Biology subjects

Xu, B.

Publications and source records attributed to Xu, B..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

An absolute quantification atlas of small non-coding RNAs across diverse mammalian tissues and cell lines

The low quantitative accuracy of conventional small noncoding RNA sequencing (sncRNA-seq) methods due to extensive ligation bias commonly limits functional investigation of microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs). Here, we develop 4NBoost, a single-tube sncRNA-seq protocol designed to minimize bias in the estimated absolute quantification of miRNA and piRNA transcripts through the incorporation of quantitative exogenous RNA spike-ins. With 4NBoost, we profile sncRNA expression across 20 murine tissues, 18 macaque tissues, and 24 widely used cell lines, as well as 4 Arabidopsis tissues, to establish a comprehensive quantitative reference atlas. Compared with existing small RNA databases, our data reveal substantial biases in miRNA abundance, strand selection, and tissue-specific expression at both individual and family levels. To further extend its utility, we employ machine learning to model and correct biases in conventional datasets, effectively recovering ground truth transcript abundances. All 4NBoost data and the accompanying bias-correction model are freely available via SmRNAQuant (http://wulg-lab.sibcb.ac.cn/SmRNAQuant/), a web-based repository for exploring sncRNA expression. Together, the 4NBoost, bias-correction model, and SmRNAQuant provide powerful resources to advance sncRNA research.

genomics↗

bioRxiv2025

Longitudinal TCR repertoires in ulcerative colitis patients show features distinguishing disease states

ABSTRACT AND KEY WORDSO_ST_ABSBackgroundC_ST_ABSUlcerative colitis (UC) affects an estimated 10 million people worldwide. The exact etiology of the disease is unknown, but T cell dysregulation and aberrant activation is associated with UC--prompting research into T cell receptor (TCR) repertoires in UC patients. However, few studies have compared UC patients TCR repertoires in flare (inflamed) and remission (uninflamed) states. Moreover, this is the first dataset to our knowledge examining multiple repertoires from UC patients over time, enabling longitudinal analyses. MethodsTCR repertoires were obtained for 21 patients across multiple timepoints, yielding a total of 58 samples. Repertoires clonality, diversity, overlap, and gene usage frequencies were compared across all patients. CDR3 sequences were split into K-mers (sequences of length K), and enriched K-mers in flare and remission states were identified using GLIPH2. ResultsAlthough repertoires vary across patients, there were significant differences in the usage of 20 V{beta} genes across flare and remission states. Moreover, calculating the overlap in repertoires with enriched K-mers showed higher overlap scores than when using full TCR sequences. 622 unique enriched K-mers were identified in flare states and 495 in remission states, with only 57 overlapping between the two states. ConclusionsOverall, these results highlight the importance of analyzing V{beta} gene usage and K-mer enrichment in TCR repertoires, particularly given the lack of public clones across patient cohorts. Future studies characterizing the specific antigenic targets associated with these features will pave the way for biomarker discovery in UC. KEY MESSAGESO_LIWhat is already known? UC is a chronic condition characterized by fluctuating periods of flares and remissions, as well as aberrant immune activity. C_LIO_LIWhat is new here? TCR repertoires were obtained from UC patients colonoscopies, with multiple timepoints per patient--enabling the analysis of repertoire characteristics within and across patients over time. C_LIO_LIHow can this study help patient care? Understanding the exact immune mechanisms in UC can pave the way for biomarker discovery and advance the state of care for patients, given that current treatments are non-specific and have adverse side effects. C_LI SummaryThis article presents an analysis of T cell receptor repertoires from ulcerative colitis patient samples collected during colonoscopies, identifying genes and motifs associated with patients flare (inflamed) and remission (uninflamed) states.

immunology↗

bioRxiv2025

A PAM-CNN recognition approach to Muscle Fatigue of Special Operators by sEMG signals

Fatigue operation was the primary accident causes of large special equipment which could lead to serious economic loss and personnel injury or death, so the establishment of early fatigue warning methods was of great significance to reduce the accident rate. In view of the working environment and biomechanics properties of operators of special equipment, theoretical and experimental method was presented to analyze the fatigue mechanism and accumulate data samples, and then a new approach was proposed to recognize muscle fatigue by classifying these datasets. Firstly, in order to deduce fatigue mechanism, hidden Markov chain was adopted to build five-element theoretical model for studying interaction between machines and operators muscles during operation process, so that influence factors and tested points of muscles were approached; Surface electromyographic (sEMG) sensors were introduced to acquire muscle signals which were taken as sample data, and wavelet packet was adopted to extract features of these data. Subsequently, a convolutional neural network (CNN) classification model based on partial attention mechanism (PAM) was proposed to execute triple fatigue classification, moreover cross entropy-Adam algorithm was applied to train and optimize this model. Finally, large crane operators were taken as case studies to verify the proposed model. By comparison results indicated when the number of extracted features was 3 and the size of patch was [5,5], PAM-CNN model could approach the optimum solution of fatigue recognition, and the average accuracy could achieve 95.6% in test datasets, which showed a good potential in practical application.

bioengineering↗

bioRxiv2025

Cross-disease comparison of dermatomyositis and lupus skin identifies inflammatory monocytes and JAK-1 signaling as drivers of vasculopathy in dermatomyositis

Dermatomyositis (DM) is a rare yet devastating autoimmune disease characterized by inflammatory and vasculopathic changes in skin and muscle. DM and systemic lupus erythematosus (lupus) skin lesions have overlapping clinical and histopathological features, yet disparate responses to available therapeutics. DM skin disease is often relapsing and recalcitrant. To investigate DM immunopathogenesis, non-lesional skin, lesional skin, and circulating immune cells from DM patients were analyzed using single-cell RNA-sequencing. Samples were analyzed in parallel with lesional and non-lesional lupus skin, healthy control skin, and peripheral blood. We demonstrate a pervasive type I interferon (IFN) signature in DM stroma that persists in culture and is distinguished from lupus by upregulation of VEGF and IL-18 signaling in DM keratinocytes. Furthermore, endothelial cells (ECs) in lesional DM exhibit decreased proliferation that was not observed in lupus. Using cell communication networks, we identified a population of DM-specific monocytes interacting with non-proliferating DM ECs. Co-culture of monocytes from DM patients with ECs resulted in increased EC apoptosis inhibited by JAK1 blockade. JAK1 inhibition also resulted in reversal of DM-stromal and inflammatory signatures. Together, our data provide a comprehensive cross-disease characterization of lesional and non-lesional skin of DM compared to lupus and implicate monocyte-mediated EC dysfunction in DM vasculopathy and support JAK inhibition for refractory skin disease.

immunology↗

bioRxiv2025

Statistically valid explainable black-box machine learning: applications in sex classification across species using brain imaging

Sex classification using neuroimaging data has the potential to revolutionize personalized diagnostics by revealing subtle structural brain differences that underlie sex-specific disease risks. Despite the promise of machine learning, traditional methods often fall short in providing both high classification accuracy and interpretable, statistically validated feature importance scores for high-dimensional imaging data. This gap is particularly evident when conventional techniques such as random forests, LIME, and SHAP are applied, as they struggle with complex feature interactions and managing noise in large datasets. We address this challenge by developing an integrated framework that combines Oblique Random Forests (ORFs) with a novel, permutation-based feature importance testing algorithm. ORFs extend traditional random forests by employing oblique decision boundaries through linear combinations of features, thereby capturing intricate interactions inherent in neuroimaging data. Our feature importance testing method, NEOFIT, rigorously quantifies the significance of each feature by generating null distributions and corrected p-values. We first validate our approach using simulated datasets, establishing its robustness and scalability under controlled conditions. We then apply our method to classify sex from both voxel-wise structural MRI and cortical thickness data in humans and macaques, facilitating direct cross-species comparisons. ORFs achieves AUC > 0.80 on human data, and > 0.70 on macaque data, while NEOFIT identifies statistically significant features aligned with sex-dimorphic neuroanatomy. Our results demonstrate that the proposed framework not only enhances classification performance but also provides clear, interpretable insights into the neuroanatomical features that distinguish sexes. These methodological advancements pave the way for improved diagnostic tools and contribute to a deeper understanding of the evolutionary basis of sex differences in brain structure.

neuroscience↗

bioRxiv2025

Loss of FMRP in microglia promotes degeneration of parvalbumin neurons and audiogenic seizures via progranulin insufficiency

Fragile X syndrome (FXS) results from loss of FMR1-encoded FMRP and is associated with reduced density of parvalbumin (PV) neurons; however, the mechanism underlying this abnormality remains unknown. Here we report that microglial FMRP regulates PV neuron density through lysosomal function. Mice with Fmr1 deletion in microglia exhibited audiogenic seizures (AGS) and decreased PV neuron density in the cortex and AGS-associated inferior colliculus (IC). FMRP increased the expression of lysosomal genes in microglia, including the progranulin-encoding Grn gene. Its loss in microglia led to impaired lysosomal function and increased apoptosis in microglia and PV neurons. Furthermore, PV neuron density in the IC was reduced similarly in male Grn+/-, Fmr1-/y, and Grn+/-;Fmr1-/y mice, and AAV8-mediated overexpression of progranulin rescued AGS and PV neuron loss in Fmr1-/y mice. This indicates that progranulin insufficiency is a determinant for PV neuron loss in FXS and elevating progranulin is a therapeutic strategy for FXS.

neuroscience↗

bioRxiv2025

Spatial mapping of proteins and their activity states in cancer models by multiplex in situ PLA

Improved methods are needed to gain insights in how proteins exert their myriad roles in cells and organs. Multiplex in situ proximity ligation assay (misPLA), described herein, can provide a window into the functional states of proteins in cells and tissues by applying pairs of antibody-oligonucleotide conjugates to generate amplifiable DNA circles upon proximal binding. The analysis reveals interactions and modifications among sets of proteins, read out by recording the identity and location of the resulting localized DNA amplification products. We applied misPLA to both primary and cultured cells and to formalin-fixated paraffin-embedded (FFPE) tissues, to map dynamic changes in protein localizations, phosphorylations and interactions across surface markers, MAPK, immune-checkpoints, T- and B-cell receptors, and adhesion panels. Comparisons of single-plex versus nine-plex assays confirmed that misPLA maintains sensitivity and specificity while increasing throughput and spatial context. Across breast cancer, lymphomas and chronic myeloid leukemia (CML) misPLA uncovered shared and disease-specific signaling patterns, underscoring convergence of oncogenic networks. By preserving tissue architecture and enabling high-content functional spatial proteomics at single-cell resolution, misPLA offers a versatile platform for dissecting signaling heterogeneity, pathway crosstalk, and therapeutic responses, with broad applications in cell biology, biomarker discovery and in precision oncology.

molecular biology↗

bioRxiv2025

HaploThread: A Scalable Integrated Desktop Platform for Constructing and Visualizing Haplotype Networks for Large-sample Sequences

This note announces HaploThread, a user-friendly GUI desktop software designed for haplotype network construction and visualization. HaploThread is written in C++ using the Qt library, integrating network visualization and multiple multi-threaded haplotype construction algorithms such as McAN and fastHaN (includes MSN, MJN and TCS) based on plugin mechanisms. It offers a straightforward approach to constructing and visualizing haplotype networks from large sample sets, and to extending functionality with plugins, facilitating the analysis of genetic variations and their evolutionary relationships. HaploThread is an open-source software released under the GNU General Public License (GPL). Its precompiled executables for Windows is freely available for download at https://ngdc.cncb.ac.cn/biocode/tool/BT007948.

bioinformatics↗

bioRxiv2025

Time-series modeling with neural flow maps

Constructing mathematical models from data is fundamental for understanding complex systems across scientific disciplines. However, real-world data often pose challenges such as irregular sampling, sparsity, and noise, that hinder the development of accurate, mechanistic models. In this work, we present a deep learning framework that directly reconstruct flow maps from data, assuming only that the observed patterns arise from an autonomous dynamical system. We demonstrate that our method accurately captures system dynamics across diverse settings, even with limited and irregularly sampled training data. When applied to the circadian transcriptomic time series data, it generates biologically valid predictions by integrating information across multiple organs. By parameterizing the full dynamical system, our proposed approach enables efficient computation of time derivatives and Jacobians directly from data, offering a powerful tool for analyzing and interpreting high-dimensional biological systems.

systems biology↗

bioRxiv2025

Peptides alleviate cognitive impairment by inhibiting and disassembling amyloid-beta aggregates in Alzheimer disease

Alzheimers disease (AD) is a devasting neurodegenerative disorder characterized by {beta}-amyloid formation, further exacerbated by RIPK1/RIPK3 necrosome-induced programmed necrosis (necroptosis). We previously showed that the RIPK1/RIPK3 necrosome forms a functional amyloid complex using its RIP homotypic interaction motifs (RHIMs). Here, we discovered that the core RIPK1/RIPK3 necrosome shares strikingly structural similarity to the C-terminal region of {beta}-amyloid (A{beta}42), and the RHIM-derived tetrapeptides (IQIG or VQVG) directly inhibit A{beta} aggregation, disassemble preformed A{beta} fibrils (PFFs), and reduce RIPK1 polymerization. Also, the peptides exhibit effective membrane permeability and could reduce A{beta}40 or A{beta}42-induced neural death and TNF-induced necroptosis in SH-SY5Y cells. IQIG and VQVG injected by ICV increase learning and memory abilities by reducing A{beta} plaques and hyperphosphorylated tau in the cortex and hippocampus of APP/PS1 double-transgenic mice. Mechanistically, the peptides directly interact with A{beta} to block A{beta} aggregation and alleviate microglia-mediated neuroinflammation. Strikingly, single-cell RNA sequencing revealed that the peptides-treated AD transgenic mice restored neuronal homeostasis with increased GABAergic neurons and decreased glutamatergic neurons. Furthermore, total cell-cell interaction strength increased while the AD risk gene Apoe expression decreased in the specific oligodendrocyte subtype of peptides-treated AD mice. Thus, our findings revealed that the peptides could improve cognition and memory capabilities and serve as promising structural templates for potential drugs against AD.

neuroscience↗

bioRxiv2025

Neuroticism Heterogeneity Through Item-Level Associations in Resting-State Functional Connectivity

Neuroticism is characterized by emotional instability and increased susceptibility to stress-related disorders. While traditionally treated as a unitary construct, growing evidence suggests that neuroticism is heterogeneous in both its genetic basis and its effects on social and health outcomes. To quantify this heterogeneity at the neurofunctional level, we analyzed resting-state functional connectivity (RSFC) in a large sample (n = 33,180) from the UK Biobank dataset. Using machine learning regression analysis, we identified RSFC patterns associated with item-level responses from the neuroticism scale of the Eysenck Personality Questionnaire. The pattern of RSFC associations across questionnaire items reflected genetically defined clusters (Worry and Depressed Affect), showing a significant correlation (r = 0.767, p < 0.001). It also aligned with psycholometrically derived factors (Anxiety/Tension and Worry/Vulnerability), reflecting a factor structure consistent with prior psychological studies. These findings were replicated in a separate MRI scan session from the UK biobank dataset. Associated connectivity was primarily observed in cognitive control, sensory integration, and self-referential processing networks. These neurofunctional signatures position RSFC as a robust intermediate phenotype, bridging genetic predisposition for neuroticism and psychological states. This framework could enhance precision in predicting psychiatric vulnerability and inform tailored therapeutic interventions.

neuroscience↗

bioRxiv2025

Laquinimod treatment attenuates EAU by inhibiting both the inductive and effector phases in an APC-dependent manner

PurposeTo evaluate the immunomodulatory effects on experimental autoimmune uveitis (EAU) of the aryl hydrocarbon receptor (AhR) agonist Laquinimod (LAQ), and its active metabolite DELAQ, with a focus on dendritic cell- and T cell-mediated mechanisms. MethodsEAU was induced in mice by active immunization or by adoptive transfer of activated T cells. Mice were treated with LAQ either from the time of immunization or from 7 days after. Effects of LAQ were examined in wild-type, global AhR-knockout, or dendritic cell-conditional AhR knockout mice. Direct vs. indirect effects of AhR agonism on dendritic cells and T cells were studied in vitro using DELAQ, a major active metabolite of LAQ. ResultsLAQ treatment from Day 0 fully suppressed EAU, while delayed treatment (Day 7) provided only partial protection. In the adoptive transfer model, LAQ-treated recipients showed reduced pathology. Global AhR-deficient mice developed severe EAU comparable to that of wild-type mice, with an elevated Th17 response. LAQ-treated mice displayed increased frequencies of cDC1 and FoxP3 regulatory T cells. In vitro, DELAQ activated AhR signaling and induced Ido1 and Ido2 expression in dendritic cells. DELAQ inhibited the activation of naive and memory mouse T cells in an APC-dependent manner, as the response to anti-CD3/CD28 stimulation was unaffected. Importantly, DELAQ suppressed recall responses of human PBMC to tetanus toxoid. ConclusionsLAQ protects against EAU by acting on AhR-expressing antigen-presenting cells to impair both priming and reactivation of pathogenic T cells. Its active metabolite DELAQ does not suppress T cells directly, but re-programs dendritic cells toward a tolerogenic, IDO-expressing phenotype that promotes immune regulation.

immunology↗

bioRxiv2025

Intralysosomal pathogens differentially influence the proteolytic potential of their niche

Avoiding lysosomal degradation is vital to the success of intracellular pathogens. The Gram-negative bacterium Coxiella burnetii and protozoan parasites of the Leishmania genus are unique in being able to replicate within the mature phagolysosomal compartment of host cells, though the exact mechanisms utilised to withstand this hostile environment are not clearly defined. We recently reported that C. burnetii removes the lysosomal protease cathepsin B during infection of mammalian cells. Here, we aimed to determine if this virulence strategy was also employed by the intralysosomal pathogen, Leishmania mexicana. In contrast to C. burnetii, decreases in the activity of specific cathepsins were not detected in L. mexicana-infected host cells as determined using immunoblotting and protease activity-based probes. Co-infection of THP-1 macrophage-like cells with both pathogens resulted in a proteolytic and secretory phenotype consistent with C. burnetii infection, suggesting that C. burnetii-induced remodelling of the lysosome is not influenced by L. mexicana. The host cell proteome and secretome of L. mexicana infected cells was defined using mass spectrometry. This confirmed that, unlike C. burnetii, L. mexicana does not induce increased abundance of lysosomal proteins either intracellularly or in the extracellular milieu. Collectively, this study reveals that although C. burnetii and L. mexicana reside in a phagolysosomal intracellular niche, they employ divergent mechanisms to survive within this hostile compartment.

microbiology↗

bioRxiv2025

Direct interoceptive input to the insular cortex shapes learned feeding behavior

The insular cortex (insula) is an interoceptive hub, which senses internal states such as hunger, thirst, pain, and emotions. Previous studies suggest that the insula directly senses internal states, but the mechanisms remain elusive. We identified a population of leptin receptor-positive cells with a unique morphology in the insula (INSLepR). Based on leptins known role in signaling adiposity, we hypothesized that INSLepR neurons detect internal states to regulate food intake and body weight. Accordingly, we found that intra-insula leptin administration or optogenetic stimulation of INSLepR neurons impacts feeding behavior. Moreover, INSLepR neuron activity encodes feeding bouts in an internal-state dependent manner, and leptin alters insula neural dynamics in response to feeding, while also reshaping the transcriptome. Taken together, our data supports a model for direct interoceptive input to the insula, in which INSLepR cells integrate adiposity level signals to regulate feeding and body weight in a learned manner.

neuroscience↗

bioRxiv2025

EZH2 alters aggressive variant prostate cancer subtype evolution, but is not required for neuroendocrine prostate cancer

Advanced prostate cancer (PrCa) remains a leading cause of cancer-related death among men because nearly all patients progress on standard therapy that targets androgen receptor (AR) signaling. An important mechanism driving therapeutic resistance is lineage plasticity, the ability of PrCa cells to reprogram into lineage variants like neuroendocrine (NE) PrCa that no longer depend on AR signaling. The histone methyltransferase EZH2 has been implicated in PrCa lineage plasticity and EZH2 inhibitors are being evaluated clinically for the treatment of PrCa. Here we test how Ezh2 impacts the evolution of PrCa lineage plasticity using genetically engineered mice and human patient data. Reduced Ezh2 expression diversifies the evolution of PrCa lineage variants, including a newly discovered variant with high expression of neurofilament genes, in both mice and humans. Lineage variant diversification is associated with activation of Klf transcription factor programs and AR cistrome reprogramming that is normally repressed by Ezh2. These findings advance the understanding of PrCa lineage plasticity and have implications for using EZH2 as a target for PrCa therapy.

cancer biology↗

bioRxiv2025

Deep learning guided discovery of antibacterial polymeric nanoparticles

Drug-resistant bacterial infections pose a serious threat to global health, driving the development of novel antibacterial strategies beyond classic antibiotics. Self-assembled polymeric nanoparticles (SANPs) have emerged as promising candidates due to their unique structural properties, which enhance membrane interaction, drug loading, and therapeutic accumulation. The structural diversity and tunable properties of SANPs provide a flexible design platform for antibacterial applications. However, navigating the vast chemical space of SANPs remains a significant challenge due to the complex structure-activity relationships. To address this, we developed PolyCLOVER, a deep learning-guided framework for the efficient discovery of antibacterial SANPs. The framework integrates multi-stage self-supervised learning, active learning, and high-throughput experimentation to iteratively guide the discovery of SANPs with potent antibacterial activity and low toxicity. Through this framework, we identified three potent SANPs within a combinatorial library of [~]100,000 poly({beta}-amino ester)s, with minimum inhibitory concentrations of 4 g/mL and 8 g/mL against clinically multidrug-resistant S. aureus and A. baumannii, respectively. Moreover, they can also act as antibiotic carriers, restoring the sensitivity of pathogens to penicillin G. In vivo studies demonstrated their therapeutic efficacy both as monotherapies and in combination therapies with antibiotics. These results demonstrate PolyCLOVER as a powerful framework for discovering multi-functional SANPs to combat antibiotic resistance.

microbiology↗

bioRxiv2025

Targeting the canonical ER stress IRE1α/XBP1 pathway counteracts pancreatic cancer-induced skeletal muscle wasting

Cancer-driven cachexia is a deleterious syndrome which involves progressive loss of skeletal muscle mass with or without fat loss, fatigue, and weakness that cannot be reversed by nutritional intake. Recent studies have shown deregulation of endoplasmic reticulum (ER)-induced unfolded protein response (UPR) pathways in skeletal muscle in various catabolic conditions, including cancer growth. However, the role of individual arms of the UPR in the regulation of muscle mass remains poorly understood. Here, we demonstrate that the IRE1/XBP1 arm of the UPR stimulates the activation of ubiquitin-proteasome system, autophagy, JAK-STAT3 signaling, and fatty acid metabolism in skeletal muscle of the KPC mouse model of pancreatic cancer cachexia. Furthermore, our results show that IRE1/XBP1 pathway is a key contributor to cachexia as targeted ablation of XBP1 transcription factor in mouse skeletal muscle inhibits KPC tumor-induced muscle wasting. Transcriptionally active XBP1 protein binds to the promoter region of multiple genes, such as Map1lc3b, Fbxo32, and Il6, whose products are involved in skeletal muscle wasting. Treatment of KPC tumor-bearing mice with 4{micro}8C, a small molecule IRE1 inhibitor, reverses cachexia-induced molecular changes and improves skeletal muscle mass and strength. Altogether, our study highlights that the IRE1/XBP1 signaling axis mediates pancreatic cancer-induced muscle wasting and inhibition of this pathway could be a potential approach to mitigate muscle wasting in pancreatic cancer patients.

physiology↗

bioRxiv2025

A unified eIF1A+ luminal cells-centered hypoxic and "cold" tumor microenvironment promotes PCa progression among different subtypes

PCa is a malignancy with high heterogeneity arises from both tumor microenvironment (TME) and histological subtypes. To achieve superior clinical efficacy, it is imperative to identify unified progression drivers within such heterogeneity in PCa, thereby enabling the development of more consistent and effective therapeutic strategies. In this study, we applied imaging mass cytometry to stain 39 proteins on 71 tissues comprising para-cancer, low-grade acinar adenocarcinoma (LgPAC), high-grade PAC (HgPAC), intraductal carcinoma (IDC) and ductal adenocarcinoma (DAC) tissues, obtaining the spatial proteomic landscape of 345,233 single cells. We discovered a hypoxic eIF1A+ luminal epithelial (LE) cluster exhibiting both translational activation and immunosuppressive properties, which was enriched in high-risk PCa including HgPAC, IDC and DAC, and associated which tumor progression and unfavorable prognosis. Additionally, eIF1A+ LE orchestrates the formation of an immunologically "cold" TME, characterized by the low infiltration of anti-cancer immune cells including PD1- T cells CD163- macrophages. Through in vivo validation and investigator-initiated study, we further found that Homoharringtonine, an inhibitor targeting protein translation process, effectively inhibited PCa growth, alleviated hypoxic microenvironment, and enhanced immune cell infiltration. This study is the first to apply spatial proteomics to delineate consistent molecular features across histological subtypes, providing transformative insights for clinical management of PCa.

cancer biology↗