Biology subjects

Lin, S.

Publications and source records attributed to Lin, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

rAAV-miniBEND: A targeted vector for brain endothelial cell gene delivery and cerebrovascular malformation modeling

Defects in brain endothelial cells (brainECs) can cause severe cerebrovascular malformations, including arteriovenous malformation (AVM) and cerebral cavernous malformation (CCM). The lack of appropriate tools for cerebrovascular disease modeling and local genetic manipulation of the brain vasculature hinders research on cerebrovascular malformations. Here we develop a recombinant adeno-associated virus (rAAV) tool miniBEND (rAAV-based mini-system for brain endothelial cells, rAAV-miniBEND), which combines a minimal promoter and an optimized cis-acting element (cis-element) isolated from the mouse gene Tek. This system achieves gene expression specifically in mouse and rat brainECs. Using rAAV-miniBEND, we achieve high-efficiency and high-specificity gene expression in brainECs through intracranial injection at various developmental stages and through intravenous administration at all postnatal stages in mice. Furthermore, we use rAAV-miniBEND to model sporadic CCMs mediated by MAP3K3I441M and AVMs mediated by BrafV600E. We demonstrate that somatic expression of BrafV600E in brainECs induces an AVM phenotype, and that brainEC proliferation are important for AVM development. Thus, our rAAV-miniBEND system provides a valuable and widely applicable tool for cerebrovascular disease modeling and local or global brainEC gene delivery.

neuroscience↗

bioRxiv2025

Purification of post-transcriptionally modified tRNAs for enhanced cell-free translation systems

Transfer RNAs (tRNAs) are utilized by the ribosome to decode the nucleic acid alphabet. tRNA structure, stability, aminoacylation efficiency, and decoding efficacy are governed by their extensive post-transcriptional modifications. In most studies, individual tRNAs are generated using in vitro transcription, which produces tRNAs devoid of these critical site-specific modifications, negatively affecting translation yields and fidelity. To address this, we have developed a purification method which couples tRNA overexpression to DNA hybridization-based purification. Using this approach, we produced native tRNAs from E. coli in high yield and purity while retaining their complement of native post-transcriptional modifications and translational activity. We extend this technique to the purification of [Formula] and [Formula], tRNAs of critical importance for genetic code expansion. We confirmed that both [Formula] and [Formula] contain native E. coli post-transcriptional modifications and provide the first complete modification profiles of each. Moreover, we found that in vivo-generated [Formula] significantly outperforms its in vitro-generated counterpart in amber codon suppression in cell-free translation reactions. Finally, we purified an engineered variant of E. coli [Formula], extending our studies to synthetic tRNAs. We present a flexible method which generates modified tRNAs in high yield and purity, addressing a critical and persistent challenge in RNA biochemistry. This toolkit enables future structural and cell-free studies through scalable access to native and engineered tRNAs, advancing the broader field of translation and synthetic biology.

biochemistry↗

bioRxiv2025

Cell Type Specific Aging Transcriptional Signatures of Human Retina Through Integrated Machine Learning and Single-Cell Transcriptomics

PurposeTo characterize cell type specific transcriptional changes during human retinal aging and develop machine learning model for cellular age discrimination in a Chinese cohort. DesignCross-sectional, laboratory-based observational study. ParticipantsEighteen unfrozen retinas from 12 Chinese donors (9 young, 34-55y; 9 old, 68-92 y). MethodsSingle-cell RNA sequencing (10x, v3.1) generated 223612 cells, batch-corrected with scVI; age-related signatures were defined by intersecting single-cell and pseudo-bulk differentially expressed genes, then cell-type-specific panels were rank-ordered with L1-regularised logistic regression plus recursive feature elimination and interpreted through hallmark-pathway enrichment and transcription-factor regulon mapping. Main Outcome MeasuresAge-related cellular composition shifts; cell-type-specific differentially expressed genes; machine-learning classifier accuracy and feature rankings; transcription factor regulon activity changes. ResultsEleven major retinal cell populations were identified. Aging showed declining rod-to-cone ratios, reduced bipolar cell proportions among interneurons, and increased astrocyte abundance. Muller glial cells exhibited the most pronounced transcriptional changes, followed by bipolar cells and rods. Machine-learning classifiers achieved 80-96% accuracy across cell types (microglia 96%, horizontal cells 93%, bipolar cells 91%, cones 90%, rods 89%). Shared aging signatures included mitochondrial dysfunction and inflammatory activation. Cell specific vulnerabilities emerged: mitochondria-centric stress in rods/bipolar cells, proteostasis-retinoid metabolism in cones, and structural-RNA maintenance in horizontal cells. ConclusionsThis study provides the first machine learning derived, cell-type specific aging signatures for human retina in a Chinese cohort, revealing both conserved molecular hallmarks and distinctive cellular vulnerabilities that inform targeted therapeutic strategies for retinal aging.

bioinformatics↗

bioRxiv2025

Molecular mechanisms regulating PDE11A4 age-related liquid-liquid phase separation (LLPS) and its reversal by selective, potent and orally-available PDE11A4 small molecule inhibitors both in vitro and in vivo

PDE11A is a little-studied phosphodiesterase family that breaks down cAMP and cGMP, with the PDE11A4 isoform enriched in the memory-related hippocampus. Age-related increases in hippocampal PDE11A expression occur in human and rodents, causing age-related cognitive decline of social memories. Interestingly, this age-related increase triggers PDE11A4 liquid-liquid phase separation (LLPS), causing the enzyme to accumulate in the brain in filamentous structures termed "ghost axons". Here we sought to identify molecular mechanisms regulating PDE11A4 LLPS and therapeutic approaches capable of reversing it. PDE11A4 LLPS was reduced by phosphorylation of PDE11A4-S163 or-S239 and the D355A mutation that blocks the effect of cGMP binding the PDE11A4 GAF-A domain. PDE11A4 LLPS was increased by inhibiting kinases with staurosporine or stimulating packaging/repacking via the trans-Golgi network by overexpressing TGN38 or RhoB. 8 PDE11 inhibitors (MLG-122, MLG-185, MLG-199, SMQ-02-57, SMQ-03-30, SMQ-03-20, tadalafil, and BC11-38) across 3 scaffolds reverse overexpression-related PDE11A4 LLPS in HT22 mouse hippocampal neuronal cells. This effect of PDE11A4 inhibitors occurs within minutes, is reversed upon washout of lower but not higher concentrations, and occurs in part by reducing PDE11A4 homodimerization. PDE11A4 inhibitors also rescued exacerbated PDE11A4 LLPS triggered by aging-like S117D/S124D phosphomimic mutations, staurosporine, or TGN38/RhoB overexpression. In vivo, orally-administered 30mg/kg SMQ-03-20 reversed age-related increases in PDE11A4 ghost axons and neuroinflammation in old mice. Thus, PDE11A inhibitors that reverse age-related PDE11A4 LLPS in HT22 hippocampal cells also reduce PDE11A4 ghost axons and neuroinflammation in the aged mouse brain, indicating therapeutical potential.

neuroscience↗

bioRxiv2025

SET1B drives sustained HIF activity and disease progression in clear cell renal cell carcinoma.

The cellular response to hypoxia is driven by hypoxia-inducible factors (HIFs), which regulate genes involved in glycolysis, angiogenesis, and cell proliferation, as well as inflammation and tumour progression. HIF activation is well-characterised and is primarily regulated by oxygen-dependent prolyl hydroxylation and subsequent degradation. However, how transcription of individual HIF target genes is regulated at the chromatin level is less clear. SET1B, a histone H3 lysine 4 (H3K4) methyltransferase, has emerged as a key modulator of HIF target gene transcription. Our study reveals that SET1B interacts with RNA Polymerase II to coordinate sustained HIF-mediated transcriptional activity through multiple functional domains. We also show that in clear cell renal cell carcinoma (ccRCC), SET1B is critical for sustained HIF activity, and SET1B expression correlates with disease progression and metastasis in patient samples. Moreover, SET1B depletion enhances the efficacy of HIF-2 inhibitors, establishing SET1B as a potential therapeutic target in ccRCC.

cancer biology↗

bioRxiv2025

A toolkit to characterize protein polymerization from cryo-electron tomography data

BackgroundCryogenic electron tomography (cryo-ET) is a powerful method to study protein structures and macromolecular complexes. These studies can provide structural information at the nanometer scale, allowing for the visualization of ultrastructures and access to subnanometer information through localized, subtomogram averaging (STA). STA alignments can provide analysts with an opportunity to quantify relationships between particles; however, the analytical tools to accomplish this are often lab or system specific. We offer a robust MATLAB script package that can be applied to a wide array of systems. MethodsMany tomographic analyses require extensive segmentation and image classification, which though useful can have poorly characterized error rates and user biases. We present a method for unbiased, numerical classification of head-to-tail polymerization in STA datasets with no outside information or user influence required. We provide this code in a modular MATLAB script package for ease of adaptation to other projects, with analyses including volumes, concentrations, binding, and fibril bundling. ResultsWe demonstrate the robust analysis possible with this script package using a model system of Rubisco in -carboxysomes (-CBs), showcasing the codes ability to evaluate global data such as volume and overall organization, polymerization data such as twist and bend, and lattice data such as lateral fibril distances and angles. DiscussionOur script package offers structural biologists a toolkit to conduct a robust biophysical analysis on STA data in an unbiased manner. The information generated will provide new insights into protein-protein interactions and the conditions favorable for larger ultrastructures. Particles can also be classified for further STA processing. This script package can be used for scientists studying proteins within isolated compartments or with clearly defined regions of interest.

biophysics↗

bioRxiv2025

Activation of complement protein C3 depicts the dynamic tissue damage of the cochlea after noise trauma.

Hearing loss is characterized by dysfunction and pathological changes of the cochlea, including the loss of sensory hair cells and connected synapses. Growing evidence has revealed that the immune system plays critical roles in shaping cochlear responses to tissue injury and the clearance of damaged cells under pathological conditions such as noise-induced hearing loss (NIHL). However, the underlying mechanisms that regulate this process remain unclear. As a crucial part of the innate immune system, the complement system is widely known to respond to tissue damage and help remove cellular debris. Such functions are yet to be fully explored in the auditory system, especially in the cochlea. Among various complement factors, the activation of complement protein C3 is an essential functional hub of the complement cascade, resulting in the phagocytosis of dead or dying cells. In this study, we sought to investigate whether C3 exists in the cochlea and what roles it might play upon noise injury. To test this, we studied C3 activation using immunohistochemistry in the cochleae of various mouse models that were noise exposed to an octave band noise (8-16 kHz) for two hours at 112 dB SPL. Mice were sacrificed at various post exposure times to examine cochlear pathology. We found damage dependent C3 activity in the organ of Corti in mice after noise exposure (NE), especially in damaged outer hair cell (OHC) area. Specifically, C3 opsonized damaged cellular structures include degenerating OHCs, OHC debris, ribbon synapses, and efferent synaptic boutons, and the temporal dynamics of the opsonization closely resemble the timing of cochlear tissue damages post exposure. Unexpectedly, C3-deficient mice exhibited similar ABR thresholds and OHC counts at baseline as wild type mice, as well as comparable ABR threshold shifts and OHC loss after NE. However, we observed significantly reduced MOC terminal bouton degeneration in C3-deficient mice upon 112 dB SPL noise injury, indicating that C3 does modulate tissue damage and clearance, at least at the MOC terminals. Our results suggest that complement C3 is dynamically activated in the cochlea upon noise injury, which may play significant roles in damage recognition and further immune recruitment during the development of NIHL.

neuroscience↗

bioRxiv2025

PepPCBench is a Comprehensive Benchmark for Protein-Peptide Complex Structure Prediction with AlphaFold3

Peptides mediate up to 40% of protein-protein interactions (PPIs), offering high specificity and the ability to target binding sites inaccessible to small molecules, making them promising candidates for drug development. Accurate modeling of protein-peptide complexes is crucial for understanding fundamental biological processes and for advancing peptide-based drug design. However, due to the high conformational flexibility of peptides, predicting their interactions with proteins remains a significant challenge. Recent advancements in artificial intelligence (AI), exemplified by all-atom protein folding neural networks (PFNNs) such as AlphaFold3 (AF3), have expanded predictive capabilities beyond proteins to encompass protein-peptide complexes. Nevertheless, existing evaluations of these methods are often limited in scope and lack systematic, multi-dimensional, and fair comparisons of PFNN performance in protein-peptide complex prediction. Here, we introduce PepPCBench, a comprehensive benchmark framework specifically developed to evaluate AF3s capabilities in predicting protein-peptide complexes. This study utilizes a carefully curated dataset named PepPCSet, which is excluded from the AF3s training or validation sets. This dataset includes 261 protein-peptide complexes with peptide lengths ranging from 5 to 30 residues. Our benchmark results indicate that AF3 outperforms other PFNNs in prediction accuracy and structural validation. However, its performance remains insufficient for practical peptide drug discovery, indicating room for improvement. It is expected that PepPCBench can provide some valuable insights into the enhancement of protein-peptide complex structure prediction and the development of peptide-based therapeutics. The dataset and pipeline protocols are available at https://github.com/zhaisilong/PepPCBench.

bioinformatics↗

bioRxiv2025

scBiopsy-seq: a platform for temporal single-cell RNA-seq analysis

The development of temporal single-cell RNA-seq (scRNA-seq) assay enabled us to systemically investigate the effects of various types of perturbations in a time course with single-cell resolution. However, the existing temporal scRNA-seq technologies have certain limitations in reliability, detection efficacy and detection diversity. In the current study, we develop scBiopsy-seq assay, which combines a synergistic electroosmosis-electrophoresis extraction method for efficient RNA extraction and digital microfluidics with contamination-isolated hydrophobic interface for high-performance sample processing. scBiopsy-seq extracts the cytoplasm at well-controlled volume to detect >10K genes per extraction with 90% successful rate. Functional enrichment analysis revealed that the genes robustly detected by scBiopsy-seq were associated to diverse biological processes, demonstrating its superb diversity of detection. scBiopsy-seq can perform the sequential extraction of the cytoplasm from the same cell multiple times, which allows us to associate the cell phenotypic responses with its transcriptional dynamics. We employed scBiopsy-seq to analyze the temporal response to a BRD4 degrader induced transcriptional suppression, which identified the key roles of fatty acid beta oxidation in this biological process. scBiopsy-seq with similar data quality as scRNA-seq will dramatically expand the application of temporal scRNA-seq towards a broader spectrum of cell biology research.

bioengineering↗

bioRxiv2025

Regulation of alternative polyadenylation events by PABPC1 affects erythroid progenitor cell expansion

Erythropoiesis is precisely regulated by multilayer networks and is crucial for maintaining steady-state hemoglobin levels and ensuring effective oxygen transport. Alternative polyadenylation (APA) is a post-transcriptional regulatory mechanism that generates multiple mRNA isoforms from a single gene, based on specific 3-untranslated region sequences. While APA plays a vital role in various cellular processes, its mechanism in erythropoiesis remains unexplored. Here, we employed an integrative approach combining bioinformatics and experimental validation to systematically analyze APAs role in erythropoiesis. We mapped the APA landscape during erythroid differentiation, discovering notable APA shifts crucial for the maturation from burst-forming unit erythroid to colony-forming unit erythroid. Notably, our findings highlighted PABPC1 as the primary APA regulator of these stages. Functional investigations revealed that knocking down PABPC1 disrupts erythroid progenitor cell proliferation and differentiation, implicating the proteins essential role in modulating cell fate through APA regulation. We further identified that decreased PABPC1 levels led to the increased usage of the proximal polyA site of TSC22D1 and gene overexpression, revealing a novel mechanism through which APA affects erythroid progenitor expansion and differentiation. These insights uncover a novel dimension of APA regulation in early erythropoiesis, providing new strategies for the treatment of diseases associated with erythropoiesis disorders.

developmental biology↗

bioRxiv2025

NLRP10 Cleaves Oxidized DNA inhibited by OGG1 inhibitors: A Newly Identified Role in DNA Damage Processing and Senescence Regulation.

Mitochondrial DNA (mtDNA) release into the cytosol is a critical event in innate immune activation, often acting as a damage-associated molecular pattern (DAMP) that triggers inflammasome assembly. Here, we demonstrate that NLRP3 plays a direct role in cleaving and facilitating the release of D-loop mtDNA into the cytosol. We further show that NLRP3 interacts with NLRP10. NLRP10-mediated ox-DNA cleavage involves a Schiff base intermediate and is inhibited by small molecules known to inhibit glycosylases. These findings support a model where NLRP10 interaction with oxidized DNA may contribute to long-term senescence secretory phenotype and modulate inflammasome activation. Our study highlights a novel mechanism by which NLRP10 can respond to mitochondrial stress signals to influence innate immunity and suggests therapeutic potential for targeting these interactions in inflammatory diseases.

immunology↗

bioRxiv2025

DORA AI Scientist: Multi-agent Virtual Research Team for Scientific Exploration Discovery and Automated Report Generation

Modern goal-oriented scientific research process involves hierarchical teams of researchers of diverse backgrounds performing generalist and domain-specific tasks. Many of these tasks include hypothesis generation, literature review, data collection, cleanup, processing and analysis, experimental design, virtual and physical experiments, research report and academic paper writing, reference management, bibliography and quality control. Most of these tasks can be performed automatically or in a co-pilot mode by the generative reinforcement learning systems. In this paper, we introduce a versatile multi-agent scientific exploration and draft outline research assistant (DORA), which provides multiple templates and workflows for automated or semi-automated research studies and report generation. Under user guidance, it employs hierarchical teams of AI agents based on the plug-and-play generalist and domain-specific large language models (LLMs) exploiting a variety of specialized research tools and open data repositories and generates high-quality research outputs publication drafts with maximally-accurate references. DORA is designed to minimize the time and effort required for manuscript preparation, thereby enabling researchers to devote more attention to high-value discovery tasks. The system is constantly evolving with user feedback with regular feature and resource updates. The platform is available at https://dora.insilico.com.

bioinformatics↗

bioRxiv2025

A humanized mouse model system mimics prenatal Zika infection and reveals premature differentiation

Zika, a mosquito-borne flavivirus, has been found in 87 countries and territories. Global outbreaks peaked in 2016. Prenatal infection of Zika virus was found to be associated with microcephaly, arthrogryposis, intracranial calcifications, fetal growth restriction, and fetal demise. The most severely affected children were diagnosed with congenital Zika syndrome, which impacts thousands worldwide. With no approved treatment or preventative measures for Zika, future viral outbreaks have the potential to cause epidemic levels of prenatal brain injury, as seen over the past 70 years. Therefore, there is a great need for a reliable and clinically translational experimental system that mimics the human condition of prenatal Zika infection. To this end, we developed a humanized, immunocompetent mouse model system of virally induced brain injury from prenatal Zika infection, which ranges from mild to severe. Here, we describe the extent to which this system mirrors the human phenotypic spectrum. Using our thorough preclinical system, we find that prenatal Zika infection of mice impacts survival rate, anthropometric measurements, tissue formation, and neurological outcomes, all of which are typical of prenatal infection. Single-cell RNA sequencing of the Zika-infected cerebral cortex reveals severely disrupted transcriptome profiles and suggests that these injuries are a result of a depletion of neural stem cells. Current and future applications include the identification of genetic or environmental modifiers of brain injury, molecular or mechanistic studies of pathogenesis, and preclinical evaluation of future therapies.

neuroscience↗

bioRxiv2025

Themis dominates T cell exhaustion by regulation of TCR and PD-1 signaling

T cell exhaustion is important to protect the host from immunopathology during chronic viral infection, but it also impairs T cell anti-tumor immunity1-5. A fundamental unresolved question is whether and how T cell exhaustion is determined at the onset of TCR signaling6-8. Here we report an unexpected role of Themis, a TCR-proximal signaling molecule9, in T cell exhaustion. Chronic viral infection in mice usually leads to T cell exhaustion and survival of the host. Surprisingly, Themis T-cell conditional knockout mice died from severe CD8+-dependent lung immunopathology in chronic viral infection, showing Themis importance in establishing T cell exhaustion. We found that Themis-deficient CD8+ T cells were hyperactivated at the single-cell level - producing more TNF and IFN{gamma} compared to wild-type counterparts - but defective in population-level expansion. Moreover, TCF-1 and TOX expression were inhibited in Themis-deficient CD8+ T cells, thereby impairing differentiation of exhausted T cell precursors (T-pex) and maintenance of terminally exhausted T cells (T-ex), respectively. Mechanistically, Themis initially promotes TCR signaling to induce PD-1 expression and subsequently mediates PD-1 signaling. In the latter, Themis binds to PD-1 and promotes PD-1 phosphorylation and its recruitment of SHP2, thereby acting as a negative regulator to inhibit T cell effector functions. Without Themis, the orderly regulation of TCR and PD-1 signaling, and therefore exhaustion, is disrupted. Thus, our results unequivocally demonstrate that Themis-mediated early TCR signaling plays a decisive role in T cell exhaustion and provide a novel mechanism of PD-1 signaling through Themis.

immunology↗

bioRxiv2025

Transcriptomic and spatial GABAergic neuron subtypes in zona incerta mediate distinct innate behaviors

Understanding the anatomical connection and behaviors of transcriptomic neuron subtypes is critical to delineating cell type-specific functions in the brain. Here we integrated single-nucleus transcriptomic sequencing, in vivo circuit mapping, optogenetic and chemogenetic approaches to dissect the molecular identity and function of heterogeneous GABAergic neuron populations in the zona incerta (ZI) in mice, a region involved in modulating various behaviors. By microdissecting ZI for transcriptomic and spatial gene expression analyses, our results revealed two non-overlapping Ecel1- and Pde11a-expressing GABAergic neurons with dominant expression in the rostral and medial zona incerta (ZIrEcel1 and ZImPde11a), respectively. The GABAergic projection from ZIrEcel1 to periaqueductal gray mediates self-grooming, while the GABAergic projection from ZImPde11a to the oral part of pontine reticular formation promotes transition from sleep to wakefulness. Together, our results revealed the molecular markers, spatial organization and specific neuronal circuits of two discrete GABAergic projection neuron populations in segregated subregions of the ZI that mediate distinct innate behaviors, advancing our understanding of the functional organization of the brain.

neuroscience↗

bioRxiv2025

Single-Cell Transcriptomics Reveals Dynamic Microglial States and Neural-Immune Networks in Human Diabetic Retinopathy

Diabetic retinopathy (DR) is a major cause of vision loss worldwide. Here, we conduct single-cell RNA sequencing of twenty human retina samples (from living and post-mortem donors) across non-diabetic, diabetic, and DR states to create a comprehensive transcriptomic atlas. We identify two stable microglial populations--homeostatic and inflammatory--that exist along a functional continuum, plus a neutrophil cluster within C1QA+ myeloid cells with dynamic transitions occurring throughout disease progression. Module-level analysis reveals divergent transcriptional trajectories: homeostatic microglia maintain energetic programs while selectively upregulating stress elements, whereas inflammatory microglia layer additional pro-inflammatory programs onto preserved biosynthetic foundations. Eleven co-expression modules organize into two major axes: an inflammatory-stress axis, and a regulatory/metabolic-motility axis, with a stable translation module persisting across disease stages. Cell communication analysis further highlights sophisticated neural-immune interactions, particularly between photoreceptors and microglia. Our findings provide insights into the complex cellular dynamics of DR progression and suggest potential therapeutic targets for early intervention.

bioinformatics↗

bioRxiv2025

Integrating transcriptomic data with metabolic model unravels the electron transfer mechanisms of Methanosarcina barkeri

Methanogenic archaea, particularly Methanosarcina, are pivotal to the global carbon cycle and renewable energy production due to their versatile metabolic capabilities. Although transcriptomic analysis is widely employed to identify key genes and pathways in Methanosarcina under various methanogenic conditions--including the emerging direct interspecies electron transfer (DIET)-based methanogenesis--the weak correlation between gene expression levels and protein abundances poses challenges for interpreting transcriptomic data. To address this, we integrated transcriptomic data into a metabolic model of Methanosarcina barkeri for the first time, enabling more refined predictions and enhancing the interpretability of transcriptomic insights. This novel integrated model was subsequently utilized to simulate aceticlastic, hydrogenotrophic, and DIET-based methanogenesis. The results revealed that previous assumptions failed to account for the role of the CO2 reduction pathway in aceticlastic methanogenesis. The model also successfully captured key transcriptomic features of DIET-based methanogenesis, clarifying the functional roles of crucial enzymes like the F420H2 dehydrogenase Fpo and the transmembrane hydrogenase Vht in electron transfer. This integrative approach provided a deeper understanding of electron transfer mechanisms in M. barkeri and offered valuable insights for advancing methanogen-based biotechnologies. Moreover, the study critically evaluated the relationship between gene expression and metabolic flux, establishing a practical framework for deriving meaningful insights from the growing volume of transcriptomic data.

bioengineering↗

bioRxiv2024

AMPK acts to remove immune barriers to CD8+ T cell-mediated immunity against hepatocellular carcinoma

Dysregulated metabolism in tumor tissues, and para-tumor tissues alike, can lead to immunosuppression, which may underlie cancer development. However, metabolic intervention as a therapeutic strategy has been of no avail. In this study, we explored the anti-cancer therapeutic effect of aldometanib that specifically targets lysosome-associated aldolase to mimic glucose starvation and thereby activates the lysosomal AMP-activated protein kinase (AMPK), a master regulator of metabolic homeostasis. We show that aldometanib inhibits the growth of HCC in an AMPK-dependent manner, allowing hepatoma-bearing mice to survive to mature ages, although aldometanib does not possess cytotoxicity towards HCC or normal cells. Intriguingly, aldometanib exerts anti-cancer effects only in immune-competent host mice, but not in immune-defective mice. We have further found that the HCC tissues in aldometanib-treated mice are massively infiltrated with CD8+ T cells, which is not seen in mice with liver-specific knockout of AMPK. Our findings thus suggest that the metabolic regulator AMPK rebalances the tumor microenvironment to allow the cytotoxic immune cells inside the body to eliminate cancer cells and effectively contain the tumor tissues. The finding that metabolic intervention can make cancer a life-long manageable disease, may potentially usher in a new era of cancer therapy.

immunology↗