Ectodysplasin A receptor (EDAR) promotes colorectal cancer cell proliferation via regulation of the Wnt/β-catenin signaling pathway

High serum EDA concentration is associated with metabolic syndrome and its determinants

BACKGROUND

Ectodysplasin A (EDA) is a novel hepatokine that plays a role in multiple metabolic-related diseases. The aim of this study was to investigate the association between serum EDA levels and metabolic syndrome (MetS).

METHODS

A total of 348 subjects, 258 patients with MetS and 90 healthy controls were enrolled. Serum EDA levels were measured using an enzyme-linked immunosorbent assay (ELISA). The correlation between EDA and various metabolic components was assessed.

RESULTS

The serum EDA levels of subjects with metabolic syndrome (MetS) were significantly higher than those without [323.78 (259.68-400.74) vs. 254.82 (182.68-347.88) pg/mL, P < 0.001]. The serum EDA level increases with the increase in metabolic score. The linear regression model revealed that age, blood pressure, fasting insulin (FIns), high-density lipoprotein cholesterol (HDL-C), and HOMA-IR were independent factors influencing EDA levels. Furthermore, in the logistic regression model, subjects in the highest tertile of EDA had a significantly higher risk of MetS, higher blood pressure, hyperglycemia, and lower HDL-C compared to those in the lowest tertile. This conclusion remained valid after adjusting for multiple confounding factors.

CONCLUSIONS

The research results for the first time found that the circulating EDA levels in patients with metabolic syndrome were significantly elevated and associated with hypertension, hyperglycemia, lower HDL-C, and insulin resistance risk, indicating that EDA may play a role in the occurrence of metabolic syndrome and may be a potential therapeutic target for metabolic syndrome.

Identification of costimulatory molecule signatures for evaluating prognostic risk in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality worldwide. Despite advances in treatment, prognosis remains poor, necessitating the identification of reliable prognostic biomarkers. Costimulatory molecules (CMs) have shown to enhance antitumor immune responses. We aimed to explore their prognostic signals in NSCLC.

Methods

This study is a combination of bioinformatics analysis and laboratory validation. Gene expression profiles from The Cancer Genome Atlas (TCGA), GSE120622, and GSE131907 datasets were collected. NSCLC samples in TCGA were clustered based on CMs using consensus clustering. We used LASSO regression to identify CMs-related signatures and constructed nomogram and risk models. Differences in immune cells and checkpoint expressions between risk models were evaluated. Enrichment analysis was performed for differentially expressed CMs between NSCLC and controls. Key results were validated using qRT-PCR and flow cytometry.

Results

NSCLC samples in TCGA were divided into two clusters based on CMs, with cluster 1 showing poor overall survival. Ten CMs-related signatures were identified using LASSO regression. NSCLC samples in TCGA were stratified into high- and low-risk groups based on the median risk score of these signatures, revealing differences in survival probability, drug sensitivity, immune cell infiltration and checkpoints expression. The area under the ROC curve values (AUC) for EDA, ICOS, PDCD1LG2, and VTCN1 exceeded 0.7 in both datasets and considered as hub genes. Expression of these hub genes was significance in GSE131907 and validated by qRT-PCR. Macrophage M1 and T cell follicular helper showed high correlation with hub genes and were lower in NSCLC than controls detected by flow cytometry.

Conclusion

The identified hub genes can serve as prognostic biomarkers for NSCLC, aiding in treatment decisions and highlighting potential targets for immunotherapy. This study provides new insights into the role of CMs in NSCLC prognosis and suggests future directions for clinical research and therapeutic strategies.

Identification of cancer-associated fibroblast-related Ectodysplasin-A as a novel indicator for prognosis and immune response in gastric cancer

Studies have indicated cancer-associated fibroblasts (CAFs) could have a significant impact in gastric cancer (GC) progression and chemotherapy resistance. However, the gene related to cancer fibroblasts that can be used as biomarkers to judge the occurrence of gastric cancer has not been fully explored. Based on two Gene Expression Omnibus (GEO) datasets, we focus on differentially expressed genes which may act as CAFs markers related to GC. Through COX regression, LASSO regression and Kaplan-Meier survival analysis, we discovered three upregulated genes (GLT8D2, GNAS and EDA) associated with poor GC patients' survival. By single-cell analysis and nomogram, we found that EDA may affect fibroblast production and disease prognosis in GC patients. EDA expression showed a positive correlation with 5-Fluorouracil IC50 values. Immunohistochemistry (IHC) and real time PCR indicated elevated EDA levels in GC tissues and cells. Enrichment analysis revealed that EDA was closely linked to immune system regulation. IHC and single-cell analysis indicated that EDA gene was associated with cancer fibroblasts marker FGF12 and influence cell interferon-gamma response, which may play a role in regulating immune-related characteristics. In summary, we concluded that EDA may be used as a new therapeutic CAFs marker for GC.

Cancer-specific functional profiling in microsatellite-unstable (MSI) colon and endometrial cancers using combined differentially expressed genes and biclustering analysis

Microsatellite-unstable (MSI) cancers have distinct genetic and clinical features from microsatellite-stable cancers, but the molecular functional differences between MSI cancers originating from different tissues or organs have not been well studied because the application of usual differentially expressed gene (DEG) analysis is error-prone, producing too many noncancer-specific normally functioning genes. To maximize therapeutic efficacy, biomarkers reflecting cancer-specific differences between MSI cancers of different tissue origins should be identified. To identify functional differences between MSI colon and endometrial cancers, we combined DEG analysis and biclustering instead of DEG analysis alone and refined functionally relevant biclusters reflecting genuine functional differences between the 2 tumors. Specifically, using The Cancer Genome Atlas and genome-tissue expression as data sources, gene ontology (GO) enrichment tests were performed after routinely identifying DEGs between the 2 tumors with the exclusion of DEGs identified in their normal counterparts. Cancer-specific biclusters and associated enriched GO terms were obtained by biclustering with enrichment tests for the preferences for cancer type (either colon or endometrium) and GO enrichment tests for each cancer-specific bicluster, respectively. A novel childness score was developed to select functionally relevant biclusters among cancer-specific biclusters based on the extent to which the enriched GO terms of the biclusters tended to be child terms of the enriched GO terms in DEGs. The selected biclusters were tested using survival analysis to validate their clinical significance. We performed multiple sequential analyses to produce functionally relevant biclusters from the RNA sequencing data of MSI colon and endometrial cancer samples and their normal counterparts. We identified 3066 cancer-specific DEGs. Biclustering analysis revealed 153 biclusters and 41 cancer-specific biclusters were selected using Fisher exact test. A mean childness score over 0.6 was applied as the threshold and yielded 8 functionally relevant biclusters from cancer-specific biclusters. Functional differences appear to include gland cavitation and the TGF-β receptor, G protein, and cytokine pathways. In the survival analysis, 6 of the 8 functionally relevant biclusters were statistically significant. By attenuating noise and applying a synergistic contribution of DEG results, we refined candidate biomarkers to complement tissue-specific features of MSI tumors.

The EDA/EDAR/NF-κB pathway in non-syndromic tooth agenesis: A genetic perspective

Non-syndromic tooth agenesis (NSTA) is one of the most common dental developmental malformations affected by genetic factors predominantly. Among all 36 candidate genes reported in NSTA individuals, EDA, EDAR, and EDARADD play essential roles in ectodermal organ development. As members of the EDA/EDAR/NF-κB signaling pathway, mutations in these genes have been implicated in the pathogenesis of NSTA, as well as hypohidrotic ectodermal dysplasia (HED), a rare genetic disorder that affects multiple ectodermal structures, including teeth. This review provides an overview of the current knowledge on the genetic basis of NSTA, with a focus on the pathogenic effects of the EDA/EDAR/NF-κB signaling pathway and the role of EDA, EDAR, and EDARADD mutations in developmental tooth defects. We also discuss the phenotypic overlap and genetic differences between NSTA and HED. Ultimately, this review highlights the importance of genetic analysis in diagnosing and managing NSTA and related ectodermal disorders, and the need for ongoing research to improve our understanding of these conditions.

The Role of Ectodysplasin A on the Ocular Surface Homeostasis

Ectodysplasin A (EDA), a ligand of the TNF family, plays an important role in maintaining the homeostasis of the ocular surface. EDA is necessary for the development of the meibomian gland, the lacrimal gland, as well as the proliferation and barrier function of the corneal epithelium. The mutation of EDA can induce the destruction of the ocular surface resulting in keratopathy, abnormality of the meibomian gland and maturation of the lacrimal gland. Experimental animal studies showed that a prenatal ultrasound-guided intra-amniotic injection or postnatal intravenous administration of soluble recombinant EDA protein can efficiently prevent the development of ocular surface abnormalities in EDA mutant animals. Furthermore, local application of EDA could restore the damaged ocular surface to some extent. Hence, a recombinant EDA-based therapy may serve as a novel paradigm to treat ocular surface disorders, such as meibomian gland dysfunction and corneal epithelium abnormalities.

The role of costimulatory molecules in glioma biology and immune microenvironment

Background: Extensive research showed costimulatory molecules regulate tumor progression. Nevertheless, a small amount of literature has concentrated on the potential prognostic and therapeutic effects of costimulatory molecules in patients with glioma. Methods: The data were downloaded from The Cancer Genome Atlas (TCGA) database, Chinese Glioma Genome Atlas (CGGA) database, and Gene Expression Omnibus (GEO) database for bioinformatics analysis. R software was applied for statistical analysis. Using the FigureYa and Xiantao online tools (https://www.xiantao.love/) for mapping. Results: The Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were utilized to identify the signature consisting of five costimulatory molecules. Multivariate regression analysis revealed that the prognosis of glioma could be independently predicted by the riskscore. Furthermore, we explored clinical and genomic feature differences between the two groups. The level of tumor mutational burden (TMB) was higher in the high-risk group, while more mutation of IDH1 was observed in the low-risk group. Results of Tumor Immune Dysfunction and Exclusion (TIDE) analysis showed that high-risk patients were more prone to be responded to immunotherapy. In addition, subclass mapping analysis was performed to validate our findings and the results revealed that a significantly higher percentage of immunotherapy response rate was observed in the high-risk group. Conclusion: A novel signature with a good independent predictive capacity of prognosis was successfully identified. And our findings reveal that patients with high-risk scores were more likely to be responded to immunotherapy.

Ectodysplasin A (EDA) Signaling: From Skin Appendage to Multiple Diseases

Ectodysplasin A (EDA) signaling is initially identified as morphogenic signaling regulating the formation of skin appendages including teeth, hair follicles, exocrine glands in mammals, feathers in birds and scales in fish. Gene mutation in EDA signaling causes hypohidrotic ectodermal dysplasia (HED), a congenital hereditary disease with malformation of skin appendages. Interestingly, emerging evidence suggests that EDA and its receptors can modulate the proliferation, apoptosis, differentiation and migration of cancer cells, and thus may regulate tumorigenesis and cancer progression. More recently, as a newly discovered hepatocyte factor, EDA pathway has been demonstrated to be involved in the pathogenesis of nonalcoholic fatty liver disease (NAFLD) and type II diabetes by regulating glucose and lipid metabolism. In this review, we summarize the function of EDA signaling from skin appendage development to multiple other diseases, and discuss the clinical application of recombinant EDA protein as well as other potential targets for disease intervention.

Morphogenesis, Growth Cycle and Molecular Regulation of Hair Follicles

As one of the main appendages of skin, hair follicles play an important role in the process of skin regeneration. Hair follicle is a tiny organ formed by the interaction between epidermis and dermis, which has complex and fine structure and periodic growth characteristics. The hair growth cycle is divided into three continuous stages, growth (anagen), apoptosis-driven regression (catagen) and relative quiescence (telogen). And The Morphogenesis and cycle of hair follicles are regulated by a variety of signal pathways. When the signal molecules in the pathways are abnormal, it will affect the development and cycle of hair follicles, which will lead to hair follicle-related diseases.This article will review the structure, development, cycle and molecular regulation of hair follicles, in order to provide new ideas for solving diseases and forming functional hair follicle.

Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer

Background

Increasing evidence suggests that tumour necrosis factor (TNF) family genes play important roles in cervical cancer (CC). However, whether TNF family genes can be used as prognostic biomarkers of CC and the molecular mechanisms of TNF family genes remain unclear.

Methods

A total of 306 CC and 13 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We identified differentially expressed TNF family genes between CC and normal samples and subjected them to univariate Cox regression analysis for selecting prognostic TNF family genes. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to screen genes to establish a TNF family gene signature. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the TNF family gene signature. Finally, methylation and copy number variation data of CC were used to analyse the potential molecular mechanisms of TNF family genes.

Results

A total of 26 differentially expressed TNF family genes were identified between the CC and normal samples. Next, a TNF family gene signature, including CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 was constructed based on univariate Cox, LASSO, and multivariate Cox regression analyses. The TNF family gene signature was related to age, pathological stages M and N, and could predict patient survival independently of clinical factors. Moreover, KEGG enrichment analysis suggested that the TNF family gene signature was mainly involved in the TGF-β signaling pathway, and the TNF family gene signature could affect the immunotherapy response. Finally, we confirmed that the mRNA expressions of CD27, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 were upregulated in CC, while that of EDA was downregulated. The mRNA expressions of CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be influenced by gene methylation and copy number variation.

Conclusion

Our study is the first to demonstrate that CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be used as prognostic biomarkers of CC and are associated with the immunotherapy response of CC.

RNA Sequencing Analysis Reveals Divergent Adaptive Response to Hypo- and Hyper-Salinity in Greater Amberjack (Seriola dumerili) Juveniles

Salinity significantly affects physiological and metabolic activities, breeding, development, survival, and growth of marine fish. The greater amberjack (Seriola dumerili) is a fast-growing species that has immensely contributed to global aquaculture diversification. However, the tolerance, adaptation, and molecular responses of greater amberjack to salinity are unclear. This study reared greater amberjack juveniles under different salinity stresses (40, 30, 20, and 10 ppt) for 30 days to assess their tolerance, adaptation, and molecular responses to salinity. RNA sequencing analysis of gill tissue was used to identify genes and biological processes involved in greater amberjack response to salinity stress at 40, 30, and 20 ppt. Eighteen differentially expressed genes (DEGs) (nine upregulated and nine downregulated) were identified in the 40 vs. 30 ppt group. Moreover, 417 DEGs (205 up-regulated and 212 down-regulated) were identified in the 20 vs. 30 ppt group. qPCR and transcriptomic analysis indicated that salinity stress affected the expression of genes involved in steroid biosynthesis (ebp, sqle, lss, dhcr7, dhcr24, and cyp51a1), lipid metabolism (msmo1, nsdhl, ogdh, and edar), ion transporters (slc25a48, slc37a4, slc44a4, and apq4), and immune response (wnt4 and tlr5). Furthermore, KEGG pathway enrichment analysis showed that the DEGs were enriched in steroid biosynthesis, lipids metabolism, cytokine-cytokine receptor interaction, tryptophan metabolism, and insulin signaling pathway. Therefore, this study provides insights into the molecular mechanisms of marine fish adaptation to salinity.

Ectodysplasin A/Ectodysplasin A Receptor System and Their Roles in Multiple Diseases

Ectodysplasin A (EDA) is a member of the tumor necrosis factor (TNF) family of ligands that was initially reported to induce the formation of various ectodermal derivatives during normal prenatal development. EDA exerts its biological activity as two splice variants, namely, EDA-A1 and EDA-A2. The former binds to the EDA receptor (EDAR), resulting in the recruitment of the intracellular EDAR-associated death domain (EDARADD) adapter protein and the activation of the NF-κB signaling pathway, while the latter binds to a different receptor, EDA2R, also known as X-linked ectodermal dysplasia receptor (XEDAR). Inactivation mutation of the EDA gene or the genes coding for its receptors can result in hypohidrosis ectodermal dysplasia (HED), a condition that is characterized by oligotrichosis, edentulosis or oligodontia, and oligohidrosis or anhidrosis. Recently, as a new liver factor, EDA is gradually known and endowed with some new functions. EDA levels were observed to be upregulated in several metabolic diseases, such as non-alcoholic fatty liver disease (NAFLD), obesity, and insulin resistance. In addition, EDA and its receptors have been implicated in tumor pathogenesis through the regulation of tumor cell proliferation, apoptosis, differentiation, and migration. Here, we first review the role of EDA and its two-receptor system in various signaling pathways and then discuss the physiological and pathological roles of EDA and its receptors.

A methylation-based prognostic model predicts survival in patients with colorectal cancer

Background

To construct a model that could effectively predict the prognosis of colorectal cancer (CRC) by searching for methylated-differentially expressed genes (MDEGs).

Methods

We identified MDEGs through four databases from Gene Expression Omnibus (GEO) and annotated their functions via bioinformatics analysis. Subsequently, after adjusting for gender, age, and grading, multivariate Cox hazard analysis was utilized to select MDEGs interrelated with the prognosis of CRC, and LASSO analysis was utilized to fit the prediction model in the training set. Furthermore, another independent dataset was harnessed to verify the effectiveness of the model in predicting prognosis.

Results

In total, 252 hypomethylated and up-regulated genes and 132 hypermethylated and down-regulated genes were identified, 27 of which were correlated with the prognosis of CRC, and a 10-gene prognostic model was established after LASSO analysis. The overall survival rate could be effectively grouped into different risks by the median score of this model in the training set [risk ratio (HR) =2.27, confidence interval (95% CI), 1.69-3.13, P=8.15×10^-8], and the validity of its effect in predicting prognosis in CRC was verified in the validation dataset (HR =1.75, 95% CI, 1.15-2.70, P=9.32×10^-3).

Conclusions

Our model could effectively predict the overall survival rate of patients with CRC and provides potential application guidelines for its clinically personalized treatment.

Beta-1 syntrophin (SNTB1) regulates colorectal cancer progression and stemness via regulation of the Wnt/β-catenin signaling pathway

Background

Beta-1 syntrophin (SNTB1) is an intracellular scaffold protein that provides a platform for the formation of signal transduction complexes, thereby modulating and coordinating various intracellular signaling events and crucial cellular processes. However, the physiological role of SNTB1 is poorly understood. This study aims to explore the role of SNTB1 in colorectal cancer (CRC) tumorigenesis and progression, with particular focus on SNTB1’s expression pattern, clinical relevance, and possible molecular mechanism in CRC development.

Methods

SNTB1 expression was analyzed in both clinical tissues and The Cancer Genome Atlas (TCGA) database. Real-time polymerase chain reaction (PCR), Western blot, and immunohistochemical assays were used to detect the relative mRNA and protein levels of SNTB1. Statistical analysis was performed to examine the correlation between SNTB1 expression and the clinicopathological characteristics of patients with CRC. Bioinformatics gene set enrichment analysis (GSEA), Western blot, luciferase assay, and agonist recovery assays were conducted to evaluate the relevance of SNTB1 and the β-catenin signaling pathway in CRC. A flow cytometry-based Hoechst 33342 efflux assay was applied to assess the proportion of the side population (SP) within total CRC cells.

Results

Elevated levels of SNTB1 were identified in CRC tissues and cell lines. The elevation of SNTB1 was positively correlated with the degree of malignancy and poor prognosis in CRC. We further revealed that, by modulating the β-catenin signaling pathway, silencing SNTB1 expression suppressed tumor growth and cancer stemness in vitro, as well as tumorigenesis in vivo.

Conclusions

These findings suggest that SNTB1 plays a crucial role in colorectal tumorigenesis and progression by modulating β-catenin signaling and the stemness maintenance of cancer cells.