significance of hepatic uridine biosynthesis to the etiology of both remains elusive. We found that de novo pyrimidine synthesis in the liver is reduced by fasting and diet-induced obesity, while suppression of hepatic pyrimidine synthesis promotes obesity and insulin resistance. The metabolic sequalae of hepatic pyrimidine synthesis suppression, however, is not associated with altered plasma uridine concentration. Instead, it is associated with an increased hepatic glucose production and a decreased hepatic insulin clearance, two key functions of hepatocytes in regulating systemic energy homeostasis. We found that enhanced gluconeogenesis is the primary reason for increased hepatic glucose production. Moreover, uridine, which was maintained stable in the circulation by adipose tissue and the liver, preferentially shut down pyrimidine synthesis in hepatocytes but not adipocytes at blood concentrations that occur with fasting. Remarkably, uridine, at fasting levels, increases gluconeogenesis further in hepatocytes when de novo pyrimidine synthesis is suppressed, indicating a synergistical action of uridine and its biosynthesis pathway in promoting hepatic glucose production, a mechanism highly relevant to the pathophysiology of insulin resistance in obesity. Theologically, maintenance of blood uridine within the narrow range protects mammals from high-rate spontaneous tumorigenesis. Since obesity promotes an increase in blood uridine from adipocytes, suppressing uridine synthesis in hepatocytes becomes a critical response to lower spontaneous tumorigenesis. Pyrimidine synthesis suppression in hepatocytes, however, promotes gluconeogenesis and ultimately triggers obesity and T2D. These findings suggest a new paradigm for the etiology of metabolic deterioration in diet-induced obesity, in which perturbations in uridine promotes obesity and T2D.

pathology↗

bioRxiv2025

Cross-task, explainable, and real-time decoding of human emotion states by integrating grey and white matter intracranial neural activity

Decoding human emotion states from intracranial neural activity is key in developing brain-computer interfaces and new therapies for affective disorders. However, real-world application of decoding requires high performance that integrates neural activity from both grey and white matter, stable generalization across different contexts, sufficient neural encoding explainability, and robust real-time implementation, all of which remain elusive. Here, we simultaneously recorded intracranial electroencephalogram (iEEG) and abundant self-rated valence and arousal scores across two emotion-eliciting tasks in eighteen subjects, forming the largest intracranial neural dataset for emotion decoding. We then developed personalized decoding models within a hybrid deep learning framework involving both self-supervised and supervised components. The models achieved high-performance decoding of continuous valence/arousal states, doubling the R-squared performance of prior EEG/iEEG decoding. Critically, the models significantly improved performance by integrating grey and white matter signals and demonstrated cross-task generalization. The models further revealed shared and preferred mesolimbic-thalamo-cortical subnetworks encoding valence and arousal, showing neurophysiological explainability. Finally, the models realized robust real-time decoding in four new subjects. Our results have implications for advancing emotion decoding neurotechnology toward deployable affective brain-computer interfaces and closed-loop therapeutic systems for affective disorders.

neuroscience↗

bioRxiv2025

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys

The subthalamic nucleus (STN) is a part of the indirect and hyperdirect pathways in the basal ganglia (BG) and has been implicated in movement control, impulsivity, and decision-making. We recently demonstrated that, for perceptual decisions, the STN includes at least three subpopulations of neurons with different decision-related activity patterns (Branam et al., 2024). Here we show that, for decisions that require both perceptual and reward-based processing, many STN neurons are sensitive to both sensory evidence and reward expectations. Within a drift-diffusion framework, three STN subpopulations show different relationships to model components reflecting formation of the decision variable, dynamics of the decision bound, and non-decision-related processes. Many STN neurons also represent quantities related to decision evaluation, including choice accuracy and reward expectation. These results help to further delineate the multiple roles that STN plays in forming and evaluating complex decisions that combine multiple sources of information.

neuroscience↗

bioRxiv2025

PlantScience.ai: An LLM-Powered Virtual Scientist for Plant Science

The accelerating growth of plant science literature presents a major challenge for researchers seeking to extract accurate, up-to-date knowledge from an increasingly fragmented and domain-specific corpus. General-purpose large language models (LLMs), while powerful, often misinterpret plant science terminology and lack mechanisms for source traceability. We created PlantScience.ai, a virtual plant biology scientist powered by our automated scientific knowledge graph construction pipeline (AutoSKG). PlantScience.ai exhibits expert-level reasoning in plant biology and maintains scholarly rigour in its citations. Through continuous learning, it integrates the latest research, ensuring that its knowledge base remains current and scientifically robust. Apart from providing the answers to the scientific questions, PlantScience.ai can interact with human scientists, follow instructions, and retrieve information with citation awareness, grounding each response in primary sources to ensure accuracy and verifiability. PlantScience.ai marks a pivotal advance toward a collaborative scientific paradigm in which virtual and human plant scientists work synergistically to accelerate discovery while preserving the unique value of human insight. PlantScience.ai is available at https://plantscience.ai.

plant biology↗

bioRxiv2025

Task-Based Spinal fMRI using a Median Nerve Stimulation Reveals Functional Alterations in Degenerative Cervical Myelopathy

Functional spinal cord MRI (fMRI) is an emerging technique for evaluating sensorimotor responses in both healthy and disease states. However, degenerative cervical myelopathy (DCM), a non-traumatic, age-related pathology characterized by spinal cord compression, often leads to motor and sensory impairments that make standard task-based fMRI paradigms challenging to perform or execute. To overcome this, we implemented an fMRI paradigm using direct electrical stimulation to the median nerve to evoke neural responses in both motor and sub-motor spinal cord pathways. In this study, 23 DCM and 23 aged-matched healthy controls (HC) underwent two task-based spinal cord fMRI sessions with direct, median nerve stimulation to the right upper limb. Motor thresholds were determined on an individual basis by a thumb/finger twitching, and sub-motor thresholds were set to be 15% underneath motor with no visible twitching. Blood Oxygenation Level Depended (BOLD) signals were analyzed across the C5-C8 cervical spinal cord segments. HCs demonstrated increased activation during motor vs sub-motor stimulation (1155 vs 496 voxels; +7.1%), whereas DCM patients showed reduction in activation with higher stimulation (1028 vs 1220 voxels; -2.2%). This activation pattern was consistent across the cervical spinal segments, with HCs peaking at C7 (sub-motor: 328 voxels, motor: 608 voxels), which is consistent with median nerve input for forearm and hand. While DCM responses were altered, with sub-motor differentially maximized at C6 (406 voxels) and abnormal recruitment at C5 (112 voxels) and C8 (198 voxels). Spatially, HC responses were focused in the gray matter (GM) and bilateral, whereas DCM responses showed reduced GM localization and were more ipsilateral. Furthermore, we saw spikes in sub-motor DCM deactivation at the overall (3032 voxels) and C6 root level (1500 voxels) that were greater than the other conditions. This study demonstrates the feasibility and effectiveness of median nerve stimulation as a task-based paradigm for assessing spinal cord function in those with spinal cord compression. Group level differences between DCM patients and age-matched HCs showed spatial and quantitatively distinct patterns across stimulation thresholds and spinal segments. Our findings suggest disrupted sub-motor and motor activation in the DCM group, highlighting the use of this approach as a functional biomarker to capture disease specific alterations.

neuroscience↗

bioRxiv2025

Class A PBPs reinforce the septal cell wall following initial synthesis by SEDS-bPBP pairs during bacterial cytokinesis

Bacterial cytokinesis requires the coordinated action of septal peptidoglycan (PG) synthases to ensure efficient and accurate septum formation. Two major types of synthases contribute: SEDS-bPBP and bifunctional class A PBPs (aPBPs). How their activities are organized in space and time has remained unclear. Using Deinococcus radiodurans, which often contains both constricting and closed septa in the same cell, we show that septal PG synthesis proceeds through distinct steps at different regions. Primary synthesis at the leading edge by SEDS-bPBP pairs drives constriction, whereas aPBPs act later at the lagging edge and in closed septa to thicken the wall, enhance cross-linking, and reinforce septal integrity. At the single-molecule level, both synthase types move directionally to perform processive PG synthesis at distinct sites. We also observed spatiotemporal separation of SEDS-bPBP and aPBP synthases in Staphylococcus aureus, suggesting that secondary septal PG synthesis is a conserved mechanism securing successful cytokinesis.

microbiology↗

bioRxiv2025

Tau-Driven Coordination of Microtubule-Actin Crosstalk in Cell-Sized Vesicles

The coordination of microtubules (MTs) and actin filaments is essential for cytoskeletal organization, yet the factors that affect their integration remain unclear. Here, we reconstitute cytoskeletal networks in giant unilamellar vesicles to characterize MT-actin crosstalk mediated by tau, a microtubule-associated protein. We show that tau promotes the organization of MTs into diverse architectures, including bundles, clusters, and networks, depending on its concentration and vesicle size. In vitro assays confirm that while tau binds and bundles MTs, it does not directly bundle actin. However, tau facilitates MT-actin colocalization in the presence of actin crosslinkers with distinct properties. Fascin, which forms rigid actin bundles, significantly enhances MT-actin colocalization with tau, whereas -actinin, which forms flexible actin bundles, induces colocalization in vesicles but not in bulk conditions. By combining cellular reconstitution and coarse-grained simulations of composite network assembly in both vesicles and bulk conditions, our findings reveal how tau-mediated cytoskeletal integration is governed by bundle mechanics and spatial confinement, providing insights into cytoskeletal organization within reconstituted synthetic cell-like systems.

biophysics↗

bioRxiv2025

Recurring Transient Brain-Wide Co-Activation Patterns from EEG Spatially Resembling Time-Averaged Resting-State Networks

It has long been established that human brains remain functionally active at rest, as demonstrated with the discovery of resting-state networks (RSNs) underlying spontaneous neural activity. Recent studies suggest that classical RSNs estimated from functional magnetic resonance imaging (fMRI) data using time-domain functional connectivity measures might be driven by recurring point-process events. Due to the slow hemodynamic response, fMRI is not able to reveal such point-processes at the timescale of neuronal events while electroencephalography (EEG) holds the promise due to its millisecond temporal resolution and successful reconstruction of fMRI-like RSNs from EEG. The present study reported a set of recurring transient (<100 milliseconds) cortical co-activation patterns (CAPs) derived from resting-state EEG using a clustering algorithm with spatial-domain measures (i.e., k-means). Our results indicate that this set of CAPs exhibit strong spatial correspondence with known RSNs, not only those derived from the same EEG data using time-domain measures (i.e., independence), but also those from fMRI literature, covering visual, auditory, motor, limbic, high-order, and default mode networks. CAPs exhibit the properties of hemispheric symmetry, spatially separatable sub-systems, and intersubject variability gradient across functional systems, which have all been observed in classical RSNs. In terms of differences between CAPs and RSNs beyond their timescales, CAPs demonstrate greater intersubject reproducibility of spatial patterns compared to their time-averaged RSNs counterparts. These findings suggest that classical RSNs might be driven by recurring transient neuronal activations captured in CAPs. More importantly, CAPs can reveal much fast dynamics of such brain-wide networked neuronal activations (e.g., different CAPs exhibit significantly different occurrences and lifetimes) and benefit from their great intersubject reproducibility, thus underscoring their potential to advance our understanding on neuronal mechanisms of spontaneous large-scale brain activation phenomena.

bioengineering↗

bioRxiv2025

Single oocyte full-length isoform sequencing unveils the impact of transposable elements on RNA diversity and stability during oocyte maturation

The oocyte-specific isoforms play crucial roles in oocyte maturation, while current understanding of the oocyte transcriptome is mainly focused on gene level. Here, we utilized single cell full-length isoform sequencing based on third generation sequencing to detect entire transcripts in human and mouse oocytes. Isoform diversity during oocyte maturation was systematically profiled, including 6,736 and 4,902 putative novel human and mouse transcripts, respectively. More than half of novel isoforms were categorized as the novel-not-in-catalog (NNC) and may serve specific functions in oocytes, including novel isoforms of ARHGAP18, colocalized with microtubules and targeted knockdown disrupting oocyte maturation. Moreover, over 25% of NNC isoforms were derived from transposable elements (TEs), and their incorporation within transcripts could enhance isoform stability during oocyte maturation. Altogether, our findings represent a valuable resource showcasing the complexity and diversity of RNA isoforms in oocytes, as well as TE co-option for novel isoform generation and isoform stability enhancement.

developmental biology↗

bioRxiv2025

Inhalable Perfluorocarbon Nanocapsules for RNA-based Immunotherapeutic Treatment of Lung Metastases

Inhalation RNA therapy offers to transform treatment of pulmonary diseases, yet mucus trapping, immune clearance, and navigation of heterogeneous lung tissue architecture still prevents RNA from reaching its target cells. Here, we develop perfluorocarbon (PFC) RNA nanocapsules that show negligible immune clearance, minimal inflammatory response, and efficient mucus transport, while passively homing to lung epithelial and tumor cells. After a single aerosolized dose in orthotopic lung metastasis model, more than 60% of tumor cells and most type II alveolar and bronchial epithelial cells internalized the nanocapsules, with observed pulmonary retention exceeding 48 h. The nanocapsule provoke negligible cytokine release, enabling repeated dosing. Treatment with therapeutic miR34-a suppresses metastatic outgrowth, potentiates anti-tumor immunity, and almost doubles median survival relative to control paclitaxel chemotherapy. By combining unique PFC disposition with RNA versatility, the delivery platform overcomes the main biological barriers for inhalable RNA medicines and opens a translatable path for treating diverse pulmonary diseases.

bioengineering↗

bioRxiv2025

Longitudinal multi-omic profiling uncovers immune escape and predictors of response in multiple myeloma

Multiple myeloma (MM) is an incurable malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment. To investigate immune factors driving treatment response and resistance, we conducted multi-omics profiling including CD138neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138pos bulk RNA and whole-genome sequencing from 209 samples. Longitudinal analyses revealed that interferon gamma signaling impairs T cell memory after autologous stem cell transplant, while naive B cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48, p = 2.3e-4). At disease progression, MM cells upregulated cancer-testis antigens and immune effector genes, with concurrent B cell depletion, enrichment of myeloid-derived suppressor cell genes in monocytes, and T cell exhaustion. These findings highlight dynamic immune-tumor interactions, identifying naive B cell reconstitution as a biomarker of durable response, and cancer-testis antigens as potential targets for high-risk disease at progression. Statement of SignificanceLongitudinal profiling of multiple myeloma and the immune microenvironment revealed dynamic immune-tumor interactions across the disease course. Dysfunctional CD8 T cells limited memory formation post-transplant, while naive B recovery associated with sustained treatment response. At progression, cancer-testis antigen expression associated with immunosuppression, revealing novel mechanisms of immune escape.

cancer biology↗

bioRxiv2025

CASTOR1: A Novel Tumor Suppressor Linking mTORC1 and KRAS Pathways in Tumorigenesis and Resistance to KRAS-Targeted Therapies in Non-Small Cell Lung Cancer

Cytosolic arginine sensor for mTORC1 Subunit 1 (CASTOR1) functions as a key regulator of mechanistic target of rapamycin complex 1 (mTORC1) signaling. Despite its frequent dysregulation in cancers via mechanisms such as KSHV microRNA-mediated inhibition or AKT-driven phosphorylation and degradation, the impact of CASTOR1 loss on tumor initiation and progression remains poorly understood. Here, we identify CASTOR1 as a critical tumor suppressor in non-small cell lung cancer (NSCLC) by demonstrating that its genetic ablation amplifies tumorigenesis in a KRAS-driven genetically engineered mouse model (GEMM;LSL-KRASG12D). CASTOR1 deficiency markedly enhances lung tumor incidence, accelerates tumor progression, and increases proliferative indices in KRASG12D-driven tumors (KRASG12D;C1KO) compared to CASTOR1 wild type (WT) tumors (KRASG12D;C1WT). Advanced-stage tumors exhibit elevated phosphorylated CASTOR1 (pCASTOR1) and reduced total CASTOR1 levels, suggesting active degradation during tumorigenesis. Mechanistically, CASTOR1 loss amplifies mTORC1 signaling, as evidenced by heightened phosphorylation of downstream effectors 4EBP1 and S6, while also augmenting AKT and ERK activation, uncovering a crosstalk between the PI3K/AKT/mTORC1 and KRAS/ERK pathways. Furthermore, CASTOR1 ablation induces genome instability, which may contribute to enhanced tumor incidence and progression. Importantly, CASTOR1 deficiency confers resistance to KRASG12D-specific inhibitors, while over half of KRASG12D;C1WT tumors also display resistance. Organoids derived from KRASG12D;C1KO and KRASG12D;C1WT tumors reveal a correlation between KRAS inhibitor resistance and hyperactivation of mTORC1, with mTORC1 and PI3K inhibitors sensitizing resistant tumors to KRASG12D-targeted therapies. These findings position CASTOR1 as a novel tumor suppressor that modulates mTORC1 and KRAS signaling to constrain NSCLC progression. Our study further highlights the therapeutic potential of combining mTORC1 or ERK inhibitors with KRAS-targeted therapies for NSCLC characterized by hyperactive KRAS signaling and impaired CASTOR1 activity. HighlightsO_LICASTOR1 functions as a tumor suppressor in NSCLC by limiting KRAS-driven tumor initiation and progression. C_LIO_LICASTOR1 is frequently lost or inactivated in wild-type tumors during tumor progression, contributing to advanced-stage malignancies. C_LIO_LICASTOR1 deficiency amplifies mTORC1 signaling and enhances PI3K/AKT and KRAS/ERK crosstalk, driving tumorigenesis and resistance to KRAS-specific inhibitors. C_LIO_LICombining mTORC1 or PI3K inhibitors with KRAS-targeted therapies effectively overcomes resistance in KRAS-driven NSCLC. C_LI

cancer biology↗

bioRxiv2025

Inference and visualization of multi-scale cell tree for decoding functional diversity with scMustree

AbstractDeciphering cellular heterogeneity and functional diversity is crucial to understanding biological systems and disease mechanisms. Although single-cell RNA sequencing (scRNA-seq) has revolutionized this field, existing methods often fail to characterize the functional associations between cell populations due to the discrete nature of clustering results. We introduce scMustree, a tree- construction algorithm that enables in-depth exploration of functional associations and transitional states among cellular populations. scMustree combines top-down iterative decomposition for high- purity leaf nodes with bottom-up merging based on quantitative functional distances, preserving local continuity and global structural clarity. Benchmarking on real datasets shows that scMustree not only outperforms existing methods in clustering accuracy but also reveals functionally coherent subtypes, anatomically related cell types, and developmentally connected transitions. In case studies, it identifies Alzheimers disease-associated microglial subtypes and captures spatial cell distribution patterns of cell types in developed embryos, demonstrating its utility as a powerful tool for multi-scale exploration of cellular heterogeneity.

bioinformatics↗