Downregulation of ST6GAL1 Promotes Liver Inflammation and Predicts Adverse Prognosis in Hepatocellular Carcinoma

Identification of significant biomarkers for predicting the risk of bipolar disorder with arteriosclerosis based on integrative bioinformatics and machine learning

Introduction

Increasing evidence has indicated a connection between bipolar disorder (BD) and arteriosclerosis (AS), yet the specific molecular mechanisms remain unclear. This study aims to investigate the hub genes and molecular pathways for BD with AS.

Methods

BD-related dataset GSE12649 were downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) and key module genes derived from Limma and weighted gene co-expression network analyses (WGCNA) were identified. AS-related genes were sourced from the DisGeNET database, and the overlapping genes between DEGs and AS-related genes were characterized as differentially expressed arteriosclerosis-related genes (DE-ASRGs). The functional enrichment analysis, protein-protein interaction (PPI) network and three machine learning algorithms were performed to explore the hub genes, which were validated with two external validation sets. Additionally, immune infiltration was performed in BD.

Results

Overall, 67 DE-ASRGs were found to be overlapping between the DEGs and AS-related genes. Functional enrichment analysis highlighted the cancer pathways between BD and AS. We identified seven candidate hub genes (CTSD, IRF3, NPEPPS, ST6GAL1, HIF1A, SOX9 and CX3CR1). Eventually, two hub genes (CX3CR1 and ST6GAL1) were identified as BD and AS co-biomarkers by using machine learning algorithms. Immune infiltration had revealed the disorder of immunocytes.

Discussion

This study identified the hub genes CX3CR1 and ST6GAL1 in BD and AS, providing new insights for further research on the bioinformatic mechanisms of BD with AS and contributing to the diagnosis and prevention of AS in psychiatric clinical practice.

Research Progress on the Role of Epigenetic Methylation Modification in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) stands as the prevailing form of primary liver cancer, characterized by a poor prognosis and high mortality rate. A pivotal factor in HCC tumorigenesis is epigenetics, specifically the regulation of gene expression through methylation. This process relies significantly on the action of proteins that modify methylation, including methyltransferases, their associated binding proteins, and demethylases. These proteins are crucial regulators, orchestrating the methylation process by regulating enzymes and their corresponding binding proteins. This orchestration facilitates the reading, binding, detection, and catalysis of gene methylation sites. Methylation ences the development, prolisignificantly influferation, invasion, and prognosis of HCC. Furthermore, methylation modification and its regulatory mechanisms activate distinct biological characteristics in HCC cancer stem cells, such as inducing cancer-like differentiation of stem cells. They also influence the tumor microenvironment (TME) in HCC, modulate immune responses, affect chemotherapy resistance in HCC patients, and contribute to HCC progression through signaling pathway feedback. Given the essential role of methylation in genetic information, it holds promise as a potential tool for the early detection of HCC and as a target to improve drug resistance and promote apoptosis in HCC cells.

Regulation of sialic acid metabolism in cancer

Sialic acid, the terminal structure of cell surface glycans, has essential functions in regulating immune response, cell-to-cell communication, and cell adhesion. More importantly, an increased level of sialic acid, termed hypersialylation, has emerged as a commonly observed phenotype in cancer. Therefore, targeting sialic acid ligands (sialoglycans) and their receptors (Siglecs) may provide a new therapeutic approach for cancer immunotherapy. We highlight the complexity of the sialic acid metabolism and its involvement in malignant transformation within individual cancer subtypes. In this review, we focus on the dysregulation of sialylation, the intricate nature of sialic acid synthesis, and clinical perspective. We aim to provide a brief insight into the mechanism of hypersialylation and how our understanding of these processes can be leveraged for the development of novel therapeutics.

Downregulation of ST6GAL2 Correlates to Liver Inflammation and Predicts Adverse Prognosis in Hepatocellular Carcinoma

Purpose

ST6 Beta-Galactoside Alpha-2,6-Sialyltransferase 2 (ST6GAL2), a member of the sialic acid transferase family, is differentially expressed in diverse cancers. However, it remains poorly understood in tumorigenesis and impacts on immune cell infiltration (ICI) in hepatocellular carcinoma (HCC).

Patients and Methods

Herein, the expression, diagnosis, prognosis, functional enrichment, genetic alterations, immune characteristics, and targeted drugs of ST6GAL2 in HCC were researched by conducting bioinformatics analysis, in vivo, and in vitro experiments.

Results

ST6GAL2 was remarkably decreased in HCC compared to non-tumor tissues, portending a poor prognosis associated with high DNA methylation levels. Functional enrichment and GSVA analyses revealed that ST6GAL2 might function through the extracellular matrix, PI3K-Akt signaling pathways, and tumor inflammation signature. We found that ST6GAL2 expression was proportional to ICI, immunostimulator, and immune subtypes. ST6GAL2 expression first increased and then decreased during the progression of liver inflammation to HCC. The dysfunctional experiment indicated that ST6GAL2 might exert immunosuppressive effects during HCC progression through regulating ICI. Several broad-spectrum anticancer drugs were obtained by drug sensitivity prediction analysis of ST6GAL2.

Conclusion

In conclusion, ST6GAL2 was a reliable prognostic biomarker strongly associated with ICI, and could be a potential immunotherapeutic target for HCC.

Automated Capillary Electrophoresis Immunoblot for the Detection of Alpha-Synuclein in Mouse Tissue

Background

Alpha-synuclein (aSyn) is a key player in neurodegenerative diseases such as Parkinson's disease (PD), dementia with Lewy bodies, or multiple system atrophy. aSyn is expressed throughout the brain, and can also be detected in various peripheral tissues. In fact, initial symptoms of PD are non-motoric and include autonomic dysfunction, suggesting that the periphery might play an important role in early development of the disease. aSyn is expressed at relatively low levels in non-central tissues, which brings challenges for its detection and quantification in different tissues.

Objective

Our goal was to assess the sensitivity of aSyn detection in central and peripheral mouse tissues through capillary electrophoresis (CE) immunoblot, considering the traditional SDS-PAGE immunoblot as the current standard.

Methods

Tissues from central and non-central origin from wild type mice were extracted, and included midbrain, inner ear, and esophagus/stomach. aSyn detection was assessed through immunoblotting using Simple Western size-based CE and SDS-PAGE.

Results

CE immunoblots show a consistent detection of aSyn in central and peripheral tissues. Through SDS-PAGE, immunoblots revealed a reliable signal corresponding to aSyn, particularly following membrane fixation.

Conclusion

Our results suggest a reliable detection of aSyn in central and peripheral tissues using the CE Simple Western immunoblot system. These observations can serve as preliminary datasets when aiming to formally compare CE with SDS-PAGE, as well as for further characterization of aSyn using this technique.

A sialyltransferases-related gene signature serves as a potential predictor of prognosis and therapeutic response for bladder cancer

BACKGROUND

Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients' outcome and therapeutic responsiveness of bladder cancer.

METHODS

RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with "DESeq2" R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan-Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan-Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve.

RESULTS

In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies.

CONCLUSIONS

The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

Protein glycosylation alterations in hepatocellular carcinoma: function and clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Understanding the cancer mechanisms provides novel diagnostic, prognostic, and therapeutic markers for the management of HCC disease. In addition to genomic and epigenomic regulation, post-translational modification exerts a profound influence on protein functions and plays a critical role in regulating various biological processes. Protein glycosylation is one of the most common and complex post-translational modifications of newly synthesized proteins and acts as an important regulatory mechanism that is implicated in fundamental molecular and cell biology processes. Recent studies in glycobiology suggest that aberrant protein glycosylation in hepatocytes contributes to the malignant transformation to HCC by modulating a wide range of pro-tumorigenic signaling pathways. The dysregulated protein glycosylation regulates cancer growth, metastasis, stemness, immune evasion, and therapy resistance, and is regarded as a hallmark of HCC. Changes in protein glycosylation could serve as potential diagnostic, prognostic, and therapeutic factors in HCC. In this review, we summarize the functional importance, molecular mechanism, and clinical application of protein glycosylation alterations in HCC.

The role of N-glycosylation modification in the pathogenesis of liver cancer

N-glycosylation is one of the most common types of protein modifications and it plays a vital role in normal physiological processes. However, aberrant N-glycan modifications are closely associated with the pathogenesis of diverse diseases, including processes such as malignant transformation and tumor progression. It is known that the N-glycan conformation of the associated glycoproteins is altered during different stages of hepatocarcinogenesis. Characterizing the heterogeneity and biological functions of glycans in liver cancer patients will facilitate a deeper understanding of the molecular mechanisms of liver injury and hepatocarcinogenesis. In this article, we review the role of N-glycosylation in hepatocarcinogenesis, focusing on epithelial-mesenchymal transition, extracellular matrix changes, and tumor microenvironment formation. We highlight the role of N-glycosylation in the pathogenesis of liver cancer and its potential applications in the treatment or diagnosis of liver cancer.

The role of N-glycosylation modification in the pathogenesis of liver cancer

N-glycosylation is one of the most common types of protein modifications and it plays a vital role in normal physiological processes. However, aberrant N-glycan modifications are closely associated with the pathogenesis of diverse diseases, including processes such as malignant transformation and tumor progression. It is known that the N-glycan conformation of the associated glycoproteins is altered during different stages of hepatocarcinogenesis. Characterizing the heterogeneity and biological functions of glycans in liver cancer patients will facilitate a deeper understanding of the molecular mechanisms of liver injury and hepatocarcinogenesis. In this article, we review the role of N-glycosylation in hepatocarcinogenesis, focusing on epithelial-mesenchymal transition, extracellular matrix changes, and tumor microenvironment formation. We highlight the role of N-glycosylation in the pathogenesis of liver cancer and its potential applications in the treatment or diagnosis of liver cancer.