Syndecan-4 in Tumor Cell Motility

SDC4 protein action and related key genes in nonhealing diabetic foot ulcers based on bioinformatics analysis and machine learning

Diabetic foot ulcers (DFU) is a complication associated with diabetes characterised by high morbidity, disability, and mortality, involving chronic inflammation and infiltration of multiple immune cells. We aimed to identify the critical genes in nonhealing DFU using single-cell RNA sequencing, transcriptomic analysis and machine learning. The GSE165816, GSE134431, and GSE143735 datasets were downloaded from the GEO database. We processed and screened the datasets, and identified the cell subsets. Each cell subtype was annotated, and the predominant cell types contributing to the disease were analysed. Key genes were identified using the LASSO regression algorithm, followed by verification of model accuracy and stability. We investigated the molecular mechanisms and changes in signalling pathways associated with this disease using immunoinfiltration analysis, GSEA, and GSVA. Through scRNA-seq analysis, we identified 12 distinct cell clusters and determined that the basalKera cell type was important in disease development. A high accuracy and stability prediction model was constructed incorporating five key genes (TXN, PHLDA2, RPLP1, MT1G, and SDC4). Among these five genes, SDC4 has the strongest correlation and plays an important role in the development of DFU. Our study identified SDC4 significantly associated with nonhealing DFU development, potentially serving as new prevention and treatment strategies for DFU.

Effects of syndecan-4 silencing on the extracellular matrix remodeling in anoikis-resistant endothelial cells

Anoikis is a process of programmed cell death induced by the loss of cell/matrix interactions. In previous work, we have shown that the acquisition of anoikis resistance upregulates syndecan-4 (SDC4) expression in endothelial cells. In addition, SDC4 gene silencing by microRNA interference reverses the transformed phenotype of anoikis-resistant endothelial cells. Due to this role of SDC4 in regulating the behavior of anoikis-resistant endothelial cells, we have evaluated that the functional consequences of SDC4 silencing in the extracellular matrix (ECM) remodeling in anoikis-resistant rabbit aortic endothelial cells submitted to SDC4 gene silencing (miR-Syn4-Adh-1-EC). For this, we evaluated the expression of adhesive proteins, ECM receptors, nonreceptor protein-tyrosine kinases, and ECM-degrading enzymes and their inhibitors. Altered cell behavior was monitored by adhesion, migration, and tube formation assays. We found that SDC4 silencing led to a decrease in migration and angiogenic capacity of anoikis-resistant endothelial cells; this was accompanied by an increase in adhesion to fibronectin. Furthermore, after SDC4 silencing, we observed an increase in the expression of fibronectin, collagen IV, and vitronectin, and a decrease in the expression of integrin α5β1 and αvβ3, besides that, silenced cells show an increase in Src and FAK expression. Quantitative polymerase chain reaction and Western blot analysis demonstrated that SDC4 silencing leads to altered gene and protein expression of MMP2, MMP9, and HSPE. Compared with parental cells, SDC4 silenced cells showed a decrease in nitric oxide production and eNOS expression. In conclusion, these data demonstrate that SDC4 plays an important role in ECM remodeling. In addition, our findings represent an important step toward understanding the mechanism by which SDC4 can reverse the transformed phenotype of anoikis-resistant endothelial cells.

Inhibition of the serine protease HtrA1 by SerpinE2 suggests an extracellular proteolytic pathway in the control of neural crest migration

We previously showed that SerpinE2 and the serine protease HtrA1 modulate fibroblast growth factor (FGF) signaling in germ layer specification and head-to-tail development of Xenopus embryos. Here, we present an extracellular proteolytic mechanism involving this serpin-protease system in the developing neural crest (NC). Knockdown of SerpinE2 by injected antisense morpholino oligonucleotides did not affect the specification of NC progenitors but instead inhibited the migration of NC cells, causing defects in dorsal fin, melanocyte, and craniofacial cartilage formation. Similarly, overexpression of the HtrA1 protease impaired NC cell migration and the formation of NC-derived structures. The phenotype of SerpinE2 knockdown was overcome by concomitant downregulation of HtrA1, indicating that SerpinE2 stimulates NC migration by inhibiting endogenous HtrA1 activity. SerpinE2 binds to HtrA1, and the HtrA1 protease triggers degradation of the cell surface proteoglycan Syndecan-4 (Sdc4). Microinjection of Sdc4 mRNA partially rescued NC migration defects induced by both HtrA1 upregulation and SerpinE2 downregulation. These epistatic experiments suggest a proteolytic pathway by a double inhibition mechanism.

SerpinE2 ┤HtrA1 protease ┤Syndecan-4 → NC cell migration.

Low expression of ZFP36L1 in osteosarcoma promotes lung metastasis by inhibiting the SDC4-TGF-β signaling feedback loop

ZFP36L1, which is a negative regulator of gene transcripts, has been proven to regulate the progression of several carcinomas. However, its role in sarcoma remains unknown. Here, by using data analyses and in vivo experiments, we found that ZFP36L1 inhibited the lung metastasis of osteosarcoma (OS). Knockdown of ZFP36L1 promoted OS cell migration by activating TGF-β signaling and increasing SDC4 expression. Intriguingly, we observed a positive feedback loop between SDC4 and TGF-β signaling. SDC4 protected TGFBR3 from matrix metalloproteinase (MMP)-mediated cleavage and therefore relieved the inhibition of TGF-β signaling by soluble TGFBR3, while TGF-β signaling positively regulated SDC4 transcription. We also proved that ZFP36L1 regulated SDC4 mRNA decay through adenylate-uridylate (AU)-rich elements (AREs) in its 3'UTR. Furthermore, treatment with SB431542 (a TGF-β receptor kinase inhibitor) and MK2 inhibitor III (a MAPKAPK2 inhibitor that increases the ability of ZFP36L1 to degrade mRNA) dramatically inhibited OS lung metastasis, suggesting a promising therapeutic approach for the treatment of OS lung metastasis.

Small extracellular vesicles: Non-negligible vesicles in tumor progression, diagnosis, and therapy

Small extracellular vesicles (sEVs) such as exosomes are nanoscale membranous particles (<200 nm) that have emerged as crucial targets for liquid biopsy and as promising drug delivery vehicles. They play a significant role in tumor progression as intercellular messengers. They can serve as biomarkers for tumor diagnosis and as drug carriers for cancer treatment. This article reviews recent studies on sEVs in oncology and explores their potential as biomarkers and drug delivery vehicles. Following tumorigenesis, sEVs in the tumor microenvironment (TME) and circulatory system undergo modifications to regulate various events in the TME, including angiogenesis, epithelial-mesenchymal transition (EMT), and tumor immunity, with either pro- or anti-tumor effects. sEVs have been investigated for use as diagnostic and prognostic biomarkers for a variety of tumors, including lung cancer, melanoma, breast cancer, prostate cancer, and hepatocellular carcinoma. sEVs can be used for cancer therapy by packaging drugs or proteins into them through pre- and post-isolation modification techniques. The clinical trials of sEVs as biomarkers and drug carriers are also summarized. Finally, the challenges in the use of sEVs are described and the possible approaches to tackling them are suggested. Overall, sEVs will advance the precision cancer medicine and has shown great potential in clinical applications.

Thy-1 (CD90)-regulated cell adhesion and migration of mesenchymal cells: insights into adhesomes, mechanical forces, and signaling pathways

Cell adhesion and migration depend on the assembly and disassembly of adhesive structures known as focal adhesions. Cells adhere to the extracellular matrix (ECM) and form these structures via receptors, such as integrins and syndecans, which initiate signal transduction pathways that bridge the ECM to the cytoskeleton, thus governing adhesion and migration processes. Integrins bind to the ECM and soluble or cell surface ligands to form integrin adhesion complexes (IAC), whose composition depends on the cellular context and cell type. Proteomic analyses of these IACs led to the curation of the term adhesome, which is a complex molecular network containing hundreds of proteins involved in signaling, adhesion, and cell movement. One of the hallmarks of these IACs is to sense mechanical cues that arise due to ECM rigidity, as well as the tension exerted by cell-cell interactions, and transduce this force by modifying the actin cytoskeleton to regulate cell migration. Among the integrin/syndecan cell surface ligands, we have described Thy-1 (CD90), a GPI-anchored protein that possesses binding domains for each of these receptors and, upon engaging them, stimulates cell adhesion and migration. In this review, we examine what is currently known about adhesomes, revise how mechanical forces have changed our view on the regulation of cell migration, and, in this context, discuss how we have contributed to the understanding of signaling mechanisms that control cell adhesion and migration.

[Keloid nomogram prediction model based on weighted gene co-expression network analysis and machine learning]

Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.

Gi/o GPCRs drive the formation of actin-rich tunneling nanotubes in cancer cells via a Gβγ/PKCα/FARP1/Cdc42 axis

The functional association between stimulation of G-protein-coupled receptors (GPCRs) by eicosanoids and actin cytoskeleton reorganization remains largely unexplored. Using a model of human adrenocortical cancer cells, here we established that activation of the GPCR OXER1 by its natural agonist, the eicosanoid 5-oxo-eicosatetraenoic acid, leads to the formation of filopodia-like elongated projections connecting adjacent cells, known as tunneling nanotube (TNT)-like structures. This effect is reduced by pertussis toxin and GUE1654, a biased antagonist for the Gβγ pathway downstream of OXER1 activation. We also observed pertussis toxin-dependent TNT biogenesis in response to lysophosphatidic acid, indicative of a general response driven by Gi/o-coupled GPCRs. TNT generation by either 5-oxo-eicosatetraenoic acid or lysophosphatidic acid is partially dependent on the transactivation of the epidermal growth factor receptor and impaired by phosphoinositide 3-kinase inhibition. Subsequent signaling analysis reveals a strict requirement of phospholipase C β3 and its downstream effector protein kinase Cα. Consistent with the established role of Rho small GTPases in the formation of actin-rich projecting structures, we identified the phosphoinositide 3-kinase-regulated guanine nucleotide exchange factor FARP1 as a GPCR effector essential for TNT formation, acting via Cdc42. Altogether, our study pioneers a link between Gi/o-coupled GPCRs and TNT development and sheds light into the intricate signaling pathways governing the generation of specialized actin-rich elongated structures in response to bioactive signaling lipids.

Inferring Cell-Cell Communications from Spatially Resolved Transcriptomics Data Using a Bayesian Tweedie Model

Cellular communication through biochemical signaling is fundamental to every biological activity. Investigating cell signaling diffusions across cell types can further help understand biological mechanisms. In recent years, this has become an important research topic as single-cell sequencing technologies have matured. However, cell signaling activities are spatially constrained, and single-cell data cannot provide spatial information for each cell. This issue may cause a high false discovery rate, and using spatially resolved transcriptomics data is necessary. On the other hand, as far as we know, most existing methods focus on providing an ad hoc measurement to estimate intercellular communication instead of relying on a statistical model. It is undeniable that descriptive statistics are straightforward and accessible, but a suitable statistical model can provide more accurate and reliable inference. In this way, we propose a generalized linear regression model to infer cellular communications from spatially resolved transcriptomics data, especially spot-based data. Our BAyesian Tweedie modeling of COMmunications (BATCOM) method estimates the communication scores between cell types with the consideration of their corresponding distances. Due to the properties of the regression model, BATCOM naturally provides the direction of the communication between cell types and the interaction of ligands and receptors that other approaches cannot offer. We conduct simulation studies to assess the performance under different scenarios. We also employ BATCOM in a real-data application and compare it with other existing algorithms. In summary, our innovative model can fill gaps in the inference of cell-cell communication and provide a robust and straightforward result.

Identification of prognostic hub genes and therapeutic targets for selenium deficiency in chicks model through transcriptome profiling

Selenium deficiency is a prevalent micronutrient deficiency that poses a major health concern worldwide. This study aimed to shed light on the molecular mechanisms underlying selenium deficiency using a chick model. Chickens were divided into control and selenium deficient groups. Plasma samples were collected to measure selenium concentration and transcriptome analyse were performed on oviduct samples. The results showed that selenium deficiency led to a significant reduction in plasma selenium levels and altered the expression of 10,266 differentially expressed genes (DEGs). These DEGs primarily regulated signal transduction and cell motility. The molecular function includes GTPase regulatory activity, and KEGG pathway analysis showed that they were mainly involved in the signal transduction. By using Cytoscape and CancerGeneNet tool, we identified 8 modules and 10 hub genes (FRK, JUN, PTPRC, ACTA2, MST1R, SDC4, SDC1, CXCL12, MX1 and EZR) associated with receptor tyrosine kinase pathway, Wnt and mTOR signaling pathways that may be closely related to cancer. These hub genes could be served as precise diagnostic and prognostic candidate biomarkers of selenium deficiency and potential targets for treatment strategies in both animals and humans. This study sheds light on the molecular basis of selenium deficiency and its potential impact on public health.

The role of glycans in the mechanobiology of cancer

Although cancer is a genetic disease, physical changes such as stiffening of the extracellular matrix also commonly occur in cancer. Cancer cells sense and respond to extracellular matrix stiffening through the process of mechanotransduction. Cancer cell mechanotransduction can enhance cancer-promoting cell behaviors such as survival signaling, proliferation, and migration. Glycans, carbohydrate-based polymers, have recently emerged as important mediators and/or modulators of cancer cell mechanotransduction. Stiffer tumors are characterized by increased glycan content on cancer cells and their associated extracellular matrix. Here we review the role of cancer-associated glycans in coupled mechanical and biochemical alterations during cancer progression. We discuss the recent evidence on how increased expression of different glycans, in the form of glycoproteins and proteoglycans, contributes to both mechanical changes in tumors and corresponding cancer cell responses. We conclude with a summary of emerging tools that can be used to modify glycans for future studies in cancer mechanobiology.

Bioinformatics analysis identifies heparan sulfate proteoglycans acting as different progress subtypes of biliary atresia

BACKGROUND

Biliary atresia (BA) is a life-threatening disorder, which is characterized by the obliteration of biliary tracts. Heparan sulfate proteoglycans (HSPGs) are important regulators in liver diseases. Whether HSPGs participate in the development of BA is poorly understood.

METHODS

RNA-seq dataset GSE122340, including 171 BA and 7 normal liver tissue, was integrated for bioinformatic analysis. R function "wilcox.test" was used to compare HSPGs expression levels, and "cor.test" was used to evaluate the correlation analysis. MCPcounter was used to assess the abundance of immunocytes. Molecular subtypes of BA were clustered via NMF clustering and LASSO regression was applied to screen hub HSPGs genes in BA clusters. RT-PCR analysis was used to assess the expression of hub HSPGs in BA liver. Immunohistochemical staining and immunofluorescence assay were used to evaluated the location and expression of hub HSPGs in BA liver tissue.

RESULTS

Majority of HSPGs was up-regulated in BA and correlated with liver fibrosis and ductular reaction markers. The abundance of immunocytes was higher in BA and associated with HSPGs. Based on the expression of HSPGs, BA patients were classified into 3 subtypes (C1, C2, and C3). Pathway enrichment analysis revealed C1 subtype had severe liver injury with SDC4 identified as the hub gene, while C3 subtype presented relatively normal liver condition with GPC3 identified as the hub gene. RT-PCR analysis demonstrated the expression levels of 2 hub genes in BA liver tissue with different jaundice clearance standards. Immunohistochemical staining and immunofluorescence assay showed that SDC4 was mostly expressed in ductular reaction area, while GPC3 was mostly expressed in hepatocytes.

CONCLUSION

Majority of HSPGs are aberrant expressed in BA. The subtype hub gene SDC4 and GPC3 might be used as a potential indicator for different types of prognosis.

Increasing cancer permeability by photodynamic priming: from microenvironment to mechanotransduction signaling

The dense cancer microenvironment is a significant barrier that limits the penetration of anticancer agents, thereby restraining the efficacy of molecular and nanoscale cancer therapeutics. Developing new strategies to enhance the permeability of cancer tissues is of major interest to overcome treatment resistance. Nonetheless, early strategies based on small molecule inhibitors or matrix-degrading enzymes have led to disappointing clinical outcomes by causing increased chemotherapy toxicity and promoting disease progression. In recent years, photodynamic therapy (PDT) has emerged as a novel approach to increase the permeability of cancer tissues. By producing excessive amounts of reactive oxygen species selectively in the cancer microenvironment, PDT increases the accumulation, penetration depth, and efficacy of chemotherapeutics. Importantly, the increased cancer permeability has not been associated to increased metastasis formation. In this review, we provide novel insights into the mechanisms by which this effect, called photodynamic priming, can increase cancer permeability without promoting cell migration and dissemination. This review demonstrates that PDT oxidizes and degrades extracellular matrix proteins, reduces the capacity of cancer cells to adhere to the altered matrix, and interferes with mechanotransduction pathways that promote cancer cell migration and differentiation. Significant knowledge gaps are identified regarding the involvement of critical signaling pathways, and to which extent these events are influenced by the complicated PDT dosimetry. Addressing these knowledge gaps will be vital to further develop PDT as an adjuvant approach to improve cancer permeability, demonstrate the safety and efficacy of this priming approach, and render more cancer patients eligible to receive life-extending treatments.

Proteoglycans Determine the Dynamic Landscape of EMT and Cancer Cell Stemness

Proteoglycans (PGs) are pivotal components of extracellular matrices, involved in a variety of processes such as migration, invasion, morphogenesis, differentiation, drug resistance, and epithelial-to-mesenchymal transition (EMT). Cellular plasticity is a crucial intermediate phenotypic state acquired by cancer cells, which can modulate EMT and the generation of cancer stem cells (CSCs). PGs affect cell plasticity, stemness, and EMT, altering the cellular shape and functions. PGs control these functions, either by direct activation of signaling cascades, acting as co-receptors, or through regulation of the availability of biological compounds such as growth factors and cytokines. Differential expression of microRNAs is also associated with the expression of PGs and their interplay is implicated in the fine tuning of cancer cell phenotype and potential. This review summarizes the involvement of PGs in the regulation of EMT and stemness of cancer cells and highlights the molecular mechanisms.

High expression of syndecan-4 is related to clinicopathological features and poor prognosis of pancreatic adenocarcinoma

Objective

Pancreatic adenocarcinoma (PAAD) is a leading cause of cancer-related mortality in adults. Syndecan-4 (SDC4) is involved in cancer pathogenesis. Therefore, this study aimed to explore the expression and clinical significance of SDC4 in PAAD.

Methods

Differentially expressed genes (DEGs) between PAAD and normal pancreas were screened from the GTEx and TCGA databases, and the correlationship between the DEGs and prognosis were analyzed. The prognostic value of the screened SDC4, SERPINE1, and SLC2A1 was evaluated using the Kaplan–Meier curve and SDC4 was subsequently selected as the better candidate. Also, SDC4 expression was analyzed in PAAD tissues, the other risk factors affecting postoperative survival were analyzed using Cox regression analysis, and SDC4-mediated pathways enrichment was identified by GSVA and GSEA. SDC4 expression in PAAD tissues and adjacent normal tissues of selected PAAD patients was detected by RT-qPCR and immunohistochemistry. The correlation between SDC4 and clinical features was evaluated by the χ² test.

Results

SDC4 was highly expressed in PAAD tissues. Elevated SDC4 was correlated with reduced overall survival. SDC4 enrichment pathways included spliceosome function, proteasome activity, pentose phosphate pathway, base excision repair, mismatch repair, DNA replication, oxidative phosphorylation, mitotic spindle formation, epithelial-mesenchymal transition, and G2M checkpoints. SDC4 was elevated in PAAD tissues of PAAD patients compared with adjacent normal tissues. High SDC4 expression was related to metastatic differentiation, TNM stage, lymphatic metastasis, and lower 3-year survival rate. SDC4 was an independent risk factor affecting postoperative survival.

Conclusion

SDC4 was highly expressed in PAAD and was related to clinicopathological features and poor prognosis, which might be an important index for PAAD early diagnosis and prognosis.

Comprehensive Analysis and Reinforcement Learning of Hypoxic Genes Based on Four Machine Learning Algorithms for Estimating the Immune Landscape, Clinical Outcomes, and Therapeutic Implications in Patients With Lung Adenocarcinoma

Background

Patients with lung adenocarcinoma (LUAD) exhibit significant heterogeneity in therapeutic responses and overall survival (OS). In recent years, accumulating research has uncovered the critical roles of hypoxia in a variety of solid tumors, but its role in LUAD is not currently fully elucidated. This study aims to discover novel insights into the mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers by exploring the potential association between hypoxia and LUAD.

Methods

Four machine learning approaches were implemented to screen out potential hypoxia-related genes for the prognosis of LUAD based on gene expression profile of LUAD samples obtained from The Cancer Genome Atlas (TCGA), then validated by six cohorts of validation datasets. The risk score derived from the hypoxia-related genes was proven to be an independent factor by using the univariate and multivariate Cox regression analyses and Kaplan-Meier survival analyses. Hypoxia-related mechanisms based on tumor mutational burden (TMB), the immune activity, and therapeutic value were also performed to adequately dig deeper into the clinical value of hypoxia-related genes. Finally, the expression level of hypoxia genes was validated at protein level and clinical samples from LUAD patients at transcript levels.

Results

All patients in TCGA and GEO-LUAD group were distinctly stratified into low- and high-risk groups based on the risk score. Survival analyses demonstrated that our risk score could serve as a powerful and independent risk factor for OS, and the nomogram also exhibited high accuracy. LUAD patients in high-risk group presented worse OS, lower TMB, and lower immune activity. We found that the model is highly sensitive to immune features. Moreover, we revealed that the hypoxia-related genes had potential therapeutic value for LUAD patients based on the drug sensitivity and chemotherapeutic response prediction. The protein and gene expression levels of 10 selected hypoxia gene also showed significant difference between LUAD tumors tissues and normal tissues. The validation experiment showed that the gene transcript levels of most of their genes were consistent with the levels of their translated proteins.

Conclusions

Our study might contribute to the optimization of risk stratification for survival and personalized management of LUAD patients by using the hypoxia genes, which will provide a valuable resource that will guide both mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers.

Eltrombopag binds SDC4 directly and enhances MAPK signaling and macropinocytosis in cancer cells

Syndecan-4 (SDC4) is a single-pass transmembrane glycoprotein implicated in a variety of oncogenic signaling pathways. It is also an intrinsically disordered protein and considered "undruggable". In the present study, we confirmed that knocking out SDC4 in pancreatic cancer cells markedly impaired macropinocytosis, colony formation, as well as xenograft tumor initiation and growth. Quantitative proteomic profiling of Sdc4 knockout (KO) cells revealed significant changes in cell metabolic pathways. In a cellular protein-based ligand interaction screening, we identified that Eltrombopag (ETBP), an FDA-approved agonist of the thrombopoietin receptor (TPOR) for immune thrombocytopenia, could directly bind to SDC4 with a Kd value of ~2 µM. We showed that the transmembrane motif was essential for SDC4 binding to ETBP. Unexpectedly, ETBP not only increased SDC4 abundance, but also enhanced SDC4-associated MAPK signaling pathway and macropinocytosis in cancer cells. Our results indicate that ETBP is a potential agonist of SDC4 in a fashion similar to its original target TPOR, and that caution should be taken when using ETBP for chemotherapy-induced thrombocytopenia in cancer patients.

Keloid Biomarkers and Their Correlation With Immune Infiltration

Objective: This work aimed to verify the candidate biomarkers for keloid disorder (KD), and analyze the role of immune cell infiltration (ICI) in the pathology of keloid disorder.

Methods: The keloid-related datasets (GSE44270 and GSE145725) were retrieved from the Gene Expression Omnibus (GEO). Then, differential expressed genes (DEGs) were identified by using the “limma” R package. Support vector machine-recursive feature elimination (SVM-RFE) and LASSO logistic regression were utilized for screening candidate biomarkers of KD. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic power of candidate biomarkers. The candidate biomarkers were further verified through qRT-PCR of keloid lesions and the matched healthy skin tissue collected from eight cases. In addition, ICI in keloid lesions was estimated through single-sample gene-set enrichment analysis (ssGSEA). Finally, the potential drugs to the treatment of KD were predicted in the Connectivity Map Database (CMAP).

Results: A total of 406 DEGs were identified between keloid lesion and healthy skin samples. Among them, STC2 (AUC = 0.919), SDC4 (AUC = 0.970), DAAM1 (AUC = 0.966), and NOX4 (AUC = 0.949) were identified as potential biomarkers through the SVM-RFE, LASSO analysis and ROC analysis. The differential expressions of SDC4, DAAM1, and NOX4 were further verified in collected eight samples by qRT-PCR experiment. ICI analysis result showed a positive correlation of DAAM1 expression with monocytes and mast cells, SDC4 with effector memory CD4⁺ T cells, STC2 with T follicular helper cells, and NOX4 with central memory CD8⁺ T cells. Finally, a total of 13 candidate small molecule drugs were predicted for keloids treatment in CMAP drug database.

Conclusion: We identified four genes that may serve as potential biomarkers for KD development and revealed that ICI might play a critical role in the pathogenesis of KD.

Syndecan-4 affects myogenesis via Rac1-mediated actin remodeling and exhibits copy-number amplification and increased expression in human rhabdomyosarcoma tumors

Skeletal muscle demonstrates a high degree of regenerative capacity repeating the embryonic myogenic program under strict control. Rhabdomyosarcoma is the most common sarcoma in childhood and is characterized by impaired muscle differentiation. In this study, we observed that silencing the expression of syndecan-4, the ubiquitously expressed transmembrane heparan sulfate proteoglycan, significantly enhanced myoblast differentiation, and fusion. During muscle differentiation, the gradually decreasing expression of syndecan-4 allows the activation of Rac1, thereby mediating myoblast fusion. Single-molecule localized superresolution direct stochastic optical reconstruction microscopy (dSTORM) imaging revealed nanoscale changes in actin cytoskeletal architecture, and atomic force microscopy showed reduced elasticity of syndecan-4-knockdown cells during fusion. Syndecan-4 copy-number amplification was observed in 28% of human fusion-negative rhabdomyosarcoma tumors and was accompanied by increased syndecan-4 expression based on RNA sequencing data. Our study suggests that syndecan-4 can serve as a tumor driver gene in promoting rabdomyosarcoma tumor development. Our results contribute to the understanding of the role of syndecan-4 in skeletal muscle development, regeneration, and tumorigenesis.