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Zou, Z.

Publications and source records attributed to Zou, Z..

At least 37 records · Page 2Linked to original sources

Identification of stem cell marker-positive subpopulations in the vocal fold of the larynx through transcriptomic analyses

Information on the maintenance of tissue homeostasis is important for the development of effective therapeutic methods, however, reports on the cellular composition and tissue stem cells of the larynx were scarce. Therefore, we analyzed mouse laryngeal mucosa using scRNA-seq, and spatial transcriptomics by photo-isolation chemistry, and performed the generation of laryngeal organoid used as an in vitro model from mouse laryngeal mucosa. As a result, we found a SOX9-positive basal cell subpopulation and a Lgr5-positive fibroblast subpopulation in the mouse vocal fold, and obtained three types of epithelial organoids from laryngeal epithelium. We also confirmed the differences in pseudostratified ciliated columnar epithelium composition between the supraglottis and subglottis of the mouse larynx. These findings provide novel insights and valuable tools for future research in laryngology and stem cell biology.

cell biology↗

Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database

BioSample is a comprehensive repository of experimental sample metadata, playing a crucial role in providing a comprehensive archive and enabling experiment searches regardless of type. However, the difficulty in comprehensively defining the rules for describing metadata and limited user awareness of best practices for metadata have resulted in substantial variability depending on the submitter. This inconsistency poses significant challenges to the findability and reusability of the data. Given the vast scale of BioSample, which hosts over 40 million records, manual curation is impractical. Rule-based automatic ontology mapping methods have been proposed to address this issue, but their effectiveness is limited by the heterogeneity of BioSample metadata. Recently, large language models (LLMs) have gained attention in natural language processing and have been expected as promising tools for automating metadata curation. In this study, we evaluated the performance of LLMs in extracting cell line names from BioSample descriptions using a gold-standard dataset derived from ChIP-Atlas, a secondary database of epigenomics experiment data, which manually curates samples. Our results demonstrated that LLM-assisted methods outperformed traditional approaches, achieving higher accuracy and coverage. We further extended this approach to extraction of information about experimentally manipulated genes from metadata where manual curation had not yet been applied in ChIP-Atlas. This also yielded successful results for the usage of the database, which facilitates more precise filtering of data and prevents misinterpretation caused by inclusion of unintended data. These findings underscore the potential of LLMs to improve the findability and reusability of experimental data in general, significantly reducing user workload and enabling more effective scientific data management.

bioinformatics↗

Evolutionary fingerprint in rodent PD1 confers weakened activity and enhanced tumor immunity compared to human PD1

Mechanistic understanding of the immune checkpoint receptor PD1 is largely based on mouse models, but human and mouse PD1 orthologs exhibit only 59.6% identity in amino acid sequences. Here we show that human PD1 is more inhibitory than mouse PD1 due to stronger interactions with the ligands PDL1 and PDL2 and with the effector phosphatase Shp2. A novel motif highly conserved among PD1 orthologs in vertebrates except in rodents is primarily responsible for the differential Shp2 recruitment. Evolutionary analysis suggested that rodent PD1 orthologs uniquely underwent functional relaxation, particularly during the K-Pg boundary. Humanization of the PD1 intracellular domain disrupted the anti-tumor activity of mouse T cells while increasing the magnitude of anti-PD1 response. Together, our study uncovers species-specific features of the PD1 pathway, with implications to PD1 evolution and differential anti-PD(L)1 responses in mouse models and human patients.

immunology↗

YTHDF1 mediates translational control by m6A mRNA methylation in adaptation to environmental challenges

Animals adapt to environmental challenges with long-term changes at the behavioral, circuit, cellular, and synaptic levels which often require new protein synthesis. The discovery of reversible N6-methyladenosine (m6A) modifications of mRNA has revealed an important layer of post-transcriptional regulation which affects almost every phase of mRNA metabolism and therefore translational control. Many in vitro and in vivo studies have demonstrated the significant role of m6A in cell differentiation and survival, but its role in adult neurons is understudied. We used cell-type specific gene deletion of Mettl14, which encodes one of the subunits of the m6A methyltransferase, and Ythdf1, which encodes one of the cytoplasmic m6A reader proteins, in dopamine D1 receptor expressing or D2 receptor expressing neurons. Mettl14 or Ythdf1 deficiency blunted responses to environmental challenges at the behavioral, cellular, and molecular levels. In three different behavioral paradigms, gene deletion of either Mettl14 or Ythdf1 in D1 neurons impaired D1-dependent learning, whereas gene deletion of either Mettl14 or Ythdf1 in D2 neurons impaired D2-dependent learning. At the cellular level, modulation of D1 and D2 neuron firing in response to changes in environments was blunted in all three behavioral paradigms in mutant mice. Ythdf1 deletion resembled impairment caused by Mettl14 deletion in a cell type-specific manner, suggesting YTHDF1 is the main mediator of the functional consequences of m6A mRNA methylation in the striatum. At the molecular level, while striatal neurons in control mice responded to elevated cAMP by increasing de novo protein synthesis, striatal neurons in Ythdf1 knockout mice didnt. Finally, boosting dopamine release by cocaine drastically increased YTHDF1 binding to many mRNA targets in the striatum, especially those that encode structural proteins, suggesting the initiation of long-term neuronal and/or synaptic structural changes. While the m6A-YTHDF1 pathway has similar functional significance at cellular level, its cell type specific deficiency in D1 and D2 neurons often resulted in contrasting behavioral phenotypes, allowing us to cleanly dissociate the opposing yet cooperative roles of D1 and D2 neurons.

neuroscience↗

Single-cell transcriptomics reveals immunosuppressive microenvironment and highlights stumor-promoting macrophage cells in Glioblastoma

Glioblastoma (GBM) is the most prevalent and aggressive primary brain malignancy in adults. Nevertheless, the cellular heterogeneity and complexity within the GBM microenvironment (TME) are still not fully understood, posing a significant obstacle in the advancement of more efficient immunotherapies for GBM. In this study, we conducted an integrated analysis of 48 tumor fragments from 24 GBM patients at the single-cell level, uncovering substantial molecular diversity within immune infiltrates. We characterized molecular signatures for five distinct tumor-associated macrophage (TAM) subtypes. Notably, the TAM_MRC1 subtype displayed a pronounced M2 polarization signature. Additionally, we identified a subtype of natural killer (NK) cells, designated CD56dim_DNAJB1. This subtype is characterized by an exhausted phenotype, evidenced by an elevated stress signature and enrichment in the PD-L1/PD-1 checkpoint pathway. Our findings also highlight significant cell-cell interactions among malignant glioma cells, TAM, and NK cells within the TME. Overall, this research sheds light on the functional heterogeneity of glioma and immune cells in the TME, providing potential targets for therapeutic intervention in this immunologically cold cancer.

cancer biology↗

Dihydrothiazolo ring-fused 2-pyridone antimicrobial compounds treat Streptococcus pyogenes skin and soft tissue infection

We have developed GmPcides from a peptidomimetic dihydrothiazolo ring-fused 2-pyridone scaffold that have antimicrobial activities against a broad-spectrum of Gram-positive pathogens. Here we examine the treatment efficacy of GmPcides using skin and soft tissue infection (SSTI) and biofilm formation models by Streptococcus pyogenes. Screening our compound library for minimal inhibitory (MIC) and minimal bactericidal (MBC) concentrations identified GmPcide PS757 as highly active against S. pyogenes. Treatment of S. pyogenes biofilm with PS757 revealed robust efficacy against all phases of biofilm formation by preventing initial biofilm development, ceasing biofilm maturation and eradicating mature biofilm. In a murine model of S. pyogenes SSTI, subcutaneous delivery of PS757 resulted in reduced levels of tissue damage, decreased bacterial burdens and accelerated rates of wound-healing, which were associated with down-regulation of key virulence factors, including M protein and the SpeB cysteine protease. These data demonstrate that GmPcides show considerable promise for treating S. pyogenes infections.

microbiology↗

Impaired Mitochondrial Calcium Homeostasis Induces Failed Remodeling of the Spiral Artery in Preeclampsia

Withdrawal StatementThe authors have withdrawn their manuscript owing to further revisions and additional experiments are needed to ensure the accuracy and completeness of the research findings. As a result, we believe it is in the best interest of the scientific community and the integrity of the manuscript to withdraw it at this time. Therefore, the authors do not wish this work to be cited as a reference for the project. If you have any questions, please contact the corresponding author.

pathology↗

Optimal Decoding of Neural Dynamics Occurs at Mesoscale Spatial and Temporal Resolutions

IntroductionUnderstanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood. Materials and MethodsIn this work we developed NeuroPixelHD, a symbolic hyperdimensional model of MUA, and used it to decode the spatial location and identity of static images shown to n = 9 mice in the Allen Institute Visual Coding - NeuroPixels dataset from large-scale MUA recordings. We parametrically varied the spatial and temporal resolutions of the MUA data provided to the model, and compared its resulting decoding accuracy. ResultsFor almost all subjects, we found 125ms temporal resolution to maximize decoding accuracy for both the spatial location of Gabor patches (81 classes for patches presented over a 9x9 grid) as well as the identity of natural images (118 classes corresponding to 118 images). The optimal spatial resolution was more heterogeneous among subjects, but was still found at either of two mesoscale levels in nearly all cases: the area level, where the spiking activity of neurons within each brain area are combined, and the population level, where the former are aggregated into two variables corresponding to fast spiking (putatively inhibitory) and regular spiking (putatively excitatory) neurons, respectively. DiscussionOur findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which the unit of information varies dynamically based on neuronal signal and noise correlations across space and time.

neuroscience↗

Mass spectrometry and split luciferase complementation assays reveal the MecA protein interactome of Streptococcus mutans

MecA is a highly conserved adaptor protein encoded by prokaryotes from the Bacillota phylum. MecA mutants exhibit similar pleiotropic defects in a variety of organisms, although most of these phenotypes currently lack a mechanistic basis. MecA mediates ClpCP-dependent proteolysis of its substrates, but only several such substrates have been reported in the literature and there are suggestions that proteolysis-independent regulatory mechanisms may also exist. Here, we provide the first comprehensive characterization of the MecA interactome and further assess its regulatory role in Clp-dependent proteolysis. Untargeted coimmunoprecipitation assays coupled with mass spectrometry revealed that the MecA ortholog from the oral pathobiont Streptococcus mutans likely serves as a major protein interaction network hub by potentially complexing with >100 distinct protein substrates, most of which function in highly conserved metabolic pathways. The interactome results were independently verified using a newly developed prokaryotic split luciferase complementation assay (SLCA) to detect MecA protein-protein interactions in vivo. In addition, we further develop a new application of SLCA to support in vivo measurements of MecA relative protein binding affinities. SLCA results were independently verified using targeted coimmunoprecipitation assays, suggesting the general utility of this approach for prokaryotic protein-protein interaction studies. Our results indicate that MecA indeed regulates its interactome through both Clp-dependent proteolysis as well as through an as yet undefined proteolysis-independent mechanism that may affect more than half of its protein interactome. This suggests a significant aspect of MecA regulatory function still has yet to be discovered.

microbiology↗

m6A mRNA Methylation Regulates Early Pancreatic β-Cell Differentiation

N6-methyladenosine (m6A) is the most abundant chemical modification in mRNA, and plays important roles in human and mouse embryonic stem cell pluripotency, maintenance, and differentiation. We have recently reported, for the first time, the role of m6A in the postnatal control of {beta}-cell function in physiological states and in Type 1 and 2 Diabetes. However, the precise mechanisms by which m6A acts to regulate the development of human and mouse {beta}-cells are unexplored. Here, we show that the m6A landscape is dynamic during human pancreas development, and that METTL14, one of the m6A writer complex proteins, is essential for the early differentiation of both human and mouse {beta}-cells.

developmental biology↗

Uropathogenic Escherichia coli wield enterobactin-derived catabolites as siderophores

Uropathogenic E. coli (UPEC) secrete multiple siderophore types to scavenge extracellular iron(III) ions during clinical urinary tract infections, despite the metabolic costs of biosynthesis. Here we find the siderophore enterobactin and its related products to be prominent components of the iron-responsive extracellular metabolome of a model UPEC strain. Using defined enterobactin biosynthesis and import mutants, we identify lower molecular weight, dimeric exometabolites as products of incomplete siderophore catabolism, rather than prematurely released biosynthetic intermediates. In E. coli, iron acquisition from iron(III)-enterobactin complexes requires intracellular esterases that hydrolyze the siderophore. Although UPEC are equipped to consume the products of completely hydrolyzed enterobactin, we find that enterobactin and its derivatives may be incompletely hydrolyzed to yield products with retained siderophore activity. These results are consistent with catabolic inefficiency as means to obtain more than one iron ion per siderophore molecule. This is compatible with an evolved UPEC strategy to maximize the nutritional returns from metabolic investments in siderophore biosynthesis.

biochemistry↗

DNA Storage Designer: A practical and holistic design platform for storing digital information in DNA sequence

DNA molecules, as natural information carriers, have several benefits over conventional digital storage mediums, including high information density and long-term durability. It is expected to be a promising candidate for information storage. However, despite significant research in this field, the pace of development has been slow due to the lack of complete encoding-decoding platform and simulaton-evaluation system. And the mutation in DNA sequences during synthesis and sequencing requires multiple experiments, and wet experiments can be costly. Thus, a silicon-based simulation platform is urgently needed for promoting research. Therefore, we proposed DNA Storage Designer, the first online platform to simulate the whole process of DNA storage experiments. Our platform offers classical and novel technologies and experimental settings that simulate three key processes: encoding, error simulation, and decoding for DNA storage system. Fisrt, 8 mainstream encoding methods were embedded in the encoding process to convert files to DNA sequences. Secondly, to uncover potential mutations and sequence distribution changes in actual experiments we integrate the simulation setting for five typical experiment sub-processes (synthesis, decay, PCR, sampling, and sequencing) in the error simulation stage. Finally, the corresponding decoding process realizes the conversion of DNA sequence to binary sequence. All the above simulation processes correspond to an analysis report will provide guides for better experiment design for researchers convenience. In short, DNA Storage Designer is an easy-to-use and automatic web-server for simulating DNA storage experiments, which could advance the development of DNA storage-related research. And it is freely available for all users at: https://dmci.xmu.edu.cn/dna/. Author summaryDNA storage technology is an emerging and promising storage technology. At the same time, DNA storage is an interdisciplinary technology that requires researchers to know both computer cryptography and biological experiments knowledge. However, DNA storage experiments are costly and lengthy, many studies have been prevented by the lack of a comprehensive design and evaluation platform to guide DNA storage experiments. Herein, we introduce DNA Storage Designer, the first integrated and practical web server for providing the simulation of the whole process of DNA storage application, from encoding, error simulation during preservation, to decoding. In the encoding process, we not only provided the coding DNA sequences but also analyzed the sequence stability. In the error simulation process, we simulated as many experimental situations as possible, such as different mutation probabilities of DNA sequences due to being stored in different bacteria hosts or different sequencing platforms. The platform provides high freedom in that users could not only encode their files and conduct the entire operation but also could upload FASTA files and only simulate the sustaining process of sequences and imitate the mutation errors together with distribution changes of sequences.

bioinformatics↗

Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data

BackgroundDespite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed "DAR-ChIPEA," to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants. MethodsLarge-scale public ChIP-Seq data (human, n = 15,155; mouse, n = 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant-TF matrices were then cross-referenced to a repository of TF-disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation dataset to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants. ResultsThe proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060; Q = 5.278 x 10-42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms. ConclusionHighlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.

pharmacology and toxicology↗

Adaptation of prokaryotic toxins for negative selection and cloning-independent markerless mutagenesis (CIMM) in Streptococcus species

The Streptococcus mutans genetic system offers a variety of strategies to rapidly engineer targeted chromosomal mutations. Previously, we reported the first S. mutans negative selection system that functions in a wild-type background. This system utilizes induced sensitivity to the toxic amino acid analog p-chlorophenylalanine (4-CP) as a negative selection mechanism, and was developed for counterselection-based cloning-independent markerless mutagenesis (CIMM). While we have employed this system extensively for our ongoing genetic studies, we have encountered a couple limitations with the system, mainly its narrow host range and the requirement for selection on a toxic substrate. Here, we report the development of a new negative selection system that addresses both limitations, while still retaining the utility of the previous 4-CP-based markerless mutagenesis system. We placed a variety of toxin-encoding genes under the control of the xylose-inducible Xyl-S expression cassette and found the Fst-sm and ParE toxins to be suitable candidates for inducible negative selection. We combined the inducible toxins with an antibiotic resistance gene to create several different counterselection cassettes. The most broadly useful of these contained a wild-type fst-sm open reading frame transcriptionally fused to a point mutant form of the Xyl-S expression system, which we subsequently named as IFDC4. IFDC4 was shown to exhibit exceptionally low background resistance, with 3 - 4 log reductions in cell number observed when plating on xylose-supplemented media. IFDC4 also functioned similarly in multiple strains of S. mutans as well as with S. gordonii and S. sanguinis. We performed CIMM with IFDC4 and successfully engineered a variety of different types of markerless mutations in all three species. The counterselection strategy described here provides a template approach that should be adaptable for the creation of similar counterselection systems in many other bacteria.

genetics↗

FMRP phosphorylation modulates neuronal translation through YTHDF1

Translation activation of local synaptic mRNAs is critical to learning and memory1-3. Despite extensive studies on how phosphorylation of ribosomal proteins and translation factors enables timely response to exogenous stimuli4, our knowledge on molecular pathways utilized by RNA binding proteins (RBPs) to control translation of specific mRNAs remains incomplete. We have previously found that YTHDF1 regulates depolarization-induced protein synthesis by promoting translation of N6-methyladenosine (m6A)-modified transcripts5. Here we report an unexpected mechanism that the stimuli-induced neuronal translation is mediated by phosphorylation of a YTHDF1-binding protein FMRP. Phosphorylation of FMRP serine 499 induced by neuronal depolarization alters the condensing behavior of prion-like protein YTHDF1. Unphosphorylated FMRP sequesters YTHDF1 away from the translation initiation complex, whereas the stimulation-induced FMRP phosphorylation releases YTHDF1 to form translational active condensates with the ribosome to activate translation of YTHDF1 target transcripts. In fragile X syndrome (FXS) models characterized by low FMRP expression, we observed YTHDF1-mediated hyperactive translation, which notably impacts FXS pathophysiology. Developmental defects in an FXS forebrain organoid model could be reversed by a selective small-molecule inhibitor of YTHDF1 which acts by suppressing its condensation in neurons. We characterized transcriptome-wide mRNA translation with inhibitor treatment in organoids and identified targets that explain alleviated FXS pathology. Our study thus reveals FMRP and its phosphorylation as an important regulator of the activity-dependent translation during neuronal development and stimulation, and identifies YTHDF1 as a potential therapeutic target for FXS in which developmental defects caused by FMRP depletion could be reversed through YTHDF1 inhibition.

molecular biology↗

CDKL5 regulates p62-mediated selective autophagy and host antiviral defense

Virophagy, the selective autophagosomal engulfment and degradation of viral components, is crucial for antiviral immunity. However, the mechanisms leading to viral antigen recognition and autophagy induction remain poorly understood. Here, we identify a novel kinase, Cyclin-dependent kinase-like 5 (CDKL5), as an essential regulator of virophagy. Deletion of CDKL5 or abrogation of its kinase activity reduced virophagy of Sindbis virus (SINV), a neurotropic RNA virus, and increased intracellular accumulation of SINV capsid proteins and cellular cytotoxicity. Mechanistically, through direct phosphorylation of the selective autophagy receptor p62, CDKL5 promoted formation of p62 inclusion bodies that bound capsid. Loss of CDKL5 disrupted the capsid-p62 interaction, and a p62 phosphomimetic mutant rescued the interaction. CDKL5 knockout mice demonstrated increased neuronal cell death after SINV infection and enhanced lethality after infection with several human viruses. Overall, these findings identify a cell-autonomous innate immune mechanism for autophagy activation to clear toxic viral capsid aggregates during infection.

microbiology↗

Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor and investigating the immunorelated genes is of great significance. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, a immunoprognosis model was constructed to identify 4 hub genes with moderate predictive values for the prognosis of ccRCC patients. Interestingly, these 4 genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltrate and could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of 3 hub genes were associated with tumor progression (P<0.1). In conclusion, 4 genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

cancer biology↗

The Prognostic Potential and Pro-tumorigenicity of Serglycin (SRGN) was Associated with Tumor Microenvironment in Liver Cancer

BackgroundSerglycin (SRGN) is a prominent hematopoietic proteoglycan that regulates tumorigenesis; however, its role in tumor immunity is unclear. Materials and methodsWe investigated the expression and prognostic potential of SRGN in liver hepatocellular cancer (LIHC) in the context of pan-cancer (for showing the similarity and heterogeneity) using the PrognoScan, GEPIA, Kaplan-Meier Plotter, and TIMER bioinformatics databases. HepG2 cells were transfected with an SRGN over-expression vector, and their proliferation, invasion, sorafenib resistance, and vasculature were examined in vitro. A subcutaneous xenograft tumor model was created in nude mice. ResultsSRGN expression was prominent in M2 macrophages in LIHC. The Kaplan-Meier Plotter indicated that SRGN RNA was a favorable prognostic factor after correcting for clinical factors. TIMER 2.0 showed that the immune infiltrates of CD8+ T cells, M1 and M2 macrophages, and endothelial cells were strongly correlated with SRGN RNA expression (r=0.552, P=5.79e-29; r=0.517, P=5.84e-25; r=0.696, P=3.26e51; and r=0.522, P=1.67e-25, respectively), and had prognostic potential in LIHC in patients with low or high levels of SRGN, in addition to resting memory CD4+ T cells, hematopoietic stem cells (HSCs), and myeloid-derived suppressor cells (MDSCs). SRGN promoted the proliferation of HepG2 cells in vitro and in vivo, and was associated with weak sorafenib resistance, invasion, and vasculature. CD206 and CD80 were up-regulated and down-regulated, respectively, in subcutaneous tumor tissues. ConclusionsThe results comprehensively revealed relationships between SRGN and tumor microenvironment(TME)-infiltrating cells, especially monocyte/macrophage subsets. These may constitute an important TME because the pro-tumorigenicity of SRGN in liver cancer.

cancer biology↗