Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 1,225 records · Page 68Linked to original sources

bioRxiv2024

Multi-omics Reveals Immune Response and Metabolic Profiles during High-Altitude Mountaineering

The physiological perturbations induced by high-altitude exposure in mountain climbers, manifesting as metabolic and immunologic deviations, have been previously reported but are not fully understood. In this study, we obtained longitudinal multi-omic profiles of blood samples for healthy mountain climbers during two mountaineering stages (acclimatization and extreme altitude mountaineering). Our integrative assay included metabolomics and lipidomics profiling of plasma coupled with single-cell transcriptomic analysis of 375,722 immune cells. Longitudinal analysis revealed dynamic immune response profiles, during the acclimatization period, characterized by the downregulation of inflammatory responses in monocytes and classical dendritic cells (cDCs) and an increase in the proportion of cytotoxic CD8+ T cells with enhanced immune effector processes. In contrast, during extreme altitude mountaineering, the activation of inflammatory responses and impairment of T cell effector function were observed, concomitant with an increased cellular response to hypoxia and oxidative stress pathways. Furthermore, we found upregulated glycolysis and antioxidant gene expression during extreme altitude mountaineering, which was primarily orchestrated by HIF1A and NFE2L2, while decreased expression of these genes was observed in dysregulated plasmacytoid dendritic cells (pDCs). Finally, high-resolution plasma metabolic analysis revealed significant alterations in the metabolism of climbers, involving enhanced glutamine and fatty acid metabolism.

bioinformatics↗

bioRxiv2024

Structural Basis for Intermodular Communication in Assembly-Line Polyketide Biosynthesis

Assembly-line polyketide synthases are large multienzyme systems with considerable potential for genetic reprogramming. To investigate the mechanisms by which reactive biosynthetic intermediates are directionally channeled across a defined sequence of active sites in a naturally occurring assembly line, we employed a bifunctional reagent to crosslink transient domain-domain interfaces of the 6-deoxyerythronolide B synthase. Structural resolution of these crosslinked states by single-particle cryogenic electron microscopy (cryo-EM) together with statistical per-particle image analysis of cryo-EM data revealed ketosynthase - acyl carrier protein (KS-ACP) interactions that discriminate between intra- and inter-modular communication, while reinforcing the relevance of asymmetric conformations during the catalytic cycle. Our findings provide a new foundation for the structure-based design of hybrid polyketide synthases comprised of biosynthetic modules from different assembly lines.

biochemistry↗

bioRxiv2024

Evolutionary conserved cis-trans regulation machinery for diterpenoid phytoalexin production in Poaceae

O_LIMomilactones and phytocassanes are diterpenoid phytoalexins involved in plant chemical defense. These metabolites, along with biosynthetic gene clusters (BGCs), are conserved in wild rice. However, the mechanisms by which phytoalexins are regulated in wild rice are unclear. Thus, we aimed to investigate the regulatory mechanisms for biosynthetic genes within the BGCs of diterpenoid phytoalexins. C_LIO_LIWe conducted a transcriptome analysis of five wild rice species, Oryza rufipogon, Oryza punctata, Oryza officinalis, Oryza brachyantha, and Leersia perrieri, after CuCl2 treatment. C_LIO_LIAmong the CuCl2-responsive transcription factors, diterpenoid phytoalexin factor (DPF), which regulates phytoalexin production in cultivated rice (Oryza sativa), was broadly conserved in wild rice and showed phytoalexin-inducing activity when introduced into cultivated rice. Highly conserved genomic regions containing N-boxes (5'-CACGAG-3'), the potential binding motif of DPF, were found. CRISPR/Cas9 genome editing to remove these regions showed that biosynthetic gene expression and phytoalexin production were significantly attenuated after CuCl2 treatment in the leaves of the edited plants. Thus, the cis-trans factor combination of DPF and N-boxes is a key determinant of regulation. C_LIO_LIDPF has evolved as a strong cis-trans regulatory system for diterpenoid phytoalexin production, with N-boxes generated within the cluster region during the evolution from wild rice to cultivated rice. C_LI

plant biology↗

bioRxiv2024

A gentle palette of plasma membrane dyes

Plasma membrane stains are one of the most important organelle markers for unambiguous assignments of individual cells and monitoring membrane morphology and dynamics. The state-of-the-art PM stains are bright, specific, fluorogenic, and compatible with super-resolution imaging. However, when recording membrane dynamics, particularly under light-intensive microscopes, PM is prone to photodynamic damages due to its phospholipid bilayer nature. Here we developed PK Mem dyes tailored for time-lapse fluorescence imaging. By integrating triplet-state quenchers into the MemBright dyes featuring cyanine chromophores and amphiphilic zwitterion anchors, PK Mem dyes exhibited a three-fold reduction in phototoxicity and a more than four-fold improvement in photostability in imaging experiments. These dyes enable 2D and 3D imaging of live or fixed cancer cell lines and a wide range of primary cells, at the same time pair well with various fluorescent markers. PK Mem dyes can be applied to neuronal imaging in brain slices and in vivo two-photon imaging. The gentle nature of PK Mem palette enables ultralong-term recording of cell migration and cardiomyocyte beating. Notably, PK Mem dyes are optically compatible with STED/SIM imaging, which can handily upgrade the routine of time-lapse neuronal imaging, such as growth cone tracking and mitochondrial transportations, into nanoscopic resolutions.

neuroscience↗

bioRxiv2024

Distinct effects of CDK8 module subunits on cellular growth and proliferation in Drosophila

The Mediator complex, composed of about 30 conserved subunits, plays a pivotal role in facilitating RNA polymerase II-dependent transcription in eukaryotes. Within this complex, the CDK8 kinase module (CKM), comprising Med12, Med13, CDK8, and CycC (Cyclin C), serves as a dissociable subcomplex that modulates the activity of the small Mediator complex. Genetic studies in Drosophila have revealed distinct phenotypes of CDK8-CycC and Med12-Med13 mutations, yet the underlying mechanism has remained unknown. Here, using Drosophila as a model organism, we show that depleting CDK8-CycC enhances E2F1 target gene expression and promotes cell-cycle progression. Conversely, depletion of Med12-Med13 affects the expression of ribosomal protein genes and fibrillarin, indicating a more severe reduction in ribosome biogenesis and cellular growth compared to the loss of CDK8-CycC. Moreover, we found that the stability of CDK8 and CycC relies on Med12 and Med13, with a mutually interdependent relationship between Med12 and Med13. Furthermore, CycC stability depends on the other three CKM subunits. These findings reveal distinct roles for CKM subunits in vivo, with Med12-Med13 disruption exerting a more pronounced impact on ribosome biogenesis and cellular growth compared to the loss of CDK8-CycC. SignificanceThe CDK8 kinase module (CKM), comprising CDK8, CycC, Med12, and Med13, is essential in the Mediator complex for RNA polymerase II-dependent transcription in eukaryotes. While expected to function jointly, CKM subunit mutations result in distinct phenotypes in Drosophila. This study investigates the mechanisms driving these differing effects. Our analysis reveals the role of Med12-Med13 pair in regulating ribosomal biogenesis and cellular growth, contrasting with the involvement of CDK8-CycC in E2F1-dependent cell-cycle progression. Additionally, an asymmetric interdependence in the stability of CDK8-CycC and Med12-Med13 was observed. CKM mutations or overexpression are associated with cancers and cardiovascular diseases. Our findings underscore the distinct impacts of CKM mutations on cellular growth and proliferation, advancing our understanding of their diverse consequences in vivo.

cell biology↗

bioRxiv2024

Super homotypic targeting by exosome surface engineering

Homotypic targeting is the inherent ability of cells for preferential interaction with cells of similar or identical types, a phenomenon commonly seen in cell adhesion, tissue formation, and immune responses. Unfortunately, its full potential remains largely untapped. Here we introduce an approach to drastically boost the homotypic targeting capabilities of cells via exosomes (nanoscale extracellular vesicles secreted by cells). By engineering exosome surfaces with lanthanides, we amplify specific cell-exosome interactions by more than 25-fold, significantly accelerating the selective capture of exosomes by cells of the same lineage. This substantial enhancement in cellular homophilicity opens up an entirely new class of applications, two of which we showcase here with unprecedented performance: using cells to detect specific exosomes and using exosomes to detect specific cells. The concept of "super homotypic targeting" offers enormous potential to transform cancer diagnostics, immunotherapy, targeted drug delivery, tissue engineering, and vaccine development.

cell biology↗

bioRxiv2024

Variable patterns of retrotransposition in different HeLa strains provide mechanistic insights into SINE RNA mobilization processes

Alu elements are non-autonomous Short INterspersed Elements (SINEs) derived from the 7SL RNA gene that are present at over one million copies in human genomic DNA. Alu mobilizes by a mechanism known as retrotransposition, which requires the Long INterspersed Element-1 (LINE-1 or L1) ORF2-encoded protein (ORF2p). Here, we demonstrate that HeLa strains differ in their capacity to support Alu retrotransposition. Human Alu elements retrotranspose efficiently in HeLa-HA and HeLa-CCL2 (Alu-permissive) strains, but not in HeLa-JVM or HeLa-H1 (Alu-nonpermissive) strains. A similar pattern of retrotransposition was observed for other 7SL RNA-derived SINEs and tRNA-derived SINEs. In contrast, mammalian LINE-1s, a zebrafish LINE, a human SINE-VNTR-Alu (SVA) element, and an L1 ORF1-containing messenger RNA can retrotranspose in all four HeLa strains. Using an in vitro reverse transcriptase-based assay, we show that Alu RNAs associate with ORF2p and are converted into cDNAs in both Alu-permissive and Alu-nonpermissive HeLa strains, suggesting that 7SL- and tRNA-derived SINE RNAs use strategies to hijack' L1 ORF2p that are distinct from those used by SVA elements and ORF1-containing mRNAs. These data further suggest ORF2p associates with the Alu RNA poly(A) tract in both Alu-permissive and Alu-nonpermissive HeLa strains, but that Alu retrotransposition is blocked after this critical step in Alu-nonpermissive HeLa strains.

molecular biology↗

bioRxiv2024

A Divide-and-Conquer Approach to Large-Scale Evolutionary Analysis of Single-Cell DNA Data

Single-cell sequencing technology is producing large datasets, often containing thousands or even tens of thousands of single-cell genomic data points from an individual patient. Evolutionary analyses of these data sets help uncover and order genetic variants in the data as well as elucidate mutation trees and intra-tumor heterogeneity (ITH) in the case of cancer data sets. To enable such large-scale analyses computationally, we propose a divide-and-conquer approach that could be used to scale up computationally intensive inference methods. The approach consists of four steps: 1) partitioning the dataset into subsets, 2) constructing a rooted tree for each subset, 3) computing a representative genotype for each subset by utilizing its inferred tree, and 4) assembling the individual trees using a tree built on the representative genotypes. Besides its flexibility and enabling scalability, this approach also lends itself naturally to ITH analysis, as the clones would be the individual subsets, and the "assembly tree" could be the mutation tree that defines the clones. To demonstrate the effectiveness of our proposed approach, we conducted experiments employing a range of methods at each stage. In particular, as clustering and dimensionality reduction methods are commonly used to tame the complexity of large datasets in this area, we analyzed the performance of a variety of such methods within our approach.

cancer biology↗

bioRxiv2024

Graph Contrastive Learning as a Versatile Foundation for Advanced scRNA-seq Data Analysis

Single-cell RNA sequencing (scRNA-seq) offers unprecedented insights into transcriptome-wide gene expression at the single-cell level. Cell clustering has been long established in the analysis of scRNA-seq data to identify the groups of cells with similar expression profiles. However, cell clustering is technically challenging, as raw scRNA-seq data have various analytical issues, including high dimensionality and dropout values. Existing research has developed deep learning models, such as graph machine learning models and contrastive learning-based models, for cell clustering using scRNA-seq data and has summarized the unsupervised learning of cell clustering into a human-interpretable format. While advances in cell clustering have been profound, we are no closer to finding a simple yet effective framework for learning high-quality representations necessary for robust clustering. In this study, we propose scSimGCL, a novel framework based on the graph contrastive learning paradigm for self-supervised pretraining of graph neural networks. This framework facilitates the generation of high-quality representations crucial for cell clustering. Our scSimGCL incorporates cell-cell graph structure and contrastive learning to enhance the performance of cell clustering. Extensive experimental results on simulated and real scRNA-seq datasets suggest the superiority of the proposed scSimGCL. Moreover, clustering assignment analysis confirms the general applicability of scSimGCL, including state-of-the-art clustering algorithms. Further, ablation study and hyperparameter analysis suggest the efficacy of our network architecture with the robustness of decisions in the self-supervised learning setting. The proposed scSimGCL can serve as a robust framework for practitioners developing tools for cell clustering. The source code of scSimGCL is publicly available at https://github.com/zhangzh1328/scSimGCL.

bioinformatics↗

bioRxiv2024

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

cancer biology↗

bioRxiv2024

Massively parallel interrogation of human functional variants modulating cancer immunosurveillance

Anti-PD-1/PD-L1 immune checkpoint blockade (ICB) therapy has revolutionized clinical cancer treatment, while abnormal PD-L1 or HLA-I expression in patients can significantly impact the therapeutic efficacy. Somatic mutations in cancer cells that modulate these critical immune regulators are closely associated with tumor progression and ICB response. However, a systematic interpretation of cancer immune-related mutations is still lacking. Here, we harnessed the ABEmax system to establish a large-scale sgRNA library encompassing approximately 820,000 sgRNAs that target all feasible Serine/Threonine/Tyrosine residues across the human genome, which systematically unveiled thousands of novel mutations that decrease or augment PD-L1 or HLA-I expression. Notably, we revealed functional mutations that co-regulate PD-L1 and HLA-I expression, represented by the clinically relevant mutation SETD2_Y1666, and verified that it can benefit from immunotherapy in vivo. Our findings generate an unprecedented resource of functional residues regulating cancer immunosurveillance, meanwhile, offer valuable guidance for clinical diagnosis, ICB therapy, and the development of innovative drugs in cancer treatment.

cancer biology↗

bioRxiv2024

The enhancement of electricity generation using cellulose based on ternary microbial consortium

Cooperation between microorganisms is crucial to design an efficient inoculum for enhancing the electricity-producing ability of carboxymethyl cellulose (CMC) fed bioreactors. In the present study, the influence of microbial mutualistic interactions and electricity generation capability were investigated by designing several co-culture and ternary culture systems. It was found that a ternary culture system of Cellulomonas Lsc-8, Bacillus subtilis C9 and Geobacter sulfurreducens PCA was used to efficiently convert cellulose into electricity. The maximum current density of 796 {+/-} 30 {micro}A{middle dot}cm-2 were achieved by the ternary culture, which were much higher than that Geobacter sulfurreducens PCA using acetate and co-culture systems to utilize CMC in bioreactors, respectively. In this consortium, Cellulomonas Lsc-8, and Bacillus subtilis C9 simultaneously digested CMC to produce acetate and secreted riboflavin as an electron shuttle; Geobacter sulfurreducens PCA utilized acetate to generate electricity. The introduction of Bacillus subtilis C9 further promoted the degradation of CMC and secreted more riboflavin to enhance electricity generation of the ternary culture. This work suggested that the synergistic interaction between interspecies in microbial consortia is emergent in designing specific community for achieving maximum power generation using CMC as substrate. This research shows new insight into the design of more efficient, stable, and robust microbial consortia applicable in waste treatment and power generation. IMPORTANCEMicrobial fuel cells (MFCs) may benefit from microbial consortia that efficiently convert carbon sources to electricity. A key challenge with this system is how to manage microbial community assembly to maximize electricity generation. Herein, we constructed and tested a three-species microbial consortium to enhance conversion of cellulose to electricity. Cellulomonas Lsc-8 and Bacillus subtilis C9 efficiently converted cellulose to acetate (electron donor) and riboflavin (electron shuttle), which enabled Geobacter sulfurreducens to generate electricity. This study laid the foundation for design of more efficient, stable, and robust microbial consortia for waste treatment and energy applications.

microbiology↗

bioRxiv2024

Large- Scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

AbstractO_ST_ABSIntroductionC_ST_ABSAlzheimers disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. MethodsDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). ResultsAs a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. DiscussionThis comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

neuroscience↗

bioRxiv2024

Towards anchoring evolutionary fitness for protein stability with virtual chemical environment recovery

Predicting the protein stability changes upon mutations is one of the effective ways to improve the efficiency of protein engineering. Here, we propose a dual-view ensemble learning-based framework, DVE-stability, for mutation-induced protein stability change prediction from single sequence. DVE-stability integrates the global and local dependencies of mutations to capture the intramolecular interactions from two views through ensemble learning, in which a structural microenvironment simulation module is designed to indirectly introduce the information of structural microenvironment at the sequence level. DVE-stability achieved state-of-the-art prediction performance on 7 single-point mutation benchmark datasets, and comprehensively surpassed other methods on 5 of them. Furthermore, DVE-stability outperformed other methods comprehensively through zero-shot inference on multiple-point mutation prediction task, demonstrating superior model generalizability to capture the epistasis of multiple-point mutations. More importantly, DVE-stability exhibited superior generalization performance in predicting rare beneficial mutations that are crucial for practical protein directed evolution scenarios. In addition, DVE-stability identified important intramolecular interactions via attention scores, demonstrating interpretable. Overall, DVE-stability provides a flexible and efficient tool for mutation-induced protein stability change prediction in an interpretable ensemble learning manner.

bioinformatics↗

bioRxiv2024

Exploring differences between depression and bipolar disorder through the urinary proteome

How to differentiate the diagnosis of depression and bipolar disorder has always been an important problem that needs to be solved urgently in clinical practice. In this study, from the perspective of urine proteomics, urine samples of similar age were collected from two hospitals to investigate the candidate biomarkers for differentiating the diagnosis of depression and bipolar disorder using both group analysis and one-to-many analysis(1 patient: many control samples). The experimental results of the paired group analysis showed that 108 differential proteins were identified in the depressed group compared to the bipolar group under strict screening conditions with screening criteria of FC [≥] 2 or [≤] 0.5 and a two-tailed unpaired t-test of P < 0.01, with an average of 3.7 randomly generated differential proteins, and a confidence level of 96.6 % for the correlation between these proteins and the disease difference. In the one-to-many analysis, 24 differential proteins were co-identified by the samples of 13 depressed patients, 16 of which showed a completely consistent trend of expression changes in all depressed patients studied, and 6 of which were associated with immunoglobulins; 41 differential proteins were co-identified by the samples of 12 depressed patients out of 13, and 19 of which showed a completely consistent trend of expression change in the These results reflect the strong consistency of differential proteins between the two groups of patients. 12 or more samples from depressed patients were enriched for differential proteins related to multiple biological processes and signaling pathways associated with the immune system, which is consistent with previous studies: immune mechanisms may be one of the pathogenetic mechanisms of major depression and that drugs with major immune targets can improve depressive symptoms. In the future, it may be possible to observe the immune status of patients with depression to provide direction and basis for the precise treatment of depression. The results of this paper show that urine proteomics can differentiate between depression and bipolar disorder, suggest possible mechanisms and potential targets for the treatment of depression and bipolar disorder, and provide a tool for future differential diagnosis and precision treatment of the diseases.

biochemistry↗

bioRxiv2024

Natural antibodies to polysaccharide capsules enable Kupffer cells to capture invading bacteria in the liver sinusoids

The interception of blood-borne bacteria in the liver defines the outcomes of invasive bacterial infections, but the mechanisms of this anti-bacterial immunity are largely speculative. This study shows that natural antibodies (nAbs) to capsules enable liver macrophage Kupffer cells (KCs) to rapidly capture and kill blood-borne encapsulated bacteria in mice. Affinity pulldown with serotype-10A capsular polysaccharides (CPS10A) of S. pneumoniae (Spn10A) led to the identification of CPS10A-binding nAbs in serum. The CPS10A-antibody interaction enabled KCs to capture Spn10A bacteria from the bloodstream, in part through complement receptors on KCs. The nAbs were found to recognize the {beta}1-6-linked galactose branch of CPS10A, and similar moieties of serotype-39 S. pneumoniae and serotype-K50 Klebsiella pneumoniae capsules. More importantly, the nAbs empowered KCs to capture serotype-39 S. pneumoniae and serotype-K50 K. pneumoniae in the liver. Collectively, our data have revealed a highly effective immune function of nAb against encapsulated bacteria, and provided a proof of concept for treating septic bacterial diseases with monoclonal antibodies. Short summaryRapid capture of potentially harmful bacteria in blood by liver macrophages are vital for the blood sterility and health. This work reports how naturally occurring antibodies in the plasma enable macrophages to capture and kill blood-borne bacteria in the liver.

microbiology↗

bioRxiv2024

Microbiota from young mice counteracts susceptibility to age-related gout through modulating butyric acid levels in aged mice

Gout is a prevalent form of inflammatory arthritis that occurs due to high levels of uric acid in the blood leading to the formation of urate crystals in and around the joints, particularly affecting the elderly. Recent research has provided evidence of distinct differences in the gut microbiota of patients with gout and hyperuricemia when compared to healthy individuals. However, the link between gut microbiota and age-related gout remained underexplored. Our study found that gut microbiota plays a crucial role in determining susceptibility to age-related gout. Specifically, we observed that age-related gut microbiota regulated the activation of the NLRP3 inflammasome pathway and modulated uric acid metabolism. More scrutiny highlighted the positive impact of "younger" microbiota on the gut microbiota structure of old or aged mice, enhancing butanoate metabolism and butyric acid content. Experimentation with butyrate supplementation indicated that butyric acid exerts a dual effect, inhibiting inflammation in acute gout and reducing serum uric acid levels. These insights emphasize the potential of gut microbiome rejuvenation in mitigating senile gout, unraveling the intricate dynamics between microbiota, aging, and gout. It potentially serves as a therapeutic target for senile gout-related conditions.

microbiology↗

bioRxiv2024

Propofol overcome Tamoxifen resistance in breast cancer by modulating tumorogenesis, immune response and metabolism

Although 70% of estrogen receptor (ER)-positive breast cancer patients benefit from Tamoxifen therapy, the developing resistance to Tamoxifen leads to high rates of metastasis and poor prognosis. Propofol, a commonly used anesthetic, has been shown to inhibit the occurrence and development of breast cancer. However, its role in anti-endocrine resistance in ER-positive breast cancer remains unclear. In this study, we found that Propofol significantly promotes cell cycle arrest, induces apoptosis, and inhibits proliferation in Tamoxifen-resistant breast cancer cells. Furthermore, transcriptome sequencing analysis revealed 1065 differentially expressed genes (DEGs) between Propofol-treated Tamoxifen-resistant MCF-7 (MCF7-TR) cells and none-treated MCF7-TR cells. Gene ontology annotation enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (KEGG), and gene set enrichment analysis (GSEA) showed that Propofol affects the expression of genes located in the plasma membrane and cell periphery, mainly regulating signals involved in cell cycle regulation, immune response modulation, and metabolism. Our results provide new insights into the mechanism by which Propofol controls resistance to Tamoxifen in breast cancer progression and offer a theoretical basis for clinical treatment.

cancer biology↗