Systematical Analysis of the Cancer Genome Atlas Database Reveals EMCN/MUC15 Combination as a Prognostic Signature for Gastric Cancer

Integrated Analysis of Serum and Tissue microRNA Transcriptome for Biomarker Discovery in Gastric Cancer

Gastric cancer (GC) poses a significant global health challenge, demanding a detailed exploration of its molecular landscape. Studies suggest that exposure to environmental pollutants can lead to changes in microRNA (miRNA) expression patterns, which may contribute to the development and progression of GC. MiRNAs have emerged as crucial regulators implicated in GC pathogenesis. The largest GC serum miRNA dataset to date, comprising 1417 non-cancer controls and 1417 GC samples was used. We conducted a comprehensive analysis of miRNA expression profiles. Differential expression analysis, co-expression network construction, and machine learning models were employed to identify key serum miRNAs and their association with clinical parameters. Weighted Gene Co-expression Network Analysis (WGCNA) and immune infiltration analysis were used to validate the importance of the key miRNA. A total of 1766 differentially expressed miRNAs were identified, with miR-1290, miR-1246, and miR-451a among the top up-regulated, and miR-6875-5p, miR-6784-5p, miR-1228-5p, and miR-6765-5p among the top down-regulated. WGCNA revealed that modules M1 and M5 were significantly associated with GC subtypes and disease status. MiRNA-target gene network analysis identified prognostically significant genes TP53, EMCN, CBX8, and ALDH1A3. Machine learning models LASSO, SVM, randomforest, and XGBOOST demonstrated the diagnostic potential of miRNA profiles. Tissue and serum miR-187 emerged as an independent prognostic factor, influencing patient survival across clinical parameters. Gene expression and immune cell infiltration were different in tissues stratified by miR-187 expression. In summary, the integration of differential gene expression, co-expression analysis, and immune cell profiling provided insights into the molecular intricacies of GC progression.

Understanding of Endomucin: a Multifaceted Glycoprotein Functionality in Vascular Inflammatory-Related Diseases, Bone Diseases and Cancers

Endomucin (MUC14), encoded by EMCN gene, is an O-glycosylated transmembrane mucin that is mainly found in venous endothelial cells (ECs) and highly expressed in type H vessels of bone tissue. Its main biological functions include promoting endothelial generation and migration through the vascular endothelial growth factor (VEGF) signaling pathway and inhibiting the adhesion of inflammatory cells to ECs. In addition, it induces angiogenesis and promotes bone formation. Due to the excellent functions of Endomucin in the above aspects, it provides a new research target for the treatment of vascular inflammatory-related diseases and bone diseases. Based on the current understanding of its function, the research of Endomucin mainly focuses on the above two diseases. As it is known, the progression of cancer is closely related to angiogenesis. Endomucin recently is found to be differentially expressed in a variety of tumors and correlated with survival rate. The biological role of Endomucin in cancer is opaque. This article introduces the research progress of Endomucin in vascular inflammatory-related diseases and bone diseases, discusses its application value and prospect in the treatment, and collects the latest research situation of Endomucin in tumors, to provide meaningful evidence for expanding the research field of Endomucin.

Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas

Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

The role of gastric mucins and mucin-related glycans in gastric cancers

Gastric mucins serve as a protective barrier on the stomach's surface, protecting from external stimuli including gastric acid and gut microbiota. Their composition typically changes in response to the metaplastic sequence triggered by Helicobacter pylori infection. This alteration in gastric mucins is also observed in cases of gastric cancer, although the precise connection between mucin expressions and gastric carcinogenesis remains uncertain. This review first introduces the relationship between mucin expressions and gastric metaplasia or cancer observed in humans and mice. Additionally, we discuss potential pathogenic mechanisms of how aberrant mucins and their glycans affect gastric carcinogenesis. Finally, we summarize challenges to target tumor-specific glycans by utilizing lectin-drug conjugates that can bind to specific glycans. Understanding the correlation and mechanism between these mucin expressions and gastric carcinogenesis could pave the way for new strategies in gastric cancer treatment.

Screening of potential hub genes involved in Kidney Wilms tumor via bioinformatics analysis and experimental validation

BACKGROUND

Wilms tumor (WT) is the most common pediatric embryonal tumor. Improving patient outcomes requires advances in understanding and targeting the multiple genes and cellular control pathways, but its pathogenesis is currently not well-researched. We aimed to identify the potential molecular biological mechanism of WT and develop new prognostic markers and molecular targets by comparing gene expression profiles of Wilms tumors and fetal normal kidneys.

METHODS

Differential gene expression analysis was performed on Wilms tumor transcriptomic data from the GEO and TARGET databases. For biological functional analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were utilized. Out of 24 hub genes identified, nine were found to be prognostic-related through univariate Cox regression analysis. These nine genes underwent LASSO regression analysis to enhance the predictive capability of the model. The key hub genes were validated in the GSE73209 datasets, and cell function experiments were conducted to identify the genes' functions in WiT-49 cells.

RESULTS

The enrichment analysis revealed that DEGs were significantly involved in the regulation of angiogenesis and regulation of cell differentiation. 24 DEGs were identified through PPI networks and the MCODE algorithm, and 9 of 24 genes were related to WT patients' prognosis. EMCN and CCNA1 were identified as key hub genes, and related to the progression of WT. Functionally, over-expression of EMCN and CCNA1 knockdown inhibited cell viability, proliferation, migration, and invasion of Wilms tumor cells.

CONCLUSIONS

EMCN and CCNA1 were identified as key prognostic markers in Wilms tumor, suggesting their potential as therapeutic targets. Differential gene expression and enrichment analyses indicate significant roles in angiogenesis and cell differentiation.

View from the Biological Property: Insight into the Functional Diversity and Complexity of the Gut Mucus

Due to mucin's important protective effect on epithelial tissue, it has garnered extensive attention. The role played by mucus in the digestive tract is undeniable. On the one hand, mucus forms "biofilm" structures that insulate harmful substances from direct contact with epithelial cells. On the other hand, a variety of immune molecules in mucus play a crucial role in the immune regulation of the digestive tract. Due to the enormous number of microorganisms in the gut, the biological properties of mucus and its protective actions are more complicated. Numerous pieces of research have hinted that the aberrant expression of intestinal mucus is closely related to impaired intestinal function. Therefore, this purposeful review aims to provide the highlights of the biological characteristics and functional categorization of mucus synthesis and secretion. In addition, we highlight a variety of the regulatory factors for mucus. Most importantly, we also summarize some of the changes and possible molecular mechanisms of mucus during certain disease processes. All these are beneficial to clinical practice, diagnosis, and treatment and can provide some potential theoretical bases. Admittedly, there are still some deficiencies or contradictory results in the current research on mucus, but none of this diminishes the importance of mucus in protective impacts.

Identification, biogenesis, function, and mechanism of action of circular RNAs in plants

Circular RNAs (circRNAs) are a class of single-stranded, closed RNA molecules with unique functions that are ubiquitously expressed in all eukaryotes. The biogenesis of circRNAs is regulated by specific cis-acting elements and trans-acting factors in humans and animals. circRNAs mainly exert their biological functions by acting as microRNA sponges, forming R-loops, interacting with RNA-binding proteins, or being translated into polypeptides or proteins in human and animal cells. Genome-wide identification of circRNAs has been performed in multiple plant species, and the results suggest that circRNAs are abundant and ubiquitously expressed in plants. There is emerging compelling evidence to suggest that circRNAs play essential roles during plant growth and development as well as in the responses to biotic and abiotic stress. However, compared with recent advances in human and animal systems, the roles of most circRNAs in plants are unclear at present. Here we review the identification, biogenesis, function, and mechanism of action of plant circRNAs, which will provide a fundamental understanding of the characteristics and complexity of circRNAs in plants.

Construction of mRNA prognosis signature associated with differentially expressed genes in early stage of stomach adenocarcinomas based on TCGA and GEO datasets

Background

Stomach adenocarcinomas (STAD) are the most common malignancy of the human digestive system and represent the fourth leading cause of cancer-related deaths. As early-stage STAD are generally mild or asymptomatic, patients with advanced STAD have short overall survival. Early diagnosis of STAD has a considerable influence on clinical outcomes.

Methods

The mRNA expression data and clinical indicators of STAD and normal tissues were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The gene expression differences were analyzed by R packages, and gene function enrichment analysis was performed. Kaplan–Meier method and univariate Cox proportional risk regression analysis were used to screen differential expressed genes (DEGs) related to survival of STAD patients. Multivariate Cox proportional risk regression analysis was used to further screen and determine the prognostic DEGs in STAD patients, and to construct a multigene prognostic prediction signature. The accuracy of predictive signature was tested by receiver operating characteristic (ROC) curve software package, and the nomogram of patients with STAD was drawn. Cox regression was used to investigate the correlation between multigene prognostic signature and clinical factors. The predictive performance of this model was compared with two other models proposed in previous studies using KM survival analysis, ROC curve analysis, Harrell consistency index and decision curve analysis (DCA). qRT-PCR and Western blot were used to verify the expression levels of prognostic genes. The pathways and functions of possible involvement of features were predicted using the GSEA method.

Results

A total of 569 early-stage specific DEGs were retrieved from TCGA-STAD dataset, including 229 up-regulated genes and 340 down-regulated genes. Enrichment analysis showed that the early-stage specific DEGs were associated with cytokine–cytokine receptor interaction, neuroactive ligand–receptor interaction, and calcium signaling pathway. Multiple Cox regression algorithm was used to identify 10 early-stage specific DEGs associated with overall survival (P < 0.01) of STAD patients, and a multi-mRNA prognosis signature was established. The patients were divided into high-risk group and low-risk group according to the risk score. In the training set, the prognostic signature was positively correlated with tumor size and stage (P < 0.05), survival curve (P < 0.001) and time-dependent ROC (AUC = 0.625). In the training dataset and test dataset, the both signatures had good predictive efficiencies. Cox regression and DCA analysis revealed that the prognostic signature was an independent factor and had a better predict effect than the conventional TNM stage classification method and the earlier published biomarkers on the prognosis of STAD patients.

Conclusion

In this study, based on the early-stage specifically expressed genes, the prognostic signature constructed through TCGA and GEO datasets may become an indicator for clinical prognosis assessment of STAD and a new strategy for targeted therapy in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00827-4.

Loss of endothelial EMCN drives tumor lung metastasis through the premetastatic niche

Background

Metastasis is the primary cause of cancer-related mortality. Metastasis involves a complex multistep process during which individual tumor cells spread primarily through destruction of the endothelial barrier, entering the circulatory system to colonize distant organs. However, the role of the endothelial barrier as the rate-limiting process in tumor metastasis and how these processes affect the regulation of the host microenvironment at the molecular level are poorly understood.

Methods

Here, we analyzed differentially expressed genes in breast cancer and lung adenocarcinoma, including metastatic and recurrent specimens, using TCGA dataset. The effects of EMCN on endothelial cells in vitro and in vivo were analyzed by assessing angiogenesis and vascular permeability, respectively. We established a syngeneic mouse model of endothelial cell-specific knockout of EMCN (EMCN^ecko) to study the role of EMCN in tumor growth and metastasis. Transcriptome sequencing, Western blotting, qPCR and immunofluorescence confirmed important factors in the premetastatic niche. A mouse model of allograft tumor resection with lung metastasis was established to confirm the therapeutic effect of a notch inhibitor combined with an anti-TGF-β antibody.

Results

We found a strong correlation of EMCN deficiency with tumor recurrence and metastasis. Comparative experiments in WT and EMCN^ecko mice revealed that endothelial EMCN deficiency did not affect primary tumor growth significantly but strongly promoted spontaneous metastasis. EMCN deficiency was associated with gene profiles that regulate cell junctions in vitro and enhance vascular permeability in vivo. Mechanistically, EMCN deficiency mainly affected the host microenvironment and led to the formation of a lung premetastatic niche by recruiting Ly6G⁺ neutrophils and upregulating MMP9, S100A8/A9 and TGF-β expression. Anti-TGF-β antibody effectively eliminated TGF-β-induced neutrophil polarization, thereby reducing lung metastasis. Notably, the combination of a Notch inhibitor and an anti-TGF-β antibody effectively inhibited tumor growth and lung metastasis and prolonged the survival time of mice.

Conclusions

We present a new translational strategy of EMCN as a new key player in tumor lung metastasis by affecting the host microenvironment. These findings could provide a sound theoretical basis for clinical treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03649-4.

Expression of Mucin Family Proteins in Non-Small-Cell Lung Cancer and its Role in Evaluation of Prognosis

Lung cancer is still the major contributor to cancer-related mortality. Over 85% of patients suffer from non-small-cell lung cancer (NSCLC). Mucins (MUCs) are large glycoproteins secreted or membrane-bound produced by epithelial cells in normal and malignant tissues. They are the major components of the mucous gel that covers the surface of the respiratory epithelium. Certain MUCs have been used or proposed to act as biomarkers for lung cancer. Nevertheless, the expression, messenger ribonucleic acid (mRNA) levels, and the prognostic value of MUCs in NSCLC are yet to be investigated systematically. In this research, the biological information of MUC proteins in patients with NSCLC was examined using a series of databases. The results based on gene expression profiling interactive analysis (GEPIA) illustrated that the expression of MUC3A, MUC4, MUC5B, MUC13, MUC16, and MUC21 mRNAs was remarkably upmodulated in lung adenocarcinoma (LUAD) patients, whereas the MUC1 expression was downregulated in lung squamous cell carcinoma (LUSC) patients. Kaplan–Meier plotter (KM Plotter) analysis revealed that elevated mRNA expression levels of MUC3A and MUC16 were linked to unfavourable overall survival (OS) in NSCLC, while increased mRNA expression of MUC1 and MUC15 was linked to good OS, especially in LUAD patients. In addition, differential expression of MUC1, MUC3A/3B, MUC8, MUC12, MUC15, and MUC16 mRNA was linked to the prognoses of NSCLC patients with varied clinical-pathological subtypes. Genetic alterations of MUCs in NSCLC primarily involved mutations, fusion, amplification, deep deletion, and multiple alterations according to cancer genomics (cBioPortal). Therefore, we propose that combinations of MUC proteins can act as prognostic biomarkers and demonstrate the therapeutic potential for NSCLC-related therapy.

PBX1, EMCN and ERG are associated with the sub-clusters and the prognosis of VHL mutant clear cell renal cell carcinoma

The molecular heterogeneity of primary clear cell renal cell carcinoma (ccRCC) has been reported. However, the classifications of Von Hippel-Lindau (VHL) mutant ccRCC are unclear. Here, VHL mutant ccRCC from The Cancer Genome Atlas and E-MTAB-1980 datasets were divided into two sub-clusters through non-negative matrix factorization algorithm. Most VHL mutant ccRCC patients in sub-cluster2 were with pathological T1 stage and VHL mutant ccRCC patients in sub-cluster1 were with decreased overall survival. DNA replication and homologous recombination scores were higher, while, WNT signaling pathway and regulation of autophagy scores were lower in sub-cluster1 VHL mutant ccRCC. Moreover, PBX1 transcriptional scores and mRNA expressions were lower in sub-cluster1 VHL mutant ccRCC patients and were associated with the overall survival of VHL mutant ccRCC. Furthermore, PBX1 associated genes EMCN and ERG were down-regulated in sub-cluster1 VHL mutant ccRCC and overall survival was decreased in EMCN or ERG lowly expressed VHL mutant ccRCC patients. Also, PBX1 and EMCN were down-regulated in ccRCC tissues, compared with normal kidney tissues. At last, we constructed risk models based on PBX1, EMCN and EGR expression features. With the increase of the risk score, the number of death of VHL mutant ccRCC patients was increased.

Identification of three immune subtypes characterized by distinct tumor immune microenvironment and therapeutic response in stomach adenocarcinoma

BACKGROUND

In primary stomach adenocarcinoma (STAD), the tumor immune microenvironment (TIME) is important for cancer occurrence and progression; however, its clinical significance remains unclear. This study investigated the association between patient survival, TIME, and therapeutic response to STAD.

METHODS

Gene expression profiles of STAD cases were collected from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus. Molecular subtypes were explored with consistent clustering methods according to 119 immune signatures and the infiltrating scores of 22 immune cells using the Multi-Omics Immuno-Oncology Biological Research algorithm. We determined IFNγ scores and immune cytolytic activity (CYT) scores on the basis of corresponding gene signatures via single-sample Gene Set Enrichment Analysis. Comparisons of survival, TIME, 10 immunity-related oncogenic pathways, immune checkpoint expression, and therapeutic response were conducted among the three subtypes. We further applied linear discriminant analysis to construct a characteristic index to classify the subtypes, and the Pearson correlation coefficient for the relationship between the index and immune checkpoint genes. Weighted Correlation Network Analysis (WGCNA) was used to mine the associated modules and specific genes.

RESULTS

We collected gene expression profiles from 352 STAD cases in the TCGA database, 300 in GSE62254, and 344 in GSE84437. Three STAD subtypes (IS1-IS3) were established according to the TIME signatures. The IS3 subtype had the highest immune score and the best prognosis, as well as markedly increased immune T-cell CYT, Th1/IFNγ scores, and immune checkpoint gene expression, compared to the other two subtypes. It was highly similar to the PD-1 response group in the previous study samples of GSE91061. The established TIME classification index performed well in classifying subtypes and was directly proportional to immune checkpoint-related gene expression levels. WGCNA explored 6 modules and 14 genes, namely DYSF, MAN1C1, HTRA3, EMCN, RFLNB, KANK3, MAGEH1, CD93, PCAT19, FUT11, BMP1, FOSB, DCHS1, and TCF3, which were associated with the established TIME classification index and STAD patient prognosis.

CONCLUSION

TIME phenotypes of STAD patients could be divided into three different molecular subtypes, which displayed different prognoses, immune features, and therapeutic responses. Our results shed new light on predicting patient outcomes and the discovery of new anti-STAD therapeutic strategies according to the TIME.

Downregulation of MUC15 by miR-183-5p.1 promotes liver tumor-initiating cells properties and tumorigenesis via regulating c-MET/PI3K/AKT/SOX2 axis

Mucin 15 (MUC15) is reportedly aberrant in human malignancies, including hepatocellular carcinoma (HCC). However, the role of MUC15 in the regulation of liver tumor-initiating cells (T-ICs) remains unknown. Here, we report that expression of MUC15 is downregulated in liver T-ICs, chemoresistance and recurrent HCC samples. Functional studies reveal that MUC15 inhibits hepatoma cells self-renewal, malignant proliferation, tumorigenicity, and chemoresistance. Mechanistically, MUC15 interacts with c-MET and subsequently inactivates the PI3K/AKT/SOX2 signaling pathway. Moreover, we find that miR-183-5p.1 directly targets MUC15 3′-UTR in liver T-ICs. Coincidentally, SOX2 feedback inhibits MUC15 expression by directly transactivating miR-183-5p.1, thus completing a feedforward regulatory circuit in liver T-ICs. Importantly, MUC15/c-MET/PI3K/AKT/SOX2 axis determines the responses of hepatoma cells to lenvatinib treatment, and MUC15 overexpression abrogated lenvatinib resistance. Analysis of patient cohort, patient-derived tumor organoids and patient-derived xenografts further suggests that the MUC15 may predict lenvatinib benefits in HCC patients. Collectively, our findings suggest the crucial role of the miR-183-5p.1/MUC15/c-MET/PI3K/AKT/SOX2 regulatory circuit in regulating liver T-ICs properties, suggesting potential therapeutic targets for HCC.

MUC14-Related ncRNA-mRNA Network in Breast Cancer

Abstract: Background Growing evidences have showed that mucins (MUCs) are linked to occurrence and progression of human cancers. However, a comprehensive study regarding the expression, diagnosis, prognosis and mechanism of MUCs in breast cancer remains absent. Methods: A series of in silico analyses were employed in this study. Results: After performing comprehensive analysis for MUCs, MUC14 was identified as the most potential regulator in breast cancer, with downregulated expression in both mRNA and protein levels and significant diagnostic and prognostic values in breast cancer. Mechanistic exploration revealed that a potential ncRNA-mRNA axis, involving LINC01128/LINC01140/SGMS1-AS1/LINC00667-miR-137/miR-429-BCL2, might be partially responsible for MUC14′s functions in breast cancer. Conclusions: Collectively, our study elucidated a key role of MUC14 in breast cancer and also provided some clues for explanation of the molecular action mechanism of MUC14 in breast cancer.

The mucin protein MUCL1 regulates melanogenesis and melanoma genes in a manner dependent on threonine content

Background

The regulation of melanogenesis has been investigated as a long‐held aim for pharmaceutical manipulations with denotations for malignancy of melanoma. Mucins have a protective function in epithelial organs; however, in the most outer organ, the skin, the role of mucins has not been studied enough.

Objectives

Our initial hypothesis developed from the identification of correlations between pigmentation and expressions of skin mucins, particularly those existing in skin tissue. We aimed to investigate the action of mucins in human melanocytic cells.

Materials and methods

The expression of mucin proteins in human skin was investigated using microarray data from the Human Protein Atlas consortium (HPA) and the Genotype‐Tissue Expression consortium (GTEx) database. Mucin expression was measured at RNA and protein levels in melanoma cells. The findings were further validated and confirmed by analysis of independent experiments.

Results

We found that the several mucin proteins showed expression in human skin cells and among these, mucin‐like protein 1 (MUCL1) showed the highest expression and also clear negative correlation with melanogenesis in epidermal melanocytes. We confirmed the correlations between melanogenesis and MUCL1 by revealing negative correlations in melanocytes with different melanin production, resulting from increased composition of threonine, mucin‐conforming amino acid, and increased autophagy‐related forkhead‐box O signalling. Furthermore, threonine itself affects melanogenesis and metastatic activity in melanoma cells.

Conclusions

We identified a significant association between MUCL1 and threonine with melanogenesis and metastasis‐related genes in melanoma cells. Our results define a novel mechanism of mucin regulation, suggesting diagnostic and preventive roles of MUCL1 in cutaneous melanoma.

Whatis already known about this topic?

Despite considerable advances in radioactive therapeutics or chemotherapeutic approaches for the treatment of abnormal melanogenesis, there are still many caveats to delivery, effectiveness and safety, thus leaving a necessity for more immediate pharmaceutical targets.

Mucins have protective and chemical barrier functions in epithelial organs; however, in the skin, mucin has scarce expression and is known only as a diagnostic aid in skin disorders such as mucinosis.

Whatdoes this study add?

We provide detailed analysis demonstrating the potential of mucin‐like protein 1 (MUCL1), which showed negative correlations in melanocytes with different melanin production, resulting from increased composition of threonine and increased autophagy‐related forkhead‐box O signalling in epidermal melanocytes and melanoma cells.

We established that through an alternative pathway for MUCL1 biosynthesis, threonine supplementation recovers MUCL1 levels in melanoma. Changes, brought on by the essential amino acid threonine, resulted in substantial modulations in melanogenesis and reduced metastasis‐related genes.

Whatis the translational message?

This study demonstrates for the first time that the mucin protein of skin cells is compounded by distorted mucin homeostasis, with major effects on melanogenesis and metastasis‐related genes in melanoma.

We anticipate that these novel findings will be of keen interest to the community of scientists and medical practitioners examining skin dysfunction.

Linked Comment: C. Casalou and D.J. Tobin. Br J Dermatol 2022; 186:388–389.

Plain language summary available online

Quantitative assessment of the diagnostic role of mucin family members in pancreatic cancer: a meta-analysis

Background

The use of mucins (MUC) as specific biomarkers for various malignancies has recently emerged. MUC1, MUC4, MUC5AC, and MUC16 can be detected at different stages of pancreatic cancer (PC), and can be valuable for indicating the initiation and progression of this disease. However, the diagnostic significance of the mucin family in patients with PC remains disputed. Herein, we assessed the diagnostic accuracy of mucins in PC using a meta-analysis.

Methods

We searched the PubMed, Cochrane Library, Institute for Scientific Information (ISI) Web of Science, Embase, and Chinese databases from their date of inception to June 1, 2020 to identify studies assessing the diagnostic performance of mucins in PC. The estimations of diagnostic indicators in selected studies were extracted for further analysis by Meta-DiSc software. Publication bias was assessed using Deeks’ funnel plot asymmetry test.

Results

Our meta-analysis included 34 studies. The pooled accuracy indicators of MUC1 in PC including the sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) (with 95% confidence intervals) were 0.84 (0.82–0.86), 0.60 (0.56–0.64), 18.37 (9.18–36.78), 2.62 (1.79–3.86), and 0.22 (0.15–0.33), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.8875 and the Q index was 0.8181. Quantitative random-effects meta-analysis of MUC4 in PC using the summary (ROC) curve model revealed a pooled sensitivity of 0.86 (95% confidence interval, 0.82–0.89) and specificity of 0.88 (95% confidence interval, 0.85–0.91). In addition, the meta-analysis of MUC5AC in PC diagnosis also showed a high sensitivity and specificity of 0.71 (95% confidence interval, 0.65–0.76) and 0.60 (95% confidence interval, 0.53–0.66), respectively. Regarding MUC16, the area under the summary ROC curve and Q index were 0.9185 and 0.8516, respectively.

Conclusions

In summary, our results suggested a good diagnostic accuracy of several crucial mucins in PC. Mucins may serve as optional indicators in PC examination, and further research is warranted to investigate the role of mucins as potential clinical biomarkers.

Research progress on the structure and function of endomucin

Endomucin is a type I integral membrane glycoprotein, which is expressed in venous and capillary endothelial cells. It consists of 261 amino acids with an extracellular domain that is highly O-glycosylated at serine and threonine residues and has several potential N-glycosylation sites. Endomucin plays an important role in biological processes such as cell interaction, molecular cell signaling, angiogenesis and cell migration, and in recent years it has also been identified as an anti-adhesion molecule and a marker of endothelial cells. While it has been shown to be involved in a number of physiological and pathological mechanisms, many of its functions remain unknown, and further study is needed. This article reviews research progress on the function of endomucin to date, in order to provide guidance for future studies.

Unsupervised Hierarchical Clustering of Pancreatic Adenocarcinoma Dataset from TCGA Defines a Mucin Expression Profile that Impacts Overall Survival

Simple Summary

Pancreatic cancer has a dramatic outcome (survival curve < 6 months) that is the consequence of late diagnosis and the lack of efficient therapy. We investigated the relationship between the 22 mucin gene expression and the patient survival in pancreatic cancer datasets that provide a comprehensive mapping of transcriptomic alterations occurring during carcinogenesis. Using unsupervised hierarchical clustering analysis of mucin gene expression patterns, we identified two major clusters of patients: atypical mucin signature (#1; MUC15, MUC14/EMCN, and MUC18/MCAM) and membrane-bound mucin signature (#2; MUC1, -4, -16, -17, -20, and -21). The signature #2 is associated with shorter overall survival, suggesting that the pattern of membrane-bound mucin expression could be a new prognostic marker for PDAC patients.

Abstract

Mucins are commonly associated with pancreatic ductal adenocarcinoma (PDAC) that is a deadly disease because of the lack of early diagnosis and efficient therapies. There are 22 mucin genes encoding large O-glycoproteins divided into two major subgroups: membrane-bound and secreted mucins. We investigated mucin expression and their impact on patient survival in the PDAC dataset from The Cancer Genome Atlas (PAAD-TCGA). We observed a statistically significant increased messenger RNA (mRNA) relative level of most of the membrane-bound mucins (MUC1/3A/4/12/13/16/17/20), secreted mucins (MUC5AC/5B), and atypical mucins (MUC14/18) compared to normal pancreas. We show that MUC1/4/5B/14/17/20/21 mRNA levels are associated with poorer survival in the high-expression group compared to the low-expression group. Using unsupervised clustering analysis of mucin gene expression patterns, we identified two major clusters of patients. Cluster #1 harbors a higher expression of MUC15 and atypical MUC14/MUC18, whereas cluster #2 is characterized by a global overexpression of membrane-bound mucins (MUC1/4/16/17/20/21). Cluster #2 is associated with shorter overall survival. The patient stratification appears to be independent of usual clinical features (tumor stage, differentiation grade, lymph node invasion) suggesting that the pattern of membrane-bound mucin expression could be a new prognostic marker for PDAC patients.

High Expression of MUC15 Is Correlated with Poor Prognosis of Pancreatic Cancer and Promotes Migration, Invasion, and Chemo-Resistance In Vitro

BACKGROUND MUC15, one of the hydrophilic glycoproteins that protect wet-surfaced epithelia, has been shown to be involved in tumorigenesis of various tumors. However, the mechanism of MUC15 in pancreatic cancer have not been revealed yet. Our study focused on investigating its clinical significance and function in pancreatic cancer. MATERIAL AND METHODS Using tissue microarrays and immunohistochemical staining, we evaluated MUC15 expression in 92 patients diagnosed with pancreatic ductal adenocarcinoma (PDAC). The correlations between MUC15 expression and clinicopathological variables and prognosis were analyzed. To validate our findings, we analyzed the data from an online database. We then demonstrated its function or mechanism in pancreatic cancer cell lines using transwell assay, cytotoxicity assay, cell apoptotic detection, and western blot. RESULTS The expression level of MUC15 was remarkably increased in PDAC tissues in comparison with para-cancerous tissues, and was associated with poor prognosis. Cytoplasmic MUC15 expression was identified as an independent prognostic indicator for overall survival by multivariate Cox regression analysis. Functionally, overexpressed MUC15 enhanced the migration and invasion ability in cancer cells. In vitro studies revealed that MUC15 enhanced the gemcitabine resistance of pancreatic cancer. Additionally, the regulatory mechanism of MUC15 in PDAC were correlated with ERK and AKT signaling pathways. CONCLUSIONS We performed integrated analysis and revealed that MUC15 is a good prognostic predictor for patients with PDAC. The functional experiments showed that MUC15 contributed to the malignant behaviors of pancreatic cancer in vitro.